Behavioral intention prediction in driving scenes: A survey
In driving scenes, road agents often engage in frequent interaction and strive to understand
their surroundings. Ego-agent (each road agent itself) predicts what behavior will be …
their surroundings. Ego-agent (each road agent itself) predicts what behavior will be …
Visual point cloud forecasting enables scalable autonomous driving
In contrast to extensive studies on general vision pre-training for scalable visual
autonomous driving remains seldom explored. Visual autonomous driving applications …
autonomous driving remains seldom explored. Visual autonomous driving applications …
Openlane-v2: A topology reasoning benchmark for unified 3d hd mapping
Accurately depicting the complex traffic scene is a vital component for autonomous vehicles
to execute correct judgments. However, existing benchmarks tend to oversimplify the scene …
to execute correct judgments. However, existing benchmarks tend to oversimplify the scene …
High-definition maps construction based on visual sensor: A comprehensive survey
In recent years, the field of autonomous vehicles has seen a significant increase in
academic research, with high-definition (HD) maps emerging as a critical component of …
academic research, with high-definition (HD) maps emerging as a critical component of …
A survey of large language models for autonomous driving
Autonomous driving technology, a catalyst for revolutionizing transportation and urban
mobility, has the tend to transition from rule-based systems to data-driven strategies …
mobility, has the tend to transition from rule-based systems to data-driven strategies …
Topomlp: An simple yet strong pipeline for driving topology reasoning
Topology reasoning aims to comprehensively understand road scenes and present drivable
routes in autonomous driving. It requires detecting road centerlines (lane) and traffic …
routes in autonomous driving. It requires detecting road centerlines (lane) and traffic …
Lanesegnet: Map learning with lane segment perception for autonomous driving
A map, as crucial information for downstream applications of an autonomous driving system,
is usually represented in lanelines or centerlines. However, existing literature on map …
is usually represented in lanelines or centerlines. However, existing literature on map …
Augmenting lane perception and topology understanding with standard definition navigation maps
Autonomous driving has traditionally relied heavily on costly and labor-intensive High
Definition (HD) maps, hindering scalability. In contrast, Standard Definition (SD) maps are …
Definition (HD) maps, hindering scalability. In contrast, Standard Definition (SD) maps are …
SemVecNet: Generalizable Vector Map Generation for Arbitrary Sensor Configurations
NE Ranganatha, H Zhang, S Venkatramani… - arXiv preprint arXiv …, 2024 - arxiv.org
Vector maps are essential in autonomous driving for tasks like localization and planning, yet
their creation and maintenance are notably costly. While recent advances in online vector …
their creation and maintenance are notably costly. While recent advances in online vector …
Occlusion-Aware 2D and 3D Centerline Detection for Urban Driving via Automatic Label Generation
This research work seeks to explore and identify strategies that can determine road topology
information in 2D and 3D under highly dynamic urban driving scenarios. To facilitate this …
information in 2D and 3D under highly dynamic urban driving scenarios. To facilitate this …