Submit to Sustainability Review for Sustainability Propose a Special Issue

Journal Menu

Journal Browser

Innovative and Sustainable Planning, Control and Optimization Methods for Urban Transportation System

Print Special Issue Flyer
Special Issue Editors
Special Issue Information
Keywords
Benefits of Publishing in a Special Issue
Published Papers

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Transportation".

Deadline for manuscript submissions: closed (2 July 2025) | Viewed by 20439

Share This Special Issue

Special Issue Editors

Prof. Dr. Yiming Bie

E-Mail Website
Guest Editor

School of Transportation, Jilin University, Changchun 130022, China
Interests: advanced transit operations; traffic design and control
Special Issues, Collections and Topics in MDPI journals

Dr. Hu Zhang

E-Mail
Guest Editor

School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255000, China
Interests: traffic operation optimization; traffic engineering

Dr. Shidong Liang

E-Mail Website
Guest Editor

Business School, University of Shanghai for Science & Technology, Shanghai 200093, China
Interests: urban transit planning and operation; traffic control
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The question of how to improve the sustainability of transportation has always been a hot topic. On the one hand, urban residents hope to improve the efficiency of the transportation system in order to reduce travel time. Conversely, transportation systems inevitably produce carbon emissions and affect the social environment. As such, scholars must propose more innovative methods for urban transportation systems in order to improve the efficiency and sustainability simultaneously. In recent years, the ownership of electric vehicles and connected autonomous vehicles has continued to increase, which can not only significantly reduce the carbon emissions of vehicles, but also make urban transportation smarter. With the application of big data and artificial intelligence technology in the transportation field, more innovative planning, control and operation optimization methods have emerged.

To make the urban transportation system safer, more efficient and low carbon, we must develop innovative methods on transportation planning, control and optimization. Efforts should also be geared toward understanding the potential, limits and mechanisms of the new vehicles and smart methods that will assist in mitigating traffic congestion and decreasing carbon emissions.

Further research is required to determine the optimal planning, control and operation plans for the urban transportation system. In this Special Issue, we invite researchers to submit original research and review articles addressing all aspects related to urban transportation systems. Potential topics include, but are not limited to, the following:

Electrified transportation system
Sustainable transit system
Multi-mode transportation system
Automated and connected transportation system
Adaptive traffic signal control
Data mining and big data in transportation system
Urban transportation infrastructure planning
Innovative methods for traffic safety and operations
Environmental impacts of transportation system
Eco-friendly mobility for urban vehicles

We look forward to receiving your contributions.

Prof. Dr. Yiming Bie
Dr. Hu Zhang
Dr. Shidong Liang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

intelligent transportation
transportation planning
traffic signal control
operation optimization
sustainable transportation
urban transit
artificial intelligence
big data
traffic safety
connected and automated vehicle

Benefits of Publishing in a Special Issue

Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (12 papers)

Download All Papers

Order results

Result details

Show export options Show export options

Select all

Export citation of selected articles as:

Research

23 pages, 2344 KiB

Open AccessArticle

Regulation and Control Strategy of Highway Transportation Volume in Urban Agglomerations Based on Complex Network

by Shuoqi Wang and Zhanzhong Wang

Sustainability 2025, 17(13), 5769; https://doi.org/10.3390/su17135769 - 23 Jun 2025

Viewed by 292

Abstract

Urban development within an urban agglomeration is unbalanced; the coordinated development of urban agglomerations is the core task of urban development. There are now many mechanisms and methods to promote the coordinated development of urban agglomerations; however, there is a lack of research on promoting the coordinated development of urban agglomerations from the perspective of highway transportation volume regulation. According to the physical characteristics of highway transportation networks, the logical characteristics of urban regional connectivity, and the connection characteristics of complex networks, a two-layer complex network model was designed. The objective function and constraint conditions for urban agglomeration transportation volume regulation were proposed, and the optimal solution of the highway transportation volume regulation was solved. Due to the many variables and constraints, a hierarchical solution method was adopted. A probability search iteration algorithm was proposed innovatively to solve multivariable, many-to-many allocation problems. The algorithm is universal and can be applied to solving similar problems. Taking provincial urban agglomerations as an example, the process of solving the regulation model and realizing the method was explained. The transportation volume regulation methods and strategies proposed in this study realize the best combination of macro control and micro control, static and dynamic control, coordinated development, and collaborative transportation. It is an innovative exploration and study of highway transportation volume allocation and collaborative transportation in urban agglomerations and opens up a new direction for research on the coordinated development of urban agglomerations. The coordinated development of urban agglomerations provides a guarantee for the sustainable development of urban agglomerations. Therefore, this study is also of great significance for promoting the sustainable development of urban agglomerations. Full article

(This article belongs to the Special Issue Innovative and Sustainable Planning, Control and Optimization Methods for Urban Transportation System)

► Show Figures

Figure 1

18 pages, 4626 KiB

Open AccessArticle

Landslide Risk Assessment Along Railway Lines Using Multi-Source Data: A GameTheory-Based Integrated Weighting Approach for Sustainable Infrastructure Planning

by Yuqiang He, Ziyan Bin, Xiaolei Xu, Hongsheng Yu, Yan Zhang, Na Li and Man Li

Sustainability 2025, 17(12), 5522; https://doi.org/10.3390/su17125522 - 16 Jun 2025

Viewed by 366

Abstract

Landslides threaten railway safety and operational sustainability. This study developed a game theory-based weighting method that integrates the Entropy Weight Method (EWM) and CRITIC with Analytic Hierarchy Process (AHP) techniques to determine indicator weights, reducing single-method biases. A risk assessment was conducted that coupled hazard likelihood with exposure. These components formed a comprehensive risk index visualized as a landslide risk map. A GIS-integrated assessment of Shandong Province railways incorporated multi-source data to support resilient infrastructure planning. The results show that high-risk zones consistently coincide with mountainous terrain, high-precipitation areas, and concentration of the population/economic activity, identifying critical intervention areas. The integrated weighting method proves effective for multi-criteria risk analysis. Decision-makers can prioritize mitigation measures using these insights, enhancing railway resilience and reducing regional disaster risk. Full article

(This article belongs to the Special Issue Innovative and Sustainable Planning, Control and Optimization Methods for Urban Transportation System)

► Show Figures

Figure 1

17 pages, 1345 KiB

Open AccessArticle

Level of Service Criteria for Urban Arterials with Heterogeneous and Undisciplined Traffic Streams

by Afzal Ahmed, Farah Khan, Syed Faraz Abbas Rizvi, Fatma Outay, Muhammad Faiq Ahmed and Muhammad Adnan

Sustainability 2025, 17(11), 5126; https://doi.org/10.3390/su17115126 - 3 Jun 2025

Viewed by 739

Abstract

Accurate evaluation of the prevailing traffic operations plays an important part in developing sustainable transport systems. This research examines the suitability of the level of service (LOS) criteria developed by the Indian and United States (US) Highway Capacity Manuals (HCM) for heterogeneous and undisciplined traffic streams and proposes new criteria using a data-driven approach. Traffic data were collected from a selected major arterial in Karachi, and fundamental diagrams were developed using these data. These fundamental diagrams and field-collected data were analyzed using the K-mean clustering approach to examine the actual traffic states at various LOS bands used in practice. Associating the field-measured volume-to-capacity ratio with the speed bands used for LOS analysis gives insights into actual traffic conditions at various LOS categories. The research shows that the volume-to-capacity ratio corresponding to the speed range for LOS A is about 0.45, which implies that the heterogeneous traffic moves with comparatively higher speeds despite an increase in traffic volume. The criteria for LOS were developed using the K-mean cluster analysis technique. The proposed values of LOS criteria for speed percentages are significantly higher than those reported in both the HCMs. This research highlights the need to develop separate LOS criteria for heterogeneous and undisciplined traffic for all transportation facilities. The development of such new criteria can provide researchers and engineers with a schematic for the effective and realistic evaluation of local traffic regimes. Full article

(This article belongs to the Special Issue Innovative and Sustainable Planning, Control and Optimization Methods for Urban Transportation System)

► Show Figures

Figure 1

29 pages, 2047 KiB

Open AccessArticle

An Integrated Two-Step Optimization Model and Aggregative Multi-Criteria Approach for Establishing Sustainable Tram Transportation Plan

by Svetla Stoilova and Ivan Pulevski

Sustainability 2025, 17(2), 543; https://doi.org/10.3390/su17020543 - 12 Jan 2025

Cited by 1 | Viewed by 1045

Abstract

The choice of the most appropriate sustainable scheme for the organization of tram transportation in cities is of great importance for tram operators, for users of transportation services, and for the protection of the environment from harmful emissions. This study aims to propose a methodology for formulating a tram transportation plan considering technological, environmental, economic, and social indicators. The variant schemes represent the routes of a tram in the tram network. The methodology includes four stages. The first stage involves the determination of variant schemes for a transportation plan of service with trams. In the second stage, a two-step optimization model is proposed to determine the number and trams by types for each tram route for each variant scheme, and also to establish the distribution of trams by depots. The third stage includes ranking the variant schemes by applying the sequential interactive model for urban systems (SIMUS) multi-criteria method. Eleven quantitative and qualitative criteria for evaluating the tram transportation plan were introduced. A verification of the results is performed in the fourth stage. For this purpose, a comparison of the preference ranking organization method for enrichment of evaluations (PROMETHEE) method and the technique for order of preference by similarity to ideal solution (TOPSIS) method is made. Both methods have different approaches for decision making and differ from the SIMUS method. Two strategies were proposed to determine the criteria weights. One is based on the Shannon entropy method and the other uses the objective weights obtained through the SIMUS method. Finally, in the fifth stage, the results obtained through the SIMUS, PROMEHEE and TOPSIS methods are combined using the expected value obtained by applying the program evaluation and review technique method (PERT). The proposed methodology was applied to study tram transportation in Sofia, Bulgaria. Five variant schemes were considered. The schemes are optimized through the criterion of minimum energy consumption. The number of trams by routes and by type was determined. An improved scheme for tram transportation in Sofia was proposed. The scheme makes it possible to increase the frequency of the trams by 13%, to reduce the zero mileage of rolling stock, and to reduce carbon dioxide pollution by 11%. Full article

(This article belongs to the Special Issue Innovative and Sustainable Planning, Control and Optimization Methods for Urban Transportation System)

► Show Figures

Figure 1

15 pages, 2609 KiB

Open AccessArticle

Is the High-Emission Vehicle Driving Area Restriction Policy an Effective Measure for Reducing Driving Distance? A Case Study of Busan, South Korea

by Hyeinn Song, Kangwon Shin and Fady M. A. Hassouna

Sustainability 2024, 16(24), 11055; https://doi.org/10.3390/su162411055 - 17 Dec 2024

Viewed by 1108

Abstract

Efforts to reduce air pollution by facilitating the transition to eco-friendly vehicles, particularly through driving restriction policies targeting high-emission vehicles (HEVs), play a crucial role in promoting environmental sustainability. Evaluating the effectiveness of the restriction in terms of reducing HEV driving mileage is essential for policy assessment and improvement. Moreover, given the overall decreasing trend in daily vehicle mileage, it remains uncertain whether the change in HEV driving distance can be directly attributed to the restriction policy. This study directly examines the effectiveness of the vehicle restriction policy using vehicle mileage data and a DID model. Data on daily mileage from 2019, 2021, and 2023 were collected for Busan, and the scenarios were divided into six groups based on the analysis group (treatment group is HEVs subject to vehicle restrictions, control A is HEVs not subject to vehicle restrictions and control B is non-HEVs) and the area of influence (catchment area, city area, and metropolitan area). The analysis revealed that while there was a reduction in daily mileage for HEVs when compared to each other, the decrease was modest, and no significant effect was observed when compared to non-HEVs. Consequently, it was confirmed that the impact of the vehicle restriction policy on reducing daily mileage is marginal. In light of the policy to expand the scope of vehicles subject to driving restrictions in South Korea, it is recommended that the number of enforcement cameras be increased, that enforcement hours be extended to an entire 24-h day, and more stringent enforcement measures be implemented. Full article

(This article belongs to the Special Issue Innovative and Sustainable Planning, Control and Optimization Methods for Urban Transportation System)

► Show Figures

Figure 1

24 pages, 3239 KiB

Open AccessArticle

Can Historical Accident Data Improve Sustainable Urban Traffic Safety? A Predictive Modeling Study

by Jing Wang, Chenhao Zhao and Zhixia Liu

Sustainability 2024, 16(22), 9642; https://doi.org/10.3390/su16229642 - 5 Nov 2024

Cited by 5 | Viewed by 1863

Abstract

Traffic safety is a critical factor for the sustainable development of urban transportation systems. This study investigates the impact of historical accident information on the prediction of future traffic accident risks, as well as the interaction between this information and other features, such as driver violations and vehicle attributes. Using a comprehensive dataset of traffic accidents involving passenger vehicles in a western Chinese city, we developed two predictive models: Model 1, which is based on vehicle information and driver violations, and Model 2, which integrates historical accident data. The results indicate that the inclusion of historical accident information significantly enhances the predictive performance of the model, particularly in terms of AUC (Area Under the Curve) and AP (Average Precision) values. Furthermore, through feature importance analysis and SHAP (SHapley Additive exPlanations) value evaluation, this study reveals the interaction effects between historical accident data and other features, and how these interactions influence model decisions. The findings suggest that historical accident data play a positive role in predicting future accident risk, with varying effects on risk mitigation. These insights provide a scientific basis for developing strategies to ensure the sustainable development of urban transportation systems. Full article

(This article belongs to the Special Issue Innovative and Sustainable Planning, Control and Optimization Methods for Urban Transportation System)

► Show Figures

Figure 1

14 pages, 6564 KiB

Open AccessArticle

Traffic Safety Evaluation of Downstream Intersections on Urban Expressways Based on Analytical Hierarchy Process–Matter-Element Method

by Tianjun Feng, Yusong Liu, Chun Chen, Keke Liu and Chongjun Huang

Sustainability 2024, 16(16), 6887; https://doi.org/10.3390/su16166887 - 10 Aug 2024

Cited by 3 | Viewed by 1797

Abstract

This study aimed to explore the traffic safety evaluation model for downstream intersections of urban expressway exits and make up for the shortcomings in safety research on downstream intersections of urban expressway exits. We constructed a comprehensive traffic safety evaluation index system, established a traffic safety evaluation model, and divided precise safety evaluation levels using the AHP–Matter-Element analysis method, establishing a traffic safety evaluation index system consisting of eleven indicators. The effectiveness of this method was validated through an assessment of traffic safety at the intersection of Dongsheng Street and Free Road in Changchun City. A theoretical basis for improving traffic safety at downstream intersections of urban expressways and a reference for subsequent related research were provided. Full article

(This article belongs to the Special Issue Innovative and Sustainable Planning, Control and Optimization Methods for Urban Transportation System)

► Show Figures

Figure 1

15 pages, 3199 KiB

Open AccessArticle

Exploring the Potential of Generative Adversarial Networks in Enhancing Urban Renewal Efficiency

by Yunfei Lin and Mingxing Song

Sustainability 2024, 16(13), 5768; https://doi.org/10.3390/su16135768 - 6 Jul 2024

Cited by 5 | Viewed by 2103

Abstract

As Chinese cities transition into a stage of stock development, the revitalization of industrial areas becomes increasingly crucial, serving as a pivotal factor in urban renewal. The renovation of old factory buildings is in full swing, and architects often rely on matured experience to produce several profile renovation schemes for selection during the renovation process. However, when dealing with a large number of factories, this task can consume a significant amount of manpower. In the era of maturing machine learning, this study, set against the backdrop of the renovation of old factory buildings in an industrial district, explores the potential application of deep learning technology in improving the efficiency of factory renovation. We establish a factory renovation profile generation model based on the generative adversarial networks (GANs), learning and generating design features for the renovation of factory building profiles. To ensure a balance between feasibility and creativity in the generated designs, this study employs various transformation techniques on each original profile image during dataset construction, creating mappings between the original profile images and various potential renovation schemes. Additionally, data augmentation techniques are applied to expand the dataset, and the trained models are validated and analyzed on the test set. This study demonstrates the significant potential of the GANs in factory renovation profile design, providing designers with richer reference solutions. Full article

(This article belongs to the Special Issue Innovative and Sustainable Planning, Control and Optimization Methods for Urban Transportation System)

► Show Figures

Figure 1

23 pages, 12409 KiB

Open AccessArticle

Short-Term Traffic Flow Forecasting Method Based on Secondary Decomposition and Conventional Neural Network–Transformer

by Qichun Bing, Panpan Zhao, Canzheng Ren, Xueqian Wang and Yiming Zhao

Sustainability 2024, 16(11), 4567; https://doi.org/10.3390/su16114567 - 28 May 2024

Cited by 5 | Viewed by 1783

Abstract

Because of the random volatility of traffic data, short-term traffic flow forecasting has always been a problem that needs to be further researched. We developed a short-term traffic flow forecasting approach by applying a secondary decomposition strategy and CNN–Transformer model. Firstly, traffic flow data are decomposed by using a Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) algorithm, and a series of intrinsic mode functions (IMFs) are obtained. Secondly, the IMF1 obtained from the CEEMDAN is further decomposed into some sub-series by using Variational Mode Decomposition (VMD) algorithm. Thirdly, the CNN–Transformer model is established for each IMF separately. The CNN model is employed to extract local spatial features, and then the Transformer model utilizes these features for global modeling and long-term relationship modeling. Finally, we obtain the final results by superimposing the forecasting results of each IMF component. The measured traffic flow dataset of urban expressways was used for experimental verification. The experimental results reveal the following: (1) The forecasting performance achieves remarkable improvement when considering secondary decomposition. Compared with the VMD-CNN–Transformer, the CEEMDAN-VMD-CNN–Transformer method declined by 25.84%, 23.15% and 22.38% in three-step-ahead forecasting in terms of MAPE. (2) It has been proven that our proposed CNN–Transformer model could achieve more outstanding forecasting performance. Compared with the CEEMDAN-VMD-CNN, the CEEMDAN-VMD-CNN–Transformer method declined by 13.58%, 11.88% and 11.10% in three-step-ahead forecasting in terms of MAPE. Full article

(This article belongs to the Special Issue Innovative and Sustainable Planning, Control and Optimization Methods for Urban Transportation System)

► Show Figures

Figure 1

24 pages, 4747 KiB

Open AccessArticle

Health Monitoring Analysis of an Urban Rail Transit Switch Machine

by Zishuo Wang, Di Sun, Jin Zhou, Kaige Guo, Jiaxin Zhang and Xiangyu Kou

Sustainability 2024, 16(9), 3527; https://doi.org/10.3390/su16093527 - 23 Apr 2024

Cited by 1 | Viewed by 1835

Abstract

This paper discusses the health evaluation of an urban rail transit switch machine. In this paper, the working current data of the S700K switch machine are processed, and four common abnormal operating current curves are obtained through the existing data. Then, the MLP is used as the feature extractor of the action current curve to analyze the input action current data, learn and capture deep features from raw current data as Q-networks, and build MLP-DQN models. The monitoring of the abnormal state operation current of the switch machine is optimized by learning and optimizing the model weight through repeated experience. The experimental results show that the training accuracy of this model is stable at about 96.67%. Finally, the Fréchet distance was used to analyze the abnormal motion current curve, combined with the occurrence frequency and repair complexity of the abnormal type curve, the calculated results were analyzed, and the health of the switch machine was evaluated, which proved the high efficiency and superiority of the MLP-DQN method in the fault diagnosis of the switch machine equipment. The good health evaluation function of the switch machine can effectively support the maintenance of the equipment, and it has an important reference value for the intelligent operation and maintenance of subway signal equipment. The research results mark the maintenance of key equipment of urban rail transit systems, represent a solid step towards intelligent and automated transformation, and provide strong technical support for the safe operation and intelligent management of future rail transit systems. Full article

(This article belongs to the Special Issue Innovative and Sustainable Planning, Control and Optimization Methods for Urban Transportation System)

► Show Figures

Figure 1

19 pages, 1494 KiB

Open AccessArticle

Enhancing Electric Bus Charging Scheduling: An Energy-Integrated Dynamic Bus Replacement Strategy with Time-of-Use Pricing

by Yang Liu, Bing Zeng, Kejun Long and Wei Wu

Sustainability 2024, 16(8), 3334; https://doi.org/10.3390/su16083334 - 16 Apr 2024

Viewed by 2111

Abstract

Existing studies on electric bus (EB) scheduling mainly focus on the arrangement of bus charging at the bus terminals, which may lead to inflexible charging plans, high scheduling costs, and low utilization of electricity energy. To address these challenges, this paper proposes a dynamic bus replacement strategy. When the power of an in-service EB is insufficient, a standby EB stationed at nearby charging stations is dispatched in advance to replace this in-service EB at a designated bus stop. Passengers then transfer to the standby bus to complete their journey. The replaced bus proceeds to the charging station and transitions into a “standby bus” status after recharging. A mixed-integer nonlinear programming (MINLP) model is established to determine the dispatching plan for both standby and in-service EBs while also designing optimal charging schemes (i.e., the charging time, location, and the amount of charged power) for electric bus systems. Additionally, this study also incorporates the strategy of time-of-use electricity prices to mitigate the adverse impact on the power grid. The proposed model is linearized to the mixed-integer linear programming (MILP) model and efficiently solved by commercial solvers (e.g., GUROBI). The case study demonstrates that EBs with different energy levels can be dynamically assigned to different bus lines using bus replacement strategies, resulting in reduced electricity costs for EB systems without compromising on scheduling efficiency. Full article

(This article belongs to the Special Issue Innovative and Sustainable Planning, Control and Optimization Methods for Urban Transportation System)

► Show Figures

Figure 1

17 pages, 2408 KiB

Open AccessArticle

CVDMARL: A Communication-Enhanced Value Decomposition Multi-Agent Reinforcement Learning Traffic Signal Control Method

by Ande Chang, Yuting Ji, Chunguang Wang and Yiming Bie

Sustainability 2024, 16(5), 2160; https://doi.org/10.3390/su16052160 - 5 Mar 2024

Cited by 5 | Viewed by 1968

Abstract

Effective traffic signal control (TSC) plays an important role in reducing vehicle emissions and improving the sustainability of the transportation system. Recently, the feasibility of using multi-agent reinforcement learning technology for TSC has been widely verified. However, the process of mapping road network states onto actions has encountered many challenges, due to the limited communication between agents and the partial observability of the traffic environment. To address this problem, this paper proposes a communication-enhancement value decomposition, multi-agent reinforcement learning TSC method (CVDMARL). The model combines two communication methods: implicit and explicit communication, decouples the complex relationships among the multi-signal agents through the centralized-training and decentralized-execution paradigm, and uses a modified deep network to realize the mining and selective transmission of traffic flow features. We compare and analyze CVDMARL with six different baseline methods based on real datasets. The results show that compared to the optimal method MN_Light, among the baseline methods, CVDMARL’s queue length during peak hours was reduced by 9.12%, the waiting time was reduced by 7.67%, and the convergence algebra was reduced by 7.97%. While enriching the information content, it also reduces communication overhead and has better control effects, providing a new idea for solving the collaborative control problem of multi-signalized intersections. Full article

(This article belongs to the Special Issue Innovative and Sustainable Planning, Control and Optimization Methods for Urban Transportation System)

► Show Figures

Journal Menu

Journal Browser

Innovative and Sustainable Planning, Control and Optimization Methods for Urban Transportation System

Share This Special Issue

Special Issue Editors

Special Issue Information

Keywords

Benefits of Publishing in a Special Issue

Published Papers (12 papers)

Research

Further Information

Guidelines

MDPI Initiatives

Follow MDPI