mlsanityData to 14 Oct 2026

DeepPool: Distributed Model-free Algorithm for Ride-sharing using Deep Reinforcement Learning

arXiv 1903.03882 ↗First posted 9 Mar 2019cs.NE cs.SY eess.SYcited by 54

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Abstract (arXiv)

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, ride-sharing allows sharing costs and, hence, reduces the congestion and emission by making better use of vehicle capacities. In this work, we develop a distributed model-free, DeepPool, that uses deep Q-network (DQN) techniques to learn optimal dispatch policies by interacting with the environment. Further, DeepPool efficiently incorporates travel demand statistics and deep learning models to manage dispatching vehicles for improved ride sharing services. Using real-world dataset of taxi trip records in New York City, DeepPool performs better than other strategies, proposed in the literature, that do not consider ride sharing or do not dispatch the vehicles to regions where the future demand is anticipated. Finally, DeepPool can adapt rapidly to dynamic environments since it is implemented in a distributed manner in which each vehicle solves its own DQN individually without coordination.

Key facts. Cited by 54 papers in the map (data through 14 Oct 2026). First posted on arXiv 9 Mar 2019.

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Citing papers per year: 2021: 14; 2022: 7; 2023: 8; 2024: 9; 2025: 12; 2026: 4.

54 papers.

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  1. 2021Reinforcement Learning for Ridesharing: An Extended Surveycited by 35
  2. 2021On the Approximation of Cooperative Heterogeneous Multi-Agent Reinforcement Learning (MARL) using Mean Field Control (MFC)cited by 32
  3. 2023Regret Analysis of Policy Gradient Algorithm for Infinite Horizon Average Reward Markov Decision Processescited by 26
  4. 2021Real-world Ride-hailing Vehicle Repositioning using Deep Reinforcement Learningcited by 22
  5. 2023Improved Communication Efficiency in Federated Natural Policy Gradient via ADMM-based Gradient Updatescited by 21
  6. 2024Asynchronous Federated Reinforcement Learning with Policy Gradient Updates: Algorithm Design and Convergence Analysiscited by 21
  7. 2023Multi-task Hierarchical Adversarial Inverse Reinforcement Learningcited by 15
  8. 2024A Sharper Global Convergence Analysis for Average Reward Reinforcement Learning via an Actor-Critic Approachcited by 15
  9. 2024Sample-Efficient Constrained Reinforcement Learning with General Parameterizationcited by 11
  10. 2021Communication Efficient Parallel Reinforcement Learningcited by 10
  11. 2024Learning General Parameterized Policies for Infinite Horizon Average Reward Constrained MDPs via Primal-Dual Policy Gradient Algorithmcited by 9
  12. 2023Mean-Field Control based Approximation of Multi-Agent Reinforcement Learning in Presence of a Non-decomposable Shared Global Statecited by 8
38 more
  1. 2025Global Convergence for Average Reward Constrained MDPs with Primal-Dual Actor Critic Algorithmcited by 8
  2. 2022A Unified Algorithm Framework for Unsupervised Discovery of Skills based on Determinantal Point Processcited by 7
  3. 2024Model-Based Transfer Learning for Contextual Reinforcement Learningcited by 7
  4. 2025BMG-Q: Localized Bipartite Match Graph Attention Q-Learning for Ride-Pooling Order Dispatchcited by 7
  5. 2025Finite-Sample Analysis of Policy Evaluation for Robust Average Reward Reinforcement Learningcited by 7
  6. 2025Regret Analysis of Average-Reward Unichain MDPs via an Actor-Critic Approachcited by 7
  7. 2021A Modular and Transferable Reinforcement Learning Framework for the Fleet Rebalancing Problemcited by 6
  8. 2021Multi-Agent Transfer Learning in Reinforcement Learning-Based Ride-Sharing Systemscited by 6
  9. 2022Can Mean Field Control (MFC) Approximate Cooperative Multi Agent Reinforcement Learning (MARL) with Non-Uniform Interaction?cited by 6
  10. 2023Quantum Computing Provides Exponential Regret Improvement in Episodic Reinforcement Learningcited by 6
  11. 2024Global Convergence Guarantees for Federated Policy Gradient Methods with Adversariescited by 6
  12. 2021The Gradient Convergence Bound of Federated Multi-Agent Reinforcement Learning with Efficient Communicationcited by 5
  13. 2022Mean-Field Approximation of Cooperative Constrained Multi-Agent Reinforcement Learning (CMARL)cited by 5
  14. 2024Stochastic Q-learning for Large Discrete Action Spacescited by 5
  15. 2025One Step is Enough: Multi-Agent Reinforcement Learning based on One-Step Policy Optimization for Order Dispatch on Ride-Sharing Platformscited by 5
  16. 2021AdaPool: A Diurnal-Adaptive Fleet Management Framework using Model-Free Deep Reinforcement Learning and Change Point Detectioncited by 4
  17. 2022On the Near-Optimality of Local Policies in Large Cooperative Multi-Agent Reinforcement Learningcited by 4
  18. 2025Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approachcited by 4
  19. 2025Triple-BERT: Do We Really Need MARL for Order Dispatch on Ride-Sharing Platforms?cited by 4
  20. 2021Deep Reinforcement Learning for Demand Driven Services in Logistics and Transportation Systems: A Surveycited by 3
  21. 2022On the Global Convergence of Fitted Q-Iteration with Two-layer Neural Network Parametrizationcited by 3
  22. 2023A Survey of Machine Learning-Based Ride-Hailing Planningcited by 3
  23. 2023Quantum Speedups in Regret Analysis of Infinite Horizon Average-Reward Markov Decision Processescited by 3
  24. 2025Coordinating Ride-Pooling with Public Transit using Reward-Guided Conservative Q-Learning: An Offline Training and Online Fine-Tuning Reinforcement Learning Frameworkcited by 3
  25. 2022A Bibliometric Analysis and Review on Reinforcement Learning for Transportation Applicationscited by 2
  26. 2021DeepFreight: Integrating Deep Reinforcement Learning and Mixed Integer Programming for Multi-transfer Truck Freight Deliverycited by 1
  27. 2021DROP: Deep relocating option policy for optimal ride-hailing vehicle repositioningcited by 1
  28. 2022An Explainable Stacked Ensemble Model for Static Route-Free Estimation of Time of Arrivalcited by 1
  29. 2025A Survey on Agentic Service Ecosystems: Measurement, Analysis, and Optimizationcited by 1
  30. 2025Primal-Only Actor Critic Algorithm for Robust Constrained Average Cost MDPscited by 1
  31. 2026Global Convergence of Average Reward Constrained MDPs with Neural Critic and General Policy Parameterizationcited by 1
  32. 2021CoordiQ : Coordinated Q-learning for Electric Vehicle Charging Recommendationcited by 0
  33. 2021H-TD2: Hybrid Temporal Difference Learning for Adaptive Urban Taxi Dispatchcited by 0
  34. 2021dFDA-VeD: A Dynamic Future Demand Aware Vehicle Dispatching Systemcited by 0
  35. 2023Data-Driven H-infinity Control with a Real-Time and Efficient Reinforcement Learning Algorithm: An Application to Autonomous Mobility-on-Demand Systemscited by 0
  36. 2024A Survey on Applications of Reinforcement Learning in Spatial Resource Allocationcited by 0
  37. 2024Mini Honor of Kings: A Lightweight Environment for Multi-Agent Reinforcement Learningcited by 0
  38. 2025Altruistic Ride Sharing: A Framework for Fair and Sustainable Urban Mobility via Peer-to-Peer Incentivescited by 0

50 most cited of 54 All 54 (JSON)