Technical Papers
May 21, 2014

Exploring Operating Speeds on Urban Arterials Using Floating Car Data: Case Study in Shanghai

Publication: Journal of Transportation Engineering
Volume 140, Issue 9

Abstract

Urban arterials in Shanghai usually have high intersection densities, which can lead to frequent and severe congestion. Research in this area of study focuses on urban arterial operating speed and its relationship with road geometry, traffic control, and traffic volume, and more study is needed before remedies to the congestion problems can be identified. In Shanghai, an opportunity exists to investigate urban arterial operating speed by accessing continuously updated global positioning system (GPS) data from taxis, hereafter called floating car data (FCD). With more than 50,000 taxis equipped with GPS running in the Shanghai road network, it is feasible to acquire comprehensive, citywide arterial speed measurements throughout the network. In this study, 45 arterials in Shanghai, which comprised of 177 two-direction segments bounded by signalized intersections, were selected for study. GPS data from taxis were captured during peak and off-peak hours to enable the calculation of the mean operating speed for each selected segment. Information of road geometry, traffic control, and traffic volume data was also acquired to examine their influence on operating speed. Multilevel linear regression models were utilized to analyze operating speed with the arterial level’s unobserved heterogeneity accounted for as well. It was identified that roadway design variables, including segment length, number of lanes, and horizontal degree of curvature, left-turn lane types, and presence of median along with saturation degree, are all significantly related to the operating speed. The results of this study shed some light on roadway design, roadway improvement, and traffic management.

Get full access to this article

View all available purchase options and get full access to this article.

Acknowledgments

The authors acknowledge the comments and suggestions of several anonymous reviewers. This study was jointly sponsored by the Chinese National Science Foundation (51008230), the program for New Century Excellent Talents in University (NCET-11-0387), and the Fundamental Research Funds for the Central Universities project.

References

Comert, G., and Cetin, M. (2009). “Queue length estimation from probe vehicle location and the impacts of sample size.” Eur. J. Oper. Res., 197(1), 196–202.
Cruzado, I., and Donnell, E. (2011). “Models of vehicle operating speeds along two-lane rural highway transition zones: Panel and multilevel modeling approaches.” Transp. Lett., 3(4), 265–278.
Esawey, M. E., and Sayed, T. (2009). “Travel time estimation in an urban network using sparse probe vehicle data and historical travel time relationships.” TRB 88th Annual Meeting Compendium of Papers (CD-ROM), Transportation Research Board of National Academy, Washington, DC.
Figueroa, A. M., and Tarko, A. P. (2005). “Speed Factors on two-lane rural highways in free-flow conditions.” TRB 84th Annual Meeting Compendium of Papers (CD-ROM), Transportation Research Board of National Academy, Washington, DC.
Fitzpatrick, K., Carlson, P. J., Brewer, M., and Wooldridge, M. D. (2001). “Design factors that affect driver speed on suburban arterials.”, Washington, DC.
Kamble, S. H., Mathew, T. V., and Sharma, G. K. (2009). “Development of real-world driving cycle: Case study of Pune, India.” Transp. Res. Part D, 14(2), 132–140.
Liu, B. (2007). “Association of intersection approach speed with driver characteristics, vehicle type, and traffic conditions comparing urban and suburban areas.” Accid. Anal. Prev., 39(2), 216–223.
Park, Y. J., and Saccomanno, F. F. (2006). “Evaluating speed consistency between successive elements of a two-lane rural highway.” Transp. Res. Part A, 40(5), 375–385.
Poe, C. M., Tarris, J. P., and Mason, J. M. (1998). “Operation speed approach to geometric design of low-speed urban arterials.” TRB 77th Annual Meeting Compendium of Papers (CD-ROM), Transportation Research Board of National Academy, Washington, DC.
SAS Institute. (2010). SAS OnlineDoc 9.2, Cary, NC.
Shenzhen Urban Transport Planning Center (2011). 〈www.sutpc.com〉 (Feb. 2, 2014).
Singer, J. D. (1998). “Using SAS PROC MIXED to fit multilevel models, hierarchical models, and individual growth models.” J. Educ. Behav. Stat., 24(4), 323–355.
Transportation Research Board. (2010). Highway capacity manual, Washington, DC.
Wang, J. (2006). “Operation speed models for low-speed urban environments based on in-vehicle GPS data.” Ph.D. thesis, School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta.
Wang, Q., Huo, H., He, K., Yao, Z., and Zhang, Q. (2008).“Characterization of vehicle driving patterns and development of driving cycles in Chinese cities.”Transp. Res. Part D, 13(5), 289–297.
Xie, K., Wang, X., Chen, X., and Huang, H. (2013). “Corridor-level signalized intersection safety analysis in Shanghai, China, using Bayesian hierarchical models.” Accid. Anal. Prev., 50(1), 25–33.
Yu, L., Yu, L., Qi, Y., Wang, J., and Wen, H. (2008). “Traffic incident detection algorithm for urban expressways based on probe vehicle data.” J. Transp. Syst. Eng. Inf. Technol., 8(4), 36–41.
Zhang, W., Xu, J., and Wang, H. (2007). “Urban traffic situation calculation methods based on probe vehicle data.” J. Transp. Syst. Eng. Inf. Technol., 7(1), 43–49.

Information & Authors

Information

Published In

Go to Journal of Transportation Engineering
Journal of Transportation Engineering
Volume 140Issue 9September 2014

History

Received: Apr 19, 2012
Accepted: Mar 12, 2014
Published online: May 21, 2014
Published in print: Sep 1, 2014
Discussion open until: Oct 21, 2014

Permissions

Request permissions for this article.

Authors

Affiliations

Xuesong Wang, Ph.D. [email protected]
Professor, School of Transportation Engineering, Tongji Univ., Shanghai 201804, China (corresponding author). E-mail: [email protected]
Haobing Liu [email protected]
Graduate Research Assistant, School of Transportation Engineering, Tongji Univ., Shanghai 201804, China. E-mail: [email protected]
Rongjie Yu, Ph.D. [email protected]
Assistant Professor, School of Transportation Engineering, Tongji Univ., Shanghai 201804, China. E-mail: [email protected]
Bing Deng, Ph.D. [email protected]
Senior Engineer, General Motors Safety Electronics and Innovation, Warren, MI 48090. E-mail: [email protected]
Xiaohong Chen, Ph.D. [email protected]
Professor, School of Transportation Engineering, Tongji Univ., Shanghai 201804, China. E-mail: [email protected]
Bing Wu, Ph.D. [email protected]
Professor, School of Transportation Engineering, Tongji Univ., Shanghai 201804, China. E-mail: [email protected]

Metrics & Citations

Metrics

Citations

Download citation

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.

Cited by

View Options

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Media

Figures

Other

Tables

Share

Share

Copy the content Link

Share with email

Email a colleague

Share