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A Review of AI-driven Trajectory Prediction Methods for Autonomous Vehicles TIAN Daxin, XIAO Xiao, ZHOU Jianshan Journal of Transportation Systems Engineering and Information Technology    2025, 25 (5): 1-24.   DOI: 10.16097/j.cnki.1009-6744.2025.05.001 Abstract （1060）      PDF （1838KB）（699）       In autonomous driving systems, trajectory prediction plays an important role in connecting vehicle's perception and decision-making, and enhancing driving safety and overall system robustness. In recent years, with the continuous advancement of artificial intelligence (AI), the AI-driven trajectory prediction methods have seen significant progress in terms of accuracy, adaptability, and the capability to model complex traffic environment. This paper provides a systematic review of mainstream trajectory prediction methods in autonomous driving, with a focus on predictive model frameworks. It first revisits traditional physics-based approaches, and then highlights current research trends, including modeling paradigms based on classical machine learning, deep neural networks, and reinforcement learning. Additionally, recent developments in explainable AI techniques aimed at improving model transparency and safety are discussed. Based on comparative analysis, the paper evaluates the strengths and limitations of various models in interaction modeling, multimodal uncertainty, and generalization capability. Furthermore, it organizes trajectory prediction evaluation metrics and publicly available trajectory prediction datasets according to their characteristics and application scenarios, and summarizes representative real-world deployments from both domestic and international sources. At last, considering the existing research bottlenecks and future development trends, the paper outlines potential directions for future studies, such as enhancing model interpretability, effectively integrating multimodal information, and designing unified frameworks for joint prediction and planning. The purpose of this review is to provide insights and references that can be used in the future research and applications.

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Collaborative Optimization of Suburban Railway and Metro Train Operation Plans Under Interconnection Operational Mode PENG Qiyuan, LIU Siyuan, JIANG Shan, FENG Tao, CHEN Yao, ZHANG Yongxiang Journal of Transportation Systems Engineering and Information Technology    2025, 25 (2): 36-47.   DOI: 10.16097/j.cnki.1009-6744.2025.02.004 Abstract （1011）      PDF （2588KB）（267）       The train operation plan plays a crucial role in improving the operational efficiency of regional multi-standard rail under the interconnection operational mode. This study develops an integrated optimization model for the suburban railway and metro train operation plans and passenger flow assignment under the interconnection operational mode to minimize the total of passenger travel cost and the enterprise operational cost. The model simultaneously optimizes the train service routes on the entire line, the frequency, composition types, and stopping plan of trains on each service route, where practical constraints such as carrying capacity, train capacity, rolling stock resources, and the number of train services are considered. An improved adaptive large-scale neighborhood search algorithm is designed and its effectiveness is verified through instances with different passenger demand levels. The results show that: 1) The improved algorithm can provide a satisfactory solution, resulting in an average decrease of 3.6% in the objective function with an average computational time of 234 seconds compared to the two-stage approach;2) Compared to the independent operational mode, the interconnection operational mode reduces the enterprise operational cost by 11.3%, full-line and cross-line passenger travel costs respectively by 3.9% and 10.7%, the transfer times of cross-line passengers by 18.7%, and the number of rolling stocks used by 14.4%. 3) Compared to the all-stop pattern, the passenger travel cost is reduced by 4.2% on average after adopting the flexible-stop pattern for the suburban railway local and cross-line trains. The proposed method provides an auxiliary decision support tool for generating the suburban railway and metro train operational plans under the interconnection operational mode.

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Comparison on Influence of Job-housing and Commuting Status on Travel Mode Choice in Multiple Types of Cities ZHOU Yuyang, ZHAO Congying, LI Jingkun, CHEN Yanyan, LIU Di, WANG Shuling Journal of Transportation Systems Engineering and Information Technology    2025, 25 (2): 26-35.   DOI: 10.16097/j.cnki.1009-6744.2025.02.003 Abstract （730）      PDF （2873KB）（350）    PDF(English version) （1195KB）（6）    Establishing a green and efficient travel service system is an important part of China's Green Travel Action Plan. It is necessary to consider the heterogeneity of job-housing status and commuting mode in different levels of cities. Based on 1788 valid questionnaires collected from three types of cities, the SEM-MNL model is constructed to quantitatively analyze the comprehensive impact of job-housing status, commuting attributes and personal economic characteristics on the choice of commuting modes in various types of cities. The findings reveal that the latent variable commuting attribute is the key factor affecting the travel mode, and the restrictive effect is more prominent in ordinary cities than in first-tier and new first-tier cities. Job-housing status indirectly affects commuting mode choice through commuting attributes. The path coefficients of three classes of cities are 0.83, 0.89, and 0.93, respectively. The effects of residential type on commuting distance and mode choice show an opposite trend in first-tier cities and ordinary cities. Highly educated travelers in first-tier cities prefer green travel modes, while in non-first-tier cities, the result is reversed. In new first-tier cities, residents with short commute distances have the highest proportion of renting, nearly half of them choose slow-speed transportation. Adjusting the job-housing distribution to increase the proportion of short-distance commuting can raise the share of green travel mode. As the city level declines, the feedback sensitivity of regulation increases. The research results provide differentiated policy recommendations for job-housing balance and transportation infrastructure planning in multiple types of cities. The results are conducive to promoting the low-carbon travel and contribute to the balance of urban transportation supply and demand and thus sustainable development.

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Effectiveness of New Energy Vehicle Incentive Strategies Considering Urban and Population Heterogeneity WENG Jiancheng, ZHOU Huiyuan, ZHANG Mengyuan, YU Jiangbo Journal of Transportation Systems Engineering and Information Technology    2025, 25 (1): 2-14.   DOI: 10.16097/j.cnki.1009-6744.2025.01.001 Abstract （694）      PDF （2998KB）（340）    PDF(English version) （1229KB）（23）    Formulating policies tailored to urban low-carbon development phases and resident characteristics is essential for optimizing incentive structures and promoting green mobility. This study evaluates new energy vehicle (NEV) incentive strategies across four city categories, considering factors such as air quality, NEV penetration, and charging infrastructure maturity. It analyzes social media data using the Latent Dirichlet Allocation (LDA) model and designs user surveys. A Latent Class Ordered Logit Model (LCOL) is employed to assess different urban populations' preferences for vehicle electrification incentives, identifying key impacted groups. The results indicate that immediate incentives, such as driving ban exemptions and significant fiscal subsidies, effectively enhance the purchasing intent of NEVs among less receptive residents. Conversely, more receptive residents respond better to regular, smaller subsidies. Cities with low NEV penetration exhibit a higher probability of purchasing under incentives, highlighting greater potential for improvement. Enhancing charging infrastructure significantly boosts purchasing intentions in infrastructure-deficient cities, with a 1% increase in likelihood for every minute reduction in charging time. However, this effect diminishes in cities with extensive charging networks. In metropolises with vehicle access restrictions, exempting NEVs from these increases purchasing probabilities by 3.5%. These insights guide NEV promotional strategy development in diverse urban settings.

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Research Progress and Challenges on Equity in Flight Slot Allocation HU Rong, ZHANG Yutong, DING Jiahao, WANG Yiren, ZHANG Junfeng Journal of Transportation Systems Engineering and Information Technology    2025, 25 (2): 1-15.   DOI: 10.16097/j.cnki.1009-6744.2025.02.001 Abstract （629）      PDF （1969KB）（361）    PDF(English version) （607KB）（12）    To further improve the feasibility of slot allocation results and reduce the unfairness among the participants in slot allocation, much literature has been studied on the fair allocation of flight schedules. By searching relevant databases at home and abroad, this paper systematically sorts out the individual fairness indicators and overall fairness goals in the optimization of existing slot allocations. Firstly, the development process and metrics of the concept of "fairness" are summarized, and the connotation of fairness in slot allocation is analyzed from three perspectives: horizontal/vertical, individual/overall and absolute/ relative. Secondly, the individual fairness index of each participant in the slot allocation are sorted out and compared based on the two dimensions of the number of slot adjustment and slot displacement. Then, from the perspectives of absolute fairness, relative fairness and Gini index, the overall fairness optimization objectives of the slot allocation model are summarized. The results show that the current fairness indicators are mainly constructed based on the principle of proportionality, while the weighted construction method is limited due to the difficulty of data acquisition and strong subjectivity. The research on the fairness goals has been relatively well-developed, and the Gini index has been widely used because of its global characteristics. Based on the content of the literature review, this paper further analyzes the shortcomings of existing studies and provides suggestions for future research. The study concludes that, in-depth research should be carried out in four aspects in the future: quantitative calculation of flight value, expansion of fairness research objects, construction of environmental fairness indicators and evaluation of the impact of dynamic parameters, to help the healthy and sustainable development of the civil aviation industry.

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Methods for Assessing Wider Economic Benefits of Urban Transportation Infrastructure Based on Integrated Modeling WANG Wanle, ZHONG Ming, HUNT John douglas Journal of Transportation Systems Engineering and Information Technology    2025, 25 (4): 1-12.   DOI: 10.16097/j.cnki.1009-6744.2025.04.001 Abstract （619）      PDF （3162KB）（431）       Transportation infrastructure has a strong driving effect on urban economic development. In particular, the construction of large-scale transportation infrastructure can have a significant impact on land use and spatial form. In response to the need for a comprehensive assessment of the economic benefits of urban transportation infrastructure, this study proposes a framework and method for assessing the Wider Economic Benefits (WEBs) of transportation infrastructure based on the Urban-Integrated Economy, Land Use, and Transport (U-IELUT) modeling. This study extends the traditional "Four-Step" transportation planning model to a "PECAS+(Production, Exchange and Consumption Allocation System)" WEBs assessment model by linking it with an economic and population forecasting, a socio-economic activities allocation, a space development, and a wider economic benefits assessment module. The WEBs assessment model is designed to evaluate both the direct economic benefits and the wider economic benefits, mainly the agglomeration benefits, of urban transportation infrastructure. Taking Wuhan Metro Line 2 as an example, the direct and wider economic benefits were assessed using the "PECAS+" wider economic benefits assessment model. The findings indicate that the direct economic benefits of the Metro Line 2 in 2027 are approximately 1.043 billion yuan. The dynamic agglomeration benefits are about 264 million yuan, which is approximately 25.3% of the direct economic benefits. This demonstrates that the wider economic benefits, especially the agglomeration benefits, should not be overlooked in the economic benefits assessment of transportation infrastructure. Meanwhile, it is also possible to ascertain the impact differences of transportation infrastructure construction on various zones of the study area, that is, the spatial distribution of wider economic benefits, which can provide multidimensional decision-making support for the investment and construction of transportation infrastructure.

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Traffic State Recognition Based on Vehicle Dynamic Behavior Characteristics LI Xiying, LU Meiyan, HE Zhaocheng, SU Shuyan, PANG Shumin Journal of Transportation Systems Engineering and Information Technology    2025, 25 (1): 44-55.   DOI: 10.16097/j.cnki.1009-6744.2025.01.005 Abstract （573）      PDF （2497KB）（230）       Traffic state recognition research is of great significance for the prevention and mitigation of traffic congestion. It provides decision support for traffic management and also effectively enhances the operational efficiency of roads. Traditional traffic state identification methods typically take into account one single macroscopic characteristic parameter, while overlooking the impact of vehicle lane-changing behaviors and the consequent mutual interference among vehicles. This leads to a relatively coarse granularity in the state division space and insufficient refinement in state identification, thereby hindering in-depth analysis of traffic congestion causes. In response to this, this study proposes a traffic state identification method based on vehicle dynamic behavior characteristics from an Unmanned Aerial Vehicle (UAV) perspective. Firstly, the method combines a vehicle detection algorithm (YOLOv8-OBB) based on rotated bounding boxes and a vehicle tracking algorithm (BoTSORT) to detect and track vehicles, addressing redundant background pixels and overlapping vehicle bounding boxes within horizontal bounding boxes, extract more accurate vehicle trajectory data such as vehicle spatial direction angle and four-point rotation coordinates, and calculate microscopic traffic flow parameters. Secondly, by utilizing the obtained vehicle driving direction angles and rotated position information, this study proposes vehicle dynamic behavior characteristics parameters: lane change interference rate and vehicle direction fluctuation index. Combined with macroscopic average speed and traffic density parameters, a multi-dimensional state feature space is constructed and applied to traffic state identification in actual road scenes. The ultimate experimental results demonstrate that the method achieved an mAP@0.5 of 0.987 in the rotated vehicle detection, with stable and continuous vehicle trajectory data output. In traffic state recognition, by introducing the lane change interference rate based on the average speed and traffic density as macroscopic feature parameters, the state recognition precision reached 0.983. Moreover, incorporating the direction fluctuation index, the state recognition precision reached 0.987. Additionally, according to the state characteristic space representation, the traffic state enables accurate classification into four states: smooth state, steady state, crowded state, and blocked state. This allows for quantitative analysis of the impact of vehicle dynamic behavior on traffic state, and provides novel theoretical insights for traffic state recognition from a UAV perspective, offering advanced fine-grained perception capabilities for intelligent transportation systems

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Integrated Optimization of Grain Loading Strategies and Transportation Routes Considering Losses WAN Min, KUANG Haibo, JIA Peng, YU Fangping, MA Qianli, ZHANG Yige, ZHAO Sue Journal of Transportation Systems Engineering and Information Technology    2025, 25 (1): 15-23.   DOI: 10.16097/j.cnki.1009-6744.2025.01.002 Abstract （548）      PDF （1877KB）（218）       A high-quality grain distribution system is critical to ensure the balance of grain supply and demand and food security. This study considers the perishable nature of grain types and aims to minimize the total costs of transportation, carbon emissions, and loss. An integrated optimization model is proposed to consider different loading methods (bagged-bulk-container) and various transportation modes (road-rail-sea). A case study was performed using the heuristic genetic algorithm in the "grain transport from North to South China" scenario in Northeast China. The results indicate that compared to bagged grain and bulk grain transport, multimodal transport of grain containers by rail, road, and water has clear advantages in terms of lower total cost and reduced loss. The proportion of grain loss cost in container transport, bagged grain transport, and bulk grain transport is 9.86%, 42.29%, and 29.82%, respectively. In the "grain transport from North to South China" process, roads are primarily used for local collection and distribution, while railways and waterways handle long- distance trunk transportation. When the delivery time requirements increase, the proportion of railway transportation would gradually increase, and the proportion of waterway transportation would decrease. When the total delivery time reaches 71.5 hours, the optimal transportation scheme would shift from container multimodal transport via road, rail, and sea to container multimodal transport via road and rail only. In the composition of total costs, the transportation costs and carbon emission costs of the optimal routes for the three loading methods are essentially the same. The study result also serves as a reference for the government regulatory agencies and logistics service providers that reducing grain transportation losses is an effective way to lower the overall logistics transportation costs.

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Review of Connected and Autonomous Vehicle Dedicated Lane Setup CHENG Guozhu, WANG Wenzhi, YANG Zihan, WANG Guopeng, CHEN Yongsheng, GU Shuang Journal of Transportation Systems Engineering and Information Technology    2025, 25 (5): 25-39.   DOI: 10.16097/j.cnki.1009-6744.2025.05.002 Abstract （548）      PDF （2429KB）（400）       With the advancement of information and communication technologies, autonomous vehicles (AV) and connected and autonomous vehicles have emerged as promising solutions to address traffic congestion, to enhance traffic safety, and to improve overall traffic efficiency. This paper provides a comprehensive review of the methods for setting up dedicated lanes for connected and autonomous vehicle (CAV). It begins by tracing the evolution of CAV dedicated lanes and elaborating on the background and significance of their implementation. Based on relevant literatures, it then delves into the methodologies for calculating road capacity, providing a foundation for predicting the impact of CAV dedicated lanes on traffic operations, evaluating strategies, and making necessary adjustments. Furthermore, the paper conducts an in-depth analysis on the strategies for setting up CAV dedicated lanes, including the conditions based on CAV penetration rates and traffic demand. It also explores the determination of the number and location of lanes, access methods, and lane separation approaches under various influencing factors. Finally, the paper proposes that future research should focus on understanding the changes in influencing factors post-implementation of CAV dedicated lanes and their alignment with real-world traffic conditions. It also emphasizes the need for establishing specific standards for setting up CAV dedicated lanes to ensure their function effectively across different traffic scenarios.

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Journal of Transportation Systems Engineering and Information Technology    2025, 25 (1): 1-.   Abstract （538）      PDF （761KB）（203）

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Review of Literature on Air-rail Intermodality Focusing on Passenger Travel Behaviour ZHANG Xiaoqiang, ZHOU Huixuan, WU Xiaoyu Journal of Transportation Systems Engineering and Information Technology    2025, 25 (3): 5-21.   DOI: 10.16097/j.cnki.1009-6744.2025.03.002 Abstract （521）      PDF （1731KB）（262）       Comprehensive transportation is the development direction of intelligent, green and safe transportation in recent years. Through comprehensive development and utilization of aviation, railway, highway, waterway and pipeline transportation modes, it builds a transportation system with advanced transportation technology, reasonable layout and structure. Air-rail intermodality is one type of comprehensive transportation, which not only reduces the waste of resources through the reasonable use of existing transportation infrastructure, but also improves transportation accessibility through low cost of transportation mode shift. Air-rail intermodality is an effective strategy to ease airport congestion, expand the scope of airport radiation, reduce carbon emissions and meet the diversity of travel demand. In recent years, related research on air-rail intermodality has included research on competition and cooperation of air-rail intermodality, air-rail intermodality network, and evaluation methods of air-rail intermodality at macro level, then research on of air-rail intermodality at the middle level, and research on passenger travel behavior of air-rail intermodality at the micro level. This paper summarizes and the representative studies in domestic and international level of air-rail intermodality from 2000 to 2024, and sorts out the research results under different operation backgrounds and different transportation network scales. It is found that domestic scholars are more concerned on transport passenger travel behavior, emphasize passenger travel demand, and scholars in other countries tend to focus on air-rail intermodality social benefits and environmental benefits, emphasize the sustainable development of air-rail intermodality. The reasons of the research differences at home and abroad are analyzed from the social background, technical background and policy support. In the future, to explore practical collaborative research, including conflicts of interest between operators and between operators and passengers, the conflict between social and environmental benefits is a valuable research direction. Systematic research on the construction of air rail intermodal network, the location of transit nodes to network optimization, construct the evaluation method system of air-rail intermodality, it has guiding significance to the development of air-rail intermodality. Expanding the study area for air-rail intermodality with the considerations of the diverse needs of travelers, coping strategies that incorporate uncertainty factors, such as providing flight delay insurance, is a very meaningful research topic. It is a practical work to deeply integrate the theoretical research and practical application of passenger travel behavior of air-rail intermodality. Atlast, the future development of air-rail intermodality should use advanced science and technology to reduce the data acquisition cost of the whole travel chain of air-rail intermodality passengers and build a travel service platform of air-rail intermodality including travel path planning, one-stop ticket purchase, connection process visualization, connection time prediction and other services.

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Influence Mechanisms and Identification of Cognitive Distraction of Car-following on Expressways PENG Jinshuan, ZHANG Lingjun, ZHOU Lei, YUAN Hao, REN Chaoyu, XU Lei Journal of Transportation Systems Engineering and Information Technology    2025, 25 (1): 221-230.   DOI: 10.16097/j.cnki.1009-6744.2025.01.021 Abstract （518）      PDF （4170KB）（306）    PDF(English version) （1356KB）（34）    To investigate the impact of cognitive distraction on drivers' car-following behavior on expressways, this study conducted driving simulation experiment with various distraction tasks. The study dynamically collected vehicle kinematics characteristics, driver manipulation, and eye movement parameters, and analyzed the influence mechanism of the secondary task state and speed interval on car-following performance. A set of cognitive distraction state representation parameters was developed for car-following behavior in different speed intervals. Methods such as the Support Vector Machine (SVM), Random Forest (RF), and Extreme Gradient Boosting (XGBoost) were introduced to identify drivers' cognitive distraction states in real-time. The findings indicated that immersive computing imposed a higher cognitive load on drivers compared to conversational secondary tasks. Cognitive distraction reduced drivers' control over the steering wheel and throttle pedal, more focused gaze on the road ahead, and suppressed visual transfer. The cognitive distraction representation parameters varied across different speed intervals. The XGBoost model outperformed both the SVM and RF. By calibrating the optimal sliding window width and step size under different speed intervals, the XGBoost model achieved recognition accuracies of respectively 85.98%, 87.98%, 88.45%, and 92.21% for the overall interval and the speed intervals of I ([60, 80) km·h-1), II [80, 100) km·h-1), and III [100, 120] km·h-1). Up to the risk threshold moment, the recognition rate for cognitive distraction samples reached a maximum of 90%. The findings provide references for recognizing cognitive distraction and optimizing early warning systems on expressways.

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Lane-based Speed Regulation of Bottlenecks Under Mixed Flow Environment CAO Danni, WANG Tao, YANG Songpo, QU Yunchao, WU Jianjun Journal of Transportation Systems Engineering and Information Technology    2025, 25 (1): 76-85.   DOI: 10.16097/j.cnki.1009-6744.2025.01.008 Abstract （496）      PDF （2184KB）（291）       To address the congestion and secondary accidents on highways involving both Connected and Automated Vehicles and Human-driven Vehicles after abnormal incidents occur, this paper focuses on a single lane and proposes a lane-based speed regulation method. This study utilizes the controllability of Connected and Automated Vehicles by controlling the passing speed to indirectly guide the driving behavior of Human-driven Vehicles. The area near the bottleneck is divided into a speed limit area and a coordination area. In the speed limit area, the Connected and Automated Vehicles speed limit values for different lanes are determined based on real-time traffic flow at the bottleneck, and the number of vehicles flowing into the coordination area is controlled to alleviate the formation and propagation of congestion waves. In the coordination area, the Connected and Automated Vehicles movement on the incident lane is controlled to ensure that vehicles could pass through the bottleneck area safely and efficiently. A set of simulation experiments are conducted, and the effectiveness of the proposed method is verified from two aspects: efficiency and safety. The simulation results show that compared to an uncontrolled baseline scenario, the average traveling time of vehicles can be increased by 2.4% and the improvement rate of TET (Time Exposed time-to-collision) can reach 14% in a 50% Connected and Automated Vehicles market penetration rates environment. And in a 90% market penetration rates environment, the average travel time can be increased by 18.5%, and the TET improvement rate rises to 51%. This paper could provide strategic recommendations and methods to control the traffic flow when an incident happens under the mixed flow environment.

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Key Node Identification of Rail Transit Network Based on Gravity Influence Model ZUO Zhongyi, LIU Zeyu, YANG Guangchuan Journal of Transportation Systems Engineering and Information Technology    2025, 25 (1): 102-112.   DOI: 10.16097/j.cnki.1009-6744.2025.01.011 Abstract （494）      PDF （2643KB）（333）    PDF(English version) （3938KB）（10）    The identification of key nodes in a rail transit network is critical to evaluate the network robustness and develop risk resistant plans and therefore ensure efficient operation of the transit network. This paper considers the mutual influence between nodes in the rail transit network and selects the Degree Centrality (DC), Betweenness Centrality (BC) and Closeness Centrality (CC) as comprehensive measurement indicators of node importance. The real rail transit network is converted as the corresponding topological network. The key nodes of the rail transit network are identified through the gravitational influence model, and the differences in network performance under different influencing factors are analyzed to obtain the optimal gravitational influence radius and attack strategy. The study assesses the robustness of the rail transit network from a gravitational perspective, and proposes relevant improvement recommendations. The results indicate that the importance of nodes is composed of the gravitational attraction generated by the target node and other nodes. When the gravitational influence model has a gravitational radius R=8 and a dynamic attack strategy is selected, the relative size decrease rate of the largest connected subgraph is respectively 13.25% and 10.39% higher than that when R=7 and R=9. The relative size decrease rate of network passenger flow efficiency is respectively 5.12% and 6.71% higher than that when R=7 and R=9 . Compared with the FGM, GC, KSGC, CI recognition models, the gravitational influence model has obvious advantages in identifying key nodes in rail transit networks. In addition, after attacking the top 30 nodes, the relative size of the largest connected subgraph in Beijing's subway network decreases by 91.68%, and the relative size of network passenger flow efficiency decreases by 86.17%. The results show that the gravitational influence model is applicable and effective in Beijing's subway network. The proposed method provides a new perspective for analyzing network robustness and provides an effective basis for decision makers to create network risk prevention plans.

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Modeling and Simulation on Reuse of Bus Lanes by Connected and Automated Vehicles JIANG Pei, MA Xinlu, LI Yibo, CHEN Jian Journal of Transportation Systems Engineering and Information Technology    2025, 25 (1): 67-75.   DOI: 10.16097/j.cnki.1009-6744.2025.01.007 Abstract （489）      PDF （2964KB）（104）       The uncontrollability inherent in human-driven vehicles poses challenges to the efficient utilization of bus lanes with intermittent priority (BLIP). To address this issue, a control method for reusing BLIP in connected and automated vehicles (CAVs) is proposed. The lane-borrowing control takes into account the time-space constraints of bus movements, while the lane-returning control focuses on coordinating with adjacent CAV platoons to handle scenarios where the safe distance for lane-return is inadequate. The proposed method is simulated via an open-boundary cellular automaton model. Simulation results showed that: (1) At a given traffic flow, reusing BLIP with CAV can significantly improve road traffic efficiency. Notably, a moderate CAV penetration rate yields the most substantial improvement, with the average road speed rising from 6.67 km·h -1 to 30.53 km·h -1. (2) Irrespective of the CAV penetration rate, collaborative lane-changing within CAV platoons is more effective in boosting road traffic efficiency compared to single-CAV collaborative lane-changing, with an increase in the average road speed by 8%~19%.

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Urban Road Dedicated Lane for Connected and Automated Vehicles WANG Lianzhen, MA Zhifei, CHENG Guozhu, ZHENG Fushui Journal of Transportation Systems Engineering and Information Technology    2025, 25 (1): 56-66.   DOI: 10.16097/j.cnki.1009-6744.2025.01.006 Abstract （485）      PDF （2854KB）（112）       In order to scientifically and effectively set up dedicated lanes for connected and automated vehicles (CAV), reduce conflicts between human-driven vehicles and CAV, and improve the safety and efficiency, this paper proposes a bi-level optimization model for urban road dedicated lanes for the CAV. The upper model has two optimization objectives, which aim to reduce the total travel time cost and reduce the traffic accident rate. The model also considers whether to set up a dedicated lane for CAV as a decision variable and uses the Strengthened Elitist Genetic Algorithm (SEGA) to solve the problem. The distribution of traffic flow in the lower model follows the user equilibrium principle. The lower model is solved using the Frank-Wolfe algorithm integrated with the golden section search. The Nguyen-Dupuis network serves as a case study to evaluate the model's effectiveness and the SEGA algorithm, and the effects of different penetration rates, capacity and total origin-destination (OD) demand on total travel time and traffic accident rate are analyzed. The results of the example show that the establishment of dedicated lanes for CAV will lead to an increase of total travel time regardless of the penetration rate of 10% or 80%. The total travel time decreases by 2.68% when the permeability is 40%. The accident rate would increase to different extents, when the penetration rate is below 20%. When the penetration rate is 40%, the accident rate decreases by 14.30%, and when the penetration rate is 80%, the accident rate decreases by 5.77%. With the increase of total OD demand, the total travel time would decrease by 0 to 6%, and the trend is insignificant. The accident rate reduces by 13.45% at low traffic demand (i.e., 14400 vehicles per hour), and reduces by 3.16% at medium traffic demand (i.e., 21600 vehicles per hour), and reduces by 10.35% at high traffic demand (i.e., 31200 vehicles per hour). The most suitable condition for establishing the CAV dedicated lanes is when traffic demand is low and the penetration rate is around 40%. The findings of this study can provide a theoretical foundation for establishing urban roads dedicated lanes for CAV.

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Cascading Failure and ResilienceAssessment of Urban Traffic Congestion Risk Fields ZHAO Xueting, HU Liwei, ZHOU Jun Journal of Transportation Systems Engineering and Information Technology    2025, 25 (2): 146-156.   DOI: 10.16097/j.cnki.1009-6744.2025.02.014 Abstract （481）      PDF （3919KB）（344）       This paper applies the information physics system to analyze the cascading failure process of urban traffic congestion risk field and proposes the quantitative method for toughness risk size assessment. A CPS(Cyber Physical Systems) control model is developed with mutual coupling of real traffic road network, traffic congestion prevention, and control type zoning of urban traffic congestion risk field in consideration of the multidimensional coupling characteristics of urban traffic congestion risk. The structural characteristics of the traffic domain is examined through the complex network theory. The CPS characteristic parameters are redefined, the four processes of CPS cascade failure are defined, and the CPS cascade failure model is developed with urban traffic congestion risk field. The risk factor is defined as the intervention point and the risk perturbation mechanism is elaborated through the network topology theory. The CPS connectivity is examined through the normalized quantitative node connectivity, delay time, average operating speed, average congestion length and other toughness indexes. The CPS damage perturbation and toughness are evaluated by different failure-recovery strategies, the indicators of the robustness, damage/recovery rate, and recovery capability. The results from case studies show that: (1) Guiyang city urban traffic congestion risk field CPS real traffic network consists of 170 intersections and 231 edges, and the traffic congestion prevention and control type zoning network consist of 21 traffic command areas and 41 edges. (2) The maximum and minimum degree value of the CPS model is respectively 22 and 1. The degree value obeys the power rate distribution function, has characteristic scale-free network features, and the mediator shows the exponential distribution. The degree value perturbation has the greatest influence on the real traffic network of Guiyang city, and the mediator perturbation has the greatest influence on the type of sub-districts of Guiyang city's traffic congestion prevention and control. (3) When t=2 , the network performance starts to decline under both meso and degree perturbation, and the meso perturbation affects the performance more than the degree perturbation, and both reach the lowest at t=7 . (4) The median recovery effect is better than the degree value recovery, under the median perturbation, the degree value recovery and median recovery effect of Guiyang city's real traffic network is poor, the toughness value is respectively 0.01123 and 0.01252, which is significantly lower than that of the toughness value of the traffic congestion prevention and control type of partitioning (0.1355). The proposed model provides reference for the quantitative evaluation and initiation of the traffic congestion control strategy at different stages.

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Cooperative Optimization of Lane Allocation and Vehicle Trajectory at Intersections Under Connected-and-Automated-Vehicle Environment SONG Lang, HU Xiaowei, YU Shanchuan, AN Shi Journal of Transportation Systems Engineering and Information Technology    2025, 25 (5): 59-71.   DOI: 10.16097/j.cnki.1009-6744.2025.05.005 Abstract （473）      PDF （2673KB）（227）       In the collaborative optimization of intersection signal timing and Connected and Automated Vehicle (CAV) trajectory planning, the CAV exit, left turn, through, and right turn lanes can be assigned dynamically in the operation period. Based on the characteristics of CAV technology, this paper proposes a set of dynamic control rules for lane assignment under CAV, named as "flexible lane strategy". Compared to the existing fixed lane strategy, the proposed strategy can adjust the number of exit lanes and entrance lanes (including left turn, through, right turn) for different directions of traffic flow during operation. Lane assignment, signal timing and CAV trajectory planning are incorporated into a unified optimization framework to build a mixed integer linear programming optimization model. Meanwhile, feasible phase and sequence schemes can be automatically generated according to lane assignment in each direction, and the effectiveness of the model is verified through a case study. The results show that the optimization model can generate the optimal lane assignment scheme according to the traffic demand of each flow direction, especially when the lane assignment of the fixed lane strategy does not match the traffic composition of each flow direction, the flexible lane strategy helps to improve the intersection traffic efficiency. In low flow scenario, the flexible Lane strategy reduces average vehicle delay by 4.08%. In high-traffic scenarios, the fixed lane strategy at the intersection will be in a supersaturated state, while the flexible lane strategy can still meet the demand.

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Parking Choice Behavior Analysis of Autonomous Vehicle Users Considering Psychological Factors HAN Yan, YUAN Changyin, TANG Xintian, GUAN Hongzhi Journal of Transportation Systems Engineering and Information Technology    2025, 25 (5): 72-82.   DOI: 10.16097/j.cnki.1009-6744.2025.05.006 Abstract （471）      PDF （2669KB）（173）       Autonomous vehicles equipped with long-range autonomous valet parking function drop off the users at their destinations and then autonomously idle to the remote parking lot to park. It can present an innovative solution to the spatial and temporal misallocation of parking resources in urban centers, and at the same time bring a new problem of choice. Based on the theory of consumer purchase decision, the parking choice mechanism of Privately-owned Automated Vehicles (PAVs) is discussed by introducing two psychological latent variables: perceived risk and waiting attitude. An empirical survey on the parking choice behavior of PAVs users was designed. And an Integrated Choice and Latent Variable (ICLV) model and MNL model were developed for the parking choice behavior of AV users. The results indicate that psychological latent variables, along with personal characteristics, travel attributes, and parking program attributes, significantly influence the parking decisions of users. Moreover, the ICLV model, which incorporates psychological latent variables, demonstrates a notably superior fit over the traditional multinomial Logit model. Destination parking fee is elastic to changes in the probability of parking choice. When the destination parking fee increases from 11 yuan·h -1 to 15 yuan·h -1, the probability of parking choice will decrease from 59.9% to 34.4%, and the probability of proximal parking slots and remote parking slots will increase from 11.8% and 28.3% to 19.4% and 46.2%, respectively. The probability of choosing destination parking will increase from 12.0% and 24.4% to 53.3% and 52.0% when the risk and pick-up waiting aversions perceived by users increase from 1 to 5, respectively. The research findings can provide a theoretical basis for differential parking pricing in regional parking lots in the era of autonomous vehicles.

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Optimization of Recovery Strategy for China's Crude Oil Import Maritime Network from a Resilience Perspective SU Wan, LV Jing, ZHANG Lingye Journal of Transportation Systems Engineering and Information Technology    2025, 25 (1): 36-43.   DOI: 10.16097/j.cnki.1009-6744.2025.01.004 Abstract （462）      PDF （1755KB）（151）       China's high dependence on imported crude oil, coupled with the escalating risks of disruptions in the maritime transportation network, necessitates urgent attention to optimizing recovery strategies and enhancing resilience. Based on actual transportation data, a model of China's crude oil import maritime network has been developed. A resilience assessment method using resilience curves and network efficiency indicators, has been proposed. An optimization model for recovery strategies is established with the objective of maximizing resilience and then applied to five simulated disruption scenarios. The results reveal that the optimal recovery strategy significantly accelerates network recovery across all scenarios, reducing resilience loss by up to 79.14% compared to traditional strategies. The model identifies crucial nodes that significantly impact the network under various scenarios, emphasizing the importance of prioritized recovery to enhance overall efficiency. Furthermore, relaxing detour cost constraints decreases resilience loss and alters the optimal node recovery sequence. The findings provide a foundational basis for decision-making in emergency recovery and resilience enhancement of China's crude oil import maritime network.