Driving risk assessment under the connected vehicle environment:a CNN-LSTM modeling approach  

作　　者：Yin Zheng Lei Han Jiqing Yu Rongjie Yu 

机构地区：[1]The Key Laboratory of Road and Traffic Engineering,Ministry of Education,No.4800 Cao'an Road,Shanghai 201804,China [2]College of Transportation Engineering,Tongji University,No.4800 Cao'an Road,Shanghai 201804,China [3]Ningbo Hangzhou Bay Bridge Development Co.,Ltd.,No.1 Hongqiao Road,Cixi 315300,Ningbo,China

出　　处：《Digital Transportation and Safety》2023年第3期211-219,共9页数字交通与安全（英文）

基　　金：sponsored by the Zhejiang Province Science and Technology Major Project of China(No.2021C01011);the National Natural Science Foundation of China(NSFC)(No.52172349);the China Scholarship Council(CSC).

摘　　要：Connected vehicle(CV)is regarded as a typical feature of the future road transportation system.One 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 critical.There 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 variability.Hence,this study proposes a driving risk assessment framework under the CV environment.Specifically,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 vehicle.Then,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 environment.It is proved that this model can reach an AUC of 0.997,outperforming the existing machine learning algorithms.This 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 

分 类 号：U46[机械工程—车辆工程]