An In-Depth Spatiotemporal Analysis of RideHailing Travel: The Chicago Case Study

With the rapid increase in ride-hailing, a need to better understand and regulate the industry arises. Conflicting results have been published by researchers and policy makers regarding ridehailing’s impact on congestion, public transit, and other aspects of traffic systems. One of the obstacles to studying ride-hailing is the lack of granular operational data over a relatively long period of time. An efficient system that can coordinate ride-hailing and other travel modes to better serve travel needs and minimize negative impacts on the transportation system requires sufficient ride-hailing trip-by-trip data and an understanding of ride-hailing trip patterns. Such patterns include the times that travelers use ride-hailing, where they are traveling from and to, how weekend and weekday ride-hailing trips differ, etc. This paper analyzes a year’s worth of ride-hailing trip data from the Greater Chicago Area, which included detailed time, date, trip length, origin, and destination information to study the ride-hailing trip patterns. More than 104 million trips were analyzed. For trip rates, the results show that the total number of trips remained stable over the year. People tend to use ride-hailing more on weekends compared to weekdays. Specifically, weekend ride-hailing trip counts (per day) are, on average, 20% higher than weekday trip counts. Spatial patterns of ride-hailing trips were analyzed in ArcGIS. The results show that longer ride-hailing trips, which have their origins and destinations located in different census tracts, are more statistically correlated to factors such as income, education level, and average transit commuting time in the area. They are also more spatially clustered compared to their shorter counterparts, which have their origins and destinations located in the same census tracts. Longer ride-hailing trips are more clustered around the central business district (CBD) and gradually become sparser while moving further away from the CBD. The results of this paper will help policy makers and transportation administrators better understand the nature of ride-hailing trips, which in turn allows for better regulation and guidance for the ride-hailing industry.

• Record URL:
  https://doi.org/10.1016/j.cstp.2021.11.010
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S2213624X21001851
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/2213624X
• Supplemental Notes:
  • © 2021 World Conference on Transport Research Society. Published by Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
• Authors:
  • Du, Jianhe
  • Rakha, Hesham A
  • Breuer, Helena
• Publication Date: 2022-3

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References; Tables;
• Pagination: pp 118-129
• Serial:
  • Case Studies on Transport Policy
  • Volume: 10
  • Issue Number: 1
  • Publisher: Elsevier
  • ISSN: 2213-624X
  • Serial URL: http://www.sciencedirect.com/science/journal/2213624X

Subject/Index Terms

• TRT Terms: Consumer behavior; Ridesourcing; Traffic data
• Geographic Terms: Chicago (Illinois)
• Subject Areas: Highways; Operations and Traffic Management;

Filing Info

• Accession Number: 01790587
• Record Type: Publication
• Files: TRIS
• Created Date: Dec 9 2021 9:13AM