Deeppool: Distributed model-free algorithm for ride-sharing using deep reinforcement learning
AO Al-Abbasi, A Ghosh… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
The success of modern ride-sharing platforms crucially depends on the profit of the ride-
sharing fleet operating companies, and how efficiently the resources are managed. Further …
sharing fleet operating companies, and how efficiently the resources are managed. Further …
A distributed model-free algorithm for multi-hop ride-sharing using deep reinforcement learning
A Singh, AO Al-Abbasi… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The growth of autonomous vehicles, ridesharing systems, and self-driving technology will
bring a shift in the way ride hailing platforms plan out their services. However, these …
bring a shift in the way ride hailing platforms plan out their services. However, these …
Flexpool: A distributed model-free deep reinforcement learning algorithm for joint passengers and goods transportation
K Manchella, AK Umrawal… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The growth in online goods delivery is causing a dramatic surge in urban vehicle traffic from
last-mile deliveries. On the other hand, ride-sharing has been on the rise with the success of …
last-mile deliveries. On the other hand, ride-sharing has been on the rise with the success of …
A distributed model-free ride-sharing approach for joint matching, pricing, and dispatching using deep reinforcement learning
M Haliem, G Mani, V Aggarwal… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Significant development of ride-sharing services presents a plethora of opportunities to
transform urban mobility by providing personalized and convenient transportation while …
transform urban mobility by providing personalized and convenient transportation while …
A deep value-network based approach for multi-driver order dispatching
Recent works on ride-sharing order dispatching have highlighted the importance of taking
into account both the spatial and temporal dynamics in the dispatching process for …
into account both the spatial and temporal dynamics in the dispatching process for …
A deep reinforcement learning approach to ride-sharing vehicle dispatching in autonomous mobility-on-demand systems
G Guo, Y Xu - IEEE Intelligent Transportation Systems …, 2020 - ieeexplore.ieee.org
This paper investigates a ride-sharing vehicle dispatching and routing problem in ride-
sharing autonomous mobility-on-demand systems. We present a new method that can …
sharing autonomous mobility-on-demand systems. We present a new method that can …
Optimization of ride-sharing with passenger transfer via deep reinforcement learning
D Wang, Q Wang, Y Yin, TCE Cheng - Transportation Research Part E …, 2023 - Elsevier
With the emergence of the sharing economy and the rapid growth of mobile communications
technologies, many novel sharing service models have been developed stemming from ride …
technologies, many novel sharing service models have been developed stemming from ride …
Real-time dispatching of large-scale ride-sharing systems: Integrating optimization, machine learning, and model predictive control
This paper considers the dispatching of large-scale real-time ride-sharing systems to
address congestion issues faced by many cities. The goal is to serve all customers (service …
address congestion issues faced by many cities. The goal is to serve all customers (service …
Deep reinforcement learning with knowledge transfer for online rides order dispatching
Ride dispatching is a central operation task on a ride-sharing platform to continuously match
drivers to trip-requesting passengers. In this work, we model the ride dispatching problem as …
drivers to trip-requesting passengers. In this work, we model the ride dispatching problem as …
MOVI: A model-free approach to dynamic fleet management
T Oda, C Joe-Wong - IEEE INFOCOM 2018-IEEE Conference …, 2018 - ieeexplore.ieee.org
Modern vehicle fleets, eg, for ridesharing platforms and taxi companies, can reduce
passengers' waiting times by proactively dispatching vehicles to locations where pickup …
passengers' waiting times by proactively dispatching vehicles to locations where pickup …