Xingjun Huang , Yilan Bu , Junbei Liu , Meng Meng , Jie Zhang , Chengxiang Zhuge
{"title":"基于空间主体的网约车系统及其环境影响模拟方法","authors":"Xingjun Huang , Yilan Bu , Junbei Liu , Meng Meng , Jie Zhang , Chengxiang Zhuge","doi":"10.1016/j.tranpol.2025.103848","DOIUrl":null,"url":null,"abstract":"<div><div>Ride-hailing services could potentially optimize vehicle use and reduce emissions. To investigate the diffusion of ride-hailing services and its impacts at the individual level, we proposed a spatial agent-based model, which integrated the supply-demand dynamics, to simulate the behaviors of the service provider, drivers, and users in Shenzhen, China, from 2023 to 2038 in various future scenarios. The results of the baseline scenario (assuming the market would evolve as before from 2023 to 2038) show a 36 % increase in annual ride-hailing usage, a 24.63 % decrease in the average ride-hailing price, and a 73.16 % increase in drivers' compensation. Carbon emissions reduces by 33.13 % (given that ride-hailing services replace existing combined transportation modes). The what-if scenarios show that price and compensation affect the ride-hailing system in the early stages and further its carbon emission reduction potential. The results would be useful for policy making and optimization of a ride-haling system.</div></div>","PeriodicalId":48378,"journal":{"name":"Transport Policy","volume":"174 ","pages":"Article 103848"},"PeriodicalIF":6.3000,"publicationDate":"2025-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A spatial agent-based approach to simulating the ride-hailing system and its environmental impacts\",\"authors\":\"Xingjun Huang , Yilan Bu , Junbei Liu , Meng Meng , Jie Zhang , Chengxiang Zhuge\",\"doi\":\"10.1016/j.tranpol.2025.103848\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Ride-hailing services could potentially optimize vehicle use and reduce emissions. To investigate the diffusion of ride-hailing services and its impacts at the individual level, we proposed a spatial agent-based model, which integrated the supply-demand dynamics, to simulate the behaviors of the service provider, drivers, and users in Shenzhen, China, from 2023 to 2038 in various future scenarios. The results of the baseline scenario (assuming the market would evolve as before from 2023 to 2038) show a 36 % increase in annual ride-hailing usage, a 24.63 % decrease in the average ride-hailing price, and a 73.16 % increase in drivers' compensation. Carbon emissions reduces by 33.13 % (given that ride-hailing services replace existing combined transportation modes). The what-if scenarios show that price and compensation affect the ride-hailing system in the early stages and further its carbon emission reduction potential. The results would be useful for policy making and optimization of a ride-haling system.</div></div>\",\"PeriodicalId\":48378,\"journal\":{\"name\":\"Transport Policy\",\"volume\":\"174 \",\"pages\":\"Article 103848\"},\"PeriodicalIF\":6.3000,\"publicationDate\":\"2025-10-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Transport Policy\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0967070X25003919\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transport Policy","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0967070X25003919","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
A spatial agent-based approach to simulating the ride-hailing system and its environmental impacts
Ride-hailing services could potentially optimize vehicle use and reduce emissions. To investigate the diffusion of ride-hailing services and its impacts at the individual level, we proposed a spatial agent-based model, which integrated the supply-demand dynamics, to simulate the behaviors of the service provider, drivers, and users in Shenzhen, China, from 2023 to 2038 in various future scenarios. The results of the baseline scenario (assuming the market would evolve as before from 2023 to 2038) show a 36 % increase in annual ride-hailing usage, a 24.63 % decrease in the average ride-hailing price, and a 73.16 % increase in drivers' compensation. Carbon emissions reduces by 33.13 % (given that ride-hailing services replace existing combined transportation modes). The what-if scenarios show that price and compensation affect the ride-hailing system in the early stages and further its carbon emission reduction potential. The results would be useful for policy making and optimization of a ride-haling system.
期刊介绍:
Transport Policy is an international journal aimed at bridging the gap between theory and practice in transport. Its subject areas reflect the concerns of policymakers in government, industry, voluntary organisations and the public at large, providing independent, original and rigorous analysis to understand how policy decisions have been taken, monitor their effects, and suggest how they may be improved. The journal treats the transport sector comprehensively, and in the context of other sectors including energy, housing, industry and planning. All modes are covered: land, sea and air; road and rail; public and private; motorised and non-motorised; passenger and freight.