Journal of Intelligent Transportation Systems最新文献

Comparing the performance of metaheuristics on the Transit Network Frequency Setting Problem 比较公交网络班次设置问题的元追求法性能

IF 2.8 3区工程技术

Journal of Intelligent Transportation Systems Pub Date : 2026-01-02 Epub Date: 2024-08-15 DOI: 10.1080/15472450.2024.2392722

İlyas Cihan Aksoy , Mehmet Metin Mutlu

{"title":"Comparing the performance of metaheuristics on the Transit Network Frequency Setting Problem","authors":"İlyas Cihan Aksoy , Mehmet Metin Mutlu","doi":"10.1080/15472450.2024.2392722","DOIUrl":"10.1080/15472450.2024.2392722","url":null,"abstract":"<div><div>The Transit Network Frequency Setting Problem (TNFSP), an NP-Hard combinatorial optimization problem, has been frequently addressed in previous investigations, most of which employ metaheuristics. However, previous studies have not investigated to determine the best metaheuristic and the most effective parameter values for the TNFSP. This study aims to fill this research gap by comprehensively comparing five well-known metaheuristics, namely, Artificial Bee Colony, Differential Evolution, Firefly Algorithm, Genetic Algorithm, and Particle Swarm Optimization, on the TNFSP. The best parameter configurations for employed metaheuristics are determined using the brute-force method. The comparative results not only highlight the significance of metaheuristic selection in addressing the TNFSP but also reveal the importance of choosing the most suitable parameter values for these metaheuristics. Furthermore, the metaheuristics are performed on the transit networks obtained from previously published studies for comparison purposes. The results demonstrate that the metaheuristics achieve better frequency sets than the original frequency sets of the used transit networks.</div></div>","PeriodicalId":54792,"journal":{"name":"Journal of Intelligent Transportation Systems","volume":"30 1","pages":"Pages 1-20"},"PeriodicalIF":2.8,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142247329","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimizing dedicated lanes and tolling schemes for connected and autonomous vehicles to address bottleneck congestion considering morning commuter departure choices 优化联网和自动驾驶汽车的专用车道和收费方案，以解决早晨通勤者出发选择的瓶颈拥堵问题

IF 2.8 3区工程技术

Journal of Intelligent Transportation Systems Pub Date : 2026-01-02 Epub Date: 2024-09-24 DOI: 10.1080/15472450.2024.2408024

Sania E. Seilabi , Mohammadhosein Pourgholamali , Mohammad Miralinaghi , Gonçalo Homem de Almeida Correia , Xiaozheng (Sean) He , Samuel Labi

{"title":"Optimizing dedicated lanes and tolling schemes for connected and autonomous vehicles to address bottleneck congestion considering morning commuter departure choices","authors":"Sania E. Seilabi , Mohammadhosein Pourgholamali , Mohammad Miralinaghi , Gonçalo Homem de Almeida Correia , Xiaozheng (Sean) He , Samuel Labi","doi":"10.1080/15472450.2024.2408024","DOIUrl":"10.1080/15472450.2024.2408024","url":null,"abstract":"<div><div>The introduction of connected and autonomous vehicles (CAVs) provides a significant opportunity to address the persistently increasing problem of urban traffic congestion. By virtue of their connectivity and automation features, CAVs can reduce vehicle headways, thereby increasing road capacity and enhancing throughput. It has been hypothesized that CAV-infrastructure design policies can influence traveler behavior in ways that could reduce congestion. This research focuses on the potential of using CAV-dedicated lanes (CAVL) to alleviate traffic congestion in a bottleneck corridor that serves both human-driven vehicles (HDVs) and CAVs. We delve into investigating the impacts of CAVLs on the departure time and lane choices of morning commuters. The study first expresses traffic equilibrium conditions as a linear program with complementarity constraints. Then, a system-optimal commute congestion management design is formulated to minimize the overall system cost, which consists of queuing delays and early and late arrival costs. The results of the computational experiments suggest that: (i) the CAV technological advancements can significantly reduce traffic congestion under CAVL deployment with an almost similar effect as a tolling policy; and (ii) the lower value of time for CAV commuters leads them to depart closer to their desired arrival time without a tolling policy, which could significantly increase the bottleneck traffic congestion that commuters experience, particularly HDVs.</div></div>","PeriodicalId":54792,"journal":{"name":"Journal of Intelligent Transportation Systems","volume":"30 1","pages":"Pages 37-54"},"PeriodicalIF":2.8,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147855399","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Consecutive attractive local regions – bidirectional long short-term memory for trip destination prediction 连续吸引局部区域-双向长短期记忆的旅行目的地预测

IF 2.8 3区工程技术

Journal of Intelligent Transportation Systems Pub Date : 2026-01-02 Epub Date: 2024-09-09 DOI: 10.1080/15472450.2024.2402699

Mohammad Iqbal , Farid Kurniatama , Mohammad Isa Irawan , Imam Mukhlash , Bandung Arry Sanjoyo

{"title":"Consecutive attractive local regions – bidirectional long short-term memory for trip destination prediction","authors":"Mohammad Iqbal , Farid Kurniatama , Mohammad Isa Irawan , Imam Mukhlash , Bandung Arry Sanjoyo","doi":"10.1080/15472450.2024.2402699","DOIUrl":"10.1080/15472450.2024.2402699","url":null,"abstract":"<div><div>We propose a sequence-to-sequence model to capture a partial trajectory that contains a few attractive local regions and forecast its destination. Therefore, the main goal of this work is to predict the destination, given the trip’s trajectory, effectively by learning from its attractive local sub-trajectory only. Conceptually, the proposed model incorporates Bidirectional Long Short-Term Memory (BiLSTM) for finding frequent trip trajectories and a Consecutive Attractive Local Regions (CALR) mechanism for only taking their few attractive local regions, called CALR-BiLSTM. Existing related works focused on observing whole regions of each trip trajectory at once to decide its attractive ones from a Global Attention Mechanism (GAM). However, GAM may hold similar attractive sub-trajectories for different destinations, which leads to worse predictions. To overcome the issue, the proposed model observes the entire trip trajectory part by part within a small window, such as focusing on a few regions that are attractive. In this work, we demonstrated the proposed model on large public datasets. As a result, we can enjoy the proposed model as the winner against the state-of-the-art models. Moreover, we present ablation studies on various recurrent neural networks and attention mechanisms to ensure the proposed model is in the right settings.</div></div>","PeriodicalId":54792,"journal":{"name":"Journal of Intelligent Transportation Systems","volume":"30 1","pages":"Pages 21-36"},"PeriodicalIF":2.8,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147855398","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Logistics park charging station optimization using improved genetic algorithms 利用改进遗传算法优化物流园区充电站

IF 2.8 3区工程技术

Journal of Intelligent Transportation Systems Pub Date : 2026-01-02 Epub Date: 2024-10-21 DOI: 10.1080/15472450.2024.2418922

Bo Liu , Liguang Li , Hua Huang , Xitong Zhang

引用次数: 0

String stable control design for automated vehicles under cyberattacks 网络攻击下自动驾驶车辆串稳定控制设计

IF 2.8 3区工程技术

Journal of Intelligent Transportation Systems Pub Date : 2026-01-02 Epub Date: 2024-11-09 DOI: 10.1080/15472450.2024.2425297

Shian Wang , Michael W. Levin , Raphael Stern

{"title":"String stable control design for automated vehicles under cyberattacks","authors":"Shian Wang , Michael W. Levin , Raphael Stern","doi":"10.1080/15472450.2024.2425297","DOIUrl":"10.1080/15472450.2024.2425297","url":null,"abstract":"<div><div>Emerging automated vehicle (AV) technologies open a door for cyberattacks, where a select number of AVs are compromised to drive in an adversarial manner, degrading the performance of transportation systems. Hence, designing stable controls for AVs that can mitigate the impact of attacks on traffic flow is important and necessary as AVs gradually become a reality. In this study, we first present a general framework for describing mixed-autonomy traffic involving AVs and human-driven vehicles (HVs) based on car-following dynamics. Under this framework, a class of malicious attacks on AV control commands (vehicle acceleration) is mathematically characterized. To deal with the lack of knowledge of the attacks, we model attacks as an unstructured process, allowing for the inclusion of both deterministic and stochastic attack behaviors, bounded by a known bound (to remain stealthy) without being subject to any specific statistical distribution. Moreover, we analytically derive a set of sufficient conditions for string stable control design of individual AVs which can help mitigate the disturbances to traffic flow caused by unknown attacks on AVs. Furthermore, for any given market penetration rate of AVs, a set of conditions is also derived for selecting appropriate feedback gains of AVs to ensure string stability of heterogeneous traffic, reducing the undesired impact of attacks on traffic flow. These sufficient conditions provide important criteria for string stable control design of AVs without requiring much knowledge of the attacks. A series of numerical results is presented to show effectiveness of the proposed approach on mitigating attack disruption.</div></div>","PeriodicalId":54792,"journal":{"name":"Journal of Intelligent Transportation Systems","volume":"30 1","pages":"Pages 177-189"},"PeriodicalIF":2.8,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147855406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Toward the integration of vehicle-to-infrastructure (V2I) communication in transportation system: an investigation of drivers’ perceptions and preferences for V2I messages 交通系统中车辆到基础设施（V2I）通信的整合：驾驶员对V2I信息的感知和偏好的调查

IF 2.8 3区工程技术

Journal of Intelligent Transportation Systems Pub Date : 2026-01-02 Epub Date: 2024-10-12 DOI: 10.1080/15472450.2024.2416165

Taniya Sultana , Hany M. Hassan , Brian Wolshon

{"title":"Toward the integration of vehicle-to-infrastructure (V2I) communication in transportation system: an investigation of drivers’ perceptions and preferences for V2I messages","authors":"Taniya Sultana , Hany M. Hassan , Brian Wolshon","doi":"10.1080/15472450.2024.2416165","DOIUrl":"10.1080/15472450.2024.2416165","url":null,"abstract":"<div><div>Vehicle-to-infrastructure (V2I) communication is a key component of the emerging Connected and Automated Vehicles (CAVs) technology. Although previous studies have investigated driver behaviors toward V2I messages, there remains a gap in understanding the underlying factors behind driver perspectives and preferences regarding this communication technology. This paper aims to examine drivers’ preferences, encompassing both their willingness to purchase V2I-equipped vehicles and their preferences for receiving V2I messages, as well as their perceptions of these messages. Additionally, the contributing factors behind these perceptions and preferences were also determined. Data from an online national survey of 1563 drivers from across the United States was analyzed using descriptive statistics and structural equation modeling. Descriptive statistics showed that over 83% of the respondents perceived V2I warning messages as ‘important or extremely important’ to their driving. The structural equation modeling revealed that gender, age, driving experience, commute time, vehicle ownership, education, and prior crash involvement significantly influence drivers’ preferences for V2I communication. The results suggested that individuals who are younger, female, novice, highly educated, long-time commuters with prior crash involvement and lower vehicle ownership are more likely to buy future V2I-equipped vehicles. These same groups also showed increased preference for receiving V2I messages at multiple locations and through multiple methods. Moreover, drivers with favorable views of existing in-vehicle safety-related features (e.g., blind-spot assistance.) demonstrated a higher inclination to own future V2I-equipped vehicles. By providing valuable insights on drivers’ preferences and perceptions, this study contributes to improved planning for the integration of V2I technology in transportation systems.</div></div>","PeriodicalId":54792,"journal":{"name":"Journal of Intelligent Transportation Systems","volume":"30 1","pages":"Pages 69-91"},"PeriodicalIF":2.8,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147855401","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Forecasting short-term subway passenger flow using Wi-Fi data: comparative analysis of advanced time-series methods 基于Wi-Fi数据的短期地铁客流预测：先进时间序列方法的对比分析

IF 2.8 3区工程技术

Journal of Intelligent Transportation Systems Pub Date : 2026-01-02 Epub Date: 2024-10-21 DOI: 10.1080/15472450.2024.2417175

Diego Da Silva , Amer Shalaby

{"title":"Forecasting short-term subway passenger flow using Wi-Fi data: comparative analysis of advanced time-series methods","authors":"Diego Da Silva , Amer Shalaby","doi":"10.1080/15472450.2024.2417175","DOIUrl":"10.1080/15472450.2024.2417175","url":null,"abstract":"<div><div>Accurately monitoring passenger demand fluctuations is crucial for streamlined operations of subway systems and informed decision-making. This study presents a detailed Time Series Analysis of the Toronto subway system using Wi-Fi data connection from devices as a predictor of passenger volume. Various time series models were tested for short-term forecasting, including Linear Regression, Exponential Smoothing, ARIMA, Random Forest, N-BEATS, and T-GCN. An end-to-end modeling implementation process was carried out, and the performance of each model was evaluated. The primary objective was to assess the effectiveness of short-term prediction models for univariate time series at the system level and discuss deployment challenges. While conventional time series models are fast to implement and interpretable, they require a more in-depth data exploration phase for validation, making scaling at the system level difficult. Additionally, maintenance is more challenging with conventional models, and their exploratory analysis phases need to be repeated when the models degrade over time. Prediction difficulty varied across each subway station, indicating the need for a more thorough calibration or hybrid approach, especially for transfer stations. Despite the different uses and qualities of each model in our scenario, Random Forest and Exponential Smoothing emerged as the best performers and could be a satisfactory option for robust demand forecasting at the system level.</div></div>","PeriodicalId":54792,"journal":{"name":"Journal of Intelligent Transportation Systems","volume":"30 1","pages":"Pages 108-128"},"PeriodicalIF":2.8,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147855403","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Robust dynamic real-time control strategies for high-frequency bus service: a multi-agent reinforcement learning framework 高频公交服务鲁棒动态实时控制策略：一个多智能体强化学习框架

IF 2.8 3区工程技术

Journal of Intelligent Transportation Systems Pub Date : 2026-01-02 Epub Date: 2024-11-10 DOI: 10.1080/15472450.2024.2425293

Victor Jian Ming Low , Hooi Ling Khoo , Wooi Chen Khoo

{"title":"Robust dynamic real-time control strategies for high-frequency bus service: a multi-agent reinforcement learning framework","authors":"Victor Jian Ming Low , Hooi Ling Khoo , Wooi Chen Khoo","doi":"10.1080/15472450.2024.2425293","DOIUrl":"10.1080/15472450.2024.2425293","url":null,"abstract":"<div><div>This study addresses the multifaceted challenge of ensuring the regularity of bus services, minimizing bus bunching, and facilitating synchronized bus connections across routes. An enhanced multi-agent reinforcement learning algorithm, namely the Multi-Agent Deep Deterministic Policy Gradient (MADDPG) algorithm, is proposed to implement real-time control strategies for addressing these issues simultaneously. The merit of the modified MADDPG algorithm lies in its ability to continuously learn while adeptly navigating the non-stationary operating nature of bus system networks. A case study of a bus corridor is used to train and test the algorithm. Four robust scenarios, each presenting varying degrees of travel time and dwell time variations, are designed to assess the algorithm’s robustness. Results indicate that the MADDPG algorithm can significantly increase the likelihood of synchronized bus transfers across multiple routes by two or three times while maintaining the service reliability on each route. Moreover, the flexibility of the MADDPG algorithm in training bus policies allows it to effectively adapt to up to 90% variations in bus travel times and demand changes, even amid disruptive events in real-world scenarios.</div></div>","PeriodicalId":54792,"journal":{"name":"Journal of Intelligent Transportation Systems","volume":"30 1","pages":"Pages 157-176"},"PeriodicalIF":2.8,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147855405","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Wide human-like neural network incorporating driving styles for human-like driving intention analysis 结合驾驶风格的广泛类人神经网络，用于类人驾驶意图分析

IF 2.8 3区工程技术

Journal of Intelligent Transportation Systems Pub Date : 2026-01-02 Epub Date: 2024-11-04 DOI: 10.1080/15472450.2024.2425304

Jiming Xie , Yan Zhang , Yaqin Qin , Ke Li , Shuai Dong , Siyu Liu , Yulan Xia

{"title":"Wide human-like neural network incorporating driving styles for human-like driving intention analysis","authors":"Jiming Xie , Yan Zhang , Yaqin Qin , Ke Li , Shuai Dong , Siyu Liu , Yulan Xia","doi":"10.1080/15472450.2024.2425304","DOIUrl":"10.1080/15472450.2024.2425304","url":null,"abstract":"<div><div>Enhancing the synergy between autonomous and human-driven vehicles at the societal level requires understanding drivers’ behaviors and cognitive patterns, as well as conducting human-like driving intention analysis. To achieve this goal, this study designs a novel framework for analyzing human-like driving intention. Firstly, a spectral clustering method is employed to characterize driving styles. Secondly, a misclassification cost matrix is tailored to different driving needs. Finally, inspired by the complex neural networks found in the human brain, we develop a specialized lightweight neural network, termed the Width Human-like Neural Network (WNN), aimed at realizing personalized cognition and facilitating human-like decision-making in driving intention. Experimental studies and validation based on natural driving trajectory data from Kunming, China, demonstrate that the method accurately infers internal implicit driving intention from external explicit and observable driving behaviors, achieving a prediction accuracy of 99.8%. This framework strategically allocates limited computational resources to critical areas for autonomous vehicles and exemplifies best practices for improving neural network performance in driving intention analysis tasks.</div></div>","PeriodicalId":54792,"journal":{"name":"Journal of Intelligent Transportation Systems","volume":"30 1","pages":"Pages 190-211"},"PeriodicalIF":2.8,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147855407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

LiDAR-camera fusion: dual-scale correction for vehicle multi-object detection and trajectory extraction 激光雷达-相机融合：车辆多目标检测和轨迹提取的双尺度校正

IF 2.8 3区工程技术

Journal of Intelligent Transportation Systems Pub Date : 2026-01-02 Epub Date: 2024-10-11 DOI: 10.1080/15472450.2024.2416164

Ting Fu , Shuke Xie , Weichao Hu , Junhua Wang , Zixuan Cui

{"title":"LiDAR-camera fusion: dual-scale correction for vehicle multi-object detection and trajectory extraction","authors":"Ting Fu , Shuke Xie , Weichao Hu , Junhua Wang , Zixuan Cui","doi":"10.1080/15472450.2024.2416164","DOIUrl":"10.1080/15472450.2024.2416164","url":null,"abstract":"<div><div>The different principles of sensor technology determine their distinct performance in vehicle detection and microscopic tracking. Vision-based sensors can provide rich semantic information but lack reliable spatial information, and their reliability is reduced in complex lighting conditions. On the other hand, LiDAR can offer high-precision spatial information independent of lighting conditions, but it suffers from low resolution and effective sampling rate limitations. Considering the strong complementarity between images and point clouds, efficient object detection can be achieved by leveraging their synergy. However, existing research has not fully explored the correlation between the features of these two types of data. This paper proposes a novel dual-scale correction strategy for feature-level fusion of camera and LiDAR data. This strategy captures spatial features of point clouds and semantic features of images at both global and local scales and establishes mapping relationships separately. The global correction results are iteratively updated based on the results of local precision correction. To validate the effectiveness of the proposed method, data is collected from highway and urban expressway scenarios. The results indicate improvements in both object detection and microscopic trajectory tracking performance compared to using single sensors alone. Furthermore, the fusion approach outperforms other methods in terms of detection accuracy and processing time. This research offers a method for real-time and accurate extraction of vehicle trajectories using roadside cameras and LiDAR devices, with potential applications in real-time trajectory tracking and traffic management.</div></div>","PeriodicalId":54792,"journal":{"name":"Journal of Intelligent Transportation Systems","volume":"30 1","pages":"Pages 55-68"},"PeriodicalIF":2.8,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147855400","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0