most citedOpenLKA: an open dataset of lane keeping assist from market autonomous vehicles

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 papers

cs.AI2026

Multi-Dimensional Comparative Scale Construction for Efficient Personalized Subjective Judgment in High-Traffic Applications

Xianglong Shi, Shifeng Liu, Sirui Zhao +2

Subjective judgments are central to many high-traffic applications, but subjective intensity is difficult to quantify and perceptions vary substantially across individuals. To addr…

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…

eess.SY2025

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…

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…