Planning and decision-making for connected autonomous vehicles at road intersections: A review
Planning and decision-making technology at intersections is a comprehensive research
problem in intelligent transportation systems due to the uncertainties caused by a variety of …
problem in intelligent transportation systems due to the uncertainties caused by a variety of …
St-p3: End-to-end vision-based autonomous driving via spatial-temporal feature learning
Many existing autonomous driving paradigms involve a multi-stage discrete pipeline of
tasks. To better predict the control signals and enhance user safety, an end-to-end approach …
tasks. To better predict the control signals and enhance user safety, an end-to-end approach …
Lateral control for autonomous wheeled vehicles: A technical review
Autonomous driving has the ability to reshape mobility and transportation by reducing road
accidents, traffic jams, and air pollution. This can yield energy efficiency, convenience, and …
accidents, traffic jams, and air pollution. This can yield energy efficiency, convenience, and …
Metadrive: Composing diverse driving scenarios for generalizable reinforcement learning
Driving safely requires multiple capabilities from human and intelligent agents, such as the
generalizability to unseen environments, the safety awareness of the surrounding traffic, and …
generalizability to unseen environments, the safety awareness of the surrounding traffic, and …
Survey of deep reinforcement learning for motion planning of autonomous vehicles
S Aradi - IEEE Transactions on Intelligent Transportation …, 2020 - ieeexplore.ieee.org
Academic research in the field of autonomous vehicles has reached high popularity in
recent years related to several topics as sensor technologies, V2X communications, safety …
recent years related to several topics as sensor technologies, V2X communications, safety …
Interaction dataset: An international, adversarial and cooperative motion dataset in interactive driving scenarios with semantic maps
Behavior-related research areas such as motion prediction/planning, representation/
imitation learning, behavior modeling/generation, and algorithm testing, require support from …
imitation learning, behavior modeling/generation, and algorithm testing, require support from …
Mp3: A unified model to map, perceive, predict and plan
High-definition maps (HD maps) are a key component of most modern self-driving systems
due to their valuable semantic and geometric information. Unfortunately, building HD maps …
due to their valuable semantic and geometric information. Unfortunately, building HD maps …
FusionPlanner: A multi-task motion planner for mining trucks via multi-sensor fusion
In recent years, significant achievements have been made in motion planning for intelligent
vehicles. However, as a typical unstructured environment, open-pit mining attracts limited …
vehicles. However, as a typical unstructured environment, open-pit mining attracts limited …
Generating useful accident-prone driving scenarios via a learned traffic prior
Evaluating and improving planning for autonomous vehicles requires scalable generation of
long-tail traffic scenarios. To be useful, these scenarios must be realistic and challenging …
long-tail traffic scenarios. To be useful, these scenarios must be realistic and challenging …
Parting with misconceptions about learning-based vehicle motion planning
The release of nuPlan marks a new era in vehicle motion planning research, offering the first
large-scale real-world dataset and evaluation schemes requiring both precise short-term …
large-scale real-world dataset and evaluation schemes requiring both precise short-term …