Volume List  / Volume 10 (3)

Article

ASSESSING THE INTEGRATION OF TRANSPORT SYSTEM: A TOTAL TRAVEL TIME APPROACH

DOI: 10.7708/ijtte.2020.10(3).03


10 / 3 / 286 - 295 Pages

Author(s)

Muhammad Haroon - Department of City & Regional Planning, University of Engineering and Technology, Lahore, Pakistan -

Amer Aziz - Department of City & Regional Planning, University of Engineering and Technology, Lahore, Pakistan -


Abstract

Total travel time from origin to destination determines convenience of public transport system because reliability of total travel time link with public transport. To better serve the needs of people and to decrease travel time, the flexible solutions for public transport system are growing. One such flexible solution is integration of transportation system. The focus of this research is to measure factors that contribute to total travel time. Six major road of Peshawar city are studied to collect data regarding access time, egress time, waiting at transit stop and walking time while mode shifting. Hypothetically significance measured of these four different times upon total travel time to assess transport integration system. The analysis shows that multi-modal public transport trips effect total travel time because, waiting and extra walking time exists in mode transfer. Access and egress times don’t have any positive significance with total travel time because access and egress times are considered part of travel time.


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References:

Ali, Z.; Shah, S.A.A.; Hussain, A. 2012. Growing Traffic in Peshawar: An Analysis of Causes and Impacts, A Research Journal of South Asian Studies 27(2): 409-420.

 

Alsnih, R.; Hensher, D.A. 2003. The Mobility and Acessibilitly Expectation of Seniors in an aging Polpulation, Sydney: Institute of Transport studies: The Australian Key Centre in Transport management.

 

Altares, P.S.; Copo, A.R.I.; Gabuyo, Y.A.; Laddaran, A.T.; Mejia, L.D.P.; Policarpio, I.A.; Sy Eag, T.H; Yao, A. 2003. Elementary statistics: a modern approach. Manila, Philippines: Rex, 18.

 

Aziz, A.; Nawaz, M.S.; Nadeem, M.; Afzal, L. 2018. Examining suitability of the integrated public transport system: A case study of Lahore, Transportation Research Part A: Policy and Practice 117: 13-25.

 

Bovy, P.; Jansen, G. 1979. Travel times for disaggregate travel demand modelling: a discussion and a new travel time model. New developments in modelling travel demand and urban systems, Saxon House, England, 129-158.

 

Brand, J.C. 2015. Assessing integration of bus network with non-motorized Acess and Egress modalitiis, Amstelland-Meerlanden: Delft University of Technology.

 

Brand, J.C. 2015. Assessing Integration of Bus Networks with Non-Motorised Access and Egress Modalities; case study Bus Network Integration with Access and Egress Modalities in Amstelland, Amstel land: Delft University of Technology.

 

Brand, J.; Hoogendoorn, S.; Oort, N.V; Schalkwijk, B. 2017. Modelling multimodal transit networks integration of bus networks with walking and cycling, Amsterdam, IEEE.

 

Brownstone, D.; Small, K.A. 2005. Valuing time and reliability: assessing the evidence from road pricing demonstrations, Transportation Research Part A: Policy and Practice 39(4): 279-293.

 

Chowdhury, S.; Ceder, A.; Sachdeva, R. 2014. The effects of planned and unplanned transfers on public transport users' perception of transfer routes, Transportation Planning and Technology 37(2): 154-168.

 

Cohen, B.M. 2006. Urbanization in developing countries: Current trends, future projections, and key challenges for sustainability, Technology in society 28(1-2): 63-80.

 

Douglas, N.J.J.M. 2013. Estimating transfer penalties and standardised income values of time by stated preference survey. Australian transport research forum, Australia.

 

Fan, Y.; Guthrie, A.; Levinson, D. 2016. Waiting time perceptions at transit stops and stations: Effects of basic amenities, gender, and security, Transportation Research Part A: Policy and Practice 88: 251-264.

 

Garcia-Martinez, A.; Cascajo, R.; Jara-Diaz, S.R.; Chowdhury, S.; Monzon, A. 2018. Transfer penalties in multimodal public transport networks, Transportation Research Part A: Policy and Practice 114: 52-66.

 

Givoni, M.; Banister, D. 2010. Integrated Transport: from policy to practice, Oxford: Routledge.

 

Government of ACT. 2015. Building the integrated transport network. Canberra: Winton Sustainable Consultants.

 

Guo, Z. 2003. Assessment of the transfer penalty to transit trips in Downtown Boston: a GIS-based disaggregate modeling approach, Doctoral dissertation, Massachusetts Institute of Technology, USA.

 

Habitat, U.N. 2015. International guidelines on urban and territorial planning. United Nations Human Settlements Programme, Nairobi.

 

Henderson, V. 2002. Urbanization in Developing Countries, The World Bank Research Observer 17(1): 89-112.

 

Khan, A; Arshad, M.A. 2015. Study of Various Mass Transit Options for Peshawar City by Life Cycle Cost Analysis, In Proceedings of the 1st International Multi-Disciplinary Conference (IMDC), The University of Lahore , Gujrat Campus, PK, 23-24 November, 4p.

 

Khan, A.; Ali, M. 2019. Impact of Built environment on groundwater depletion in Peshawar, Pakistan, Journal of Himalayan Earth Science 52(1): 86-105.

 

Kok, A.; Hans, E.; Schutten, J. 2012. Vehicle routing under time-dependent travel times: the impact of congestion avoidance, Computers & operations research 39(5): 910-918.

 

Krygsman, S.; Dijst, M.; Arentze, T. 2004. Multimodal public transport: an analysis of travel time elements and the interconnectivity ratio, Transport Policy 11: 265-275.

 

Levinson, D.M.; Kumar, A. 1997. Density and the journey to work, Growth and change 28(2): 147-172.

 

Lint, J.V.; Zuylen, H.J.V.; Tu, H. 2008. Travel time unreliability on freeways: Why measures based on variance tell only half the story, Transportation Research Part A: Policy and Practice 42(1): 258-277.

 

Lo, H.K.; Luo, X.; Siu, B.W. 2006. Degradable transport network: Travel time budget of travelers with heterogeneous risk aversion, Transportation Research Part B: Methodological 40(9):792-806.

 

Montgomery, D.C.; Peck, E.A.; Vining, G.G. 2012. Introduction to linear regression analysis. Fourth ed., Vol. 821. John Wiley & Sons.

 

Navarette, F.J.; Ortuzar, J. 2013. Subective valuation of the transit transfer experience: the case of Santiago de Chile, Transport Policy 25: 138-147.

 

NEA; OGM; TSU. 2003. Integration and Regulatory Structures in Public Transport, Brussels: DGTREN.

 

Ortuzar, J.; Willumsen, L. 2002. Modelling transport. Third ed. West Sussex, England: Wiley.

 

Peer, S.; Koopsmans, C.C.; Verhoef, E.T. 2012. Prediction of travel time variability for cost-benefit analysis, Transportation Research Part A: Policy and Practice 46: 79–90.

 

Rietveld, P. 2000. The accessibility of railway stations: the role of the bicycle in The Netherlands, Transportation Research Part D: Transport and Environment 5(1): 71-75.

 

Steiger, J.H.; Shapiro, A.; Browne, M.W. 1985. On the multivariate asymptotic distribution of sequential chi-square statistics, Psychometrika 50(3): 253-263.

 

Sweet, M.N.; Chen, M. 2011. Does regional travel time unreliability influence mode choice?, Transportation 38(4): 625-642.

 

The Central Transportation Planning Staff. 1997. Transfer penalties in urban mode choice modeling. TMIP. United State: US Department of Transportation.

 

Van Nes, R. 2002. Design of multimodal transport networks: A hierarchical approach, Netherland: DUP Science.

 

Wen, W. 2008. A dynamic and automatic traffic light control expert system for solving the road congestion problem, Expert Systems with Applications 34(4): 2370–2381.

 

Wu, N.; Geistefeldt, J. 2014. Standard Deviation of Travel Time in a Freeway Network-A Mathematical Quantifying Tool for Reliability Analysis. In CICTP 2014: Safe, Smart, and Sustainable Multimodal Transportation Systems, 3292-3303.

 

Yeung, T. 2004. Editorial to using IT tools to improve service, Public Transportation International 53(6): 2-3.