1 citations · 2 across the 15 of their papers we have counts for
16 papers
TriDrive: Joint Driver, Vehicle, and Road Modeling for Forecasting and Driver Monitoring
Yuhang Wang, Jingxin Yang, Chuheng Wei +4
Predicting how drivers, vehicles, and road scenes interact and evolve together is central to driver monitoring. Prior work models in-cabin activity or traffic-conditioned driver mo…
Observe Before You Alert: Adaptive Driver Alerting with Vision-Language Models
Yuhang Wang, Lingyao Li, Hao Zhou
Driver alerting from dashcam video requires sequential decision-making under partial observability: a system must decide not only whether a scene is risky, but also when the eviden…
DriveMotion: A Large-Scale Multi-Source Benchmark for Driver Motion Sequence Modeling and Forecasting
Yuhang Wang, Chuheng Wei, Jingxin Yang +2
Driver motion can provide cues to ongoing behavior, attention, and near-term driving intent. However, most existing driver-centric datasets focus on recognizing predefined driver b…
Scale-CDA: A Scalable Aftermarket Platform to Democratize Cooperative Driving Automation in Production Cars
Hao Zhou, Shengming Yuan, Yuhang Wang +2
Scaling cooperative driving automation (CDA) to production passenger vehicles requires an affordable retrofit platform that can accommodate heterogeneous OEM Controller Area Networ…
DriveDNA: A Large-Scale Multimodal Naturalistic Driving Dataset and Benchmark for Driving Style Identification
Yuhang Wang, Lingyao Li, Hao Zhou
Driving style captures stable, driver-specific patterns in how a vehicle is driven. In naturalistic data, however, this signal is hard to isolate because drivers are observed in di…
A Closed-loop, State-centric, Multi-agent Framework for Passenger Load Estimation from Heterogeneous Data Streams
Yiyao Xu, Hao Zhou, Yuhang Wang +1
To support operations and passenger-facing services, transit agencies need reliable passenger load trajectories. Currently, load estimates are typically inferred from imperfect sen…
Cut-In Gap Acceptance Toward Autonomous vs. Human-Driven Vehicles: Evidence from the Waymo Open Motion Dataset
Abdulaziz Alhuraish, Yuhang Wang, Hao Zhou
Autonomous vehicles (AVs) are widely known to follow conservative, rule-based motion policies that surrounding drivers can learn to anticipate. A direct consequence is that human d…
BATON: A Multimodal Benchmark for Bidirectional Automation Transition Observation in Naturalistic Driving
Yuhang Wang, Yiyao Xu, Chaoyun Yang +3
Existing driving automation (DA) systems on production vehicles rely on human drivers to decide when to engage DA while requiring them to remain continuously attentive and ready to…
ADAS-TO: A Large-Scale Multimodal Naturalistic Dataset and Empirical Characterization of Human Takeovers during ADAS Engagement
Yuhang Wang, Yiyao Xu, Jingran Sun +1
Takeovers remain a key safety vulnerability in production ADAS, yet existing public resources rarely provide takeover-centered, real-world data. We present ADAS-TO, the first large…
TaPD: Temporal-adaptive Progressive Distillation for Observation-Adaptive Trajectory Forecasting in Autonomous Driving
Mingyu Fan, Yi Liu, Hao Zhou +3
Trajectory prediction is essential for autonomous driving, enabling vehicles to anticipate the motion of surrounding agents to support safe planning. However, most existing predict…
Analytical Framework for Evaluating Traffic Capacity Impacts of Electric Vehicles' Regenerative Braking Dynamics
Yuhang Wang, Md. Zidan Shahriar, Hao Zhou
Regenerative braking (RB) significantly influences electric vehicle (EV) car-following (CF) dynamics, yet traditional traffic-flow models rarely capture these effects. We introduce…
Bridging Human Oversight and Black-box Driver Assistance: Vision-Language Models for Predictive Alerting in Lane Keeping Assist Systems
Yuhang Wang, Hao Zhou
Lane Keeping Assist systems, while increasingly prevalent, often suffer from unpredictable real-world failures, largely due to their opaque, black-box nature, which limits driver a…
Empirical Performance Evaluation of Lane Keeping Assist on Modern Production Vehicles
Yuhang Wang, Abdulaziz Alhuraish, Shuyi Wang +1
Leveraging a newly released open dataset of Lane Keeping Assist (LKA) systems from production vehicles, this paper presents the first comprehensive empirical analysis of real-world…
AI-CDA4All: Democratizing Cooperative Autonomous Driving for All Drivers via Affordable Dash-cam Hardware and Open-source AI Software
Shengming Yuan, Hao Zhou
As transportation technology advances, the demand for connected vehicle infrastructure has greatly increased to improve their efficiency and safety. One area of advancement, Cooper…
OpenLKA: An Open Dataset of Lane Keeping Assist from Recent Car Models under Real-world Driving Conditions
Yuhang Wang, Abdulaziz Alhuraish, Shengming Yuan +1
Lane Keeping Assist (LKA) is widely adopted in modern vehicles, yet its real-world performance remains underexplored due to proprietary systems and limited data access. This paper…
OpenLKA: an open dataset of lane keeping assist from market autonomous vehicles
Yuhang Wang, Abdulaziz Alhuraish, Shengming Yuan +2
The Lane Keeping Assist (LKA) system has become a standard feature in recent car models. While marketed as providing auto-steering capabilities, the system's operational characteri…