IOCAS-IR
GPS data in urban online ride-hailing: A comparative analysis on fuel consumption and emissions
Sui, Yi1,2; Zhang, Haoran2; Song, Xuan2; Shao, Fengjing1,3; Yu, Xiang1; Shibasaki, Ryosuke2; Sun, Rechengcheng1,3; Yuan, Meng4; Wang, Changying3; Li, Shujing1,3; Li, Yao5
2019-08-01
发表期刊JOURNAL OF CLEANER PRODUCTION
ISSN0959-6526
卷号227页码:495-505
通讯作者Zhang, Haoran([email protected]) ; Song, Xuan([email protected])
摘要The transportation sector has become the leading and most-rapidly growing contributor to greenhouse gas emissions. Promoting low-carbon travel mode is critical to alleviate this issue. As a new travel mode, online ride-hailing (such as Didi Chuxing and Uber), is becoming increasingly popular in cities around the world. However, there is still no comparative analysis on fuel consumption and emissions: does online ride-hailing have a distinct fuel consumption and emissions pattern with traditional taxis? In this study, we use one month global positioning system dataset and orders dataset, averagely covering around 7 thousand taxis with 0.3 million trips and 23 thousand Didi Chuxing Express vehicles with 0.1 million trips per day in Chengdu, China to answer this question. Empirical results show that taxi trips associate with longer idle distance and shorter delivery distance than Didi trips. Didi trips' average idle velocity is apparently smaller than their delivery velocity. Online ride-hailing mode is concluded to contribute to these difference: after dropping off previous passengers, Didi drivers usually park their cars until being dispatched new orders and then drive directly to pick up passengers rather than search circuitously. Fuel consumption and carbon monoxide, nitrogen oxides, hydrocarbon emissions per passenger-on kilometer of taxi trips are found to be about 1.36, 1.45, 1.36 and 1.44 times that of Didi trips, respectively. Additionally, only taxi drivers with good performance have the ability to reduce fuel consumption and emissions: while most Didi drivers can perform well on fuel consumption saving and emissions reduction. Finally, several feasible policies are suggested for improving and upgrading the traditional taxi business. Our study provides convincing evidence for understanding the advantage of online ride-hailing mode in reduction fuel consumption and emissions sourced from empty cruising, so as to support better traffic policy making and the promotion on low-carbon travel mode. (C) 2019 Elsevier Ltd. All rights reserved.
关键词Online ride-hailing mode Fuel consumption and emissions Traditional taxis Travel patterns
DOI10.1016/j.jclepro.2019.04.159
收录类别SCI
语种英语
资助项目Young Scientists Fund of the National Natural Science Foundation of China[41706198]###2698; National Statistical Science Research Project of China[2017LY82]###2699; Shandong Computer Science Provincial Key Laboratory Joint Open Fund Project of China###2700; Shandong Province Higher Educational Science and Technology Program of China[J17KA056]###2701; Young Scientists Fund of the National Natural Science Foundation of China[41706198]; National Statistical Science Research Project of China[2017LY82]; Shandong Computer Science Provincial Key Laboratory Joint Open Fund Project of China; Shandong Province Higher Educational Science and Technology Program of China[J17KA056]
WOS研究方向Science & Technology - Other Topics ; Engineering ; Environmental Sciences & Ecology
WOS类目Green & Sustainable Science & Technology ; Engineering, Environmental ; Environmental Sciences
WOS记录号WOS:000470939600046
出版者ELSEVIER SCI LTD
引用统计
被引频次:72[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.qdio.ac.cn/handle/337002/161623
专题中国科学院海洋研究所
通讯作者Zhang, Haoran; Song, Xuan
作者单位1.Qingdao Univ, Coll Comp Sci & Technol, Ningxia Rd 308, Qingdao 266071, Peoples R China
2.Univ Tokyo, Ctr Spatial Informat Sci, 5-1-5 Kashiwanoha, Kashiwa, Chiba 2778568, Japan
3.Inst Smart City & Big Data Technol, Ningxia Rd 308, Qingdao 266071, Peoples R China
4.China Univ Petr, Beijing Key Lab Urban Oil & Gas Distribut Technol, Natl Engn Lab Pipeline Safety, Fuxue Rd 18, Beijing 102249, Peoples R China
5.Chinese Acad Sci, Inst Oceanol, Nanhai Rd 7, Qingdao 266071, Peoples R China
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Sui, Yi,Zhang, Haoran,Song, Xuan,et al. GPS data in urban online ride-hailing: A comparative analysis on fuel consumption and emissions[J]. JOURNAL OF CLEANER PRODUCTION,2019,227:495-505.
APA Sui, Yi.,Zhang, Haoran.,Song, Xuan.,Shao, Fengjing.,Yu, Xiang.,...&Li, Yao.(2019).GPS data in urban online ride-hailing: A comparative analysis on fuel consumption and emissions.JOURNAL OF CLEANER PRODUCTION,227,495-505.
MLA Sui, Yi,et al."GPS data in urban online ride-hailing: A comparative analysis on fuel consumption and emissions".JOURNAL OF CLEANER PRODUCTION 227(2019):495-505.
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