[HTML][HTML] An integrated ride-matching and vehicle-rebalancing model for shared mobility on-demand services
K Tuncel, HN Koutsopoulos, Z Ma - Computers & Operations Research, 2023 - Elsevier
Shared mobility on demand (MoD) services are receiving increased attention as many high-
volume ride-hailing companies are offering shared services (eg UberPool, LyftLine) at an …
volume ride-hailing companies are offering shared services (eg UberPool, LyftLine) at an …
Hybrid multi-agent deep reinforcement learning for autonomous mobility on demand systems
We consider the sequential decision-making problem of making proactive request
assignment and rejection decisions for a profit-maximizing operator of an autonomous …
assignment and rejection decisions for a profit-maximizing operator of an autonomous …
Learning-based online optimization for autonomous mobility-on-demand fleet control
Autonomous mobility-on-demand systems are a viable alternative to mitigate many
transportation-related externalities in cities, such as rising vehicle volumes in urban areas …
transportation-related externalities in cities, such as rising vehicle volumes in urban areas …
Graph meta-reinforcement learning for transferable autonomous mobility-on-demand
Autonomous Mobility-on-Demand (AMoD) systems represent an attractive alternative to
existing transportation paradigms, currently challenged by urbanization and increasing …
existing transportation paradigms, currently challenged by urbanization and increasing …
A general maximum-stability dispatch policy for shared autonomous vehicle dispatch with an analytical characterization of the maximum throughput
MW Levin - Transportation Research Part B: Methodological, 2022 - Elsevier
Shared autonomous vehicles (SAVs) have been studied through analytical dispatch
methods and simulation. A common question of interest is how many customers can be …
methods and simulation. A common question of interest is how many customers can be …
Modeling, Analysis, and Control of Autonomous Mobility-on-Demand Systems: A Discrete-Time Linear Dynamical System and a Model Predictive Control Approach
A Aalipour, A Khani - IEEE Transactions on Intelligent …, 2024 - ieeexplore.ieee.org
Autonomous vehicles are rapidly evolving and will soon enable large-scale mobility-on-
demand (MoD) systems applications. Managing the fleets of available vehicles, commonly …
demand (MoD) systems applications. Managing the fleets of available vehicles, commonly …
Data-driven h-infinity control with a real-time and efficient reinforcement learning algorithm: An application to autonomous mobility-on-demand systems
A Aalipour, A Khani - arXiv preprint arXiv:2309.08880, 2023 - arxiv.org
Reinforcement learning (RL) is a class of artificial intelligence algorithms being used to
design adaptive optimal controllers through online learning. This paper presents a model …
design adaptive optimal controllers through online learning. This paper presents a model …
Maximum throughput dispatch for shared autonomous vehicles including vehicle rebalancing
J Robbennolt, MW Levin - IEEE Transactions on Intelligent …, 2023 - ieeexplore.ieee.org
Shared autonomous vehicles (SAVs) provide on demand point-to-point transportation for
passengers. This service has been extensively studied using dispatch heuristics and agent …
passengers. This service has been extensively studied using dispatch heuristics and agent …
Offline Hierarchical Reinforcement Learning via Inverse Optimization
Hierarchical policies enable strong performance in many sequential decision-making
problems, such as those with high-dimensional action spaces, those requiring long-horizon …
problems, such as those with high-dimensional action spaces, those requiring long-horizon …
Staggered Routing in Autonomous Mobility-on-Demand Systems
In autonomous mobility-on-demand systems, effectively managing vehicle flows to mitigate
induced congestion and ensure efficient operations is imperative for system performance …
induced congestion and ensure efficient operations is imperative for system performance …