32 citations · 55 across the 13 of their papers we have counts for
15 papers
How corner is a corner case? Percentile control for highway scenario generation
Jiaxi Liu, Hang Zhou, Hangyu Li +5
Generating corner-case scenarios with appropriate adversity in a simulation environment is critical for testing an autonomous vehicle (AV) software stack's safety performance befor…
High-Slip-Ratio Control for Peak Tire-Road Friction Estimation Using Automated Vehicles
Zhaohui Liang, Hang Zhou, Heye Huanh +1
Accurate estimation of the tire-road friction coefficient (TRFC) is critical for ensuring safe vehicle control, especially under adverse road conditions. However, most existing met…
Developing Fundamental Diagrams for Urban Air Mobility Traffic Based on Physical Experiments
Hang Zhou, Yuhui Zhai, Shiyu Shen +3
Urban Air Mobility (UAM) is an emerging application of unmanned aerial vehicles that promises to reduce travel time and alleviate congestion in urban transportation systems. As dro…
Real-Time Lane-Level Crash Detection on Freeways Using Sparse Telematics Data
Shixiao Liang, Chengyuan Ma, Pei Li +7
Real-time traffic crash detection is critical in intelligent transportation systems because traditional crash notifications often suffer delays and lack specific, lane-level locati…
SRA-CP: Spontaneous Risk-Aware Selective Cooperative Perception
Jiaxi Liu, Chengyuan Ma, Hang Zhou +5
Cooperative perception (CP) offers significant potential to overcome the limitations of single-vehicle sensing by enabling information sharing among connected vehicles (CVs). Howev…
CATS-V2V: A Real-World Vehicle-to-Vehicle Cooperative Perception Dataset with Complex Adverse Traffic Scenarios
Hangyu Li, Bofeng Cao, Zhaohui Liang +16
Vehicle-to-Vehicle (V2V) cooperative perception has great potential to enhance autonomous driving performance by overcoming perception limitations in complex adverse traffic scenar…
Unveiling Uniform Shifted Power Law in Stochastic Human and Autonomous Driving Behavior
Wang Chen, Heye Huang, Ke Ma +4
Accurately simulating rare but safety-critical driving behaviors is essential for the evaluation and certification of autonomous vehicles (AVs). However, current models often fail…
Benchmarking Tesla's Traffic Light and Stop Sign Control: Field Dataset and Behavior Insights
Zheng Li, Peng Zhang, Shixiao Liang +5
Understanding how Advanced Driver-Assistance Systems (ADAS) interact with Traffic Control Devices (TCDs) is critical for assessing their influence on traffic operations, yet this i…
Towards Full-Scenario Safety Evaluation of Automated Vehicles: A Volume-Based Method
Hang Zhou, Chengyuan Ma, Shiyu Shen +2
With the rapid development of automated vehicles (AVs) in recent years, commercially available AVs are increasingly demonstrating high-level automation capabilities. However, most…
Online Adaptive Platoon Control for Connected and Automated Vehicles via Physics Enhanced Residual Learning
Peng Zhang, Heye Huang, Hang Zhou +3
This paper introduces a physics enhanced residual learning (PERL) framework for connected and automated vehicle (CAV) platoon control, addressing the dynamics and unpredictability…
Modular Vehicle Routing Problem: Applications in Logistics
Hang Zhou, Yang Li, Chengyuan Ma +2
Recent studies and industry advancements indicate that modular vehicles (MVs) have the potential to enhance transportation systems through their ability to dock and split during a…
An Advanced Microscopic Energy Consumption Model for Automated Vehicle:Development, Calibration, Verification
Ke Ma, Zhaohui Liang, Hang Zhou +1
The automated vehicle (AV) equipped with the Adaptive Cruise Control (ACC) system is expected to reduce the fuel consumption for the intelligent transportation system. This paper p…
A Unified Longitudinal Trajectory Dataset for Automated Vehicle
Hang Zhou, Ke Ma, Shixiao Liang +2
Automated Vehicles (AVs) promise significant advances in transportation. Critical to these improvements is understanding AVs' longitudinal behavior, relying heavily on real-world t…
Online Physical Enhanced Residual Learning for Connected Autonomous Vehicles Platoon Centralized Control
Hang Zhou, Heye Huang, Peng Zhang +3
This paper introduces an online physical enhanced residual learning (PERL) framework for Connected Autonomous Vehicles (CAVs) platoon, aimed at addressing the challenges posed by t…
A Review on Trajectory Datasets on Advanced Driver Assistance System
Hang Zhou, Ke Ma, Xiaopeng Li
This paper presents a comprehensive review of trajectory data of Advanced Driver Assistance System equipped-vehicle, with the aim of precisely model of Autonomous Vehicles (AVs) be…