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Transit Signal Priority under Connected Vehicle Environment: Deep Reinforcement Learning Approach 车联网环境下的公交信号优先:深度强化学习方法
IF 3.6 3区 工程技术 Q3 TRANSPORTATION Pub Date : 2024-02-29 DOI: 10.1080/15472450.2024.2324385
Tianjia Yang, Wei (David) Fan
Transit Signal Priority (TSP) is a traffic signal control strategy that can provide priority to transit vehicles and thus improve transit service and enhance transportation equity. Conventional TSP...
公交信号优先(TSP)是一种交通信号控制策略,可为公交车辆提供优先权,从而改善公交服务并提高交通公平性。传统的 TSP...
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引用次数: 0
An anti-disturbance lane-changing trajectory tracking control method combining extended Kalman filter and robust tube-based model predictive control 结合扩展卡尔曼滤波器和鲁棒管基模型预测控制的抗干扰变道轨迹跟踪控制方法
IF 3.6 3区 工程技术 Q3 TRANSPORTATION Pub Date : 2024-02-26 DOI: 10.1080/15472450.2024.2315136
Fangzhi Yin, Changyin Dong, Ye Li, Yujia Chen, Hao Wang
This paper proposes a trajectory tracking control method combining extended Kalman filter (EKF) and robust tube-based model predictive control (RTMPC) methods to improve the anti-disturbance capabi...
本文提出了一种结合扩展卡尔曼滤波器(EKF)和鲁棒性管基模型预测控制(RTMPC)方法的轨迹跟踪控制方法,以提高飞机的抗干扰能力。
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引用次数: 0
A spatiotemporal distribution identification method of vehicle weights on bridges by integrating traffic video and toll station data 整合交通视频和收费站数据的桥梁车辆重量时空分布识别方法
IF 3.6 3区 工程技术 Q3 TRANSPORTATION Pub Date : 2024-02-25 DOI: 10.1080/15472450.2024.2312810
Jianliang Zhang, Yuyao Cheng, Jian Zhang, Zhishen Wu
Real-time monitoring of the spatiotemporal distribution of vehicle weights on bridge decks is an important component of bridge structural health monitoring systems. However, it is still a challenge...
实时监测桥面上车辆重量的时空分布是桥梁结构健康监测系统的重要组成部分。然而,这仍然是一项挑战...
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引用次数: 0
Fuzing multiple erroneous sensors to estimate travel time 引信多个错误传感器来估算旅行时间
IF 3.6 3区 工程技术 Q3 TRANSPORTATION Pub Date : 2024-02-13 DOI: 10.1080/15472450.2024.2315514
Fatemeh Banani Ardecani, Ahmadreza Mahmoudzadeh, Mahmoud Mesbah
Estimating accurate travel time information is one of the fundamental tasks in controlling city traffic. In general, fuzing multiple sensors can generate more accurate information to measure traffi...
估算准确的旅行时间信息是控制城市交通的基本任务之一。一般来说,使用多个传感器可以产生更准确的信息来测量交通流量。
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引用次数: 0
Deep survival analysis model for incident clearance time prediction 用于事故清理时间预测的深度生存分析模型
IF 3.6 3区 工程技术 Q3 TRANSPORTATION Pub Date : 2024-02-12 DOI: 10.1080/15472450.2024.2315126
Eui-Jin Kim, Min-Ji Kang, Shin Hyoung Park
Incident clearance time prediction is a key task for traffic incident management. A hazard-based duration model is a prevalent approach for predicting and analyzing the incident clearance time, whi...
事故清理时间预测是交通事故管理的一项关键任务。基于危险的持续时间模型是预测和分析事故清理时间的一种常用方法,它可以预测和分析事故清理时间。
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引用次数: 0
Reinforcement learning approach to develop variable speed limit strategy using vehicle data and simulations 利用车辆数据和模拟,采用强化学习方法制定变速限制策略
IF 3.6 3区 工程技术 Q3 TRANSPORTATION Pub Date : 2024-02-08 DOI: 10.1080/15472450.2024.2312808
Yunjong Kim, Kawon Kang, Nuri Park, Juneyoung Park, Cheol Oh
A variety of studies have been conducted to evaluate real-time crash risk using vehicle trajectory data and to establish active traffic safety management measures. Speed management is an effective ...
为了利用车辆轨迹数据评估实时碰撞风险并制定积极的交通安全管理措施,已经开展了多项研究。车速管理是一种有效的交通安全管理措施。
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引用次数: 0
Real-time anomaly detection of short-term traffic disruptions in urban areas through adaptive isolation forest 通过自适应隔离林实时检测城市地区短期交通中断的异常情况
IF 3.6 3区 工程技术 Q3 TRANSPORTATION Pub Date : 2024-02-08 DOI: 10.1080/15472450.2024.2312809
Jingqin Gao, Kaan Ozbay, Yu Hu
The escalating congestion impacts of short-term traffic disruptions, such as double parking or short-duration work zones, are gaining increased attention. This study introduces an enhanced isolatio...
短期交通中断(如双倍停车或短时工作区)对交通拥堵造成的影响日益严重,正受到越来越多的关注。本研究引入了一种增强型隔离系统,它能在短时间内对交通拥堵造成的影响进行分析。
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引用次数: 0
Predicting the duration of reduced driver performance during the automated driving takeover process 预测自动驾驶接管过程中驾驶员表现下降的持续时间
IF 3.6 3区 工程技术 Q3 TRANSPORTATION Pub Date : 2024-02-07 DOI: 10.1080/15472450.2024.2307029
Changshuai Wang, Chengcheng Xu, Chang Peng, Hao Tong, Weilin Ren, Yanli Jiao
This study carried out a simulator test to determine and predict the duration of reduced driver performance during the automated driving takeover process. Vehicle trajectory and driver behavior dat...
本研究进行了模拟器测试,以确定并预测自动驾驶接管过程中驾驶员表现下降的持续时间。车辆轨迹和驾驶员行为数据...
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引用次数: 0
Generative adversarial network for car following trajectory generation and anomaly detection 用于生成汽车行驶轨迹和异常检测的生成对抗网络
IF 3.6 3区 工程技术 Q3 TRANSPORTATION Pub Date : 2024-02-06 DOI: 10.1080/15472450.2023.2301691
Haotian Shi, Shuoxuan Dong, Yuankai Wu, Qinghui Nie, Yang Zhou, Bin Ran
Car-following trajectory generation and anomaly detection are critical functions in the sensing module of an automated vehicle. However, developing models that capture realistic trajectory data dis...
汽车行驶轨迹生成和异常检测是自动驾驶汽车传感模块的关键功能。然而,开发能捕捉真实轨迹数据的模型并不容易。
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引用次数: 0
Optimal lane allocation strategy for shared autonomous vehicles mixed with regular vehicles 自动驾驶车辆与普通车辆混合共用的最佳车道分配策略
IF 3.6 3区 工程技术 Q3 TRANSPORTATION Pub Date : 2024-01-31 DOI: 10.1080/15472450.2024.2307027
Yangbeibei Ji, Jingwen Liu, Hanwan Jiang, Xinru Xing, Wurong Fu, Xueqing Lu
Autonomous driving technology has the potential to alter the way we travel and is rapidly evolving. Sharing rides in autonomous vehicles may become a popular mode of public transportation in the fu...
自动驾驶技术有可能改变我们的出行方式,并且正在迅速发展。在未来,共享自动驾驶汽车可能会成为一种流行的公共交通方式。
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引用次数: 0
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Journal of Intelligent Transportation Systems
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