A hierarchical framework for improving ride comfort of autonomous vehicles via deep reinforcement learning with external knowledge
Ride comfort plays an important role in determining the public acceptance of autonomous
vehicles (AVs). Many factors, such as road profile, driving speed, and suspension system …
vehicles (AVs). Many factors, such as road profile, driving speed, and suspension system …
A deep reinforcement learning based distributed control strategy for connected automated vehicles in mixed traffic platoon
This paper proposes an innovative distributed longitudinal control strategy for connected
automated vehicles (CAVs) in the mixed traffic environment of CAV and human-driven …
automated vehicles (CAVs) in the mixed traffic environment of CAV and human-driven …
Bus bunching: a comprehensive review from demand, supply, and decision-making perspectives
Public transport service reliability is crucial for all stakeholders, including users, operators,
and society. Bus bunching, where two or more buses on the same route travel closely …
and society. Bus bunching, where two or more buses on the same route travel closely …
An integrated car-following and lane changing vehicle trajectory prediction algorithm based on a deep neural network
Vehicle trajectory prediction is essential for the operation safety and control efficiency of
automated driving. Prevailing studies predict car following and lane change processes in a …
automated driving. Prevailing studies predict car following and lane change processes in a …
Physics-informed deep reinforcement learning-based integrated two-dimensional car-following control strategy for connected automated vehicles
Connected automated vehicles (CAVs) are broadly recognized as next-generation
transformative transportation technologies having great potential to improve traffic safety …
transformative transportation technologies having great potential to improve traffic safety …
Dynamic urban traffic rerouting with fog‐cloud reinforcement learning
Dynamic rerouting has been touted as a solution for urban traffic congestion. However, its
implementation is stymied by the complexity of urban traffic. To address this, recent studies …
implementation is stymied by the complexity of urban traffic. To address this, recent studies …
[HTML][HTML] 3D reconstruction based on hierarchical reinforcement learning with transferability
Abstract 3D reconstruction is extremely important in CAD (computer-aided design)/CAE
(computer-aided Engineering)/CAM (computer-aided manufacturing). For interpretability …
(computer-aided Engineering)/CAM (computer-aided manufacturing). For interpretability …
Multi-agent simulation of autonomous industrial vehicle fleets: Towards dynamic task allocation in V2X cooperation mode
J Grosset, AJ Fougères… - Integrated Computer …, 2024 - content.iospress.com
The smart factory leads to a strong digitalization of industrial processes and continuous
communication between the systems integrated into the production, storage, and supply …
communication between the systems integrated into the production, storage, and supply …
Rolling‐horizon–based strategy of fully cooperative traffic under signalized intersections
Dedicated left‐turn lanes are traditionally used at intersections. This practice may not be
optimal where heavy traffic exists from multiple directions. As is well known, the capacity can …
optimal where heavy traffic exists from multiple directions. As is well known, the capacity can …
Advancing the white phase mobile traffic control paradigm to consider pedestrians
R Niroumand, L Hajibabai… - Computer‐Aided Civil …, 2024 - Wiley Online Library
Current literature on joint optimization of intersection signal timing and connected automated
vehicle (CAV) trajectory mostly focuses on vehicular movements paying no or little attention …
vehicle (CAV) trajectory mostly focuses on vehicular movements paying no or little attention …