Dynamic joint decision of matching parameters and relocation strategies in ride-sourcing systems interacting with traffic congestion-Reference-Cited by-同舟云学术

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Dynamic joint decision of matching parameters and relocation strategies in ride-sourcing systems interacting with traffic congestion

Published:2024-04 Issue: Volume:161 Page:104524
ISSN:0968-090X
Container-title:Transportation Research Part C: Emerging Technologies
language:en
Short-container-title:Transportation Research Part C: Emerging Technologies

Author:

Zhang Jun,Hu Lu^ORCID,Li Yan,Xu Weiyao,Jiang Yangsheng

Funder

Fundamental Research Funds for the Central Universities

Sichuan Province Department of Science and Technology

National Natural Science Foundation of China

Publisher

Elsevier BV

Reference58 articles.

1. A continuum model for cities based on the macroscopic fundamental diagram: a semi-Lagrangian solution method;Aghamohammadi;Transp. Res. Procedia,2019

2. On-demand high-capacity ride-sharing via dynamic trip-vehicle assignment;Alonso-Mora;Proc. Natl. Acad. Sci. USA,2017

3. W-SPSA in practice: Approximation of weight matrices and calibration of traffic simulation models;Antoniou;Transp. Res. C,2015

4. Dynamic stochastic matching under limited time;Aouad,2020

5. A bathtub model of downtown traffic congestion;Arnott;J. Urban Econ.,2013

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1. State-dependent multi-agent discrete event simulation for urban rail transit passenger flow;Physica A: Statistical Mechanics and its Applications;2024-10

2. Reinforcement Learning Optimization of Mobility and Relocation Incentives for Carsharing Free-Floating Electric Fleets;2024

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