Combining reinforcement learning with model predictive control for on-ramp merging
We consider the problem of designing an algorithm to allow a car to autonomously merge on
to a highway from an on-ramp. Two broad classes of techniques have been proposed to …
to a highway from an on-ramp. Two broad classes of techniques have been proposed to …
Novel decision-making strategy for connected and autonomous vehicles in highway on-ramp merging
Z el abidine Kherroubi, S Aknine… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
High-speed highway on-ramp merging is a significant challenge toward realizing fully
automated driving (level 4). Connected Autonomous Vehicles (CAVs), that combine …
automated driving (level 4). Connected Autonomous Vehicles (CAVs), that combine …
A deep reinforcement learning-based approach for autonomous driving in highway on-ramp merge
H Wang, S Yuan, M Guo, X Li… - Proceedings of the …, 2021 - journals.sagepub.com
In this paper, we focus on the problem of highway merge via parallel-type on-ramp for
autonomous vehicles (AVs) in a decentralized non-cooperative way. This problem is …
autonomous vehicles (AVs) in a decentralized non-cooperative way. This problem is …
Learning-based MPC for Autonomous Motion Planning at Freeway Off-ramp Diverging
Off-ramp diverging road segment is the preparation area for vehicles driving away from the
freeway, while it causes more traffic conflicts making it a typical safety bottleneck. Focusing …
freeway, while it causes more traffic conflicts making it a typical safety bottleneck. Focusing …
Automated driving highway traffic merging using deep multi-agent reinforcement learning in continuous state-action spaces
L Schester, LE Ortiz - 2021 IEEE Intelligent Vehicles …, 2021 - ieeexplore.ieee.org
Achieving the highest levels of automated driving will require effective solutions to the key
challenging maneuver of highway on-ramp merging. This paper extends our previous work …
challenging maneuver of highway on-ramp merging. This paper extends our previous work …
Autonomous highway merging in mixed traffic using reinforcement learning and motion predictive safety controller
Deep reinforcement learning (DRL) has a great potential for solving complex decision-
making problems in autonomous driving, especially in mixed-traffic scenarios where …
making problems in autonomous driving, especially in mixed-traffic scenarios where …
An explainable and robust motion planning and control approach for autonomous vehicle on-ramping merging task using deep reinforcement learning
B Hu, L Jiang, S Zhang, Q Wang - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Reinforcement learning (RL) has the capability to discover optimal interactions with the
surrounding environment, with the advantage that nearly all required computations can be …
surrounding environment, with the advantage that nearly all required computations can be …
Autonomous ramp merge maneuver based on reinforcement learning with continuous action space
P Wang, CY Chan - arXiv preprint arXiv:1803.09203, 2018 - arxiv.org
Ramp merging is a critical maneuver for road safety and traffic efficiency. Most of the current
automated driving systems developed by multiple automobile manufacturers and suppliers …
automated driving systems developed by multiple automobile manufacturers and suppliers …
Longitudinal position control for highway on-ramp merging: A multi-agent approach to automated driving
L Schester, LE Ortiz - 2019 IEEE Intelligent Transportation …, 2019 - ieeexplore.ieee.org
Highly automated driving requires effective handling of many complex scenarios. Here we
study a specific important task of highly automated driving: merging into traffic from a …
study a specific important task of highly automated driving: merging into traffic from a …
Learning when to drive in intersections by combining reinforcement learning and model predictive control
T Tram, I Batkovic, M Ali… - 2019 IEEE Intelligent …, 2019 - ieeexplore.ieee.org
In this paper, we propose a decision making algorithm intended for automated vehicles that
negotiate with other possibly non-automated vehicles in intersections. The decision …
negotiate with other possibly non-automated vehicles in intersections. The decision …
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- predictive control reinforcement learning
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