Cover Image

Generalising Travel Time Prediction To Varying Route Choices In Urban Networks

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Gorczyca, Łukasz, Drozd, Kacper, Bujak, Michał, Kucharski, Rafał
Format:	Preprint
Published:	2026
Subjects:	Multiagent Systems Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Collaboration Between the City and Machine Learning Community is Crucial to Efficient Autonomous Vehicles Routing
by: Psarou, Anastasia, et al.
Published: (2025)

RouteRL: Multi-agent reinforcement learning framework for urban route choice with autonomous vehicles
by: Akman, Ahmet Onur, et al.
Published: (2025)

Autonomous vehicles need social awareness to find optima in multi-agent reinforcement learning routing games
by: Psarou, Anastasia, et al.
Published: (2025)

PC3D: Zero-Shot Cooperation Across Variable Rosters via Personalized Context Distillation
by: Akman, Ahmet Onur, et al.
Published: (2026)

Adaptive Optimisation of Ride-Pooling Personalised Fares in a Stochastic Framework
by: Bujak, Michal, et al.
Published: (2025)

Optimizing Ride-Pooling Revenue: Pricing Strategies and Driver-Traveller Dynamics
by: Akhtar, Usman, et al.
Published: (2024)

Modelling the Rise and Fall of Two-Sided Mobility Markets with Microsimulation
by: Ghasemi, Farnoud, et al.
Published: (2022)

Generalisable Agents for Neural Network Optimisation
by: Tessera, Kale-ab, et al.
Published: (2023)

MixTTE: Multi-Level Mixture-of-Experts for Scalable and Adaptive Travel Time Estimation
by: Jiang, Wenzhao, et al.
Published: (2026)

Interpretable Cascading Mixture-of-Experts for Urban Traffic Congestion Prediction
by: Jiang, Wenzhao, et al.
Published: (2024)

MaaSSim -- agent-based two-sided mobility platform simulator
by: Kucharski, Rafał, et al.
Published: (2020)

URB -- Urban Routing Benchmark for RL-equipped Connected Autonomous Vehicles
by: Akman, Ahmet Onur, et al.
Published: (2025)

Multi-Agent Training-free Urban Food Delivery System using Resilient UMST Network
by: Hasan, Md Nahid, et al.
Published: (2026)

Graph Learning-based Fleet Scheduling for Urban Air Mobility under Operational Constraints, Varying Demand & Uncertainties
by: Paul, Steve, et al.
Published: (2024)

Generalising Multi-Agent Cooperation through Task-Agnostic Communication
by: Jayalath, Dulhan, et al.
Published: (2024)

Dynamics of Learning under User Choice: Overspecialization and Peer-Model Probing
by: Narang, Adhyyan, et al.
Published: (2026)

Probabilistic Multi-Agent Aircraft Landing Time Prediction
by: Kim, Kyungmin, et al.
Published: (2025)

Multi-Agent Environments for Vehicle Routing Problems
by: Gama, Ricardo, et al.
Published: (2024)

Learning to Design City-scale Transit Routes
by: Poudel, Bibek, et al.
Published: (2025)

Detection of coordinated fleet vehicles in route choice urban games. Part I. Inverse fleet assignment theory
by: Jamróz, Grzegorz, et al.
Published: (2025)

USPR: Learning a Unified Solver for Profiled Routing
by: Hua, Chuanbo, et al.
Published: (2025)

MasRouter: Learning to Route LLMs for Multi-Agent Systems
by: Yue, Yanwei, et al.
Published: (2025)

Self-Evolving Multi-Agent Network for Industrial IoT Predictive Maintenance
by: Saleh, Rebin, et al.
Published: (2026)

Adaptive Urban Planning: A Hybrid Framework for Balanced City Development
by: Singla, Pratham, et al.
Published: (2024)

Balancing Profit and Traveller Acceptance in Ride-Pooling Personalised Fares
by: Bujak, Michal, et al.
Published: (2024)

MACTAS: Self-Attention-Based Inter-Agent Communication in Multi-Agent Reinforcement Learning with Action-Value Function Decomposition
by: Wojtala, Maciej, et al.
Published: (2025)

Robust Correlated Equilibrium: Definition and Computation
by: Misra, Rahul, et al.
Published: (2023)

Driver Fatigue Prediction using Randomly Activated Neural Networks for Smart Ridesharing Platforms
by: Akula, Sree Pooja, et al.
Published: (2024)

Joint Pedestrian and Vehicle Traffic Optimization in Urban Environments using Reinforcement Learning
by: Poudel, Bibek, et al.
Published: (2025)

Multi-Agent Coordination in Autonomous Vehicle Routing: A Simulation-Based Study of Communication, Memory, and Routing Loops
by: Saifullah, KM Khalid, et al.
Published: (2025)

Network-Constrained Policy Optimization for Adaptive Multi-agent Vehicle Routing
by: Arasteh, Fazel, et al.
Published: (2025)

Impact of Collective Behaviors of Autonomous Vehicles on Urban Traffic Dynamics: A Multi-Agent Reinforcement Learning Approach
by: Akman, Ahmet Onur, et al.
Published: (2025)

Learning to Solve the Min-Max Mixed-Shelves Picker-Routing Problem via Hierarchical and Parallel Decoding
by: Luttmann, Laurin, et al.
Published: (2025)

Combat Urban Congestion via Collaboration: Heterogeneous GNN-based MARL for Coordinated Platooning and Traffic Signal Control
by: Peng, Xianyue, et al.
Published: (2023)

The Overcooked Generalisation Challenge: Evaluating Cooperation with Novel Partners in Unknown Environments Using Unsupervised Environment Design
by: Ruhdorfer, Constantin, et al.
Published: (2024)

Equilibria in routing games with connected autonomous vehicles will not be strong, as exclusive clubs may form
by: Kucharski, Rafał, et al.
Published: (2025)

VariAntNet: Learning Decentralized Control of Multi-Agent Systems
by: Koifman, Yigal, et al.
Published: (2025)

Conformal Off-Policy Prediction for Multi-Agent Systems
by: Kuipers, Tom, et al.
Published: (2024)

ARMove: Learning to Predict Human Mobility through Agentic Reasoning
by: Wang, Chuyue, et al.
Published: (2026)

CAMAR: Continuous Actions Multi-Agent Routing
by: Pshenitsyn, Artem, et al.
Published: (2025)