30 citations · 32 across the 6 of their papers we have counts for
6 papers
Advanced Assistance for Traffic Crash Analysis: An AI-Driven Multi-Agent Approach to Pre-Crash Reconstruction
Gerui Xu, Boyou Chen, Huizhong Guo +6
Traffic collision reconstruction traditionally relies on human expertise and can be accurate, but pre-crash reconstruction is more challenging. This study develops a multi-agent AI…
Assessing the Effectiveness of Driver Training Interventions in Improving Safe Engagement with Vehicle Automation Systems
Chengxin Zhang, Huizhong Guo, Zifei Wang +3
This study investigates how targeted training interventions can improve safe driver interaction with vehicle automation (VA) systems, focusing on Adaptive Cruise Control (ACC) and…
From Narratives to Probabilistic Reasoning: Predicting and Interpreting Drivers' Hazardous Actions in Crashes Using Large Language Model
Boyou Chen, Gerui Xu, Zifei Wang +6
Vehicle crashes involve complex interactions between road users, split-second decisions, and challenging environmental conditions. Among these, two-vehicle crashes are the most pre…
A systematic review of safety-critical scenarios between automated vehicles and vulnerable road users
Aditya Deshmukh, Zifei Wang, Aaron Gunn +6
Automated vehicles (AVs) are of great potential in reducing crashes on the road. However, it is still complicated to eliminate all the possible accidents, especially those with vul…
Cause-and-Effect Analysis of ADAS: A Comparison Study between Literature Review and Complaint Data
Jackie Ayoub, Zifei Wang, Meitang Li +4
Advanced driver assistance systems (ADAS) are designed to improve vehicle safety. However, it is difficult to achieve such benefits without understanding the causes and limitations…
A Probabilistic Framework for Estimating the Risk of Pedestrian-Vehicle Conflicts at Intersections
Pei Li, Huizhong Guo, Shan Bao +1
Pedestrian safety has become an important research topic among various studies due to the increased number of pedestrian-involved crashes. To evaluate pedestrian safety proactively…