most citedEmpirical Performance Evaluation of Lane Keeping Assist on Modern Production Vehicles

1 citations · 2 across the 13 of their papers we have counts for

collaborators

13 papers

cs.CV2026

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…

cs.CV2026

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…

cs.ET2026

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…

cs.LG2026

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…

cs.LG2026

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…

cs.RO2026

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…

cs.HC2026

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…

cs.HC2026

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…

physics.soc-ph2025

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…

cs.RO2025

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…

cs.RO2025★ 1 cited

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…

cs.CV2025

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…

cs.RO2025★ 1 cited

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…