2 citations · 5 across the 32 of their papers we have counts for
7 papers · 1 filter
LiDAR-Camera Fusion for Video Panoptic Segmentation without Video Training
Fardin Ayar, Ehsan Javanmardi, Manabu Tsukada +2
Panoptic segmentation, which combines instance and semantic segmentation, has gained a lot of attention in autonomous vehicles, due to its comprehensive representation of the scene…
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…
Large Language Models for Human-like Autonomous Driving: A Survey
Yun Li, Kai Katsumata, Ehsan Javanmardi +1
Large Language Models (LLMs), AI models trained on massive text corpora with remarkable language understanding and generation capabilities, are transforming the field of Autonomous…
Accurate Cooperative Localization Utilizing LiDAR-equipped Roadside Infrastructure for Autonomous Driving
Yuze Jiang, Ehsan Javanmardi, Manabu Tsukada +1
Recent advancements in LiDAR technology have significantly lowered costs and improved both its precision and resolution, thereby solidifying its role as a critical component in aut…
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 Distinct Identity: a Standard-compatible Sybil-resistant Pseudonym Extension for C-ITS
Ye Tao, Hongyi Wu, Ehsan Javanmardi +2
Pseudonyms are widely used in Cooperative Intelligent Transport Systems (C-ITS) to protect the location privacy of vehicles. However, the unlinkability nature of pseudonyms also en…
RaceMOP: Mapless Online Path Planning for Multi-Agent Autonomous Racing using Residual Policy Learning
Raphael Trumpp, Ehsan Javanmardi, Jin Nakazato +2
The interactive decision-making in multi-agent autonomous racing offers insights valuable beyond the domain of self-driving cars. Mapless online path planning is particularly of pr…