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 …
End-to-end interpretable neural motion planner
In this paper, we propose a neural motion planner for learning to drive autonomously in
complex urban scenarios that include traffic-light handling, yielding, and interactions with …
complex urban scenarios that include traffic-light handling, yielding, and interactions with …
Rethinking integration of prediction and planning in deep learning-based automated driving systems: a review
Automated driving has the potential to revolutionize personal, public, and freight mobility.
Besides the enormous challenge of perception, ie accurately perceiving the environment …
Besides the enormous challenge of perception, ie accurately perceiving the environment …
Baidu apollo em motion planner
In this manuscript, we introduce a real-time motion planning system based on the Baidu
Apollo (open source) autonomous driving platform. The developed system aims to address …
Apollo (open source) autonomous driving platform. The developed system aims to address …
Lookout: Diverse multi-future prediction and planning for self-driving
In this paper, we present LookOut, a novel autonomy system that perceives the environment,
predicts a diverse set of futures of how the scene might unroll and estimates the trajectory of …
predicts a diverse set of futures of how the scene might unroll and estimates the trajectory of …
Review of learning-based longitudinal motion planning for autonomous vehicles: research gaps between self-driving and traffic congestion
Self-driving technology companies and the research community are accelerating the pace of
use of machine learning longitudinal motion planning (mMP) for autonomous vehicles (AVs) …
use of machine learning longitudinal motion planning (mMP) for autonomous vehicles (AVs) …
Epsilon: An efficient planning system for automated vehicles in highly interactive environments
In this article, we present an efficient planning system for automated vehicles in highly
interactive environments (EPSILON). EPSILON is an efficient interaction-aware planning …
interactive environments (EPSILON). EPSILON is an efficient interaction-aware planning …
Fail-safe motion planning for online verification of autonomous vehicles using convex optimization
Safe motion planning for autonomous vehicles is a challenging task, since the exact future
motion of other traffic participant is usually unknown. In this article, we present a verification …
motion of other traffic participant is usually unknown. In this article, we present a verification …
Driving in dense traffic with model-free reinforcement learning
Traditional planning and control methods could fail to find a feasible trajectory for an
autonomous vehicle to execute amongst dense traffic on roads. This is because the obstacle …
autonomous vehicle to execute amongst dense traffic on roads. This is because the obstacle …
Safetynet: Safe planning for real-world self-driving vehicles using machine-learned policies
In this paper we present the first safe system for full control of self-driving vehicles trained
from human demonstrations and deployed in challenging, real-world, urban environments …
from human demonstrations and deployed in challenging, real-world, urban environments …