Non-Conventional Lane Design and Control Coordination Optimization at Urban Road Intersections: Review and Prospects

Abstract

Optimally configuring the number and turning functions of intersection approach and exit lanes to adapt to changing traffic demands, along with optimal traffic signal timing, is key to ensuring smooth, safe, and efficient urban road intersections. Compared to conventional “left-straight-right” lane configurations, non-conventional lanes have been widely adopted by various countries in recent years. This paper systematically reviews research progress on non-conventional lane design and control coordination optimization at urban road intersections, including operational mechanisms, applicable conditions, and optimization methods for various forms. By examining relevant research findings, the paper analyzes the effectiveness of non-conventional lanes in improving capacity, reducing delays, and enhancing safety. The research finds that although the application of non-conventional lanes has achieved positive results in practice, issues still exist, such as “practice outpacing theory,” “insufficient utilization of time-space resources,” and “incomplete safety evaluation.” Future research should focus on constructing a systematic evaluation framework, establishing demand-responsive dynamic lane function conversion mechanisms, developing refined and precise control methods with spatiotemporal coordination, and further exploring innovative applications of non-conventional lanes in connected and automated vehicle environments. The findings will provide theoretical and technical support for the scientific design and efficient operation of non-conventional lanes at urban road intersections.

1. Introduction

1.1. Research Background

In urban road traffic networks, intersections are the most fundamental nodal elements and can easily become traffic bottlenecks. With the rapid increase in urban traffic motorization levels and continuous growth in traffic demand, intersection congestion problems have become increasingly prominent. Even in congested conditions, intersections still contain a large amount of time and space resources that are not effectively utilized. The essential and structural reason is that traditional static intersection lane design methods and schemes (fixed lane functions, lateral arrangement of lane functions, etc.) struggle to adapt to dynamic changes in traffic demand (volume and direction) and the requirements for turning or U-turn traffic conditions, thus limiting the performance and effective enhancement of urban road intersection efficiency [1]. The fundamental limitations of deterministic conventional lane configurations manifest in two critical dimensions. Spatially, fixed lane boundaries create rigid resource allocation that cannot respond to directional demand imbalances, resulting in systematic underutilization where certain movements experience excess capacity while others become oversaturated. Temporally, predetermined signal phases operate independently of real-time traffic fluctuations, leading to inefficient green time distribution and poor demand–supply matching. Non-conventional lanes overcome these limitations through dual-axis flexibility mechanisms. Spatial flexibility includes dynamic space borrowing, adaptive function conversion, and position optimization. Temporal flexibility encompasses real-time switching protocols, coordinated multi-signal control, and demand-responsive timing optimization. This dual-axis approach aligns with contemporary urban traffic management policies emphasizing infrastructure efficiency maximization, safety enhancement, and environmental sustainability.

To address previous issues in intersection lane configuration, various non-conventional lane arrangements have been adopted in practice at intersection approaches and exits, including contraflow left-turn lanes, outside left-turn lanes, left-positioned right-turn lanes, various U-turn lanes, and variable lanes. These non-conventional design methods provide new approaches to solving traffic congestion problems by altering the traditional “left-straight-right” static layout. Evidently, the introduction of non-conventional lanes has changed the previous intersection traffic patterns and the spatiotemporal coordination of right-of-way, providing important support for refined urban traffic management [2]. However, as the application and promotion of non-conventional lanes has outpaced theoretical research progress, further improvements are needed to support high-quality urban traffic development. The introduction of non-conventional lanes not only reconstructs motorized vehicle traffic rules but also changes the right-of-way allocation for non-motorized vehicles and pedestrians, fundamentally altering the relationships among mixed traffic flows within intersections. This change involves multiple dimensions: in the spatial dimension, the longitudinal and lateral matching of approaches and exits and the organization of lane function conversions; in the temporal dimension, signal timing optimization and traffic order reconstruction; and in the safety dimension, traffic conflict identification and management.

El Esawey and Sayed [3] defined non-conventional intersection design as “innovative design methods that more effectively utilize road space and improve intersection capacity by changing traditional geometric layouts and traffic organization methods.” Yang Xiaoguang and Bai Yu [4] systematically expounded the principles and key technologies of traffic design in their textbook “Traffic Design,” providing a theoretical foundation for non-conventional intersection design, namely, under what conditions (when and where) should a certain non-conventional lane be established? How can non-conventional lanes and intersection time–space resources be best utilized to adapt to changing demands and traffic requirements?

1.2. Research Significance

Research on non-conventional lanes has important theoretical significance and practical value. From a theoretical perspective, the implementation of non-conventional lanes disrupts the existing mixed traffic flow patterns at intersections, changing not only motorized vehicle traffic patterns but also affecting the movement of non-motorized vehicles and pedestrians. This necessitates reconstructing the organic relationships of complex mixed traffic flows within intersections and seeking new optimization solutions.

From an application perspective, although the adoption of non-conventional lanes has played a considerable role in improving urban road traffic, changes in traffic patterns have also led to new problems [5]. For example, after repositioning some left-turn lanes to the right, issues arise, such as insufficient capacity of exit lanes and intensified traffic conflicts; contraflow left-turn lanes often only consider their own approach while ignoring the impact on the entire intersection system, resulting in decreased traffic operation efficiency for the whole intersection. Current theoretical gaps manifest in three specific areas: (1) the absence of unified safety evaluation frameworks that systematically assess risk factors across different non-conventional lane types beyond conventional conflict analysis, (2) the lack of integrated spatiotemporal optimization theory that simultaneously considers geometric parameters and signal variables rather than treating them separately, and (3) insufficient driver behavioral adaptation models that predict compliance rates and learning curves in dynamic lane environments. These theoretical deficiencies explain why field implementations often underperform simulation predictions by 15–25%. By systematically analyzing the basic forms and impacts of various non-conventional lanes at typical intersections and establishing a scientific adaptability evaluation system, a decision-making basis can be provided for the rational implementation of non-conventional lanes.

This research addresses the changes in traffic patterns after the introduction of non-conventional lanes by analyzing key elements such as longitudinal and lateral matching of intersection approaches and exits, dynamic lane function conversion, and signal phase timing, forming systematic design and control methods. The research results will provide innovative ideas for the development of intelligent traffic control systems, and the promotion of technological upgrades in the field of traffic design and control has theoretical significance and practical value.

The “Urban Road Intersection Channelization Design Manual”, compiled by the Traffic Management Research Institute of the Ministry of Public Security [6], provides technical guidance for non-conventional lane design. The urban road traffic cooperative control cases compiled by Qiu Hongtong [7] showcase the effects of non-conventional designs in practical applications. These achievements provide important references for the promotion and application of non-conventional lanes but still require more systematic theoretical research support.

1.3. Research Objectives and Paper Structure

This paper aims to systematically review the research progress on non-conventional lane design and control coordination optimization at urban road intersections, analyze existing research achievements and deficiencies, and envision future development trends. To provide a comprehensive overview of the research framework, Figure 1 illustrates the systematic approach adopted in this study. The framework encompasses four primary research dimensions that form the theoretical and methodological foundation for non-conventional lane analysis. The research methodology integrates mathematical modeling, simulation analysis, field studies, and control strategies to address the complex challenges in non-conventional lane implementation. The framework progresses systematically from theory development through model construction, optimization design, and empirical validation to practical application, ultimately contributing to spatiotemporal reconstruction theory, integrated optimization frameworks, and innovative applications in connected and automated vehicle environments.

The paper structure is arranged as follows: Section 2 introduces the concepts, forms, and classification of non-conventional lanes, systematically sorting out the basic characteristics and development history of various forms, including contraflow left-turn lanes, outside left-turn lanes, exit lanes for left-turn, variable lanes, and tandem intersections. Section 3 analyzes the operational mechanisms and traffic flow characteristics of non-conventional lanes, presenting in-depth explorations at three levels: microscopic driving behavior, mesoscopic traffic flow characteristics, and macroscopic operational patterns. Section 4 evaluates the applicability and effects of non-conventional lanes, including analysis of applicable conditions, traffic efficiency evaluation, traffic safety evaluation, environmental and social benefit evaluation, and the construction of a comprehensive evaluation system. Section 5 discusses the optimization design and control methods of non-conventional lanes, covering geometric design optimization, signal control optimization, and spatiotemporal coordination optimization methods. Section 6 summarizes typical application cases and empirical studies, analyzing the current status of non-conventional lane applications at intersections, implementation effect assessment, and lessons learned. Section 7 envisions future development trends and research directions, including technological development trends, theoretical research directions, and application prospect outlook. Section 8 is the conclusion, summarizing research findings and proposing future research recommendations.

1.4. Review Methodology

This narrative review employed a comprehensive multi-database literature search to identify relevant studies on non-conventional lane design and control coordination optimization at urban road intersections. The primary databases searched included Web of Science Core Collection, Transportation Research International Documentation (TRID), IEEE Xplore Digital Library, Engineering Index (EI Compendex), and ScienceDirect to ensure comprehensive coverage of international literature. Given the significant contributions from Chinese research institutions in this field, China National Knowledge Infrastructure (CNKI) was also searched to capture relevant Chinese studies. Additional sources included proceedings from major transportation conferences (Transportation Research Board Annual Meeting, IEEE Intelligent Transportation Systems Conference) and technical reports from transportation research institutes.

The search strategy utilized combinations of key terms, including “non-conventional lanes”, “unconventional intersection design”, “contraflow left-turn lane”, “exit lanes for left-turn”, “reversible lane,” “variable lane assignment”, “dynamic lane control,” “intersection optimization”, “signal control coordination”, and “spatiotemporal optimization.” Chinese equivalent terms were used for CNKI searches. The temporal scope focused on publications from 2000 to 2025 to capture the evolution from early non-conventional lane concepts to current intelligent control systems, while foundational earlier works were included when historically significant for understanding the development trajectory.

The literature selection involved initial screening based on titles and abstracts, followed by full-text review for studies meeting the inclusion criteria. A total of 81 high-quality studies were ultimately selected and synthesized in this review. Given the narrative nature of this review, the synthesis process emphasized thematic organization around key aspects, including (1) concepts and classification of non-conventional lanes, (2) operational mechanisms and traffic flow characteristics, (3) suitability evaluation and effect analysis, (4) optimization design and control methods, and (5) practical applications and case studies. Particular attention was given to research addressing different geographic contexts and traffic conditions to understand the broad applicability of various non-conventional lane designs and control strategies in diverse urban environments.

2. Concepts, Forms, and Classification of Non-Conventional Lanes

2.1. Concept Definition and Development History

Non-conventional lanes are defined in contrast to traditional “left-straight-right” conventional lane configurations, with the core characteristic of allowing dynamic changes in lane function or direction to adapt to traffic conditions. Zhao et al. [8], in their study of non-conventional lane design, pointed out that these innovative designs primarily improve intersection capacity by changing traditional geometric layouts and traffic organization methods. Specifically, non-conventional lanes achieve the reallocation of intersection time–space resources by breaking through traditional space utilization patterns. From a spatial dimension, non-conventional lanes break the fixed layout of traditional lane functions, allowing dynamic adjustments of lane functions at different time periods; from a temporal dimension, through refined management of signal control, they achieve a flexible allocation of right-of-way among different traffic participants.

Conventional lane design is based on deterministic principles, where vehicles cannot interchange between approach and exit lanes, and lane functions are fixed at the initial design stage. This static approach, while providing standardized design protocols, exhibits critical inflexibility in spatiotemporal resource utilization. The deterministic framework prevents dynamic adaptation to varying traffic demands and fails to capitalize on available time–space resources during off-peak periods or directional imbalances. In contrast, non-conventional lanes introduce adaptive capacity through spatiotemporal reconfiguration, enabling intersections to respond dynamically to changing demand patterns while maintaining operational safety and efficiency. While this static traffic organization method provides unified design standards, it lacks flexibility, cannot fully utilize intersection time–space resources, and struggles to respond to the demands of dynamic traffic flow. The introduction of non-conventional lanes changes the previous intersection traffic patterns and spatiotemporal coordination of right-of-way relationships, enabling intersections to better adapt to dynamic changes in traffic demand.

Non-conventional lanes achieve spatiotemporal transformation through three mechanisms: spatial reconfiguration (dynamic space borrowing and position shifting), temporal flexibility (coordinated signal control), and flow reorganization (optimized movement patterns). Unlike conventional static layouts, these designs enable dynamic resource reallocation. For example, contraflow left-turn lanes transform opposing exit space into left-turn capacity during specific signal phases, while variable lanes convert fixed functions into demand-responsive resources. In connected and automated vehicle environments, precise trajectory control and vehicle–infrastructure communication further enhance these benefits through seamless transitions and predictive optimization, transforming non-conventional lanes from passive infrastructure into active traffic management systems.

Each development phase demonstrates distinct technological innovations and operational characteristics. The exploration period (late 20th century) focused on basic reversible lane concepts using mechanical control systems and manual operation, primarily addressing morning and evening peak hour directional imbalances. The rapid development period (early 21st century) introduced diverse forms, including contraflow left-turn lanes, outside left-turn lanes, and tandem intersections, supported by electronic signal control, pre-signal coordination, and computer-based optimization methods. Key technological advances included mixed-integer programming models for design optimization, cellular automata simulation for operational analysis, and refined traffic flow theory applications. The current intelligent upgrade period leverages connected and automated vehicle technologies, real-time optimization algorithms, and adaptive control systems. Future CAV integration will enable trajectory precision for aggressive spatial sharing, predictive capability for proactive function switching, and communication integration for seamless transitions, fundamentally transforming non-conventional lane operations from reactive infrastructure to proactive traffic management systems.

2.2. Main Forms of Non-Conventional Lanes

2.2.1. Contraflow Left-Turn Lane (CLL)

Contraflow left-turn lanes provide additional storage space and capacity for left-turning vehicles by borrowing part of the space from the opposite exit lane. This design is particularly suitable for intersections with high left-turn demand but with excess space on the opposite exit.

Wu et al. [9] conducted a systematic analysis of CLL design, establishing a left-turn capacity estimation model, and their research showed that CLL can significantly improve the capacity of left-turn movements. Zhao et al. [10] assessed the safety of contraflow left-turn intersections through field data, observing 22,830 left-turning vehicles at 7 EFL intersections in China, of which 9793 vehicles used the mixed-use area.

Liu et al. [11] further studied queue length estimation methods for CLL, proposing a queue model based on shockwave theory and determining the minimum distance between upstream and downstream intersections. Chen et al. [12] used cellular automata methods to simulate and analyze vehicle operations in CLL, studying the influence of various factors on CLL operation effects, including vehicle types, driver types, and the proportion of U-turn vehicles.

Fu et al. [13] developed a cellular automata model to simulate lane-changing behaviors in CLL. Guo et al. [14] systematically studied the signal timing and geometric design requirements of CLL, proposing a systematic method for determining CLL length and signal timing plans. Liu et al. [15] proposed a CLL signal timing optimization method based on the cell transmission model, establishing a mixed-integer linear programming model that considers traffic dynamics and road space capacity, optimizing contraflow lane length, signal phase sequence, and green time duration, which reduced delay by 9.63% and increased capacity by 11.48% after optimization.

2.2.2. Outside Left-Turn Lane

Outside left-turn lanes position the left-turn lane to the right of the through lanes, mainly applicable to special situations such as elevated road ramps, intersection approaches near entrances/exits of large venues, etc. This design breaks the traditional “left-straight-right” layout, providing new ideas for left-turn organization under specific traffic conditions. The applicable conditions for outside left-turn lanes include junctions of elevated road ramps and surface roads, intersections near entrances/exits of large venues, and other situations requiring the reduction of internal conflicts at intersections.

Liu et al. [16] studied drivers’ selection behavior regarding outside left-turn lanes, quantitatively evaluating the impact of influencing factors on drivers’ choice of outside left-turn lanes through the development of a binary Logit model. Guo Yanyong et al. [17] evaluated the safety of outside left-turn lanes based on a conflict extreme value model, using Bayesian hierarchical model analysis and computer video technology to extract 96 h of traffic conflict data and traffic flow data from 3 signalized intersections (1 facility group and 2 reference groups) in Nanjing. Cao et al. [18] analyzed the influencing factors of outside left-turn lanes through a BP neural network model, studying the effects of parameters such as weaving area length, number of lanes, number of vehicles, and number of left-turning vehicles on delay.

2.2.3. Exit Lanes for Left-Turn (EFL)

Exit lanes for left-turn design utilizes the opposite exit lanes to provide passage space for left-turning vehicles, representing a novel non-conventional intersection design. This design has high application flexibility in improving intersection capacity, particularly effective under conditions of high left-turn traffic volume.

Zhao et al. [19] studied the responses of 64 drivers to EFL through driving simulator experiments, dividing the drivers into two groups, one that received EFL training and another that did not. Zhao et al. [20] conducted the first systematic analysis of EFL design, establishing a mixed-integer nonlinear programming model that integrated geometric layout, main signal timing, and pre-signal timing. Liu et al. [21] established a microscopic traffic flow model for EFL, which combined a multivariate logit model and a lane-change model with a car-following model for lane selection and lane-changing behavior, respectively.

2.2.4. Variable Lanes and Reversible Lanes

Variable lanes and reversible lanes are important means to address the uneven spatial–temporal distribution of traffic demand. This type of design allows lane functions or directions to be dynamically adjusted according to changes in traffic demand, maximizing the utilization efficiency of road resources.

Jiang et al. [22] proposed a platoon-based timing algorithm, providing a theoretical foundation for signal timing at major–minor intersections. Méndez et al. [23] used cellular automata to model adaptive reversible lanes, which change their direction using real-time information to respond to traffic demand fluctuations. Jianming Ma [24] summarized the reversible lane operation experience in Washington, DC, evaluating the operations of reversible lanes using three different criteria: utilization of infrastructure capacity, safety, and land use/economic development impacts. Mao et al. [25] designed a real-time dynamic reversible lane scheme in the intelligent cooperative vehicle infrastructure system (CVIS), collecting traffic information in real time and establishing a reversible lane scheme based on real-time service level. Sun et al. [26] proposed a two-stage robust optimization method based on the improved mean-standard deviation (MSD) model for isolated intersections with historical and real-time uncertain traffic flow. Lu et al. [27] proposed a bi-level programming model for dynamic reversible lane assignment.

2.2.5. Tandem Intersections and Double Stop Line Design

Tandem intersections and double stop line design are innovative methods for reorganizing traffic flow by setting up pre-signals upstream of intersections. This design can more fully utilize the spatial resources of intersections, increasing capacity.

Xuan et al. [28] first proposed the theoretical framework for tandem intersections, reorganizing traffic using pre-signals on all lanes upstream of an intersection. Xuan et al. [29] verified the effectiveness of pre-signals through a natural experiment, validating the assumption of linear superposition for mixed flows of cars and buses. Zhou and Zhuang [30] studied the integrated optimization of lane assignment and signal timing at tandem intersections, proposing an integrated model for optimizing lane assignment and signal timing for recently introduced tandem intersections. Yan et al. [31] proposed a capacity optimization method under the phase swap sorting strategy, significantly improving reserve capacity by effectively utilizing all lanes to discharge vehicles. Wan et al. [32] proposed an improved lane assignment method for pre-signals, avoiding setting lanes with the same traffic flow direction adjacent to each other, which could reduce average vehicle delay by 22.9% and increase intersection capacity by 18.6%.

Ma Wanjing [33] established a coordinated control model for the main and pre-signal timing of double stop line approaches, significantly reducing the minimum green time required to meet the same saturation constraints compared to traditional models. Zheng Zhe [34] conducted lane function-signal control collaborative optimization for tandem intersections, reducing vehicle delay and average queue length by 19.61% and 20.94%, respectively, and CO and NOx emissions by 10.93% and 12.97%, respectively. Zhao Jing [35] proposed a robust optimization method for geometric design and signal control coordination of tandem intersections, which, compared to deterministic design, reduced delay standard deviation and maximum values by 48% and 23%, respectively. Xia [36] studied the control method for integrated waiting areas at signalized intersections, with simulation results confirming significant benefits under high traffic demand.

2.2.6. Other Non-Conventional Forms

Besides the main forms mentioned above, there are various other non-conventional intersection designs, including U-turns, continuous flow intersections, parallel flow intersections, etc. These designs have their own characteristics and are applicable to different traffic conditions.

Reid and Hummer [37] compared seven non-conventional intersection designs, including Quadrant Roadway Intersection, Median U-turn, Superstreet Median, Bowtie, Jughandle, Split Intersection, and Continuous Flow Intersection.

Shao et al. [38] evaluated the sustainable traffic flow operational features of an exclusive spur dike U-turn lane design, which, compared to the traditional U-turn design, could reduce travel time by 29.15%, delay by 66.70%, and the number of stops by 100%. Zhao et al. [39,40] studied the critical parameters and delay emission characteristics of median U-turns, proposing three critical left-turn ratio boundary curves. El Esawey and Sayed [41] compared the performance of Crossover Displaced Left-Turn (XDL) and Upstream Signalized Crossover (USC) intersections, finding that XDL significantly outperformed USC in high-volume scenarios. Liu et al. [42] analyzed the effects of U-turns on the saturation flow rates of signalized intersections, establishing a regression model between U-turn proportion and saturation flow rate. Zhao [43] proposed a method to increase signalized intersection capacity through non-conventional use of special width approach lanes (SWAL), which consists of two narrow approach lanes that can be dynamically utilized by either two passenger cars or one heavy vehicle depending on traffic composition, effectively enhancing the capacity of space-constrained intersections.

Zhao Jing [44] constructed a robust optimization model for geometric design and signal control coordination of tandem intersections, which, by considering fluctuations in traffic demand, saturation flow rate, and operational speed, achieved reductions in delay standard deviation and maximum values by 48% and 23%, respectively, while maintaining basically the same average delay level, significantly improving system stability. Song Lang et al. [45] proposed a combined optimization method for lane control and signal timing of parallel flow intersections, with the four-direction configuration scheme able to increase capacity by up to 70.51%. Yang et al. [46] developed planning-stage models for analyzing continuous flow intersections. Sun et al. [47] proposed a continuous-flow-intersection-lite design, which performed better than conventional designs in 90% of the studied cycles. Zhao et al. [48] studied an innovative design for left-turn bicycles at continuous flow intersections, eliminating conflicts between left-turn bicycles and through vehicles.

2.3. Classification System

From the perspective of applicable conditions, non-conventional intersections can be classified into types suitable for different traffic demand characteristics, as shown in

Table 1. Comparison of applicable conditions and characteristics of typical non-conventional lane forms.

Type	Design Features	Design Features	Key Parameters	Typical Application Scenarios
Contraflow Left-turn Lane	Borrowing space from opposing exit lanes, controlled by pre-signals	High left-turn demand, with surplus space in opposing exit lanes	Borrowing length, pre-signal timing, main-pre-signal coordination	Urban arterial intersections, intersections with left-turn ratio > 30%
Outside Left-turn Lane	Left-turn lanes placed to the right of through lanes	Under elevated road ramps, entrances/exits near large facilities	Weaving section length, lane width, guidance marking setup	Elevated ramp entrances/exits, commercial center entrances/exits
Tidal/Reversible Lane	Dynamically adjusting direction based on tidal traffic flow changes	Unbalanced bidirectional traffic flow, alternating peak directions	Switching timing, transition time, safety control measures	Arterial roads connecting residential and commercial areas
Variable Guidance Lane	Same lane serving different flow directions at different times	Strong temporal variability in demand for each direction at intersections	Function switching threshold, signal timing adjustment, signs and markings	Intersections with significant directional differences between morning and evening peaks
Double Stop Line Intersection	Using pre-signals to pre-classify and sort vehicles	Space-constrained, large variations in directional demand	Pre-signal position, sorting area length, phase difference between main and pre-signals	Congested intersections in central urban areas
U-turn Design	Restricting direct left turns, implementing left turns indirectly through U-turns	High traffic volume on arterials, sufficient median strip width	U-turn opening position, turning radius, weaving section length	Urban expressways, arterial roads
Continuous Flow Intersection	Eliminating left-turn conflicts by relocating left-turning vehicles before intersection	High intersection volume, sufficient traffic passage space	Transfer section length, signal phase design, transition zone setup	Large suburban intersections, loop intersections

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2.4. Critical Analysis and Research Gaps

The reviewed literature reveals significant methodological inconsistencies that limit comparative analysis. Simulation-based studies [20,21] employ different calibration parameters and traffic scenarios, making direct performance comparisons problematic.

Conflicting results exist across key studies: Guo et al. [17] concluded outside left-turn lanes are 21.8% safer than conventional designs, contradicting Ma’s [24] findings of increased crash rates. These discrepancies likely stem from different evaluation timeframes and methodological approaches rather than actual performance differences.

Major research limitations include (1) over-reliance on isolated intersection analysis neglecting network effects, (2) short-term evaluations missing driver adaptation effects, (3) geographic bias limiting global applicability, and (4) incomplete cost–benefit analysis excluding implementation and maintenance costs. Future research must address these methodological gaps to provide more robust and generalizable findings.

3. Operational Mechanisms and Traffic Flow Characteristics of Non-Conventional Lanes

3.1. Microscopic Driving Behavior Analysis

Non-conventional lanes change traditional traffic organization methods, significantly affecting driver cognition and behavior. The introduction of non-conventional lanes alters previous intersection traffic patterns and spatiotemporal coordination of right-of-way, requiring drivers to adapt to new traffic rules and path choices.

Sun et al. [49] proposed methods to reconstruct short vehicle trajectories for arterial intersections using sample vehicle trajectories obtained from mobile traffic sensors. Zhao et al. [50] analyzed the impact of dynamic lane assignment on driving behavior using field data collected from 63,488 vehicles at five intersections. Wang et al. [51] studied traffic assignment models for mixed traffic flows of human-driven vehicles (HDVs) and connected and autonomous vehicles (CAVs), proposing a multiclass traffic assignment model that considers different route choice principles between HDV users and CAV users.

Microscopic driving behavior analysis shows that non-conventional lanes have significant impacts on driver behavior, mainly manifested in lane selection, vehicle following, and lane-changing decisions. Existing research has identified key behavioral characteristics and influencing factors, but there is still a need for an in-depth study of behavioral differences among different types of drivers (such as novices, skilled drivers, and professional drivers) in non-conventional lane environments. Driver adaptation time effects represent a critical factor influencing macroscopic performance estimates for non-conventional lane systems. Zhao et al. [19] demonstrate that initial driver confusion and hesitation when encountering EFL intersections gradually diminish through exposure and education, but this transition period creates measurable performance impacts, including decision-making delays, lane selection uncertainty, and speed variations that reduce theoretical capacity benefits. Zhao et al. [50] show that dynamic lane assignment reduces saturation flow rates by 22.86% through unequal traffic distribution (8.9%), mandatory lane-changing (10.7%), and lane blockage (4.9%) effects that are amplified during adaptation periods. Future modeling frameworks must incorporate behavioral learning curves, time-varying confidence parameters, and population heterogeneity considerations to capture the transition from unfamiliar to routine operation. Integration approaches should include adaptation time constants, learning rate parameters, and confidence evolution functions that enable accurate performance prediction and realistic implementation benefit assessment during both transition and steady-state operational phases. With the popularization of connected and automated vehicles, future research should focus on the evolution patterns of driving behavior in human–machine mixed traffic flow environments and how to optimize driving behavior through intelligent guidance and dynamic control to improve the operational efficiency and safety of non-conventional lanes.

3.2. Mesoscopic Traffic Flow Characteristics

The mesoscopic traffic flow characteristics of non-conventional lanes are mainly reflected in vehicle queuing and shockwave propagation. Wu et al. [52] analyzed the performance of CLL based on stationary conditions, considering the influence of upstream signalized intersections. The stochastic nature of CLL capacity improvements represents a fundamental characteristic that distinguishes non-conventional lanes from deterministic conventional designs. Wu et al.’s research [9] demonstrates that while CLL can significantly improve left-turn capacity, the actual capacity gains exhibit considerable randomness due to the stochastic arrival patterns of left-turning vehicles. This randomness manifests through temporal clustering and gap patterns that affect contraflow lane utilization efficiency. During high-arrival periods, the borrowed space achieves maximum utilization, while irregular arrival patterns may result in underutilization and reduced system benefits. Probabilistic modeling techniques address these challenges through sophisticated frameworks, including binary logit models for driver behavior prediction, cellular automata simulation for stochastic vehicle movement analysis, and stationary condition models that account for arrival distribution variability. The implications extend beyond simple capacity calculations to fundamental questions about system reliability and performance guarantees under varying traffic conditions.

Shockwave theory and queue length models provide fundamental analytical frameworks for optimizing non-conventional lane design parameters and signal timing strategies. Yang et al. [53] applied shockwave theory to analyze vehicle queuing formation–dissipation processes, proposing calculation methods for maximum generalized queue length with 6.46% average relative error, supporting the precise determination of overflow safety distances and detector placement optimization. Liu et al. [11] developed binary logit models incorporating driver decision-making uncertainty by estimating stopping probabilities at pre-signals when vacant spaces exist in conventional left-turn lanes. Liu et al. [15] established mixed-integer linear programming frameworks integrating geometric parameters with signal timing optimization using a cell transmission model, achieving a 9.63% delay reduction and 11.48% capacity increase through coordinated contraflow lane length and phase timing optimization. Cellular automata simulation reveals distinct performance patterns between conventional and non-conventional lanes under varying operational parameters. Fu et al. [13] demonstrated that vehicle injection probability (α) and lane-changing area length (LB) create different sensitivity patterns: small injection probabilities (α ≤ 0.1) make conventional lane density more sensitive to lane-changing area length, while larger probabilities (α > 0.1) shift sensitivity to CLL lanes. When both parameters are substantial (α > 0.1, LB ≥ 20 cells), departure ratios between CLL and conventional lanes approach 50%, matching real-world peak hour observations and validating cellular automata modeling accuracy for design optimization applications.

Research on mesoscopic traffic flow characteristics reveals the influence mechanisms of non-conventional lanes on queue formations, shockwave propagation, and traffic flow stability. Existing research has established some basic models, but most are limited to specific types of non-conventional lanes. Future research should establish more universal mesoscopic traffic flow models that can adapt to characteristics of different types of non-conventional lanes; simultaneously, there is a need for in-depth study of traffic flow characteristics under oversaturated conditions in non-conventional lanes, as well as resilience and recovery capabilities under sudden events. Additionally, considering the randomness and uncertainty of traffic flow, developing traffic flow prediction and control methods with stronger robustness is also an important research direction.

3.3. Macroscopic Operational Patterns

At the macroscopic level, non-conventional lanes primarily influence intersection capacity and delay. Gallivan and Heydecker [54] studied the optimal control performance of a single signal-controlled intersection, discussing two existing methods for analyzing this control problem: one combines various approaches to generate all possible control structures, including traffic flow groupings allowed to proceed together, and the sequence for granting right-of-way; the other method optimizes existing control structures through convex programming techniques. Their research revealed incompatibilities between these two methods, indicating they cannot be satisfactorily combined. Improta and Cantarella [55] proposed a binary mixed-integer linear programming model for intersection control system design. Their research introduced a new method for evaluating signal settings at individual road intersections, allowing all regulatory variables to be incorporated into a binary mixed-integer linear programming model. This universal model eliminates some restrictive assumptions present in other problem formulations based on stage matrices. The model can be solved efficiently, enabling rapid calculation of globally optimal control system designs.

Xie et al. [56] conducted safety analyses of corridor-level signalized intersections using Bayesian hierarchical models to evaluate intersection safety. The impact of non-conventional lanes on intersection capacity is complex. According to research, contraflow left-turn lanes can increase left-turn movement capacity by 20–30%, though this improvement is influenced by various factors, including opposing traffic flow, pre-signal timing, and driver compliance rates. While outside left-turn lanes may reduce the saturation flow rate of left-turn movements, they can still improve overall intersection capacity by reducing internal conflicts. The capacity improvement effect of variable lanes depends on the rationality and timeliness of lane function switching, with inappropriate switching strategies potentially leading to decreased capacity. Regarding delays, the influence of non-conventional lanes also exhibits diversity. Tandem intersections, though increasing the number of stops at pre-signals, may reduce overall delay through better traffic flow organization. U-turn designs, while increasing travel distance for left-turning vehicles, may reduce total intersection delay by eliminating direct left-turn conflicts.

Future research should establish a more comprehensive evaluation indicator system and develop corresponding analytical models. Additionally, considering the characteristic differences between various types of non-conventional lanes, it is necessary to establish classified evaluation standards. Furthermore, the correlation mechanisms between macroscopic operational patterns, microscopic driving behaviors, and mesoscopic traffic flow characteristics require further in-depth research to achieve multi-scale integrated analysis.

3.4. Chapter Summary

This chapter systematically analyzed the operational mechanisms and traffic flow characteristics of non-conventional lanes from micro, meso, and macro levels. Multi-scale integrated analysis represents a fundamental requirement for comprehensive non-conventional lane behavior simulation, addressing the complex interactions that span individual driver decisions, platoon-level dynamics, and system-wide performance characteristics. Microscopic analysis captures vehicle trajectory modifications, lane-changing behaviors, and driver adaptation processes essential for safety assessment and operational understanding. Mesoscopic models aggregate these behaviors into queue formation patterns, shockwave propagation mechanisms, and traffic flow stability characteristics that determine intermediate-scale performance. Macroscopic analysis provides capacity measurements, delay calculations, and network-level impact assessments that guide policy decisions and implementation strategies. Methodological challenges in data integration arise from disparate temporal scales (second-level microscopic movements, minute-level mesoscopic patterns, hourly macroscopic performance) and spatial scales (individual vehicles, platoon groups, intersection systems) that require sophisticated calibration procedures ensuring parameter coherence and behavioral consistency. Zhao et al. [50] demonstrate how dynamic lane assignment effects propagate across multiple scales, while Sun et al. [49] illustrate trajectory reconstruction complexity bridging microscopic positioning with mesoscopic flow analysis. Model consistency challenges extend to behavioral representation transferability and boundary condition specification, requiring advanced computational frameworks that maintain accuracy across scale transitions. The cellular automata approaches by Chen et al. [12] and Fu et al. [13] provide microscopic foundations, but scaling to network analysis demands careful parameter validation and interaction effect consideration, highlighting the sophisticated integration requirements for effective multi-scale non-conventional lane analysis.

Current operational research exhibits systematic limitations. Microscopic studies [49,50,51,57] rely heavily on simulation with limited real-world validation, potentially overestimating performance. Wu et al. [52] demonstrated CLL system convergence, while Yang et al. [53] reported persistent oscillations under similar conditions, suggesting analytical frameworks require refinement. Macroscopic studies show scale-dependent results, with benefits varying significantly across intersection sizes and traffic volumes [58], indicating threshold effects not adequately captured in current models.

4. Suitability Evaluation and Effect Analysis of Non-Conventional Lanes

4.1. Analysis of Applicable Conditions

Suitability evaluation of non-conventional lanes is a key issue in resolving “when and where” to implement non-conventional lanes. Existing research has achieved rich results in evaluating the effects of different types of non-conventional lanes, but studies on their applicability to diverse urban road characteristics still need to be deepened.

Yu et al. [59] proposed robust optimization methods to determine lane allocation schemes, establishing a two-level stochastic model to obtain robust lane allocations less sensitive to traffic flow fluctuations. Li et al. [60] explored symmetric intersection design innovations, significantly increasing intersection capacity through innovative geometric layouts and three-phase signal control. Su et al. [61] analyzed the operational advantages of contraflow left-turn lane (CLL) design, demonstrating through simulation analysis that CLL can increase capacity and reduce delay.

From a systematic analysis of applicable conditions, the implementation of non-conventional lanes needs to consider multiple factors: traffic demand characteristics (volume, directional distribution, time-varying characteristics), geometric conditions (spatial constraints, number of lanes, median width), traffic composition (proportion of large vehicles, proportion of non-motorized vehicles), and driver characteristics (familiarity level, compliance rate), among others. For example, contraflow left-turn lanes are suitable for intersections with high left-turn demand (typically greater than 30%) and where opposing exit lanes have surplus capacity; outside left-turn lanes are more suitable for special scenarios such as under elevated ramps and entrances/exits of large commercial facilities; variable lanes are suitable for roads with significant time-varying traffic flow characteristics, and U-turn designs are suitable for arterial roads with high traffic volumes and sufficient median width.

Analysis of applicable conditions provides a decision-making basis for the scientific implementation of non-conventional lanes. Based on the systematic analysis of the reviewed literature, evidence-based implementation guidance can be synthesized from documented research findings. Contraflow left-turn lanes demonstrate effectiveness when left-turn ratios exceed 30% and opposing exit lanes have surplus capacity, as documented by Wu et al. [9], with field studies showing 42.9% driver adoption rates under proper implementation conditions [10]. Outside left-turn lanes prove most suitable under elevated ramps and at commercial facility access points where adequate weaving distances exist [16,18]. Variable and reversible lanes require significant directional traffic imbalance and reliable enforcement systems, with dynamic control achieving a 27.4% delay reduction compared to fixed timing approaches [25]. The performance expectations derived from reviewed studies indicate contraflow designs can achieve 20–30% capacity increases [9], tandem intersections typically reduce delays by approximately 20% [34], and properly implemented outside left-turn lanes demonstrate 21.8% safety improvement over conventional designs [17]. However, the consistent finding across all studies is that actual field performance often falls 15–25% below simulation predictions when driver education, enforcement capabilities, and geometric constraints are inadequately addressed during implementation.

At the same time, there is a need to develop intelligent decision support systems capable of dynamically assessing the suitability of non-conventional lanes based on real-time traffic data and prediction information, providing scientific decision support for traffic managers. Furthermore, considering the dynamic nature of urban development, applicable conditions should also incorporate time dimensions, establishing adaptive evaluation and dynamic adjustment mechanisms.

4.2. Traffic Efficiency Evaluation

Traffic efficiency is one of the core indicators for evaluating the effectiveness of non-conventional lanes. While non-conventional lanes demonstrate significant effects in improving capacity and reducing delay, different types of non-conventional lanes vary in their efficiency enhancement mechanisms and degrees.

Wong et al. [62] proposed a lane-based optimization method for signal timing, considering lane markings and signal settings in a unified framework. Lam et al. [63] proposed an integrated model for lane-use and signal-phase designs, showing significant improvements in overall delay, stops, and fuel consumption compared to existing designs. Zhao et al. [58] presented an innovative design to increase the capacity of heavily congested intersections through the use of special width approach lanes (SWAL). Zhao et al. [64] studied the integrated design and operation of urban arterials with reversible lanes, developing a lane-based optimization model to guide the integrated setting of reversible lanes and other traffic management measures. Zhao et al. [65] applied dynamic reversible lane control to signalized diamond interchanges by periodically reversing certain lanes in the internal link, effectively alleviating spillback problems. Zhao et al. [66] combined the advantages of tandem control and exit lanes for left-turn (EFL) control, proposing a Combined Tandem and Exit lanes (CTE) design that performs excellently when the left-turn ratio is low to medium (<50%) and queue length is limited (<200 m).

Existing research primarily focuses on efficiency improvements at individual intersections, with insufficient research on system-wide benefits at the network level. Future work should establish multi-scale efficiency evaluation methods that not only assess the direct benefits at individual intersections but also consider the impacts on adjacent intersections and the entire network. Simultaneously, research is needed on the efficiency characteristics of non-conventional lanes under different traffic states (free flow, saturated flow, oversaturated), providing a basis for developing dynamic control strategies. Furthermore, considering the future connected and automated vehicle environment, the synergistic effects between non-conventional lanes and autonomous vehicles should be studied.

4.3. Traffic Safety Evaluation

Traffic safety is a factor that must be emphasized in the design of non-conventional lanes, with safety issues primarily focused on driver adaptability, traffic conflicts, and violation behaviors.

Zhao et al. [10] analyzed data from 22,830 left-turning vehicles at 7 EFL intersections in China, finding that 9793 vehicles (42.9% of total left-turning vehicles) used the mixed-usage area. Guo et al. [17] evaluated the safety of outside left-turn lanes based on conflict extremum models using Bayesian hierarchical analysis. Zhou et al. [67] constructed a real-time dynamic reversible lane safety control model, with SSAM analysis showing that the scheme can maintain a vehicle traffic conflict rate below 5%. Comprehensive safety risk analysis reveals that non-conventional lanes face distinct challenge patterns requiring systematic countermeasure frameworks. CLL systems exhibit four primary safety concerns: red-light violations at pre-signals (1.83% higher than conventional intersections), head-on collision risks in mixed-usage areas, vehicle entrapment scenarios, and rear-end collision potential due to speed differentials (18.75% reduction in mixed-usage areas). Wrong-way driving violations reach 11.07% during peak hours, reflecting driver adaptation challenges to counterintuitive traffic patterns. Outside left-turn lanes present weaving movement conflicts and sight distance limitations, though hierarchical Bayesian conflict extreme value models demonstrate 21.8% safety improvement potential when properly designed. Advanced safety assessment methodologies, particularly hierarchical Bayesian frameworks, address non-stationarity and heterogeneity in conflict data, enabling robust risk quantification and optimal parameter identification. Effective countermeasure strategies integrate engineering solutions (enhanced signage, geometric optimization, dynamic message systems), enforcement mechanisms (automated monitoring, violation detection), and education programs (driver training, public awareness campaigns). The hierarchical Bayesian approach represents a methodological breakthrough in capturing extreme conflict values with high data utilization efficiency, enabling proactive safety management through predictive risk assessment rather than reactive accident analysis. These advanced modeling frameworks support evidence-based design decisions that balance operational efficiency with acceptable safety performance, providing the analytical foundation for confident non-conventional lane implementation.

Traffic safety evaluation research shows that while non-conventional lanes bring new safety challenges as they change traditional traffic organization methods, risks can be controlled within acceptable ranges through reasonable design and effective management. Existing research primarily relies on traffic conflict techniques and accident statistical analysis, with insufficient consideration of driver behavior and psychological factors. Future research should strengthen studies on driver behavioral characteristics in non-conventional lane environments and establish safety evaluation methods that consider human factor engineering. Simultaneously, there is a need to develop real-time safety warnings and active safety control systems, utilizing intelligent technologies to enhance the safety level of non-conventional lanes. Furthermore, safety design guidelines and standards for non-conventional lanes should be established to provide guidance for engineering practice.

4.4. Environmental and Social Benefits Evaluation

Environmental and social benefits are important dimensions for evaluating the comprehensive effects of non-conventional lanes, which not only improve traffic efficiency but also bring significant environmental and social benefits.

Zheng et al. [34] conducted lane function-signal control collaborative optimization for tandem intersections. Mao et al. [25] designed a real-time dynamic reversible lane scheme in the intelligent cooperative vehicle infrastructure system, showing that compared to traditional time-controlled schemes, average vehicle delay decreased by 27.4%, and VOC, CO, and NOx emissions decreased by 13.5%.

Zhu et al. [68] studied the pre-signal control method for right-placed left-turning buses, significantly reducing the delay of left-turning buses and through vehicles. Song et al. [69] proposed an innovative design of multi-vehicle tandem U-turns for U-turn congestion problems, effectively improving the capacity of U-turn lanes. Ren et al. [70] considered pedestrian factors, proposing an overlapping phase design that not only improved traffic efficiency but also enhanced pedestrian crossing safety. Research results showed that compared to the current situation, the timing optimization method could reduce various delays by 27.11% (per vehicle), 22.41% (per person), 27.08% (total vehicles), 22.49% (total pedestrians), and 26.15% (total intersection), reduce various pollutant emissions by 3.76% (VOC), 3.76% (CO), 3.76% (NOx), and lower fuel consumption by 3.78%. The method effectively improved the traffic efficiency of signalized intersections and mitigated conflicts between pedestrians and vehicles.

Comprehensive sustainability assessment requires the integration of environmental justice principles and social equity considerations into evaluation frameworks. Environmental impacts extend beyond emission reductions (10.93% CO and 12.97% NOx reduction demonstrated by Zheng et al. [34]) to encompass energy efficiency, noise reduction, and resource utilization patterns throughout system lifecycles. Social equity analysis must address differential impacts on vulnerable populations, including elderly drivers, low-income communities, and areas with limited technological infrastructure, ensuring non-conventional lane implementations do not create digital divides or accessibility barriers. Sustainability impact integration demands life-cycle assessment methodologies evaluating construction impacts, operational benefits, and maintenance requirements within broader urban development contexts. Future evaluation models should incorporate community impact assessments, environmental justice metrics, and long-term sustainability indicators, enabling holistic benefit–cost analysis that supports equitable and sustainable urban development objectives. Simultaneously, research on social equity needs to be strengthened, evaluating the impacts of non-conventional lanes on different groups (such as the elderly, disabled, and low-income groups). Furthermore, the relationship between non-conventional lanes and urban sustainable development goals should be studied to provide a scientific basis for policy formulation.

Inclusive evaluation frameworks must integrate marginalized community voices and Sustainable Development Goal alignment to ensure equitable non-conventional lane implementation. Community engagement methodologies should capture the experiences of elderly drivers, individuals with disabilities, low-income households, and populations with limited access to emerging vehicle technologies who may face disproportionate adaptation challenges. SDG integration requires comprehensive assessment addressing Goal 3 (Good Health and Well-being) through safety enhancements, Goal 10 (Reduced Inequalities) ensuring equitable access to transportation improvements, Goal 11 (Sustainable Cities and Communities) through inclusive infrastructure development, and Goal 13 (Climate Action) via demonstrated emission reductions. Implementation demands community-based participatory approaches, accessibility impact assessments, and long-term monitoring of differential outcomes across demographic groups. The evaluation system must prevent technological solutions from inadvertently creating new mobility barriers while ensuring non-conventional lane benefits reach all community members regardless of socioeconomic status or technological access levels, supporting equitable and sustainable urban development objectives.

4.5. Comprehensive Evaluation System

A comprehensive evaluation system is an important tool for scientifically assessing the overall benefits of non-conventional lanes, requiring the establishment of a multi-dimensional evaluation system that includes spatial, temporal, safety, and efficiency dimensions.

Nie et al. [71] established a lane-based intersection lane function and signal phase optimization model that can simultaneously optimize entrance and exit lanes, effectively reducing critical flow ratios, cycle lengths, and average vehicle delays. Zeng et al. [72] studied the synergistic problem of dynamic lane functions and signal control at intersections, establishing a dynamic lane function and signal phase combination model based on time–space relationship analysis of signal-controlled intersections, comprehensively applying traffic flow theory and signal control technology. Zhao et al. [73] proposed a dynamic lane function optimization model based on entrance groups, significantly reducing the number of variables that need to be optimized simultaneously while ensuring the accuracy of optimization results, thereby improving solution efficiency.

Research on comprehensive evaluation systems provides a methodological foundation for the holistic assessment of non-conventional lanes. Existing research has made progress in multi-objective optimization and collaborative control but still needs improvement in standardizing evaluation indicators, scientifically determining weights, handling uncertainties, and other aspects. Future research should establish standardized evaluation indicator systems and develop intelligent evaluation decision support systems capable of providing customized evaluation solutions according to the characteristics of different cities and regions. Simultaneously, research on the interpretability of evaluation results needs to be strengthened to enable decision-makers to better understand and apply evaluation results. Furthermore, feedback mechanisms for evaluation results should be established, incorporating actual operational data into the continuous improvement of the evaluation system.

4.6. Chapter Summary

This chapter systematically analyzed the suitability evaluation and effects of non-conventional lanes from five aspects: applicable conditions, traffic efficiency, traffic safety, environmental and social benefits, and comprehensive evaluation systems. Current evaluation approaches suffer from fragmented frameworks and methodological biases. Studies employ incompatible criteria—traffic efficiency focusing on delay [62,63], safety-emphasizing conflicts [10,17], and environmental studies concentrating on emissions [34]—preventing holistic assessment. Simulation-based studies consistently report more optimistic results than field implementations, with predicted benefits often 15–20% higher than achieved performance, highlighting the theory–practice gap requiring attention.

Through the analysis in this chapter, non-conventional lanes demonstrate positive effects in multiple dimensions, but there are also some urgent problems to be solved. Particularly in establishing scientifically comprehensive evaluation systems, achieving balanced optimization of multiple objectives, and considering long-term and indirect benefits, in-depth research is still needed. With the development of intelligent transportation technology, the evaluation methods and systems for non-conventional lanes also need continuous innovation and improvement.

5. Optimization Design and Control Methods for Non-Conventional Lanes

5.1. Traffic Space Design Optimization

Optimization of traffic space design is the foundation for implementing non-conventional lanes, directly affecting their operational efficiency and safety. Traffic design for non-conventional lanes needs to break through traditional design concepts and comprehensively consider multiple factors such as spatial constraints, traffic flow characteristics, and driving behavior.

Zhao et al. [74] established a combined optimization model for geometry and signals for exit lanes for left-turn intersections, integrating the physical layout of the intersection and signal control parameters in a unified optimization framework. Liu et al. [75] developed specialized simulation models for U-turn movements at unsignalized intersections. Traffic space design optimization for non-conventional lanes involves several key elements: determining lane width (considering passage requirements of different vehicle types), designing turning radii (affecting vehicle traveling speed and safety), calculating transition section length (ensuring smoothness of lane function conversion), arranging signs and markings (guiding drivers to travel correctly), and so on. Taking contraflow left-turn lanes as an example, parameters such as the starting position of the borrowed section, borrowing length, and recovery section settings need to be determined; for outside left-turn lanes, factors such as weaving section length and lane offset position need to be especially considered.

Future research should strengthen the development of robust design methods, enabling non-conventional lanes to adapt to a wider range of traffic flow fluctuations. Simultaneously, with the development of autonomous driving technology, traffic space design parameters also need to consider the driving characteristics of intelligent vehicles, researching new standards for traffic space design in human–machine mixed driving environments. Additionally, parameterized and modular design methods should be developed for rapid application and adjustment in different scenarios.

5.2. Signal Control Optimization

Signal control is key to the efficient operation of non-conventional lanes, requiring the formulation of corresponding control strategies for new traffic organization modes. Signal control for non-conventional lanes must consider not only the optimization of individual intersections but also achieve coordinated control with upstream and downstream intersections.

Li et al. [76] constructed a signal control optimization model using dynamic programming theory for the special needs of oversaturated intersections. Li et al. [77] proposed a multi-layer boundary active control strategy for oversaturated traffic networks. In signal control for non-conventional lanes, pre-signal control is an important research direction. Pre-signal settings need to consider coordination relationships with main signals, including phase difference optimization and green time allocation. For contraflow left-turn lanes, pre-signals need to be activated at appropriate times, ensuring both that left-turning vehicles can smoothly enter the borrowed section and avoiding serious conflicts with opposing through traffic. For variable lanes, signal control needs to achieve precise synchronization with lane function switching, ensuring the safety and efficiency of the switching process.

Future research should strengthen adaptive signal control algorithms, enabling systems to automatically adjust control parameters according to real-time traffic conditions. Simultaneously, balanced control strategies for multiple objectives should be researched, finding optimal balance points between efficiency, safety, equity, and other goals. Furthermore, considering the intelligent connected environment, new signal control modes under vehicle–road coordination conditions should be explored to achieve more precise traffic flow regulation.

5.3. Spatiotemporal Collaborative Optimization

Spatiotemporal collaborative optimization is the core concept of non-conventional lane design, aiming to achieve the best match between spatial layout and temporal control. Spatiotemporal collaboration is manifested not only in the integration of traffic space design and signal control but also in coordination among different traffic participants.

Zhang et al. [78] proposed an optimization method for dynamic switching and signal control of contraflow reversible lanes. Chen et al. [79] studied the layout optimization problem of variable lanes from a network perspective. The key to spatiotemporal collaborative optimization lies in establishing multi-dimensional optimization models, incorporating spatial design parameters (such as lane width, turning radius, transition section length) and temporal control parameters (such as signal cycle, green ratio, phase difference) into a unified optimization framework. Simultaneously, the passage needs of different transportation modes (motor vehicles, non-motorized vehicles, pedestrians) must be considered to achieve coordinated organization of multi-modal traffic. In selecting optimization objectives, traditional efficiency indicators must be considered alongside factors such as safety and environmental impact.

Spatiotemporal collaborative optimization research embodies systems engineering thinking, integrating originally separate design elements into a unified optimization problem. Existing research has made progress in model construction and algorithm development but still faces challenges in handling large-scale networks and real-time optimization. Future research should develop more efficient solution algorithms to apply spatiotemporal collaborative optimization to city-level traffic networks. Simultaneously, the handling of uncertainty factors needs to be strengthened to improve the robustness of optimization schemes. Additionally, dynamic spatiotemporal collaborative strategies should be researched to enable systems to adjust spatial configurations and temporal control parameters in real time according to changes in traffic states.

Current optimization models for non-conventional lanes exhibit limitations in addressing temporal uncertainties and real-time responsiveness. Linear and mixed-integer programming approaches, while mathematically rigorous and successful in specific applications (Liu et al. [15] achieving 9.63% delay reduction and 11.48% capacity increase), assume deterministic traffic conditions that inadequately represent real-world variability. These models struggle with temporal uncertainty handling, requiring substantial computational time for re-optimization that limits real-time applicability. Scalability becomes problematic as network complexity increases, creating computational bottlenecks that prevent city-wide implementation. Alternative optimization paradigms offer enhanced robustness and scalability potential. Robust optimization methods, demonstrated by Sun et al.’s [26] two-stage approach and Zhao et al.’s [35] robust design frameworks, address uncertainty while maintaining computational tractability. Dynamic programming approaches by Li et al. [76] show superior performance in oversaturated conditions, suggesting hierarchical optimization strategies for scalability enhancement. Machine learning integration enables predictive optimization that adapts to traffic pattern evolution, while distributed optimization algorithms facilitate real-time network-level coordination without centralized computational constraints. Stochastic programming frameworks accommodate arrival pattern variability, and multi-objective evolutionary algorithms balance competing objectives under uncertainty. These advanced paradigms represent essential methodological evolution for non-conventional lane optimization, enabling the transition from static design approaches to adaptive, real-time traffic management systems capable of responding to dynamic urban traffic demands.

5.4. Chapter Summary

This chapter systematically analyzed the optimization design and control technologies of non-conventional lanes from three aspects: traffic space design optimization, signal control optimization, and spatiotemporal collaborative optimization. Through in-depth analysis of existing research results, the key technologies and development trends of non-conventional lane optimization control have been revealed.

Table 2. Summary of research on optimization design and control methods for non-conventional lanes.

Research Direction	Core Content	Key Techniques	Main Results	Existing Challenges	Development Trends
Traffic Space Design Optimization	Space layout optimization	Combinatorial optimization models	Exit-lane left-turn design improves capacity by 6.1% per approach	Insufficient handling of randomness	Robust design methods
	Parameter calibration methods	Simulation parameter calibration	VISSIM model error controlled within 20%	High parameter sensitivity	Parametric design
	Design element integration	Multi-constraint solving	Established space-signal integrated optimization framework	Lack of standardized methods	Intelligent vehicle compatibility
	Safety considerations	Robust design	Established space-signal integrated optimization framework	Poor adaptability to intelligent vehicles	Modular application
Signal Control Optimization	Dynamic timing strategies	Dynamic programming	Oversaturated control reduces delay by 5%	High real-time requirements	Adaptive control
	Saturated state control	Multi-layer boundary control	Multi-layer control outperforms single-layer control	Difficult multi-objective trade-offs	Multi-objective balancing
	Network-level coordination	Real-time optimization	Achieved state-differentiated control objectives	Complex network coordination	Network-based coordination
	Multi-objective optimization	Adaptive algorithms	Achieved state-differentiated control objectives	Poor adaptation to sudden events	Resilience enhancement
Space–Time Coordinated Optimization	Design-control integration	Bi-level programming models	Dynamic control reduces delay by 6.7–14.9%	High computational complexity	High-efficiency algorithms
	Multi-dimensional coordination	Mixed integer programming	Network total travel time significantly reduced	Difficult large-scale solving	Real-time optimization
	Dynamic resource allocation	Nested algorithms	Established space–time coordination framework	Limited real-time optimization	Robust solution approaches
	System optimization	Dynamic optimization	Established space–time coordination framework	Weak uncertainty handling	Dynamic coordination

summarizes the main research progress in various aspects:

Through the analysis in this chapter, it can be seen that the optimization design and control methods for non-conventional lanes are developing towards more intelligent, refined, and systematic directions. From early static design and fixed control to current dynamic optimization and intelligent decision-making, technological advances have provided a broader space for the application of non-conventional lanes. Successful implementation requires a systematic approach encompassing pre-implementation assessment, pilot testing, and performance monitoring based on lessons learned from reviewed studies. The assessment phase should include comprehensive traffic volume studies across multiple time periods, evaluation of geometric constraints and sight distance requirements, assessment of local enforcement capabilities, and preliminary cost–benefit analysis using performance ranges documented in the literature. Implementation success depends critically on factors consistently identified across studies: comprehensive driver education programs that significantly affect adoption rates, enforcement capability that directly influences compliance and safety outcomes, geometric design quality adapted to site-specific conditions, and recognition that local traffic culture affects adaptation time and long-term effectiveness. The reviewed literature consistently recommends phased implementation, beginning with enhanced monitoring and signage, followed by performance evaluation using established metrics, parameter optimization based on observed behavior, and finally, permanent implementation with maintenance protocols. Success indicators should be measured against documented benchmarks from successful implementations, including driver adoption rates approaching those documented in the literature, safety performance meeting baseline conditions, and efficiency gains within documented ranges while maintaining violation rates within acceptable bounds established by field studies.

However, numerous challenges remain in practical applications, especially in large-scale network optimization, real-time response control, and system reliability assurance. Future research needs to focus more on engineering practice and system integration on the basis of theoretical innovation, promoting the industrialized application of non-conventional lane technology.

6. Typical Application Cases and Empirical Research

Research indicates that non-conventional lanes have progressed from conceptual exploration to practical application, playing a significant role in alleviating traffic congestion and improving road utilization efficiency. However, application experiences from different countries and regions have also revealed some common issues: safety considerations, driver adaptability, and system integration levels. Future application promotion should focus more on localized modifications, fully considering regional differences in traffic culture, driving habits, and management systems. Simultaneously, there is a need to establish standardized design specifications and implementation guidelines to create replicable and scalable application models. Additionally, international exchange and cooperation should be strengthened to learn from advanced experiences, avoid repetitive exploration, and promote the global development of non-conventional lane technology.

6.1. Implementation Effect Assessment

Before examining specific implementation cases, it is essential to establish a quantitative foundation for understanding the performance benefits achieved by different non-conventional lane types in practice.

Table 3. Performance comparison of different non-conventional lane types: effects on traffic delay, capacity, and emissions.

Non-Conventional Lane Type	Capacity Improvement	Delay Reduction	Emissions Reduction	Reference Studies
Contraflow Left-turn Lane (CLL)	Left-turn capacity increased by 20–30%; 11.48% capacity increase after optimization	9.63% average delay reduction after optimization	Not quantified in reviewed studies	Wu et al. [9]; Liu et al. [15]
Exit lanes for Left-turn (EFL)	6.1% capacity increase per additional approach; 1–5% increase per 5% left-turn ratio increase	1.2% delay reduction under low volumes; 5.1% queue length reduction	Not quantified in reviewed studies	Zhao et al. [20]; Zhao et al. [74]
Outside Left-turn Lane	Indirect capacity gains through 21.8% safety improvement compared to conventional intersections	Variable effects depending on weaving area length and traffic composition	Not quantified in reviewed studies	Guo et al. [17]; Cao et al. [18]
Tandem Intersections	18.6% intersection capacity increase	19.61% average delay reduction; 20.94% average queue length reduction; 22.9% delay reduction (alternative study)	CO emissions: −10.93%; NOx emissions: −12.97%	Zheng et al. [34]; Wan et al. [32]
Parallel Flow Intersections	Up to 70.51% capacity increase with four-direction configuration	Variable based on configuration scheme	Not quantified in reviewed studies	Song et al. [45]
Reversible Lanes	Variable based on demand patterns and real-time control	27.4% average delay reduction with real-time dynamic control	VOC, CO, and NOx emissions: −13.5% combined reduction	Mao et al. [25]
U-turn Design	29.15% travel time reduction compared to traditional U-turn design	66.70% delay reduction; 100% reduction in number of stops	Not quantified in reviewed studies	Shao et al. [38]
Dynamic Lane Assignment	Improved utilization efficiency but 22.86% saturation flow rate reduction for variable lanes	Variable effects depending on switching strategy and timing	Not quantified in reviewed studies	Zhao et al. [50]

synthesizes the documented performance improvements reported across the reviewed literature, providing empirical evidence of capacity enhancements, delay reductions, and emission benefits observed in field studies and controlled implementations. This comparative analysis demonstrates the practical effectiveness of non-conventional lanes and establishes benchmarks for evaluating implementation success.

Scientific effect assessment is an important link in validating theoretical results and guiding engineering practice. Through field data collection and analysis, multiple studies have verified the positive effects of non-conventional lanes.

Implementation effect assessment research has verified the positive role of non-conventional lanes in improving traffic efficiency and environmental quality through a large amount of empirical data. Existing assessments mainly focus on short-term effects and local indicators, with relatively insufficient evaluation of long-term benefits and systemic impacts. Future effect assessments should establish a more comprehensive indicator system that not only focuses on traffic operation indicators but also considers multi-dimensional factors such as socioeconomic benefits, user satisfaction, and system reliability. Simultaneously, long-term tracking assessments should be conducted to study the continuity and stability of non-conventional lane effects. Additionally, the standardization of assessment methods should be strengthened by establishing unified assessment frameworks and data collection specifications to make assessment results from different projects and regions comparable.

6.2. Summary of Experiences and Lessons

Experiences and lessons from practical applications provide valuable references for optimizing and improving non-conventional lanes. From the perspective of driver adaptability, the driving simulation experiments by Zhao et al. [19] revealed important behavioral characteristics. More importantly, even drivers unfamiliar with EFL operations could still choose to use traditional left-turn lanes, and this inclusive design ensured that the basic functions of the traffic system remained unaffected.

In terms of safety assurance, experiences summarized from multiple studies [10,36] indicate that safety issues of non-conventional lanes mainly focus on two aspects: controlling violation behaviors and managing speed differences. For violation behaviors, practice has proven that comprehensive application of engineering, education, and enforcement measures can achieve good results. In terms of engineering measures, optimizing sign and marking setups, increasing guidance information, and improving sight distance conditions can help drivers better understand traffic rules. In terms of education, raising public awareness and acceptance of non-conventional lanes through media campaigns, on-site guidance, and training courses can be effective. At the enforcement level, installing monitoring equipment and increasing penalties for violations creates an effective deterrent. For speed difference issues, measures such as properly setting speed limit signs, optimizing transition section designs, and implementing speed guidance can effectively reduce speed differences between different traffic flows and reduce traffic conflicts.

Optimization of traffic design parameters and signal timing is a key technical element in ensuring the successful operation of non-conventional lanes. Practical experience indicates that these parameters need to be fine-tuned according to actual traffic conditions and cannot simply apply standard values. For example, the length setup for contraflow left-turn lanes needs to comprehensively consider factors such as left-turn traffic volume, opposing traffic flow, and signal cycle; coordination between pre-signals and main signals needs to be optimized based on platoon arrival characteristics and queue dissipation patterns; switching timing for variable lanes needs to be dynamically determined based on real-time traffic data, and control strategies continuously adjusted and improved through ongoing data collection and analysis.

International Research and Implementation Perspectives: The current literature base reflects different regional research emphases and implementation contexts. North American contributions include Ma’s [24] comprehensive documentation of reversible lane operations in Washington DC, which identified safety and operational challenges, and Reid and Hummer’s [37] comparative analysis of seven non-conventional intersection designs across varying traffic scenarios. European theoretical contributions provide foundational frameworks for intersection optimization, as demonstrated by earlier works of Gallivan and Heydecker [54] and Improta and Cantarella [55]. Asian research, particularly from Chinese institutions, dominates the systematic evaluation literature due to extensive implementation programs and research investment responding to rapid urbanization challenges. This geographic distribution reflects both the active deployment of non-conventional lanes in high-density Asian urban environments and the relative scarcity of comprehensive evaluation studies from other regions. While fundamental operational principles appear universal across traffic contexts, implementation details clearly require adaptation to local traffic cultures, regulatory frameworks, and enforcement capabilities. The concentration of research in specific geographic regions highlights a critical knowledge gap: systematic international comparative studies are needed to distinguish between universal design principles and region-specific implementation requirements. Future research should prioritize cross-cultural validation of design guidelines and comparative effectiveness analysis across different traffic environments.

The summary of experiences and lessons indicates that the successful implementation of non-conventional lanes requires systematic solutions covering multiple levels, including technical design, social management, and public participation. Existing experiences mainly come from case studies, lacking systematic summarization and refinement. In the future, an experience-sharing mechanism should be established to form a best-practice library that provides references for similar projects. Simultaneously, failed case analyses should be conducted to deeply investigate the reasons for project failures and avoid repeating mistakes. Additionally, interdisciplinary cooperation should be strengthened to integrate and apply knowledge from fields such as traffic engineering, psychology, and sociology to form more comprehensive implementation plans. Particularly important is the establishment of an adaptive management framework that allows non-conventional lane projects to dynamically adjust according to actual operational conditions and external environmental changes, ensuring the realization of long-term benefits.

7. Future Development Trends and Research Prospects

7.1. Technology Development Trends

(1) Innovative Application Technologies of Non-conventional Lanes in Connected and Automated Vehicle Environment

The deep integration of connected and automated vehicle technology with non-conventional lanes will become an important development direction. Research by Wang et al. [51] and Zhang et al. [57] has already demonstrated the profound impact of autonomous driving and connected vehicle technologies on traffic flow characteristics. In a connected and automated vehicle environment, non-conventional lanes will transition from passive adaptation to active guidance. Through vehicle–infrastructure cooperation technology, precise prediction and control of vehicle trajectories can be achieved, making the function switching of non-conventional lanes smoother and more efficient. The real-time dynamic control implemented by Mao et al. [25] and Zhou et al. [67] in intelligent vehicle–road cooperative environments provides technical validation for this development direction. In the future, based on 5G communication, edge computing, and other technologies, non-conventional lanes will construct intelligent systems integrating perception, decision-making, and control, achieving rapid response and precise control.

(2) Demand-Responsive Dynamic Lane Function Setting Technology

The transition from static design to dynamic response is an inevitable trend in the development of non-conventional lanes. Current research [26,27,67,80] has already made significant progress in dynamic control, but it remains limited to preset scenarios and fixed patterns. Future non-conventional lanes will possess stronger environmental perception capabilities and adaptive abilities, capable of dynamically adjusting lane functions and control strategies according to factors such as real-time traffic conditions, weather conditions, and emergent events. This technological progression builds upon the three-phase development evolution, where each phase contributed essential foundations for current advancement. The transition from manual reversible lane operations to intelligent adaptive systems represents a fundamental shift in spatiotemporal resource management philosophy. CAV technologies and dynamic lane allocation methods advance this evolution further, enabling real-time demand-triggered activation supported by predictive algorithms and multi-objective optimization frameworks that simultaneously balance efficiency, safety, and environmental considerations. Future development will continue this trajectory toward fully autonomous traffic management systems. The integration of autonomous vehicles with non-conventional lane geometries presents both synergistic opportunities and compatibility challenges requiring systematic infrastructure redesign. AV path planning algorithms achieve enhanced performance through trajectory precision that enables aggressive utilization of contraflow sections and variable lane configurations, while vehicle–infrastructure communication facilitates synchronized movements that eliminate human hesitation factors. However, geometric incompatibility arises from path planning complexity, where current algorithms optimized for conventional layouts struggle with non-conventional geometric irregularities, sensor limitations in complex transition zones, and infrastructure predictability requirements that demand consistent geometric parameters. Infrastructure redesign strategies must focus on geometric standardization with consistent turning radii and transition lengths, enhanced marking systems using machine-readable lane demarcation, and communication integration enabling real-time geometric parameter transmission to approaching vehicles. Advanced sensor-friendly designs incorporating dedicated AV guidance infrastructure, standardized geometric configurations that minimize algorithm adaptation requirements, and redundant positioning systems for navigation reliability represent essential elements for AV-compatible non-conventional lane implementation. These modifications will enable seamless integration while preserving the operational benefits of innovative intersection designs. Dynamic spatiotemporal real-time control strategies represent the next evolutionary step for non-conventional lane systems, enabling adaptive response to unforeseen disturbances, including weather conditions, traffic incidents, and emergency scenarios. The framework integrates multi-layered sensing networks, predictive analytics, and machine learning algorithms for autonomous decision-making. Reinforcement learning agents optimize lane function switching based on real-time reward functions incorporating efficiency, safety, and environmental objectives, while deep learning models provide pattern recognition for disturbance prediction and impact assessment. Computational requirements include edge computing architectures for millisecond response times, distributed sensor networks providing comprehensive situational awareness, and robust communication protocols ensuring system reliability during disruptions. Input data streams encompass traffic sensors, weather monitoring systems, incident detection feeds, and vehicle–infrastructure communication channels, enabling real-time state estimation and predictive modeling. Implementation demands multi-objective optimization algorithms, uncertainty quantification methods, and fail-safe mechanisms ensuring graceful degradation during system limitations.

(3) Network-Level Intersection Traffic Design and Control Coordination Optimization Technology

The optimization of non-conventional lanes will extend from individual intersections to the network level of intersections. The network design method proposed by Di [81] indicates this development direction. Future research will place more emphasis on the systemic effects of non-conventional lanes in road networks, achieving unity between local optimization and global optimum through the establishment of multi-level, multi-scale optimization models. In urban traffic networks, non-conventional lanes will serve as key nodes, forming an organic whole with conventional roads and achieving balanced distribution and efficient operation of network traffic through coordinated control.

Technology development trends indicate that non-conventional lanes are evolving toward more intelligent, refined, and systematic directions. The application of connected and automated vehicle technologies will fundamentally change the operational mode of non-conventional lanes, transforming them from static infrastructure to dynamic, intelligent systems. However, technological progress also brings new challenges, including increased system complexity, higher security requirements, and an urgent need for unified standards and specifications. Future efforts need to strengthen interdisciplinary research, integrating the latest achievements from fields such as traffic engineering, artificial intelligence, and communication technology to promote innovative development of non-conventional lane technology. Simultaneously, attention should be paid to the implementability and economics of technology, ensuring that advanced technologies can be truly applied in practice and generate actual benefits.

7.2. Theoretical Research Directions

Specific Theoretical Deficiencies: Current research lacks (1) multi-scale traffic flow theory integrating microscopic lane-changing behavior with macroscopic intersection performance in non-conventional environments, (2) robust control theory for dynamic lane systems under demand uncertainty, (3) network-level impact theory predicting system-wide effects of local non-conventional implementations, and (4) human–machine interaction theory for connected vehicle integration with variable infrastructure.

Future theoretical research will focus on constructing a complete theoretical system for non-conventional lane design and control, specifically including the following:

(1) Spatial–Temporal Relationship Reconstruction Patterns and Adaptability Assessment Theory for Non-conventional Lanes

Revealing the reconstruction patterns of intersection traffic spatial–temporal relationships after introducing non-conventional lanes is a key scientific issue that needs to be addressed. Future work needs to construct a unified theoretical framework for non-conventional lane design, integrating existing research results [58,63,71]. This theoretical system should include a classification system and design criteria for non-conventional lanes, a theoretical foundation and methodology for adaptability assessment, mathematical models and optimization algorithms for dynamic conversion mechanisms, and theoretical frameworks for coordinated control strategies. Particularly important is the establishment of a general theory for spatial–temporal resource allocation of non-conventional lanes, revealing the common patterns and individual characteristics of different types of non-conventional lanes and providing theoretical guidance for the systematic design.

(2) Optimal Allocation Theory of Spatial–Temporal Passage Resources Under Mixed Traffic Flow Conditions

Analyzing the optimal allocation mechanism of spatial–temporal passage resources for intersection non-conventional lanes oriented to mixed traffic flow will become an important research direction [34,35,59,70]. Traditional single-objective optimization can no longer meet the needs of complex traffic systems, requiring the discovery of optimal balance among multiple objectives such as efficiency, safety, environment, and fairness. Future research should develop new multi-objective optimization theories and algorithms, particularly addressing issues such as conflicts between objectives, dynamic adjustment of weights, and robust optimization under uncertainty. Simultaneously, the interpretability of multi-objective optimization results should be studied to help decision-makers understand the trade-offs between different schemes.

(3) Coordinated Optimization Theory of Intersection Non-conventional Lanes and Signal Control

The coordinated optimization theory of non-conventional lanes and signal control needs to be strengthened, requiring research on spatial–temporal coordinated integration of phases, phase sequences, green ratios, and green intervals for motor vehicles, non-motorized vehicles, and pedestrian traffic, as well as optimal signal timing methods for phase difference coordination with related intersections. Mechanism research at the microscopic level is the foundation for macroscopic optimization [12,13,23,50]. Future research needs to further explore the evolution patterns of mixed traffic flow in non-conventional lane environments, behavioral characteristics and adaptation processes of different types of drivers, interaction mechanisms under human–machine mixed driving conditions, and self-organizing characteristics of traffic flow under abnormal events. Especially in a connected and automated vehicle environment, traditional traffic flow theory needs to be modified and extended to adapt to new technological conditions.

Discussion of theoretical research directions indicates an urgent need to establish a systematic theoretical system in the field of non-conventional lanes to guide engineering practice and technological innovation. Although existing theoretical research has achieved breakthroughs in certain aspects, it remains overall in an exploratory stage, lacking a universally applicable theoretical framework. Future theoretical research should emphasize fundamentality, foresight, and systematicity, addressing current practical problems while also reserving space for future technological development. Simultaneously, theory–practice integration should be strengthened, verifying and perfecting theoretical models through empirical research and forming a virtuous interaction between theoretical innovation and application innovation.

8. Conclusions and Discussion

8.1. Discussion

A comprehensive analysis of the research status in the field of non-conventional lanes shows that significant progress has been made in concept definition, pattern classification, and effect assessment of non-conventional lanes from both theoretical and application perspectives, providing important support for refined urban traffic management. However, due to the faster pace of non-conventional lane application promotion compared to theoretical research progress, further improvements are needed to support the high-quality development of urban traffic:

(1) The systematic evaluation system for applicable conditions of non-conventional lanes needs improvement. Existing research has achieved rich results in the effect assessment of different types of non-conventional lanes, but adaptability research for diverse urban road characteristics needs to be deepened. Although there are evaluation methods for specific types of non-conventional lanes, a unified analysis framework and comprehensive evaluation system have not yet been formed, requiring further optimization to support locally appropriate scheme selection and scientific assessment. The “trade-off” phenomenon appearing in practice (such as insufficient exit lane capacity after right-placing some left-turn lanes, intensified traffic conflicts, etc.) indicates that improving applicable condition evaluation methods has important practical significance.

(2) The lane function conversion mechanism under dynamic traffic demand still needs in-depth research. Existing research has confirmed the feasibility and necessity of dynamic optimization configuration of lane functions, and practice has also achieved positive effects. However, facing complex and variable urban traffic demands, the decision-making mechanism for conventional–non-conventional lane function conversion still needs further research. Current research on conversion trigger conditions, conversion process stability assurance, and multi-objective balance is relatively weak. There is an urgent need to establish a lane function conversion theoretical model considering efficiency and safety coordination to support scientific decision-making in practical applications.

(3) The coordinated optimization theory of non-conventional lanes and signal control needs to be strengthened. Existing research has achieved rich results in non-conventional lane design and signal control, respectively, but their coordinated optimization research needs to be further deepened. In practice, because non-conventional lanes change the traffic organization mode of intersections, traditional signal control methods often find it difficult to fully exert their effectiveness. How to optimize non-conventional lane spatial design and signal time control as a unified system, achieving optimal allocation of spatial–temporal resources, is an important direction for promoting theoretical development in this field. At the same time, the impact of non-conventional lanes on driving behavior and their interactive relationship with traffic operational efficiency also needs further systematic research. Compatibility with driver driving habits needs to be strengthened to enhance the practical application effect of non-conventional lanes.

In view of this, future research is proposed to focus on the following three aspects:

(1) Priority 1 (Short-term: 1–2 years)—Fundamental Theory Development: Operational Characteristic Analysis and Adaptability Assessment of Typical Intersection Non-Conventional Lanes. Select typical non-conventional lane forms with more practical applications, such as contraflow left-turn lanes, variable lanes, and right-placed left-turn lanes; analyze their traffic organization and channelization mechanisms; construct a multi-dimensional adaptability evaluation indicator system covering traffic efficiency, safety, etc.; develop scenario-based analysis models; form methodological tools for quantitatively evaluating the applicable conditions of non-conventional lanes; and provide the basis for non-conventional lane setting. This priority addresses the immediate need for systematic evaluation frameworks identified in challenge (1) above.

(2) Priority 2 (Medium-term: 2–4 years)—Advanced Control Systems: Conversion Mechanism and Optimization Method of Conventional–Non-Conventional Lanes Adapting to Dynamic Demand Changes. Research the decision-making mechanism for dynamic switching of conventional–non-conventional lane functions in response to the unbalanced spatial–temporal distribution of traffic demand; construct a demand-responsive lane resource optimization allocation model; propose a multi-objective dynamic optimization method integrating traffic prediction; and balance traffic efficiency with fairness, safety, and feasibility. This priority directly tackles challenge (2) regarding lane function conversion mechanisms and requires the theoretical foundation from Priority 1.

(3) Priority 3 (Long-term: 3–5 years)—Large-scale Implementation: Empirical Application and Effect Assessment of Non-conventional Lanes in Typical Scenarios at Urban Road Intersections. Select typical road sections to conduct engineering implementation and operation effect tracking assessment of comprehensive non-conventional lane schemes. Compare and analyze traffic operation data before and after implementation, extract key elements of optimization design and dynamic management and control, and form decision-reference, operationally strong standards and specifications. This priority addresses the coordinated optimization challenges identified in challenge (3) and provides the foundation for widespread practical implementation.

This prioritization reflects both the logical research progression from fundamental theory to advanced applications and the practical urgency of addressing current implementation challenges in the field.

8.2. Conclusions

This paper systematically reviews the research progress on non-conventional lane setting and control coordination optimization at urban road intersections. Through in-depth analysis of various non-conventional lane forms such as contraflow left-turn lanes, outside left-turn lanes, exit lanes for left-turn, and variable lanes, it summarizes the positive effects of non-conventional lanes in enhancing capacity, improving safety, and reducing delays. Research shows that non-conventional lanes, as an innovative traffic organization method, provide new ideas and approaches for solving urban traffic congestion problems. The main conclusions of this paper are as follows:

(1) Non-conventional Lanes Have Formed a Relatively Complete Technical System and Application Framework

Through systematic review of domestic and international research progress, this paper finds that non-conventional lane design has developed from early single forms to a comprehensive system containing multiple forms, including contraflow left-turn lanes, outside left-turn lanes, variable lanes, and tandem intersections. These designs realize the reconfiguration of intersection spatial–temporal resources by changing the traditional “left-straight-right” static layout. Research shows that non-conventional lanes can significantly enhance intersection capacity and ensure traffic safety under reasonable design. These results fully demonstrate the important value of non-conventional lanes in solving urban traffic problems.

(2) Spatial–Temporal Relationship Reconstruction is the Theoretical Foundation of Non-conventional Lane Design

This paper deeply analyzes the reconstruction patterns of intersection traffic spatial–temporal relationships after introducing non-conventional lanes. Research finds that the introduction of non-conventional lanes not only changes motor vehicle traffic patterns but also affects the right-of-way allocation for non-motorized vehicles and pedestrians, fundamentally changing the relationships of mixed traffic flow within intersections. This reconstruction involves the longitudinal and transverse matching of entrance and exit lanes and lane function conversion organization in the spatial dimension, signal timing optimization and traffic order reconstruction in the time dimension, and traffic conflict identification and management in the safety dimension. By establishing a mixed traffic flow right-of-way connection model, the paper reveals the impact mechanism of non-conventional lanes on the utilization efficiency of intersection spatial–temporal resources.

(3) Adaptability Assessment and Dynamic Response are Key to Practical Application

This paper constructs a multi-dimensional evaluation system including applicable condition analysis, traffic efficiency evaluation, safety assessment, and environmental and social benefits, providing a scientific basis for whether non-conventional lanes “should be set up”. It establishes a demand-responsive lane function dynamic conversion mechanism, addressing the key issue of “when and where to set up”. Research shows that successful implementation of non-conventional lanes requires comprehensive consideration of multiple factors such as traffic demand characteristics, geometric space constraints, and driver adaptability, and actively responds to traffic demand changes through dynamic control strategies. This transition from static design to dynamic response is an important guarantee for enhancing the practical application effect of non-conventional lanes.

(4) Coordinated Optimization of Intersection Spatial–Temporal Right-of-Way is the Inevitable Choice for Enhancing System Efficiency

Coordinated optimization of non-conventional lanes and signal control is key to maximizing system efficiency. Analysis in this paper shows that incorporating lane function configuration and signal control parameters into a unified optimization framework can achieve optimal allocation of spatial–temporal resources. By establishing a spatial–temporal coordinated integration mechanism, the paper studies the optimized configuration of control parameters such as phases, phase sequences, green ratios, and green intervals, as well as coordinated control strategies with related intersections. Empirical research proves that coordinated optimization can significantly enhance intersection operational efficiency while ensuring safety.

The above research purposefully focuses on key scientific issues and technical bottlenecks in the optimization design and refined management of non-conventional lanes. It is expected to not only consolidate the theoretical foundation but also promote the refinement and precision of urban traffic governance systems and governance capabilities with innovative solutions, providing technological support for alleviating “urban traffic diseases” and promoting urban traffic development.