Simulates a dispatching algorithm serving exogenous transportation requests with a fleet of vehicles. Does not simulate the universe, unlike MATSim. Batteries are included.
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Updated
Jun 19, 2026 - Python
Simulates a dispatching algorithm serving exogenous transportation requests with a fleet of vehicles. Does not simulate the universe, unlike MATSim. Batteries are included.
Neural Approximate Dynamic Programming for On-Demand Ride-Pooling implemented in PyTorch.
This simulator uses a proposed non-myopic cost function approximation policy to allow passengers to have synchronized transfers within a ride-pooling system.
Development of a Ride Pooling Heuristic and Simulation
NOMAD-RPS is a dynamic ride-pooling simulator that uses a non-myopic cost function approximation policy to make sequential decisions and find the best matches between riders and vehicles in the system
A fleet-based simulation platform that connects MATSim with external ride-pooling simulators
Supplementary data to reproduce the figures in the article "Identifying the threshold to sustainable ridepooling"
Portfolio edition of dynamic ridepooling research: rolling-horizon simulation, Gurobi trip-vehicle assignment, shareability-aware features, and NODE/Transformer ETA residual prediction.
[Transportation Research Part C] Official Repository for The Paper, Real-Time Order Assignment for Ride-Sharing Platforms with a Mixture of Pre-booked and On-Demand Requests
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