2 citations · 4 across the 10 of their papers we have counts for
10 papers
SUG-Occ: Explicit Semantics and Uncertainty Guided Sparse Learning for Efficient 3D Occupancy Prediction
Hanlin Wu, Pengfei Lin, Ehsan Javanmardi +4
3D semantic occupancy prediction has emerged as a critical perception task for autonomous driving due to its ability to offer voxel-level semantic and geometric understanding of th…
A Synthetic Benchmark for Collaborative 3D Semantic Occupancy Prediction in V2X-Enabled Autonomous Driving
Hanlin Wu, Pengfei Lin, Ehsan Javanmardi +4
3D semantic occupancy prediction is an emerging perception paradigm in autonomous driving, providing a voxel-level representation of both geometric details and semantic categories.…
eRSS-RAMP: A Rule-Adherence Motion Planner Based on Extended Responsibility-Sensitive Safety for Autonomous Driving
Pengfei Lin, Ehsan Javanmardi, Yuze Jiang +3
Driving safety and responsibility determination are indispensable pieces of the puzzle for autonomous driving. They are also deeply related to the allocation of right-of-way and th…
A Rule-Compliance Path Planner for Lane-Merge Scenarios Based on Responsibility-Sensitive Safety
Pengfei Lin, Ehsan Javanmardi, Yuze Jiang +1
Lane merging is one of the critical tasks for self-driving cars, and how to perform lane-merge maneuvers effectively and safely has become one of the important standards in measuri…
Zero-Knowledge Proof of Traffic: A Deterministic and Privacy-Preserving Cross Verification Mechanism for Cooperative Perception Data
Ye Tao, Ehsan Javanmardi, Pengfei Lin +4
Cooperative perception is crucial for connected automated vehicles in intelligent transportation systems (ITSs); however, ensuring the authenticity of perception data remains a cha…
Clothoid Curve-based Emergency-Stopping Path Planning with Adaptive Potential Field for Autonomous Vehicles
Pengfei Lin, Ehsan Javanmardi, Manabu Tsukada
The Potential Field (PF)-based path planning method is widely adopted for autonomous vehicles (AVs) due to its real-time efficiency and simplicity. PF often creates a rigid road bo…
Occlusion-Aware Path Planning for Collision Avoidance: Leveraging Potential Field Method with Responsibility-Sensitive Safety
Pengfei Lin, Ehsan Javanmardi, Jin Nakazato +1
Collision avoidance (CA) has always been the foremost task for autonomous vehicles (AVs) under safety criteria. And path planning is directly responsible for generating a safe path…
Potential Field-based Path Planning with Interactive Speed Optimization for Autonomous Vehicles
Pengfei Lin, Ehsan Javanmardi, Jin Nakazato +1
Path planning is critical for autonomous vehicles (AVs) to determine the optimal route while considering constraints and objectives. The potential field (PF) approach has become pr…
Time-to-Collision-Aware Lane-Change Strategy Based on Potential Field and Cubic Polynomial for Autonomous Vehicles
Pengfei Lin, Ehsan Javanmardi, Ye Tao +3
Making safe and successful lane changes (LCs) is one of the many vitally important functions of autonomous vehicles (AVs) that are needed to ensure safe driving on expressways. Rec…
zk-PoT: Zero-Knowledge Proof of Traffic for Privacy Enabled Cooperative Perception
Ye Tao, Yuze Jiang, Pengfei Lin +2
Cooperative perception is an essential and widely discussed application of connected automated vehicles. However, the authenticity of perception data is not ensured, because the ve…