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Article

QUEUE DISCHARGE HEADWAY: CHARACTERISTICS, DISTRIBUTIONS AND EFFECTS ON SATURATION FLOW RATES AT SELECTED SIGNALIZED INTERSECTIONS IN LAGOS

DOI: 10.7708/ijtte2022.12(1).09


12 / 1 / 123 - 139 Pages

Author(s)

Olanrewaju Akinfala - Department of Geography, University of Lagos, Lagos, Nigeria -

Folorunso Ogunwolu - Department of Systems Engineering, University of Lagos, Lagos, Nigeria -

Emmanuel Ege - Department of Geography, University of Lagos, Lagos, Nigeria -

Shakirudeen Odunuga - Department of Geography, University of Lagos, Lagos, Nigeria -


Abstract

Saturation flow rate (SFR) and headway are highly localized essential parameters for accurate and effective performance analysis and optimization of signalized intersections. This study examined the saturation flow rate (SFR) and characterized headways at eight signalized intersection approaches, six of which were ideal while two were typical approaches of Lagos conditions. Over 700 cycle to cycle headway data was collected and analyses such as Fuzzy level 1; statistical tests such as Wilcoxon-Signed rank, Mann-Whitney and Shapiro-Wilks tests were performed on the observed headways. The average SFR observed for ideal approaches was 1,927 veh/hr/lane which is higher than values observed in many developed countries, while at typical approaches, it was 1,342 veh/hr/lane. Statistically, SFR differed significantly during peak and off-peak periods (230 veh/hr/lane) and at ideal and typical approaches (between 460-750 veh/hr/lane). Across all traffic conditions observed, the Burr group of distributions were the overall best fit for modelling headways. A fuzzy-based SFR of 1,789 veh/hr/lane was proposed. This study shows that indeed, headway and SFR differ considerably spatiotemporally. Therefore, appropriate SFR and headway values which reflect actual operating conditions must be adopted to ensure optimal operational performance at signalized intersections.


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References:

Akcelik, R. 1998. Traffic Signals: Capacity and Timing Analysis. 123. Vermont South, Victoria, Australia: Australian Roads Research Board (ARRB), Seventh reprint, 108p.

 

Agent, K.R.; Crabtree, J.D. 1982. Analysis of saturation flow at signalized intersections. UKTRP-82-8. Frankfort: Kentucky Transportation Center, 43p.

 

Angel, A.; Hickman, M. 2003. A Method for Analyzing the Performance of Signalized Intersection from Airborne Imagery’, in. Transportation Research Board 82nd Annual Meeting, Washington, D.C. 20p.

 

Alex, S.; Isaac, K.P. 2014. Traffic simulation model and its application for estimating saturation flow at signalized intersection, International Journal for Traffic and Transport Engineering, 4(3): 320–338. doi:http://dx.doi.org/10.7708/ijtte.2014.4(3).06.

 

Alhassan, H.M.; Ben-Edigbe, J. 2011. Effect of Rain On Probability Distributions Fitted to Vehicle Time Headways, International Journal on Advanced Science Engineering and Information Technology, 2(2): 31–37. doi:10.18517/ijaseit.2.2.173.

 

Arhin, S. et al. 2016. Prevailing saturation flow rates for lane groups in urban areas, International Journal for Traffic and Transport Engineering, 6(2): 231–242. doi:http://dx.doi.org/10.7708/ijtte.2016.6(2).10.

 

Aydin, M.M.; Topal, A. 2019. Effects Of Pavement Surface Deformations On Traffic Flow, Transport, 34(2): 204–214. doi:https://doi.org/10.3846/transport.2019.8631.

 

Bara, W.A.; Ahmad, H.A.; Mohamad, S.A. 2021. Investigation of saturation flow rate using video camera at signalized intersections in Jordan, De Gruyter Open Eng, 11(1):216–226. doi:https://doi.org/10.1515/eng-2021-0021.

 

Ben-Edigbe, J.; Ferguson, N. 2005. Extent of capacity loss resulting from pavement distress, Proceedings of the Institution of Civil Engineers – Transport, 158(1): 27–32. doi:https://doi.org/10.1680/tran.2005.158.1.27.

 

Ben-Edigbe, J.E.; Ferguson, N.S. 2009. Qualitative road service reduction resulting from pavement distress, in. WIT International Conference on Urban Transport, Bologna.

 

Bonneson, J. et al. 2005. Guidelines for quantifying the influence of area type and other factors on saturation flow rates. Research Report PR9385-V2. Tallahassee, USA: Florida Department of Transport, 88p.

 

Chodur, J.; Ostrowski, J.; Tracz, M. 2011. Impact of saturation flow changes on performance of traffic lanes at signalized intersections, Procedia Social and Behavioural Sciences, 16(6): 600–611. doi:https://doi.org/10.1016/j.sbspro.2011.04.480.

 

Economic Intelligence Unit (EIU). 2013. The Socio-economic Costs of Traffic Congestion in Lagos. Working Paper Series No 2. Lagos: Ministry of Economic Planning & Budget, Lagos State, 14p. Available at: http://mepb.lagosstate.gov.ng/wp-content/uploads/sites/29/2017/01/EIU-Working-Paper-2-Draft-2-Traffic-Congestion.pdf.

 

Filani, M.O. 2012. The Changing Face of Lagos: From Vision to Reform and Transformation. Brussels, Belgium: Cities Alliance: Cities Without Slums, 44p. Available at: https://www.citiesalliance.org/sites/default/files/Lagos-reform-report-lowres.pdf (Accessed: 18 February 2021).

 

Fornalchyk, Y.; Mohyhla, I.; Hilevych, V. 2013. Saturation flow volume as a function of intersection passing speed, Transport problems, 8(3): 43–52.

 

Ghasemlou, K. et al. 2012. Effect of Dwell Time on Performance of Signalized Intersections , in. 10th International Congress on Advances in Civil Engineering, Ankara, Turkey. 1–10.

 

Ghasemlou, K.; Aydin, M.M.; Yildrim, M.S. 2016. An Investigation of Lane Blockage Effects at Signalized Intersections, International Journal for Traffic and Transport Engineering, 6(3): 289–302. doi:10.7708/ijtte.2016.6(3).05.

 

Greenshields, B.D.; Schapiro, D.; Ericksen, E.L. 1947 Traffic Performance at Urban Street Intersections. Technical Report 1. Yale Bureau of Highway Traffic, Eno Foundation for Highway Traffic Control. 23–30.

 

Highway Capacity Manual. 2010. Fifth edition. Washington, D.C: Transportation Research Board.

 

Jin, X. et al. 2009. Departure headways at signalized intersections: A log-normal distribution model approach, Transportation Research Part C: emerging technologies, 17:318–327. doi:10.1016/j.trc.2009.01.003.

 

Koonce, P. et al. 2008. Traffic Signal Timing Manual. FHWA-HOP-08-024. U.S. Department of Transportation- Federal Highway Administration, 265p. Available at: https://nacto.org/docs/usdg/signal_timing_manual_fhwa.pdf (Accessed: 19 April 2016).

 

Kulakarni, R. et al. 2020. Estimation of Saturation Flow at Signalized Intersections Under Heterogeneous Traffic Conditions, In Transportation Research, Lecture Notes in Civil Engineering, 45: 591–605. doi:https://doi.ord/10.1007/978-981-32-9042-6_47.

 

Lagos Bureau of Statistics. 2016. Abstract of Local Government Statistics. Lagos State: Ministry of Economic Planning and Budget, 94p.

 

Lagos State Ministry of Transport. 2019. Signalized Intersections in Lagos State. Unpublished Internal Report. LAMATA. 2021. Available at: https://lamata.lagosstate.gov.ng/ (Accessed: 18 February 2021).

 

LASG. 2019. Available at: https://lagosstate.gov.ng/blog/2019/08/29/transport-commissioner-says-over-1-6m-vehicles-ply-lagos- roads-daily/ (Accessed: 18 February 2021).

 

Majeed, A.A. et al. 2014. Field-based saturation headway model for planning level applications, International Journal of Traffic and Transportation Engineering, 3(5): 207–215. doi:10.5923/j.ijtte.20140305.01.

 

Manikandan, S. 2011. Measures of central tendency: Median and mode, J Pharmacol Pharmacother, 2(3): 214–215. doi:10.4103/0976-500X.83300.

 

NCSS Statistical Software. 2020. ‘Normality Tests’. Available at: https://pdf4pro.com/view/chapter-194-normality-tests-ncss-5b7449.html (Accessed: 12 May 2020).

 

Oni, S.I. et al. 2008. A Daily Flow Profile of Traffic in an Urban Traffic Corridor: The Nigerian Experience, Indus Journal of Management & Social Sciences, 2(2):99–109.

 

Ranasinghe, W.; Bunker, V.; Bhaskar, A. 2017. Saturation headway variation at a signalized intersection approaches with a downstream bus stop and bicycle lane, in. Australian Transport Research Forum Proceedings, Auckland.

 

Sedgwick, P. 2010. Skewed distributions, BMJ [Preprint], (341). doi:https://doi.org/10.1136/bmj.c6276.

 

Shang, H.; Zhang, Y.; Fan, L. 2014. Heterogeneous lanes’ saturation flow rates at signalized intersections, Procedia Social and Behavioural Sciences, 138, pp. 3–10. doi:10.1016/j.sbspro.2014.07.175.

 

Shao, C.; Liu, X. 2012. Estimation of saturation flow rates at signalized intersections, Discrete Dynamics in Nature and Society, 9 p. doi:https://doi.org/10.1155/2012/720474.

 

Stokes, R. W. 1988. Comparison of Saturation flow rates at signalized intersections, IΤΕ journal, Institute of Transportation Engineers, 58(11):15–20.

 

Turner, J.; Harahap, G. 1993. Simplified saturation flow data collection methods. Research Report PA1292/93. Crowthorne: Transport Research Laboratory, 12p.

 

Wang, Y. et al. 2020. An Analysis of the Interactions between Adjustment Factors of Saturation Flow Rates at Signalized Intersections, Sustainability, 12(2): 665. doi:10.3390/su12020665.

 

Webster, F.V. 1958. Traffic Signal Settings. Road Research Technical Report No.39. Her Majesty’s Stationery Office, London, England: Road Research Laboratory, 45p.

 

Webster, F.V.; Cobbe, B.M. 1966. Traffic Signals. Road Research Technical Report No. 56. Her Majesty’s Stationery Office, London, England: Road Research Laboratory, 111p.

 

Willemsen, J. et al. 2008. The Dula Dangerous Driving Index: An Investigation of Reliability and Validity across Cultures, Accid Anal Prev, 40(2): 798–806. doi:10.1016/j.aap.2007.09.019.

 

Zhao, Y. et al. 2015. Estimation of saturation flow rate and start-up lost time for signal timing based on headway distribution, Discrete Dynamics in Nature and Society, 7p. doi:https://doi.org/10.1155/2015/304823.