A full-stack simulation of a ridesharing app

Real-time simulation library for ridesharing and other VRP problems

Simulation of Ridesharing Market and the MDP Order Dispatch Policy

A Rideshare Simulation built in C++, using OpenStreetMap data

Simulation of Pooled versus Dedicated Rideshares http://www.telegraphresearch.com/ridesharing/

End-to-end data engineering platform simulating a real-time ride-sharing network in Sao Paulo. Features a multi-agent discrete event simulator that generates synthetic traffic, rides, and financial data, processed through a modern Lakehouse architecture using Kafka, Databricks, Delta Lake, and Airflow.

Built a Java simulation for shared autonomous vehicle fleets in ridesharing. The simulation ensures optimal passenger pickup and drop-offs by minimizing passenger wait times using Dijkstra's shortest path algorithm, linear programming with IBM’s CPLEX API, and a genetic algorithm.

RideSync is a real-time rideshare simulation. It visualizes customer-driver interactions on a dynamic map powered by Leaflet.js, simulates live ETA and fuel usage, and uses routing logic over a parsed road network from OpenStreetMap data.

Rideshare simulation

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C++ event-driven simulation of a rideshare system with driver-rider assignment and performance metrics.

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A rideshare backend simulation built in java

Rideshare Simulation in a Complex Road Network

RideSharing Simulation Codes with Huy.Vo in CUSP, NYU

Agent-based simulation model for dynamic ridesharing systems with stochastic travel times

Planning and Regulation for Autonomous Ridesharing Services Based on Survey and Simulation

A quick rideshare simulation made in 15 minutes by Gemini 3 Pro

A Java-based rideshare simulator. It emulates ride pickups, drop-offs, and food delivery operations for a simple, interactive simulation of a rideshare app.

This is an extension of the work of Haliem et al. on Dynamic Ridesharing Pooling Simulation which can be found in the following repo: https://github.com/marina-haliem/Dynamic-RideSharing-Pooling-Simulator

The "Agent-based Ridesharing Simulation" project involves creating a Python program to simulate a ridesharing system in a city. Focus on implementing the algorithm with 30 vehicles and random graph structures, optimizing pickup and drop-off requests for efficiency.

simulation of a rideshare network that couples Machine Learning (Demand Forecasting) with Operations Research (Real-time Dispatch) to minimize rider wait times and maximize fleet efficiency.

A simulation that models a ridesharing platform’s dynamic matching between drivers and passengers. It features real-time routing, ride request generation, and performance analytics for scalable evaluation

Dynamic Ridesharing: D-RIDE AMS consist of the source-code and the compiled application used as part of the AMS (Analysis, Modeling and Simulation Testbeds for DMA and ATDM Evaluation) Phoenix Testbed.

RideShare simulation using object-oriented design and the Visitor pattern to enable dynamic drawing of Customers and Drivers on a city map. Implemented location-based ride matching with driver filtering based on vehicle capacity and rating.

This is ridesharing simulation written in NETLOGO published in: Simulating the Ride-sharing Economy: The Individual Agent Metro-Washington Area Ride-sharing Model, Complex Adaptive Systems: Views from the Physical, Natural, & Social Sciences, 2019. ISBN: 978-1-5108-6014-8