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Sustainability 2017, 9(6), 949; doi:10.3390/su9060949

Observing Trip Chain Characteristics of Round-Trip Carsharing Users in China: A Case Study Based on GPS Data in Hangzhou City

1,2,* , 1,2
,
1,2
and
3
1
The Key Laboratory of Road and Traffic Engineering, Ministry of Education, Shanghai 201804, China
2
College of Transportation Engineering, Tongji University, Shanghai 201804, China
3
Hangzhou Institute of Communications Planning Design & Research, Hangzhou 310000, China
*
Author to whom correspondence should be addressed.
Academic Editor: Tan Yigitcanlar
Received: 13 March 2017 / Revised: 23 May 2017 / Accepted: 24 May 2017 / Published: 5 June 2017
(This article belongs to the Section Sustainable Urban and Rural Development)
View Full-Text   |   Download PDF [3018 KB, uploaded 5 June 2017]   |  

Abstract

Carsharing as a means to provide individuals with access to automobiles to complete a personal trip has grown significantly in recent years in China. However, there are few case studies based on operational data to show the role carsharing systems play in citizens’ daily trips. In this study, vehicle GPS data of a round-trip carsharing system in Hangzhou, China was used to describe the trip chain characteristics of users. For clearer delineation of carshare usage, the car use time length of all observations chosen in the study was within 24 h or less. Through data preprocessing, a large pool (26,085) of valid behavior samples was obtained, and several trip chaining attributes were selected to describe the characteristics. The pool of observations was then classified into five clusters, with each cluster having significant differences in one or two trip chain characteristics. The cluster results reflected that different use patterns exist. By a comparative analysis with trip survey data in Hangzhou, differences in trip chain characteristics exist between carsharing and private cars, but in some cases, shared vehicles can be a substitute for private cars to satisfy motorized travel. The proposed method could facilitate companies in formulating a flexible pricing strategy and determining target customers. In addition, traffic administration agencies could have a deeper understanding of the position and function of various carsharing modes in an urban transportation system. View Full-Text
Keywords: carsharing; GPS data; CLARA clustering algorithm; trip chain characteristics; use pattern carsharing; GPS data; CLARA clustering algorithm; trip chain characteristics; use pattern
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MDPI and ACS Style

Hui, Y.; Ding, M.; Zheng, K.; Lou, D. Observing Trip Chain Characteristics of Round-Trip Carsharing Users in China: A Case Study Based on GPS Data in Hangzhou City. Sustainability 2017, 9, 949.

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