Search Results (81)

Traditional location models for Park-and-Ride (P&R) facilities are constrained by the Independent and Identically Distributed (IID) assumption, failing to simultaneously capture inter-modal substitution elasticity and spatial path overlap, which leads to systematic demand forecasting biases. To address this gap, this study proposes an integrated Cross-Nested Logit (CNL) and Paired Combinatorial Logit (PCL) behavioral kernel within a bi-level programming framework, where the upper level minimizes total system generalized cost and the lower level simulates multi-modal Stochastic User Equilibrium (SUE). A hybrid GA-MSA solution strategy is developed. Experiments on the classic Sioux Falls benchmark network demonstrate that the proposed model identifies the optimal construction scale (N = 3) and the critical parking fee threshold (65 CNY) for mode shift. Compared to the un-nested MNL-PCL formulation, the integrated CNL-PCL framework provides an 11.75% downward behavioral correction in P&R market-share estimation, effectively counteracting the overestimation tendency inherent in conventional architectures. The optimal spatial layout (Nodes 4, 6, and 19) achieves a 54.40% share for “P&R + Public Transport” green modes and yields an annual net CO₂ mitigation of 957 tons. These findings confirm that synergistically characterizing mode correlation and path overlap provides a more prudent foundation for sustainable P&R planning. The proposed framework is also generalizable to other multi-modal facility location problems, such as transit-oriented hub sizing or electric vehicle charging network planning. Full article

With rapid urbanization and increasing motorization, understanding the impact of parking facilities on urban metro ridership is crucial for alleviating traffic congestion and promoting public transport priority strategies. However, few studies have systematically examined the influence of built environment characteristics, especially parking facilities, on metro ridership. To address this research gap, this study utilizes metro ridership data and parking facility data, and employs a gradient boosting regression tree (GBRT) model to analyze the relationship between built environment factors (including parking) and metro ridership. Additionally, accumulated local effects (ALE) plots are used to reveal nonlinear effects and interaction patterns. The empirical results demonstrate that parking space density has a significant nonlinear influence on metro ridership. Furthermore, a clear threshold effect is observed in the joint impact of parking space density and distance to the central business district (CBD), providing valuable theoretical and practical insights for optimizing park and ride (P+R) facility planning around metro stations. These findings contribute to a deeper understanding of the interplay between built environment factors and metro ridership, offering evidence-based guidance for sustainable urban transport planning. Full article

The widespread integration of wind energy conversion systems has fundamentally reshaped modern power grid architecture. However, the limited dynamic response of wind turbine (WT) converters during grid faults—particularly their inability to provide sufficient reactive current and maintain voltage stability under severe dips—necessitates a redefinition of the conventional low-voltage ride-through (LVRT) curve. This study addresses this challenge by proposing a Mutation-Adaptive Mean Variance Mapping Optimization (A-MVMO) algorithm for the control of grid-side converters (GSCs) in wind farms (WFs). To systematically assess post-fault voltage recovery, a Time-Segmented Analysis for Voltage Recovery (T-SAVR) approach is developed with a multi-objective function. The performance of the proposed A-MVMO is benchmarked against standard MVMO and conventional particle swarm optimization (PSO) under both moderate (0.7 pu) and severe (0.15 pu) voltage dips using the IEEE 39-bus system implemented in DIgSILENT/PowerFactory. The results demonstrate that A-MVMO achieves fast, oscillation-free voltage recovery with negligible overshoot (<1%) and lower current injection than PSO and MVMO, while satisfying all engineering constraints. Moreover, the co-optimization of Park-level and turbine-level controllers ensures seamless coordination, as evidenced by the close tracking between the farm-wide reactive power reference and the aggregated turbine response. The T-SAVR method proves essential for focusing optimization on controllable recovery dynamics, yielding a superior LVRT curve. Full article

Against the background of carbon neutrality, the government’s carbon regulations have had a profound impact on the distributed energy sharing behavior of industrial parks. To deeply explore the interactive relationship between distributed energy sharing in industrial parks and government regulation, this paper constructs a three-party evolutionary game model composed of the government, core enterprises and supporting enterprises; endogenizes government behavior; and integrates inter-enterprise contractual mechanisms into the evolutionary framework. By establishing a revenue payment matrix and a replication dynamic equation, the stability conditions and system evolution paths of the strategy choices of each subject are analyzed, and numerical simulations are conducted. The results show that there are multiple evolutionary stable equilibria in the system, among which the equilibrium where core enterprises actively share, supporting enterprises actively share, and the government actively regulates carbon is the ideal state. Cost-sharing contracts and cooperative penalty contracts play a significant role in promoting the participation of supporting enterprises in sharing and curbing “free-riding” behavior, respectively. The changes in government subsidy rates and carbon tax rates have a crucial impact on the evolution of corporate strategies. Quantitatively, the carbon tax rate exhibits a threshold effect; enterprises shift to positive energy sharing when the tax rate exceeds 0.8, while a subsidy rate above 0.4 leads the government to withdraw from regulation. This indicates that a reasonable design of carbon regulations can help achieve coordinated energy emission reduction between the government and enterprises. The findings provide theoretical support for optimizing carbon regulations and designing cooperation strategies. Full article

The effort to reduce the intensity of car traffic in city centres is among the core objectives of sustainable development. One important means of achieving this aim is the creation of Park-and-Ride facilities. This article examines the challenges encountered during the planning and construction of a Park-and-Ride designed to ease the transport burden of a larger city, yet situated on the edge of a small historic town in Poland. Using a research-through-design method, the study identifies the project’s challenges. The article highlights the overlooked issue of locating Park-and-Ride schemes within sensitive contexts. The accompanying interventions enabled the realisation of an undertaking, originally conceived as a strictly engineering investment fulfilling global policy objectives, but ultimately adapted to manage local priorities. The pursuit of sustainable transport development thus became an opportunity to foreground the dual role of transport spaces: both as organisers of movement and as educators in conveying cultural meaning. The project serves as an example of how local problems may be addressed through investments framed as advancing global political goals. The Park-and-Ride in Stary Sącz also provides material evidence of the significance of decisions made by local authorities to resolve local challenges while contributing to global goals. Full article

Bike-sharing services contribute to reducing emissions and conserving natural resources within urban transportation systems. They also promote public health by encouraging physical activity and generate economic benefits through shorter travel times, lower transportation costs, and decreased demand for parking infrastructure. This paper examines the use of shared micro-mobility services in the Italian cities of Florence and Bologna, based on an analysis of GPS origin–destination data and associated temporal coordinates provided by the RideMovi company. Given the still-limited number of studies on free-floating and electric-scooter-sharing systems, the objective of this work is to quantify the performance of electric bikes and e-scooters in bike-sharing schemes and compare it to traditional, muscular bikes. Trips were reconstructed starting from GPS data of origin and destination of the trip with a shortest path criteria that considers the availability of bike lanes. Results show that e-bikes are from 22 to 26% faster on average with respect to muscular bikes, extending trip range in Bologna but not in Florence. Electric modes attract more users than traditional bikes, e-bikes have from 40 to 128% higher daily turnover in Bologna and Florence and e-scooters from 33 to 62% higher in Florence with respect to traditional bikes. Overall, turnover is fairly low, with less than two trips per vehicle per day. The performance is measured in terms of trip duration, speed, and distance. Further characteristics such as daily turnover by transport mode are investigated and compared. Finally, spatial analysis was conducted to observe demand asymmetries in the two case studies. The results aim to support planners and operators in designing and managing more efficient and user-oriented services. Full article

Vehicle congestion and the environmental problems associated with the increasing vehicle fleet have led stakeholders to create solutions to these problems. Park-and-Ride (P&R) facilities are provided as a solution for public transportation to avoid increasing vehicular flow and using private vehicles. However, the optimal location of these facilities is still a challenge to be considered. Therefore, this article aims to present a systematic review of the mathematical models applied for P&R localization, using the PRISMA protocol to ensure a comprehensive analysis. A total of 44 articles between 2002 and 2025 were identified into four categories: decision support models, econometric models, optimization models, and other models. The review also examines the term distribution of urban contexts where the mathematical models are applied, distinguishing between Global North versus Global South urban contexts. The results showed the efficiency of mathematical models within the decision support models category due to their integration with multiple criteria. The econometric models analyze factors influencing user behavior, while the optimization models improve and optimize the efficiency of transport networks despite facing computational challenges. Finally, other models, such as multilevel programming and fuzzy logic, offer adaptive solutions for highly variable urban environments. The primary contribution of this study is its comprehensive application of the mathematical models used for the location of P&R facilities. This offers a systematic approach for anticipating future urban situations, developing supporting policies, and analyzing their effects. Full article

In the context of big data and intelligent connectivity, optimizing scheduled bus dispatch can enhance urban transit efficiency and passenger experience, which is vital for the sustainable development of urban transportation. This paper, based on existing fixed bus stops, integrates traditional demand-responsive transit and travel booking models, considering the spatiotemporal variations in scheduled travel demands and passenger flows and addressing the combined scheduling issues of fixed-capacity bus models and skip-stop strategies. By leveraging intelligent connected technologies, it introduces a dynamic grouping method, proposes an intelligent connected bus dispatching model, and optimizes bus timetables and dispatch control strategies. Firstly, the inherent travel characteristics of potential reservation users are analyzed based on actual transit data, subsequently extracting demand data from reserved passengers. Secondly, a two-stage optimization program is proposed, detailing passenger boarding and alighting at each stop and section passenger flow conditions. The first stage introduces a precise bus–traveler matching dispatch model within a spatial–temporal–state framework, incorporating ride matching to minimize parking frequency in scheduled travel scenarios. The second stage addresses spatiotemporal variations in passenger demand and station congestion by employing a skip-stop and bus operation control strategy. This strategy enables the creation of an adaptable bus operation optimization model for temporal dynamics and station capacity. Finally, a dual-layer optimization model using an adaptive parameter grid particle swarm optimization algorithm is proposed. Based on Beijing’s Route 300 operational data, the simulation-driven study implements contrasting scenarios of different bus service patterns. The results demonstrate that this networked dispatching system with dynamic vehicle grouping reduces operational costs by 29.7% and decreases passenger waiting time by 44.15% compared to baseline scenarios. Full article

Traffic calming measures are implemented more and more often in residential districts as part of home zone sustainability projects. For economic reasons, road humps are the most commonly used traffic calming measures to slow down the traffic within the home zone. Prefabricated units or concrete pavers are the materials of choice for their construction. The studies carried out so far on many different road hump types covered the effect of height, approach/departure ramp inclination(s), and intervals between successive humps on the final speed and the safety of road traffic. The impacts of braking before and acceleration after passing a hump on the pavement and the effect of the associated shocks on the riding comfort of both drivers and passengers and vehicle suspension were also investigated. What is missing in the available literature is information on the slowing effect of road humps depending on the longitudinal gradient of the street and the street’s landscaping. This article is intended to fill this gap by presenting the results of speed surveys carried out on three selected two-way streets located in home zones with different longitudinal gradients and a few humps of different designs that are placed at different intervals. Speeds were measured both before and after each of the successive humps. The “after” speeds were found to depend not only on the hump type and parameters but also on the direction of travel, vertical alignment of the street, parking location, and orientation of the parking space relative to the road axis. Full article

With the continuous increase in car ownership, alleviating traffic congestion and reducing carbon emissions have become key challenges in urban traffic management. This study constructs a multi-agent model to evaluate the impact of various traffic optimization interventions on citizens’ travel behavior and traffic carbon emission levels. Different from previous mathematical models, this model integrates computer technology and geographic information systems, abstracting travelers as agents with self-control capabilities who can make independent decisions based on their own circumstances, thus reflecting individual differences in travel behavior. Using the real geographical and social environment of the high-density travel area in Xiaodian District, Taiyuan City as a case study, this research explores the overall improvement in the urban transportation system through the implementation of multiple traffic optimization interventions, such as a parking reservation system, the promotion of the park-and-ride mode, and the optimization of public transportation services. Studies have demonstrated that, compared to reducing bus fares, travelers exhibit a greater sensitivity to waiting times. Reducing bus departure intervals can increase the proportion of park-and-ride trips to 25.79%, surpassing the 19.19% increase observed with fare adjustments. A moderate increase in the proportion of reserved parking spaces can elevate the public transport load to 49.85%. The synergistic effect of a combined strategy can further boost the public transport share to 50.62%, while increasing the park-and-ride trip proportion to 33.6%, thereby highlighting the comprehensive benefits of implementing multiple strategies in tandem. When the parking reservation system is effectively implemented, carbon dioxide emissions can be reduced from over 800 kg to below 200 kg, and the proportion of vehicle cruising can decrease from over 20% to under 15%. These results underscore the critical role of the parking reservation strategy in optimizing traffic flow and advancing environmental sustainability. Full article

This study aimed to quantify the postures and muscle activity while parks and gardens workers operated ride-on mowers during a typical shift. Eight participants operated ride-on mowers in the same park but on different terrains (flat and undulating). Body postures and muscle activity were collected wirelessly and unobtrusively. Participants adopted a forward-flexed seated posture with the predominant movement being head rotation. Oscillatory movements (20–40° from neutral) of the thorax in all three planes of movement were noted in all participants. Low levels (<30% MVIC) of muscle activity were recorded in all muscles tested. These levels were elicited for most (>90%) of the recording time. Higher (>50% MVIC) activation levels were interspersed through the data, but these were not sustained. There was no difference in posture or muscle activity between the flat and undulating terrain. The forward-flexed posture combined with vibration can increase the risk of discomfort and injury in the low back while ride-on mowing. The low levels of muscle activity suggest participants did not actively brace for the occupational situation and task. The large inter-participant difference in posture attests to subjective variation to accommodate muscular stress, and this may not be optimal for injury mitigation. Full article

The park-and-ride (P&R) system is crucial for urban development and mobility as its strategic location helps to reduce congestion, reduce pollution, and encourage the use of public transport. Various methods have been proposed to determine its optimal location, ranging from algorithms and mathematical equations to multi-criteria approaches that consider a set of criteria and sub-criteria. Multi-criteria methods are diverse, and it is essential to know which methods have been applied to the optimal location of a P&R system. This study addresses the existing gaps in multi-criteria methods used in the localization of a P&R system through a systematic review based on the PRISMA protocol, examining 25 articles published between 2014 and 2024 in Science Direct, Scopus, and Web of Science (WOS). The results highlight that the multi-criteria AHP method is the most relevant and widely used. The criterion of accessibility to public transport is the most important criterion for setting up a P&R system in an urban environment. The flexibility of the multi-criteria AHP method, combined with other factors, makes it relevant in the process of P&R locations. However, the multi-criteria methods found in this research show that a wide range of multi-criteria methods have not yet been applied. Future research should focus on developing comprehensive systems that combine multiple multi-criteria methods, which is essential to optimize mobility solutions adapted to the specific characteristics and objectives of each city in establishing a P&R system. Full article

Public transportation is essential for improving urban mobility, enhancing travel quality, reducing reliance on private vehicles, and alleviating traffic congestion. However, inadequate public transportation in outer Melbourne is a significant issue limiting urban development. While existing research primarily focuses on walking distance to define service catchments, commuters in transit-disadvantaged or outlying urban areas often drive to transit, noted as the park-and-ride mode. This research uniquely examines drive-distance catchments for park-and-ride transit accessibility in outer Melbourne, using spatial SQL and GIS techniques to provide a detailed, multi-dimensional analysis of population coverage, parking capacity, and accessibility gaps. This approach fills a gap in the existing literature by offering adaptable insights and approaches to other outer urban areas with transit disadvantages. The findings underscore the necessity for targeted enhancements in public transportation in outer Melbourne: Most of the outer residents concentrate near the train stations, though significant spatial gaps exist; The general accessibility status of residential mesh blocks is found; Parking capacity varies with high tension found at certain stations. This study contributes insights to create more equitable and sustainable transportation systems by providing a detailed spatial analysis of current transit coverage and identifying critical gaps. Full article

Connected and automated vehicles (CAVs) are poised to revolutionize mobility. The relocation feature of CAVs enhances parking convenience for the public. Users can instruct CAVs to arrive at their work destination, drop them off, and then assign CAVs to a cost-effective parking facility through an optimized itinerary. However, realizing the benefits of CAVs depends on user acceptance, and the impact of relocation features on CAV acceptance remains an area that is yet to be explored. This study introduces a novel acceptance model to mainly investigate the effects of relocation-related factors on CAV acceptance through 717 valid responses. The results indicate that the perceived convenience of relocation (PCOR) indirectly increases human acceptance through three determinants, initial trust, perceived usefulness (PU), and perceived ease of use (PEOU), while initial trust, PU, and PEOU directly increase human acceptance. The public expectations of saving on parking fees (EOSPF) can enhance PCOR. Additionally, a multigroup analysis revealed that PCOR exerts a more positive impact on PU or PEOU in subgroups including males, pre-Generation-Z individuals, experienced drivers, and those with autopilot riding experience. The findings on mediators are also discussed. This study provides valuable insights for further research and the practical adoption of emerging CAVs. Full article

Traffic problems in China’s river–valley-type cities are prominent. In order to solve these traffic problems, this paper presents four aspects of motorists’ terrain spatial perception according to the characteristics of river–valley-type cities. Based on the structural equation model (SEM), four-dimensional terrain spatial perception is reduced by second-order confirmatory factor analysis. The SEM–Logit model was constructed to analyze the influences of individual socioeconomic attributes, objective built-environment attributes, travel characteristics, and terrain spatial perception on Park and Ride (P&R) use behavior, as well as the moderating effects of terrain spatial perception. The results show that the four latent variables can explain the terrain spatial perception of motorists in river–valley-type cities well. Objective built environments and motorists’ subjective terrain spatial perception have significant impacts on the use of P&R facilities in river–valley-type cities. The terrain spatial perception of motorists in a river–valley-type city moderates the impact of work–residence distance, road slope, river crossing demand, group travel, departure time, and the time saved on P&R use behavior. The research results can provide some reference for solving traffic problems in river–valley-type cities. Full article