Self-organized routing for autonomous vehicles via deep reinforcement learning
Routing for autonomous vehicles with global traffic information and sufficient direct
cooperation among vehicles has been widely studied to relieve traffic congestion in recent …
cooperation among vehicles has been widely studied to relieve traffic congestion in recent …
An edge-assisted vehicle routing method based on game-theoretic multiagent learning
B Zhu, J Li, Q Yuan, J Lu, S Yang - 2019 IEEE 25th …, 2019 - ieeexplore.ieee.org
Traffic congestion is a serious social issue confronting modern cities. To improve traffic
efficiency, route planning for the individual vehicle based on dynamic traffic conditions has …
efficiency, route planning for the individual vehicle based on dynamic traffic conditions has …
Autonomous vehicle routing optimization in a competitive environment: A reinforcement learning application
This paper presents a multiagent approach to identify the shortest path for the intelligent
agents (ie, autonomous vehicles) traveling through the transportation network using a Q …
agents (ie, autonomous vehicles) traveling through the transportation network using a Q …
Incentive-based decentralized routing for connected and autonomous vehicles using information propagation
Routing strategies under the aegis of dynamic traffic assignment have been proposed in the
literature to optimize system performance. However, challenges have persisted in their …
literature to optimize system performance. However, challenges have persisted in their …
Traffic Management of Autonomous Vehicles using Policy Based Deep Reinforcement Learning and Intelligent Routing
Deep Reinforcement Learning (DRL) uses diverse, unstructured data and makes RL
capable of learning complex policies in high dimensional environments. Intelligent …
capable of learning complex policies in high dimensional environments. Intelligent …
Ensemble-based deep reinforcement learning for vehicle routing problems under distribution shift
While performing favourably on the independent and identically distributed (iid) instances,
most of the existing neural methods for vehicle routing problems (VRPs) struggle to …
most of the existing neural methods for vehicle routing problems (VRPs) struggle to …
A multi-vehicle cooperative routing method based on evolutionary game theory
J Lu, J Li, Q Yuan, B Chen - 2019 IEEE Intelligent …, 2019 - ieeexplore.ieee.org
Increasing number of vehicles is making congestion problem become more and more
deteriorate. This problem could be alleviated by route planning which guides vehicles to …
deteriorate. This problem could be alleviated by route planning which guides vehicles to …
A bi-level network-wide cooperative driving approach including deep reinforcement learning-based routing
Cooperative driving of connected and automated vehicles (CAVs) has attracted extensive
attention and researchers have proposed various approaches. However, existing …
attention and researchers have proposed various approaches. However, existing …
An efficiency enhancing methodology for multiple autonomous vehicles in an Urban network adopting deep reinforcement learning
QD Tran, SH Bae - Applied Sciences, 2021 - mdpi.com
To reduce the impact of congestion, it is necessary to improve our overall understanding of
the influence of the autonomous vehicle. Recently, deep reinforcement learning has become …
the influence of the autonomous vehicle. Recently, deep reinforcement learning has become …
Distributed learning for vehicle routing decision in software defined Internet of vehicles
K Lin, C Li, Y Li, C Savaglio… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
With the increasing number of vehicles, the traffic congestion is becoming more and more
serious. In order to alleviate such a problem, this article considers transmission and …
serious. In order to alleviate such a problem, this article considers transmission and …