A markov decision process framework to incorporate network-level data in motion planning for connected and automated vehicles
Autonomy and connectivity are expected to enhance safety and improve fuel efficiency in
transportation systems. While connected vehicle-enabled technologies, such as coordinated …
transportation systems. While connected vehicle-enabled technologies, such as coordinated …
Optimization-based path-planning for connected and non-connected automated vehicles
A path-planning algorithm for connected and non-connected automated road vehicles on
multilane motorways is derived from the opportune formulation of an optimal control …
multilane motorways is derived from the opportune formulation of an optimal control …
Predictive trajectory planning for autonomous vehicles at intersections using reinforcement learning
In this work we put forward a predictive trajectory planning framework to help autonomous
vehicles plan future trajectories. We develop a partially observable Markov decision process …
vehicles plan future trajectories. We develop a partially observable Markov decision process …
Distributed maneuver planning with connected and automated vehicles for boosting traffic efficiency
Connected and automated vehicles (CAVs) have the potential to improve traffic throughput
and achieve a more efficient utilization of the available roadway infrastructure. They also …
and achieve a more efficient utilization of the available roadway infrastructure. They also …
[HTML][HTML] General Optimal Trajectory Planning: Enabling Autonomous Vehicles with the Principle of Least Action
This study presents a general optimal trajectory planning (GOTP) framework for autonomous
vehicles (AVs) that can effectively avoid obstacles and guide AVs to complete driving tasks …
vehicles (AVs) that can effectively avoid obstacles and guide AVs to complete driving tasks …
Hierarchical and game-theoretic decision-making for connected and automated vehicles in overtaking scenarios
This paper presents a hierarchical and game-theoretic decision-making strategy for
connected and automated vehicles (CAVs). A CAV can receive preview information using …
connected and automated vehicles (CAVs). A CAV can receive preview information using …
Online longitudinal trajectory planning for connected and autonomous vehicles in mixed traffic flow with deep reinforcement learning approach
This manuscript presents an Adam optimization-based Deep Reinforcement Learning model
for Mixed Traffic Flow control (ADRL-MTF), so as to guide Connected and Autonomous …
for Mixed Traffic Flow control (ADRL-MTF), so as to guide Connected and Autonomous …
An integrated framework of decision making and motion planning for autonomous vehicles considering social behaviors
This paper presents a novel integrated approach to deal with the decision making and
motion planning for lane-change maneuvers of autonomous vehicle (AV) considering social …
motion planning for lane-change maneuvers of autonomous vehicle (AV) considering social …
Predictively coordinated vehicle acceleration and lane selection using mixed integer programming
RA Dollar, A Vahidi - Dynamic Systems and Control …, 2018 - asmedigitalcollection.asme.org
Autonomous vehicle technology provides the means to optimize motion planning beyond
human capacity. In particular, the problem of navigating multi-lane traffic optimally for trip …
human capacity. In particular, the problem of navigating multi-lane traffic optimally for trip …
Transportation planning for connected autonomous vehicles: how it all fits together
BJ Cottam - Transportation Research Record, 2018 - journals.sagepub.com
As connected and autonomous vehicle (CAV) technology continues to evolve and rapidly
develop new capabilities, it is becoming increasingly important for transportation planners to …
develop new capabilities, it is becoming increasingly important for transportation planners to …