Heuristic Platoon Control Method for CAVs at Urban Intersections

[国外交通期刊数据库] 作者:Zhuoran Li;Gongyuan Lu;Xiaobo Liu;Peng Cao

摘要:Reservation-based intersection control for connected and automated vehicles (CAVs) is promising to improve travel mobility, safety, energy consumption, and reducing emissions. Though the first-come-first-served (FCFS) policy is proven to be effective in i

Capacity Adjustment of Lane Number for Mixed Autonomous Vehicles Flow Considering Stochastic Lateral Interactions

[国外交通期刊数据库] 作者:Hongsheng QI

摘要:Autonomous vehicles (AVs) are revolutionizing the transportation system and necessitating a reevaluation of infrastructure capacity. Apart from their shorter headway, AVs exhibit distinct behavioral characteristics compared to human-driven vehicles (HDVs)

Quantitative Analysis of Vehicular Traffic Flow Order at Signalized Intersections

[国外交通期刊数据库] 作者:Rongji Zhang;Jing Zhao;Pengfei Liu;Xinwei Wang

摘要:A quantitative evaluation of the traffic flow order is necessary to improve the operational level at intersections. To date, how to assess the subjective perceptions of the traffic flow order at intersections is unclear. This study develops a visual analo

Informing the Work Zone Safety Policy Analysis: Reconciling Multivariate Prediction and Artificial Neural Network Modeling

[国外交通期刊数据库] 作者:Amin Shaer;Ahmadreza Talebian;Sabyasachee Mishra

摘要:Work zone safety, as an issue requiring complex solutions and tech-driven investment, has been a major concern for transportation agencies and policymakers. To help decision-makers prioritize investments, there is a need for tools enabling them to assess

Cloud-Based Platoon Predictive Cruise Control Considering Fuel-Efficient and Platoon Stability

[国外交通期刊数据库] 作者:Zhou Wang;Duanfeng Chu;Bolin Gao;Liang Wang;Xiaobo Qu;Keqiang Li

摘要:This work investigates commercial vehicle platoon predictive cruise control for highways. We propose a cloud-based platoon predictive cruise control method (CPPCC). A two-layered control architecture of the CPPCC is proposed as a platoon predictive cruise

Modified Reliability Theory for Speed-Based Evaluation of Successive Geometric Elements

[国外交通期刊数据库] 作者:Apratim Datta;Gourab Sil;Avijit Maji

摘要:The current study proposes a modified reliability theory and methodology for the speed-based evaluation of successive geometric elements such as a long tangent followed by a curve. A formulation based on lower limit and upper limit speed adjustments, S_L

Research on a Novel Arresting System for Escape Ramps: Design and Experiment

[国外交通期刊数据库] 作者:Xiuchen Xu;Hongchao Zhang;Xiaobo Du;Xianpeng Zhao

摘要:Runaway accidents caused by vehicle braking have been extensively studied from the perspective of passenger safety. The traditional escape ramp alleviates such conditions to some extent, which places higher demands on human protection and more complex app

An Attention Reinforcement Learning-Based Strategy for Large-Scale Adaptive Traffic Signal Control System

[国外交通期刊数据库] 作者:Gengyue Han;Xiaohan Liu;Hao Wang;Changyin Dong;Yu Han

摘要:This paper proposes a reinforcement learning (RL)-based traffic control strategy integrated with attention mechanism for large-scale adaptive traffic signal control (ATSC) system. The proposed attention RL integrates attention mechanism into a multiagent

Overnight Charging Scheduling Optimization for Electric Battery Buses with Controllable Charging Completion Levels

[国外交通期刊数据库] 作者:Feifeng Zheng;Zhixin Wang;Yinfeng Xu;Ming Liu

摘要:In the application of battery electric buses, cruising range anxiety, high charging cost, and unreasonable allocation of charging resources are essential factors hindering their promotion. This study aims to identify an overnight charging schedule for bat

Prediction of Truck-Involved Crsh Severity on Rurl Mountinous Freewy Using Trnsfer Lerning with ResNet-50 Deep Neurl Network

[国外交通期刊数据库] 作者:Nasim Khan;Anik Das;Mohamed M. Ahmed

摘要:Crashes involving heavy trucks on rural mountainous freeways are known to result in severe injuries and fatalities, particularly under challenging driving conditions. This study aims to develop a robust model to accurately predict fatal and injury crashes