Bibliographie — Ridesharing & Mobility-on-Demand

Focus : systèmes MoD avec ride-sharing, simulation multi-agents, comportements émergents. Période : 2020–2026.

138 articles

Tableau récapitulatif

Liste des articles

• Adnan et al. (2016) — SimMobility: A Multi-Scale Integrated Agent-Based Simulation
• Agatz Niels; Erera Alan; Savelsbergh Martin; Wang Xing (2012) — Optimization for dynamic ride-sharing: A review
• Al-Abbasi et al. (2019) — DeepPool: Distributed Model-Free Algorithm for Ride-Sharing
• Alessandretti Laura; Natera Orozco Luis Guillermo; Saberi Meead; Szell Michael; Battiston Federico (2023) — Multimodal Urban Mobility and Multilayer Transport Networks
• Alonso-Mora et al. (2017) — On-demand high-capacity ride-sharing via dynamic trip-vehicl
• Alonso-Mora Javier; Samaranayake Samitha; Wallar Alex; Frazzoli Emilio; Rus Daniela (2017) — On-demand high-capacity ride-sharing via dynamic trip-vehicl
• Angrist et al. (2021) — Uber versus Taxi: A Driver’s Eye View
• Auld et al. (2016) — POLARIS: Agent-based modeling framework development and impl
• Banerjee et al. (2015) — Pricing in Ride-Sharing Platforms: A Queueing-Theoretic Appr
• Basu et al. (2018) — Automated Mobility-on-Demand vs. Mass Transit: A Multi-Modal
• Bei et al. (2018) — Algorithms for trip-vehicle assignment in ride-sharing
• Bimpikis et al. (2019) — Spatial Pricing in Ride-Sharing Networks
• Bischoff et al. (2016) — Simulation of City-wide Replacement of Private Cars with Aut
• Boesch et al. (2016) — Autonomous vehicle fleet sizes required to serve different l
• Bokanyi Eszter; Hannak Aniko (2020) — Understanding Inequalities in Ride-Hailing Services Through
• Bonabeau Eric; Dorigo Marco; Theraulaz Guy (1999) — Swarm Intelligence: From Natural to Artificial Systems
• Bongiorno Christian; Micciche Salvatore; Mantegna Rosario N.; Tumminello Michele (2013) — Agent-Based Modeling and Simulation of Emergent Behavior in
• Bösch et al. (2018) — Cost-Based Analysis of Autonomous Mobility Services
• Antonio Bucchiarone et al. (2021) — Agent-based Framework for Self-Organization of Collective an
• Bucchiarone Antonio; De Sanctis Martina; Bencomo Nelly (2021) — Agent-Based Framework for Self-Organization of Collective an
• Cachon et al. (2017) — The Role of Surge Pricing on a Service Platform with Self-Sc
• Caiati Valeria; Rasouli Soora; Timmermans Harry (2020) — Bundling, pricing schemes and extra features preferences for
• Alberto Castagna et al. (2021) — Demand-responsive rebalancing zone generation for reinforcem
• Castillo et al. (2017) — Surge Pricing Solves the Wild Goose Chase
• Cohen et al. (2016) — Using Big Data to Estimate Consumer Surplus: The Case of Ube
• Cramer et al. (2016) — Disruptive Change in the Taxi Business: The Case of Uber
• Baudouin Dafflon et al. (2020) — Emergent micro-communities for ride-sharing enabled Mobility
• de Ruijter Arjan; Cats Oded; van Lint Hans (2024) — Ridesourcing platforms thrive on socio-economic inequality
• Dia et al. (2017) — Autonomous Shared Mobility-On-Demand: Melbourne Pilot Simula
• Beza Abebe Diro; Demissie Merkebe Getachew; Kattan Lina (2025) — Equity implications of emerging mobility services and public
• Engelhardt et al. (2022) — FleetPy: A Modular Open-Source Simulation Tool for Mobility
• Fagnant et al. (2014) — The Travel and Environmental Implications of Shared Autonomo
• Fagnant et al. (2015) — Operations of Shared Autonomous Vehicle Fleet for Austin, Te
• Fagnant et al. (2015) — Preparing a Nation for Autonomous Vehicles: Opportunities, B
• Fielbaum Andres; Kucharski Rafal; Cats Oded; Alonso-Mora Javier (2022) — How to split the costs and charge the travellers sharing a r
• Fréchette et al. (2019) — Frictions in a Competitive, Regulated Market: Evidence from
• Furuhata et al. (2013) — Ridesharing: The state-of-the-art and future directions
• Gammelli et al. (2021) — Graph Neural Network Reinforcement Learning for Autonomous M
• Gammelli et al. (2022) — Graph Meta-Reinforcement Learning for Transferable Autonomou
• Garg et al. (2022) — Driver Surge Pricing
• Guériau et al. (2018) — SAMoD: Shared Autonomous Mobility-on-Demand using Decentrali
• Maxime Guériau et al. (2020) — Shared Autonomous Mobility-on-Demand: Learning-based Approac
• Guo et al. (2023) — Surge Pricing and Consumer Surplus in the Ride-Hailing Marke
• Guo Xiaotong; Xu Hanyong; Zhuang Dingyi; Zheng Yunhan; Zhao Jinhua (2024) — Fairness-Enhancing Vehicle Rebalancing in the Ride-hailing S
• Hall Jonathan D.; Palsson Craig; Price Joseph (2018) — Is Uber a substitute or complement for public transit?
• Hall et al. (2023) — Ride-Sharing Markets Re-Equilibrate
• Helbing Dirk; Molnar Peter (1995) — Social Force Model for Pedestrian Dynamics
• Helbing Dirk (2001) — Traffic and Related Self-Driven Many-Particle Systems
• Ho Chinh Q.; Hensher David A.; Mulley Corinne; Wong Yale Z. (2018) — Potential uptake and willingness-to-pay for Mobility as a Se
• Bao Hongqing; Luo Xia; Li Xuan; Zhao Yiyang (2025) — Unveiling Self-Organization and Emergent Phenomena in Urban
• Hörl et al. (2019) — Fleet operational policies for automated mobility: A simulat
• Hörl et al. (2019) — Shared Autonomous Vehicle Simulation and Service Design
• Hörl et al. (2021) — Introducing the eqasim pipeline: From raw data to agent-base
• Hörl et al. (2021) — Synthetic population and travel demand for Paris and Île-de-
• Horni et al. (2016) — The Multi-Agent Transport Simulation MATSim
• Hyland Michael; Mahmassani Hani S. (2018) — Dynamic autonomous vehicle fleet operations: Optimization-ba
• Hyland et al. (2018) — Dynamic autonomous vehicle fleet operations: Optimization-ba
• Iglesias et al. (2018) — Data-Driven Model Predictive Control of Autonomous Mobility-
• OECD) (2015) — Urban Mobility System Upgrade: How Shared Self-Driving Cars
• Jiao et al. (2021) — Real-world ride-hailing vehicle repositioning using deep rei
• Jittrapirom Peraphan; Caiati Valeria; Feneri Anna-Maria; Ebrahimigharehbaghi Shima; Alonso-González María J.; Narayan Jaap (2017) — Mobility as a Service: A Critical Review of Definitions, Ass
• Kamargianni Maria; Li Weibo; Matyas Melinda; Schafer Andreas (2016) — A Critical Review of New Mobility Services for Urban Transpo
• Ke Jintao; Zheng Hongyu; Yang Hai; Chen Xiqun (2017) — Short-term forecasting of passenger demand under on-demand r
• Ke et al. (2020) — Pricing and Equilibrium in On-Demand Ride-Pooling Markets
• Ke Jintao; Feng Shuwei; Zhu Zhen; Yang Hai; Ye Jieping (2021) — Joint predictions of multi-modal ride-hailing demands: A dee
• Kerner Boris S. (1998) — Experimental Features of Self-Organization in Traffic Flow
• Krajzewicz et al. (2002) — SUMO (Simulation of Urban MObility) - an open-source traffic
• Krajzewicz et al. (2012) — Recent Development and Applications of SUMO - Simulation of
• Krueger Rico; Rashidi Taha H.; Rose John M. (2016) — Preferences for shared autonomous vehicles
• Kucharski et al. (2020) — Exact matching of attractive shared rides (ExMAS) for system
• Kucharski Rafal; Cats Oded (2020) — Exact matching of attractive shared rides (ExMAS) for system
• Kucharski Rafal; Cats Oded (2022) — Simulating Two-Sided Mobility Platforms with MaaSSim
• Kucharski et al. (2022) — MaaSSim: agent-based two-sided mobility platform simulator
• Rafał Kucharski et al. (2024) — Ride-pooling service assessment with rational, heterogeneous
• Kullman et al. (2022) — Dynamic Ride-Hailing with Electric Vehicles
• Kumar Pramesh; Khani Alireza (2021) — An algorithm for integrating peer-to-peer ridesharing and sc
• Laval Jorge A. (2023) — Self-Organized Criticality of Traffic Flow: Implications for
• Lavieri Patrícia S.; Bhat Chandra R. (2019) — Modeling individuals’ willingness to share trips with strang
• Lin et al. (2018) — Efficient Large-Scale Fleet Management via Multi-Agent Deep
• () — Revue de littérature — Ridesharing & Mobility-on-Demand (202
• Liu et al. (2022) — Deep dispatching: A deep reinforcement learning approach for
• Lokhandwala et al. (2018) — Dynamic ride sharing using traditional taxis and shared auto
• Lopez et al. (2018) — Microscopic Traffic Simulation using SUMO
• Ma et al. (2013) — T-share: A large-scale dynamic taxi ridesharing service
• Ma Shuo; Zheng Yu; Wolfson Ouri (2013) — T-share: A large-scale dynamic taxi ridesharing service
• Maciejewski et al. (2017) — Towards a Testbed for Dynamic Vehicle Routing Algorithms
• Markov et al. (2021) — Simulation-based design and analysis of on-demand mobility s
• Masoud et al. (2017) — A real-time algorithm to solve the peer-to-peer ride-matchin
• Moody Joanna; Zhao Jinhua; Zhao Fang; Zhao Yang (2022) — A joint demand modeling framework for ride-sourcing and dyna
• Nagel Kai; Schreckenberg Michael (1992) — A Cellular Automaton Model for Freeway Traffic
• Nagel Kai; Paczuski Maya (1995) — Emergent Traffic Jams
• Nahmias-Biran Bat-hen; Oke Jimi B.; Kumar Nishant; Basak Kakali; Araldo Andrea; Seshadri Ravi; Akkinepally Arun; Lima Azevedo Carlos; Ben-Akiva Moshe (2021) — Evaluating the impacts of shared automated mobility on-deman
• Narayanan et al. (2020) — Shared Autonomous Vehicle Services: A Comprehensive Review
• Raman Naveen; Shah Sanket; Dickerson John (2021) — Data-Driven Methods for Balancing Fairness and Efficiency in
• Oda et al. (2018) — MOVI: A Model-Free Approach to Dynamic Fleet Management
• Oeschger Giulia; Carroll Páraic; Caulfield Brian (2020) — Micromobility and public transport integration: The current
• Ozkan et al. (2020) — Dynamic Matching for Real-Time Ride Sharing
• Pavone et al. (2012) — Robotic Load Balancing for Mobility-on-Demand Systems
• Pavone et al. (2015) — Autonomous Mobility-on-Demand Systems for Future Urban Mobil
• Qin et al. (2020) — Ride-Hailing Order Dispatching at DiDi via Reinforcement Lea
• Qin et al. (2022) — Reinforcement learning for ridesharing: An extended survey
• Rayle Lisa; Dai Danielle; Chan Nick; Cervero Robert; Shaheen Susan (2016) — Just a better taxi? A survey-based comparison of taxis, tran
• Reck Daniel J.; Hensher David A.; Ho Chinh Q. (2020) — MaaS bundle design
• Rizzoli Andrea E.; Montemanni Roberto; Lucibello Eric; Gambardella Luca M. (2007) — Ant Colony Optimization for Real-World Vehicle Routing Probl
• Ruch et al. (2018) — AMoDeus, a Simulation-Based Testbed for Autonomous Mobility-
• Salazar et al. (2020) — Intermodal Autonomous Mobility-on-Demand
• Santi et al. (2014) — Quantifying the benefits of vehicle pooling with shareabilit
• Santi Paolo; Resta Giovanni; Szell Michael; Sobolevsky Stanislav; Strogatz Steven H.; Ratti Carlo (2014) — Quantifying the benefits of vehicle pooling with shareabilit
• Sayarshad et al. (2017) — Non-myopic relocation of idle mobility-on-demand vehicles as
• Schelling Thomas C. (1971) — Dynamic Models of Segregation
• Schröder et al. (2020) — Anomalous Supply Shortages from Dynamic Pricing in On-Demand
• Simonetto et al. (2019) — Real-time city-scale ridesharing via linear assignment probl
• Smith Göran; Sochor Jana; Karlsson I.C. MariAnne (2018) — Mobility as a Service: Development scenarios and implication
• Soza-Parra Jaime; Kucharski Rafal; Cats Oded (2022) — The shareability potential of ride-pooling under alternative
• Spieser et al. (2014) — Toward a Systematic Approach to the Design and Evaluation of
• Steiner Konrad; Irnich Stefan (2020) — Strategic Planning for Integrated Mobility-on-Demand and Urb
• Stiglic et al. (2015) — The benefits of meeting points in ride-sharing systems
• Stiglic Mitja; Agatz Niels; Savelsbergh Martin; Gradisar Mirko (2015) — The benefits of meeting points in ride-sharing systems
• Stiglic Mitja; Agatz Niels; Savelsbergh Martin; Gradisar Mirko (2018) — Enhancing Urban Mobility: Integrating Ride-sharing and Publi
• Tachet Remi; Sagarra Oleguer; Santi Paolo; Resta Giovanni; Szell Michael; Strogatz Steven H.; Ratti Carlo (2017) — Scaling Law of Urban Ride Sharing
• Tafreshian et al. (2020) — Frontiers in Service Science: Ride Matching for Peer-to-Peer
• Tang et al. (2019) — A Deep Value-network Based Approach for Multi-Driver Order D
• Tikoudis Ioannis; Martinez Luis; Farrow Katherine; Bouyssou Clara G.; Petrik Olga; Oueslati Walid (2021) — Ridesharing services and urban transport CO2 emissions: Simu
• Tirachini Alejandro; del Rio Cristobal (2019) — Ride-hailing in Santiago de Chile: Users’ characterisation a
• Vazifeh et al. (2018) — Addressing the minimum fleet problem in on-demand urban mobi
• Vosooghi Reza; Puchinger Jakob; Jankovic Milan; Vouillon Arthur (2024) — Shared Autonomous Vehicles and Agent Based Models: A Review
• Wallar et al. (2018) — Vehicle Rebalancing for Mobility-on-Demand Systems with Ride
• Wen et al. (2017) — Rebalancing shared mobility-on-demand systems: A reinforceme
• Wong Yale Z.; Hensher David A.; Mulley Corinne (2020) — Mobility as a service (MaaS): Charting a future context
• Xie et al. (2023) — Two-Sided Deep Reinforcement Learning for Dynamic Mobility-o
• Yan et al. (2020) — Dynamic Pricing and Matching in Ride-Hailing Platforms
• Yang et al. (2002) — Demand–Supply Equilibrium of Taxi Services in a Network unde
• Yang et al. (2011) — Equilibrium Properties of Taxi Markets with Search Frictions
• Zha et al. (2018) — Surge Pricing and Labor Supply in the Ride-Sourcing Market
• Zhang et al. (2016) — Control of Robotic Mobility-On-Demand Systems: a Queueing-Th
• Zhu Pengyu; Mo Haoyu (2022) — The potential of ride-pooling in VKT reduction and its envir
• Ziemke et al. (2019) — The MATSim Open Berlin Scenario: A multimodal agent-based tr
• Zwick et al. (2022) — Shifts in perspective: Operational aspects in (non-)autonomo

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