Self-driving cars: A survey

C Badue, R Guidolini, RV Carneiro, P Azevedo… - Expert systems with …, 2021 - Elsevier
We survey research on self-driving cars published in the literature focusing on autonomous
cars developed since the DARPA challenges, which are equipped with an autonomy system …

Interaction dataset: An international, adversarial and cooperative motion dataset in interactive driving scenarios with semantic maps

W Zhan, L Sun, D Wang, H Shi, A Clausse… - arXiv preprint arXiv …, 2019 - arxiv.org
Behavior-related research areas such as motion prediction/planning, representation/
imitation learning, behavior modeling/generation, and algorithm testing, require support from …

Milestones in autonomous driving and intelligent vehicles—part ii: Perception and planning

L Chen, S Teng, B Li, X Na, Y Li, Z Li… - … on Systems, Man …, 2023 - ieeexplore.ieee.org
A growing interest in autonomous driving (AD) and intelligent vehicles (IVs) is fueled by their
promise for enhanced safety, efficiency, and economic benefits. While previous surveys …

Baidu apollo em motion planner

H Fan, F Zhu, C Liu, L Zhang, L Zhuang, D Li… - arXiv preprint arXiv …, 2018 - arxiv.org
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 …

Federated learning on the road autonomous controller design for connected and autonomous vehicles

T Zeng, O Semiari, M Chen, W Saad… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The deployment of future intelligent transportation systems is contingent upon seamless and
reliable operation of connected and autonomous vehicles (CAVs). One key challenge in …

Kinodynamic trajectory optimization and control for car-like robots

C Rösmann, F Hoffmann… - 2017 IEEE/RSJ …, 2017 - ieeexplore.ieee.org
This paper presents a novel generic formulation of Timed-Elastic-Bands for efficient online
motion planning of car-like robots. The planning problem is defined in terms of a finite …

Efficient sampling-based maximum entropy inverse reinforcement learning with application to autonomous driving

Z Wu, L Sun, W Zhan, C Yang… - IEEE Robotics and …, 2020 - ieeexplore.ieee.org
In the past decades, we have witnessed significant progress in the domain of autonomous
driving. Advanced techniques based on optimization and reinforcement learning become …

Epsilon: An efficient planning system for automated vehicles in highly interactive environments

W Ding, L Zhang, J Chen, S Shen - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
In this article, we present an efficient planning system for automated vehicles in highly
interactive environments (EPSILON). EPSILON is an efficient interaction-aware planning …

Safe trajectory generation for complex urban environments using spatio-temporal semantic corridor

W Ding, L Zhang, J Chen, S Shen - IEEE Robotics and …, 2019 - ieeexplore.ieee.org
Planning safe trajectories for autonomous vehicles in complex urban environments is
challenging since there are numerous semantic elements (such as dynamic agents, traffic …

Hybrid trajectory planning for autonomous driving in highly constrained environments

Y Zhang, H Chen, SL Waslander, J Gong… - IEEE …, 2018 - ieeexplore.ieee.org
In this paper, we introduce a novel and efficient hybrid trajectory planning method for
autonomous driving in highly constrained environments. The contributions of this paper are …