Travel Time Estimation on Urban Street Segment

  • Jelena Kajalić The Faculty of Transport and Traffic Engineering, Belgrade University
  • Nikola Čelar The Faculty of Transport and Traffic Engineering, Belgrade University
  • Stamenka Stanković The Faculty of Transport and Traffic Engineering, Belgrade University
Keywords: urban street, level of service, speed-flow curve, travel time survey,

Abstract

Level of service (LOS) is used as the main indicator of transport quality on urban roads and it is estimated based on the travel speed. The main objective of this study is to determine which of the existing models for travel speed calculation is most suitable for local conditions. The study uses actual data gathered in travel time survey on urban streets, recorded by applying second by second GPS data. The survey is limited to traffic flow in saturated conditions. The RMSE method (Root Mean Square Error) is used for research results comparison with relevant models: Akcelik, HCM (Highway Capacity Manual), Singapore model and modified BPR (the Bureau of Public Roads) function (Dowling - Skabardonis). The lowest deviation in local conditions for urban streets with standardized intersection distance (400-500 m) is demonstrated by Akcelik model. However, for streets with lower signal density (<1 signal/km) the correlation between speed and degree of saturation is best presented by HCM and Singapore model. According to test results, Akcelik model was adopted for travel speed estimation which can be the basis for determining the level of service in urban streets with standardized intersection distance and coordinated signal timing under local conditions.

Author Biographies

Jelena Kajalić, The Faculty of Transport and Traffic Engineering, Belgrade University
Teaching assistant, PhD student, Faculty of Transport and Traffic Engineering, Belgrade University
Nikola Čelar, The Faculty of Transport and Traffic Engineering, Belgrade University
Assistant proffesor, Faculty of Transport and Traffic Engineering, Belgrade University
Stamenka Stanković, The Faculty of Transport and Traffic Engineering, Belgrade University
Teaching assistant, PhD student, Faculty of Transport and Traffic Engineering, Belgrade University

References

Mtoi ET, Moses R. Calibration and Evaluation of Link Congestion Functions: Applying Intrinsic Sensitivity of Link Speed as a Practical Consideration to Heterogeneous Facility Types within Urban Network. Journal of Transportation Technologies. 2014; 4(2): 141-149.

Ali AT, Venigalla MM, Flannery A. Estimating Running Time on Urban Street Segments. Proceedings of the 3rd Urban Street Symposium, 24-27 June 2007, Seattle, Washington. Washington DC: Transportation Research Board of the National Academies of Science; 2007. p. 1-12. Available from: http://www.urbanstreet.

info/3rd_symp_proceedings/Estimating Running

Time.pdf [Accessed 18th January 2016]

Xie C, Cheu RL, Lee D. Calibration-Free Arterial Link Speed Estimation Model Using Loop Data. Journal of Transportation Engineering. 2001; 127(6): 507-514.

Dowling R, Skabardonis A. Urban Arterial Speed-Flow Equations for Travel Demand Models. Proceedings of the Innovations in Travel Demand Modeling, 21-23 May 2006, Austin, Texas. Transportation Research Board, Washington DC. 2008; 2(42): 109-113.

Highway Capacity Manual. Washington DC: Transportation Research Board, National Research Council; 2000.

Highway Capacity Manual. Washington DC: Transportation Research Board, National Research Council; 2010.

Akcelik R. Travel time functions for transport planning purposes: Davidson’s function, its time dependent form and alternative travel time function. Australian Road Research. 1991; 21(3): 49-59.

Moses R, Mtoi E, McBean H, Ruegg S. Development of Speed Models for Improving Travel Forecasting and Highway Performance Evaluation. Florida Department of Transportation. Final Report Project No. BDK83-977-14, 2013. Available from: http://www.fsutmsonline.net/images/uploads/reports/Speed_Modeling_Final_Report.pdf [Accessed 23rd March 2016]

Davis GA, Xiong H. Access to Destinations: Travel Time Estimation on Arterials. Minnesota Department of Transportation. Report 2007-35, 2007.

Published
2018-02-23
How to Cite
1.
Kajalić J, Čelar N, Stanković S. Travel Time Estimation on Urban Street Segment. Promet [Internet]. 2018Feb.23 [cited 2023Jan.31];30(1):115-20. Available from: https://traffic.fpz.hr/index.php/PROMTT/article/view/2473
Section
Articles