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Dynamic Ride-Sourcing Systems For City-Scale Networks: Matching Design And Model Formulation And Validation.pdf

MR-AV-TRC2023.pdf
Preview of Dynamic Ride-Sourcing Systems for City-Scale Networks: Matching Design and Model Formulation and Validation
🔗 Source: transportlab.sydney.edu.au
📊 Size: 2.54 MB
👤 Author: Mohsen Ramezani
⬇️ Downloads: 43

Summary

This research paper presents a dynamic model for ride-sourcing systems, aiming to optimize vehicle–passenger matching and idle vehicle repositioning in city-scale networks. The study focuses on two key aspects:

1. Vehicle–Passenger Matching: The authors propose a spatio-temporal matching method that dynamically determines the optimal time instances and maximum matching distances to minimize passenger waiting times. This method considers network congestion levels and adapts to changes in traffic conditions and passenger requests.

2. Idle Vehicle Repositioning: A controller for repositioning idle vehicles is designed, as discussed in a companion paper (Part II), to balance vehicle supply and passenger demand based on the proposed dynamic model.

Model Development:

- The researchers introduce a macroscopic non-equilibrium dynamic model, represented by a set of first-order differential equations, to capture the dynamics of ride-sourcing systems.
- They address limitations in previous studies by considering both unlimited matching distance and adaptively changing matching intervals.
- The proposed model predicts the evolution of vehicle and passenger states (idle, transferred, dispatched, occupied) across different regions of the network.

Key Findings:

- The microsimulation results validate the accuracy of the proposed model in predicting system behavior under varying traffic congestion and passenger request scenarios.
- The adaptive matching method significantly reduces waiting times for both ride-sourcing vehicles and passengers, demonstrating its effectiveness.

Contribution:

The study offers a comprehensive approach to modeling dynamic ride-sourcing systems, considering real-world complexities like network congestion and variable demand. It provides valuable insights into optimizing vehicle–passenger matching and idle vehicle management in large-scale urban networks.

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Description

It examines the integration of smart devices and emerging ride-hailing companies, challenging traditional taxi services through two-sided markets and shared mobility.

Technical Information

  • File Format: PDF
  • File Size: 2.54 MB
  • Pages: 22
  • Language: EN
  • Author: Mohsen Ramezani
  • Total Downloads: 43
  • Last Updated: 6 days ago

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This PDF document about Dynamic Ride-Sourcing Systems for City-Scale Networks: Matching Design and Model Formulation and Validation provides comprehensive information and guidance. Whether you're a beginner or advanced user, this resource offers valuable insights into Dynamic Ride-Sourcing Systems for City-Scale Networks: Matching Design and Model Formulation and Validation.

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If you're interested in Dynamic Ride-Sourcing Systems for City-Scale Networks: Matching Design and Model Formulation and Validation, you might also want to explore:

Dynamic guideDynamic tutorialRide-Sourcing guideRide-Sourcing tutorialSystems guideSystems tutorialCity-Scale guideCity-Scale tutorialNetworks: guideNetworks: tutorialMatching guideMatching tutorialDesign guideDesign tutorialModel guideModel tutorialFormulation guideFormulation tutorialValidation guideValidation tutorial

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