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Article

TRAVEL TIME VARIABILITY ANALYSIS: THE CASE OF KUMASI, GHANA

DOI: 10.7708/ijtte.2020.10(4).08


10 / 4 / 494-507 Pages

Author(s)

Abena A. Obiri-Yeboah - Kumasi Technical University, Civil Engineering Department, Ghana -

Joseph F. X. Ribeiro - Kumasi Technical University, Mechanical Engineering Department, Ghana -

Benjamin Pappoe - Ghana Highway Authority, Ghana -


Abstract

Travel time variability describes the adjustable and probable changes in travel times that occur during a typical trip on a monitored road segment. Fluctuations in the travel time have direct impact on the route capacity which, in turn, negatively impacts the effectiveness of operational measures of the subject route’s capacity. In this study, travel time analysis was carried out for three different frequently used road segments using three different travel modes: private and commercial (mass transit (“trotro”) and shared taxis) for 13 days by measuring travel times from start to the end of each study section. Three different times of day were employed for the analysis that is the morning peak (7:00am to 10:00am), afternoon peak (1:00pm to 3:00pm) and the evening peak periods (4:00pm to 7:00pm). The results obtained suggest that there are huge variations in the travel time variability for both the morning, afternoon and evening peak periods for the three travel modes studied on the selected routes. The paper concludes that the wide differences in travel time variability, which could be attributed to the prevalence of side friction agents and multiple stops, make trip planning and its related prediction efforts extremely challenging and recommends a scale-up of study to establish the conclusions made from this study.


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Acknowledgements:

The authors acknowledge the contribution of Benjamin Pappoe, a recent Bachelor of Technology graduate from the Civil Engineering Department of Kumasi Technical University for leading the data collection. All project costs were borne by the authors.


References:

Abdel-Aty, M.; Kitamura, R.; Jovanis, P. 1995. Exploring route choice behavior using geographical information system-based alternative routes and hypothetical travel time information input, Transportation Research Record 1493: 74–80.

 

Ammons, D.N. 2001. Municipal benchmarks: Assessing local performance and establishing community standards. 2nd ed, Thousand Oaks: Sage Publications.

 

Biliyamin, I. A.; Abosede, B. A. 2012. Effects of congestion and travel time variability along Abuja-Keffi corridor in Nigeria, Global Journal of Researches in Engineering Civil and Structural Engineering 12(3): 19-25.

 

Chien, S.; Liu, X. 2012. An investigation of measurement for travel time variability. In Intelligent Transportation Systems. Abdel-Rahim, A. (Ed.), IntechOpen, 22-40.

 

China Dialy. 2012. $500m of Chinese loan used on roads in Ghana, says Minister. Available from Internet: http://www.chinadaily.com.cn/bizchina/2012-12/05/content_15986854.htm.

 

Demetsky, M.J.; Bin-Mau Lin, B. 1982. Bus stop location and design, Transportation Engineering Journal of ASCE 108(4): 313– 327.

 

Durán-Hormazábal, E.; Tirachini, A. 2016. Estimation of travel time variability for cars, buses, metro and door-to-door public transport trips in Santiago, Chile, Research in Transportation Economics 59: 26–39.

 

FHWA. 1998. Travel time data collection handbook. Office of Highway Information Management. FHWA, US Department of Transport, Texas Transportation Institute, Texas, A&M University System. Report No. FHWA-PL-98-035.

 

Fosgerau, M. 2017. The valuation of travel-time variability. 39–56 p. Available from Internet: https://doi.org/10.1787/9789282108093-3-en.

 

Fosgerau, M.; Hjorth, K.; Brems, C.; Fukuda, D. 2008. Travel time variability: Definition and valuation. Technical University of Denmark, Copenhagen. 89 p.

 

Furth, P.G.; Rahbee, A.B. 2000. Optimal bus stop spacing through dynamic programming and geographic modeling, Transportation Research Record 1731(1): 15-22.

 

Gaver Jr, D. P. 1968. Headstart strategies for combating congestion. Transportation Science 2(2): 172-181.

 

GIPC. 2020. Infrastructure – Transportation. Ghana Investment Promotion Centre. Available from Internet: https://www.gipcghana.com/invest-in-ghana/why-ghana/infrastructure/transportation-infrastructure.html.

 

Google Maps. 2020. Accessed on the 15th of February, 2020.

 

Gopi, K. M.; Tanenlimalil, S. G.; Paul, B. 2019. Total travel time analysis for students in a metropolitan area: A study from India, International Journal for Traffic and Transport Engineering 9(4): 419–430.

 

Javid, J. R.; Javid, J. R. 2018. A framework for travel time variability analysis using urban traffic incident data, IATSS Research 42(1): 30–38.

 

Kieu, L. M.; Bhaskar, A.; Chung, E. 2015. Public transport travel-time variability definitions and monitoring, Journal of Transportation Engineering 141(1): 23p. Available from Internet: https://doi.org/10.1061/(ASCE)TE.1943-5436.0000724.

 

Knight, T. E. 1974. An approach to the evaluation of changes in travel unreliability: A 'safety margin' hypothesis, Transportation 3(4): 393-408.

 

Kwon, J.; Coifman, B.; Bickel, P. 2000. Day-to-day travel time trends and travel-time prediction from loop-detector data, Transportation Research Record 1717(1): 120-129.

 

Li, H.; Bertini, R.L. 2008. Optimal bus stop spacing for minimizing transit operation cost. In Proceedings of the 6th International Conference on Traffic and Transportation Studies, 553-564.

 

Li, H.; Bertini, R.L. 2009. Assessing a model for optimal bus stop spacing with high-resolution archived stop-level data, Transportation Research Record 2111(1): 24-32.

 

Li, R. 2004. Examining travel time variability using AVI data. In Proceedings of the Conference of Australian Institutes of Transport Research (CAITR), Melbourne, Victoria, Australia. No. 36. 16 p.

 

Ministry of Roads and Highways. 2019. Medium term expenditure framework (MTEF) for 2019 – 2022, programme-based budget estimates for 2019. Available from Internet: https://www.mofep.gov.gh/sites/default/files/pbb-estimates/2019/2019-PBB-MRH.pdf.

 

Obiri-Yeboah, A. A.; Amoah, A. S.; Gbeckor-Kove, M. S. 2020. Analysis of congestion on some road link sections using roadside friction in congestion index in Kumasi, International Journal for Traffic and Transport Engineering 10(1): 31-40.

 

Raheem, S. B.; Olawoore, W. A.; Olagunju, D. P.; Adeokun, E. M. 2015. The cause, effect and possible solution to traffic congestion on Nigeria road: a case study of Basorun-Akobo road, Oyo State, International Journal of Engineering Science Invention 4(9): 10-14.

 

Reilly, J. M. 1997. Transit service design and operation practices in Western European Countries, Transportation Research Record 1604(1): 3-8.

 

Rodrigue, J.P.; Notteboom, T. 2020. The Economic Importance of Transportation (Chapter 3) in: The Geography of Transport Systems, New York: Routledge, 456 p. ISBN 978-0-367-36463-2 Available from Internet: https://transportgeography.org/?page_id=5260.

 

Sankar, R.; Kavitha, J.; Karthi, S. 2003. Optimization of bus stop locations using GIS as a tool for Chennai city - A case study. In Map India Conference, Poster Session.

 

Schrank, D.; Eisele, B.; Lomax, T. 2012. TTI’s 2012 Urban Mobility Report. Texas A&M Transportation Institute, 68 p.

 

Styles, L.; Trigona, C. 2018. Ghana Road Network. Available from Internet: https://dlca.logcluster.org/display/public/DLCA/2.3+Ghana+Road+Network.

 

Sun, C.; Arr, G.; Ramachandran, R. P. 2003. Vehicle re-identification as method for deriving travel time and travel Time Distribution, Transportation Research Record 1826(1): 25-31.

 

Twerefou, D. K.; Chinowsky, P.; Adjei-Mantey, K.; Strzepek, N. L. 2015. The economic impact of climate change on road infrastructure in Ghana, Sustainability 7(9): 11949-11966.

 

van Nes, R.; Bovy, P.H. 2000. Importance of Objectives in Urban Transit-Network Design, Transportation Research Record 1735(1): 25-34.

 

Winston, C. 2013. On the performance of the U.S. Transportation System: Caution Ahead, Journal of Economic Literature 51(3): 773–824. doi:10.1257/jel.51.3.773.

 

Xu, X.; Chen, A.; Cheng, L. 2013. Assessing the effects of stochastic perception error under travel time variability, Transportation 40(3): 525–548.

 

Yesufu, T. K.; Otesile, R. O.; Ejidokun, T. O.; Ogunseye, A. A. 2019. Investigation and analysis of travel time variability of selected road intersection, International Journal for Traffic and Transport Engineering 9(4): 442 – 455.