Zhigang Xu (徐志刚)
Zhigang Xu (徐志刚)
Потвърден имейл адрес: chd.edu.cn - Начална страница
What drives people to accept automated vehicles? Findings from a field experiment
Z Xu, K Zhang, H Min, Z Wang, X Zhao, P Liu
Transportation research part C: emerging technologies 95, 320-334, 2018
Public acceptance of fully automated driving: Effects of social trust and risk/benefit perceptions
P Liu, R Yang, Z Xu
Risk Analysis 39 (2), 326-341, 2019
DSRC versus 4G‐LTE for connected vehicle applications: a study on field experiments of vehicular communication performance
Z Xu, X Li, X Zhao, MH Zhang, Z Wang
Journal of advanced transportation 2017 (1), 2750452, 2017
Fusion of 3D LIDAR and camera data for object detection in autonomous vehicle applications
X Zhao, P Sun, Z Xu, H Min, H Yu
IEEE Sensors Journal 20 (9), 4901-4913, 2020
Willingness to pay for self-driving vehicles: Influences of demographic and psychological factors
P Liu, Q Guo, F Ren, L Wang, Z Xu
Transportation Research Part C: Emerging Technologies 100, 306-317, 2019
How safe is safe enough for self‐driving vehicles?
P Liu, R Yang, Z Xu
Risk analysis 39 (2), 315-325, 2019
Field experiments on longitudinal characteristics of human driver behavior following an autonomous vehicle
X Zhao, Z Wang, Z Xu, Y Wang, X Li, X Qu
Transportation research part C: emerging technologies 114, 205-224, 2020
Road tests of self-driving vehicles: Affective and cognitive pathways in acceptance formation
P Liu, Z Xu, X Zhao
Transportation research part A: policy and practice 124, 354-369, 2019
A piecewise trajectory optimization model for connected automated vehicles: Exact optimization algorithm and queue propagation analysis
X Li, A Ghiasi, Z Xu, X Qu
Transportation Research Part B: Methodological 118, 429-456, 2018
Modeling relationship between truck fuel consumption and driving behavior using data from internet of vehicles
Z Xu, T Wei, S Easa, X Zhao, X Qu
Computer‐Aided Civil and Infrastructure Engineering 33 (3), 209-219, 2018
A 3D LiDAR data-based dedicated road boundary detection algorithm for autonomous vehicles
P Sun, X Zhao, Z Xu, R Wang, H Min
IEEE Access 7, 29623-29638, 2019
V2V‐based method for the detection of road traffic congestion
R Wang, Z Xu, X Zhao, J Hu
IET Intelligent Transport Systems 13 (5), 880-885, 2019
Public attitude toward self-driving vehicles on public roads: Direct experience changed ambivalent people to be more positive
P Liu, Z Xu
Technological Forecasting and Social Change 151, 119827, 2020
Congestion propagation based bottleneck identification in urban road networks
C Li, W Yue, G Mao, Z Xu
IEEE Transactions on Vehicular Technology 69 (5), 4827-4841, 2020
Domain adaptation from daytime to nighttime: A situation-sensitive vehicle detection and traffic flow parameter estimation framework
J Li, Z Xu, L Fu, X Zhou, H Yu
Transportation Research Part C: Emerging Technologies 124, 102946, 2021
Machines versus humans: People’s biased responses to traffic accidents involving self-driving vehicles
P Liu, Y Du, Z Xu
Accident Analysis & Prevention 125, 232-240, 2019
A fault detection and diagnosis system for autonomous vehicles based on hybrid approaches
Y Fang, H Min, W Wang, Z Xu, X Zhao
IEEE Sensors Journal 20 (16), 9359-9371, 2020
Modeling and field experiments on autonomous vehicle lane changing with surrounding human‐driven vehicles
Z Wang, X Zhao, Z Xu, X Li, X Qu
Computer‐Aided Civil and Infrastructure Engineering 36 (7), 877-889, 2021
A fault diagnosis framework for autonomous vehicles with sensor self-diagnosis
H Min, Y Fang, X Wu, X Lei, S Chen, R Teixeira, B Zhu, X Zhao, Z Xu
Expert Systems with Applications 224, 120002, 2023
PaTAVTT: A hardware‐in‐the‐loop scaled platform for testing autonomous vehicle trajectory tracking
Z Xu, M Wang, F Zhang, S Jin, J Zhang, X Zhao
Journal of Advanced Transportation 2017 (1), 9203251, 2017
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