

The Analysis of Modal Choice Behavior of Commuters in Ibadan, Oyo State, Nigeria
Abstract
Increasing use of single or fewer occupant vehicles has increased traffic congestion and green gas emission, public transport as mass transit options are increasingly being encouraged amongst travelers to use as this is an influential strategy to improve the transport network performance. The aim of the study was to examine work trip modal choice and also to examine the relationship between modal choice and travel time of residents within Ibadan areas of Oyo State. The study used quantitative research design to obtain information from the respondents, multi-stage random sampling techniques were used to select the respondents. The data was collected through self-administered question. The findings of the study revealed that 66 percent of those who owned a motorized vehicle owned only one while those that own 2-3 motorized vehicles were 8 percent. It was also revealed that Ibadan city suffers from constant challenges of urban transportation such as delay in commuting from one place to other due to waiting time. Multiple regression method was used to determine the pattern of modal choice and travel time of commuters as it has a coefficient of determination (R2 ) value of 0.122 as well as F ratio of 5.041. The study recommended the government and transport policy workers in the state should develop and promote other means or mode of transport in the area.
References
Ackaah, W. (2016). Empirical Analysis of Real-time Traffic Information for Navigation and the Variable Speed Limit System (Doctoral dissertation, Universitätsbibliothek der Universität der Bundeswehr München).
Adeyinka, A. M. (2013). Assessment of the quality of urban transport services in Nigeria. Academic Journal of Interdisciplinary Studies, 2(1), 49-49.
Akpoghomeh, O. S. (2012). The terror of transport and the transportation of terror. inaugural Lecture series, 94.
Basorun, J. O., &Rotowa, O. O. (2012). Regional assessment of public transport operations in Nigerian cities: The case of Lagos island. International Journal of Developing Societies, 1(2), 82-87.
Ben-Akiva, M., & Morikawa, T. (1990). Estimation of travel demand models from multiple data sources. In International Symposium on Transportation and Traffic Theory, 11th, 1990, Yokohama, Japan.
Beuran, M., Gachassin, M., &Raballand, G. (2015). Are There Myths on Road Impact and Transport in Sub‐Saharan Africa?. Development Policy Review, 33(5), 673-700.
Bocarejo S, J. P., & Oviedo H, D. R. (2012). Transport accessibility and social inequities: a tool for identification of mobility needs and evaluation of transport investments. Journal of transport geography, 24, 142-154.
Fagnant, D. J., &Kockelman, K. (2015). Preparing a nation for autonomous vehicles: opportunities, barriers and policy recommendations. Transportation Research Part A: Policy and Practice, 77, 167-181.
Fezzi C, Bateman I.J, Ferrini S (2014). Using revealed preferences to estimate the value of travel time to recreation sites. Journal of Environmental Economics and Management, 67(1): 58-70.
Keuchel S, Richter C (2011). Applying integrated hierarchical information integration to mode choice modeling in public transport. Procedia-Social and Behavioral Sciences, 20: 875-884.
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