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Digital Transportation and Safety 2023年第3期2卷 211-219页

作者： Yin Zheng Lei Han Jiqing Yu Rongjie Yu The Key Laboratory of Road and Traffic Engineering Ministry of EducationNo.4800 Cao'an RoadShanghai 201804China College of Transportation Engineering Tongji UniversityNo.4800 Cao'an RoadShanghai 201804China Ningbo Hangzhou Bay Bridge Development Co. Ltd.No.1 Hongqiao RoadCixi 315300NingboChina

connected vehicle(CV)is regarded as a typical feature of the future road transportation *** core benefit of promoting CV is to improve traffic safety,and to achieve that,accurate driving risk assessment under vehicle-to-vehicle(V2V)communications is *** are two main differences concluded by comparing driving risk assessment under the CV environment with traditional ones:(1)the CV environment provides high-resolution and multi-dimensional data,e.g.,vehicle trajectory data,(2)Rare existing studies can comprehensively address the heterogeneity of the vehicle operating environment,e.g.,the multiple interacting objects and the time-series ***,this study proposes a driving risk assessment framework under the CV ***,first,a set of time-series top views was proposed to describe the CV environment data,expressing the detailed information on the vehicles surrounding the subject ***,a hybrid CNN-LSTM model was established with the CNN component extracting the spatial interaction with multiple interacting vehicles and the LSTM component solving the time-series variability of the driving *** is proved that this model can reach an AUC of 0.997,outperforming the existing machine learning *** study contributes to the improvement of driving risk assessment under the CV environment.

关键词： connected vehicle connected vehicle environment Driving risk assessment CNN-LSTM Traffic safety

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Predictive car-following scheme for improving traffic flows on urban road networks

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Control Theory and Technology 2019年第4期17卷 325-334页

作者： A.S.M.BAKIBILLAH Mahmudul HASAN Md Mustafijur RAHMAN Md Abdus Samad KAMAL School of Engineering Monash UniversityBandar SunwaySelangorMalaysia Technology Operations Department Grameenphone Ltd.DhakaBangladesh Department of Electrical and Electronic Engineering Manarat International UniversityDhakaBangladesh Division of Mechanical Science and Technology Graduate School of Science and TechnologyGunma UniversityJapan

Driving behavior is one of the main reasons that causes bottleneck on the freeway or restricts the capacity of signalized *** paper proposes a car-following scheme in a model predictive control(MPC)framework to improve the traffic flow behavior,particularly in stopping and speeding up of individual vehicles in dense urban traffic under a connected vehicle(CV)*** information received through vehicle-to-vehicle(V2V)communication,the scheme predicts the future states of the preceding vehicle and computes the control input by solving a constrained optimization problem considering a finite future *** objective function is to minimize the weighted costs due to speed deviation,control input,and unsafe *** scheme shares the planned driving information with the following vehicles so that they can make better cooperative driving *** proposed car-following scheme is simulated in a typical driving scenario with multiple vehicles in dense traffic that has to stop at red signals in multiple *** speeding up or queue clearing and stopping characteristics of the traffic using the proposed scheme is compared with the existing car-following scheme through numerical simulation.

关键词： Car-following scheme model predictive control vehicle string connected vehicle environment distributed control

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