mlsanityData to 7 Oct 2026

Reinforcement Learning for Ridesharing: An Extended Survey

arXiv 2105.01099 ↗First posted 3 May 2021cs.LG cs.AIcited by 35

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Abstract (arXiv)

In this paper, we present a comprehensive, in-depth survey of the literature on reinforcement learning approaches to decision optimization problems in a typical ridesharing system. Papers on the topics of rideshare matching, vehicle repositioning, ride-pooling, routing, and dynamic pricing are covered. Most of the literature has appeared in the last few years, and several core challenges are to continue to be tackled: model complexity, agent coordination, and joint optimization of multiple levers. Hence, we also introduce popular data sets and open simulation environments to facilitate further research and development. Subsequently, we discuss a number of challenges and opportunities for reinforcement learning research on this important domain.

Key facts. Cited by 35 papers in the map (data through 7 Oct 2026). Builds on 48 of its 168 references that are in the map. First posted on arXiv 3 May 2021.

Builds on

48 of 168 references.

References · 48

  1. 2017Proximal Policy Optimization Algorithmscited by 14,441
  2. 2017CARLA: An Open Urban Driving Simulatorcited by 2,431
  3. 2016Asynchronous Methods for Deep Reinforcement Learningcited by 2,218
  4. 2017Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environmentscited by 1,519
  5. 2019Dota 2 with Large Scale Deep Reinforcement Learningcited by 1,084
  6. 2015Pointer Networkscited by 882
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  8. 2016Neural Combinatorial Optimization with Reinforcement Learningcited by 600
  9. 2018Reinforcement Learning for Solving the Vehicle Routing Problemcited by 327
  10. 2018A Survey of Inverse Reinforcement Learning: Challenges, Methods and Progresscited by 294
  11. 2018Distributed Prioritized Experience Replaycited by 260
  12. 2018Mean Field Multi-Agent Reinforcement Learningcited by 202
36 more
  1. 2016Sample Efficient Actor-Critic with Experience Replaycited by 185
  2. 2020SMARTS: Scalable Multi-Agent Reinforcement Learning Training School for Autonomous Drivingcited by 121
  3. 2020Deep Reinforcement Learning for Intelligent Transportation Systems: A Surveycited by 94
  4. 2020Reinforcement Learning with Combinatorial Actions: An Application to Vehicle Routingcited by 61
  5. 2019Efficient Ridesharing Order Dispatching with Mean Field Multi-Agent Reinforcement Learningcited by 57
  6. 2019DeepPool: Distributed Model-free Algorithm for Ride-sharing using Deep Reinforcement Learningcited by 54
  7. 2019Neural Approximate Dynamic Programming for On-Demand Ride-Poolingcited by 33
  8. 2020Multi-Vehicle Routing Problems with Soft Time Windows: A Multi-Agent Reinforcement Learning Approachcited by 30
  9. 2019Deep Reinforcement Learning for Multi-Driver Vehicle Dispatching and Repositioning Problemcited by 29
  10. 2019Multi-Agent Reinforcement Learning for Order-dispatching via Order-Vehicle Distribution Matchingcited by 26
  11. 2020Deep Reinforcement Learning for Electric Vehicle Routing Problem with Time Windowscited by 25
  12. 2019Continual Reinforcement Learning deployed in Real-life using Policy Distillation and Sim2Real Transfercited by 24
  13. 2017Data-Driven Model Predictive Control of Autonomous Mobility-on-Demand Systemscited by 23
  14. 2018MOVI: A Model-Free Approach to Dynamic Fleet Managementcited by 23
  15. 2019CoRide: Joint Order Dispatching and Fleet Management for Multi-Scale Ride-Hailing Platformscited by 22
  16. 2021Real-world Ride-hailing Vehicle Repositioning using Deep Reinforcement Learningcited by 22
  17. 2019ORL: Reinforcement Learning Benchmarks for Online Stochastic Optimization Problemscited by 21
  18. 2020A Distributed Model-Free Ride-Sharing Approach for Joint Matching, Pricing, and Dispatching using Deep Reinforcement Learningcited by 17
  19. 2019Environment Reconstruction with Hidden Confounders for Reinforcement Learning based Recommendationcited by 16
  20. 2016Taxi Dispatch with Real-Time Sensing Data in Metropolitan Areas: A Receding Horizon Control Approachcited by 13
  21. 2020Scalable Deep Reinforcement Learning for Ride-Hailingcited by 12
  22. 2019A Distributed Model-Free Algorithm for Multi-hop Ride-sharing using Deep Reinforcement Learningcited by 11
  23. 2020Reward Design for Driver Repositioning Using Multi-Agent Reinforcement Learningcited by 11
  24. 2019Optimal Passenger-Seeking Policies on E-hailing Platforms Using Markov Decision Process and Imitation Learningcited by 10
  25. 2020Curriculum in Gradient-Based Meta-Reinforcement Learningcited by 9
  26. 2020Deep Hurdle Networks for Zero-Inflated Multi-Target Regression: Application to Multiple Species Abundance Estimationcited by 9
  27. 2018Approximate Dynamic Programming for Planning a Ride-Sharing System using Autonomous Fleets of Electric Vehiclescited by 8
  28. 2018Optimizing Taxi Carpool Policies via Reinforcement Learning and Spatio-Temporal Miningcited by 8
  29. 2018Dynamic Type Matchingcited by 8
  30. 2019Can Sophisticated Dispatching Strategy Acquired by Reinforcement Learning? - A Case Study in Dynamic Courier Dispatching Systemcited by 8
  31. 2018Spatio-Temporal Pricing for Ridesharing Platformscited by 7
  32. 2020Auxiliary-task Based Deep Reinforcement Learning for Participant Selection Problem in Mobile Crowdsourcingcited by 6
  33. 2016Predictive Positioning and Quality Of Service Ridesharing for Campus Mobility On Demand Systemscited by 5
  34. 2020Learn to Earn: Enabling Coordination within a Ride Hailing Fleetcited by 3
  35. 2021Driver Positioning and Incentive Budgeting with an Escrow Mechanism for Ridesharing Platformscited by 2
  36. 2020Competitive ride-sourcing market with a third-party integratorcited by 1

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 2; 2022: 5; 2023: 8; 2024: 9; 2025: 9; 2026: 2.

35 papers.

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  1. 2021Mean-Field Multi-Agent Reinforcement Learning: A Decentralized Network Approachcited by 27
  2. 2023Neurosymbolic Reinforcement Learning and Planning: A Surveycited by 24
  3. 2023A Better Match for Drivers and Riders: Reinforcement Learning at Lyftcited by 9
  4. 2022Policy Evaluation for Temporal and/or Spatial Dependent Experimentscited by 8
  5. 2023Evaluating Dynamic Conditional Quantile Treatment Effects with Applications in Ridesharingcited by 7
  6. 2024An End-to-End Reinforcement Learning Based Approach for Micro-View Order-Dispatching in Ride-Hailingcited by 7
  7. 2025HCRide: Harmonizing Passenger Fairness and Driver Preference for Human-Centered Ride-Hailingcited by 7
  8. 2024Combining Experimental and Historical Data for Policy Evaluationcited by 6
  9. 2022Reinforcement Learning in Practice: Opportunities and Challengescited by 5
  10. 2024GARLIC: GPT-Augmented Reinforcement Learning with Intelligent Control for Vehicle Dispatchingcited by 5
  11. 2024i-Rebalance: Personalized Vehicle Repositioning for Supply Demand Balancecited by 4
  12. 2024Multi Agent Reinforcement Learning for Sequential Satellite Assignment Problemscited by 4
23 more
  1. 2025DECAF: Learning to be Fair in Multi-agent Resource Allocationcited by 4
  2. 2023A Survey of Machine Learning-Based Ride-Hailing Planningcited by 3
  3. 2022A Bibliometric Analysis and Review on Reinforcement Learning for Transportation Applicationscited by 2
  4. 2023Multi-Agent Reinforcement Learning for Fast-Timescale Demand Response of Residential Loadscited by 2
  5. 2023Learning to Control Autonomous Fleets from Observation via Offline Reinforcement Learningcited by 2
  6. 2024Causal Deepsets for Off-policy Evaluation under Spatial or Spatio-temporal Interferencescited by 2
  7. 2021DROP: Deep relocating option policy for optimal ride-hailing vehicle repositioningcited by 1
  8. 2023A Unified Representation Framework for Rideshare Marketplace Equilibrium and Efficiencycited by 1
  9. 2025Atomic Proximal Policy Optimization for Electric Robo-Taxi Dispatch and Charger Allocationcited by 1
  10. 2026D3-Subsidy: Online and Sequential Driver Subsidy Decision-Making for Large-Scale Ride-Hailing Marketcited by 1
  11. 2022Processing Network Controls via Deep Reinforcement Learningcited by 0
  12. 2022Towards More Efficient Shared Autonomous Mobility: A Learning-Based Fleet Repositioning Approachcited by 0
  13. 2023Dynamic Adjustment of Matching Radii under the Broadcasting Mode: A Novel Multitask Learning Strategy and Temporal Modeling Approachcited by 0
  14. 2024Learning Under Moral Hazard with Instrumental Regression and Generalized Method of Momentscited by 0
  15. 2024Discovering Cyclists' Visual Preferences Through Shared Bike Trajectories and Street View Images Using Inverse Reinforcement Learningcited by 0
  16. 2024SPO-VCS: An End-to-End Smart Predict-then-Optimize Framework with Alternating Differentiation Method for Relocation Problems in Large-Scale Vehicle Crowd Sensingcited by 0
  17. 2025The Spoils of Algorithmic Collusion: Profit Allocation Among Asymmetric Firmscited by 0
  18. 2025Scalable Ride-Sourcing Vehicle Rebalancing with Service Accessibility Guarantee: A Constrained Mean-Field Reinforcement Learning Approachcited by 0
  19. 2025Semi-on-Demand Transit Feeders with Shared Autonomous Vehicles and Reinforcement-Learning-Based Zonal Dispatching Controlcited by 0
  20. 2025Altruistic Ride Sharing: A Framework for Fair and Sustainable Urban Mobility via Peer-to-Peer Incentivescited by 0
  21. 2025Non-myopic Matching and Rebalancing in Large-Scale On-Demand Ride-Pooling Systems Using Simulation-Informed Reinforcement Learningcited by 0
  22. 2025RAST-MoE-RL: A Regime-Aware Spatio-Temporal MoE Framework for Deep Reinforcement Learning in Ride-Hailingcited by 0
  23. 2026Deep Reinforcement Learning solution for pickup and delivery routing problems with time window and capacity constraintscited by 0