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Keywords: Work ; journey ; pattern ; Warri
The Texas Transportation Institute studied 68 cities in the United States of America and observed that congestion cost in these cities amounted to 92 billion dollars. Similarly, in Britain, drivers lose about 1.5 billion man-hours a year to traffic congestion.
According to Ogunsanya (2002) in Nigeria, many cities experience alarming traffic problems. These problems range from road congestion which has reached crisis level in large cities, to the absence of or very poor system of public transport in smaller but fast growing towns. The issue of journey to work is one that is common in both developed and developing countries. In Warri metropolis, the increasing intensity of land use has given rise to an increased traffic flow constituted by large number of workers and their automobiles.
Pooley and Turnbull (2001) examined changing attitudes to different modes based on a survey of 1834 individuals. They demonstrate that in general, the reasons why men and women choose one mode of transport have been consistent overtime. To the policy makers, their papers suggests that once a particular mode of transport becomes established people are often reluctant to change.
Adidjaja et al. (1999) analysed change in journey to work patterns in the tri-state metropolitan regions (New York, New Jersey, and Connecticut). Between 1980 and 1990, journey to work in these regions increased by 13 percent from 1960 to 1990. The regions indicates that trips by drive alone mode increased by 35 percent, while nationally, trips by drive alone increased by 35 percent. They believe that possible reason is a combination of facts including an increased in the number of dual income families, increase participation of women in labour force and decentralized development patterns.
Kingham et. al.(2001) examined commuters perception of their mode choice during journey to work based on surveys administered at two large companies in U.K. The result of the survey indicate that 97% and 88% of staff at the respective companies travel to work by car, while only 2% and 7% of respondents cycled to work. Although only 0% and 3% currently use public transport for the journey to work, they express their willingness to shift to public transport if services are improved.
De Palma and Rochat (2000), investigate the mode choice for trips in the city of Geneva by means of a nested logic approach. They focus on the joint nature of
the decision of how many cars to own in the household and the precision to use the car for the trip to work. Their findings suggest that travel time and travel cost play a key role in mode split choice between car and transit.
Blumenberg and Waller (2003) studied some cities with transit service and noticed that transit travel time on average, far exceed auto travel time because of walking to and from stops, waits at vehicle stops along the way.
Lekan (1999), looked at the causes of traffic congestion in Lagos State and traced the causes in the metropolis to complete disregard of traffic rules and regulations, impatient driving and pedestrian abuse of roadways. Adedimila (1977), studied the ways to improve traffic flow in Lagos metropolitan area, he emphasized the extension of rail-lines to the Lagos Island and construction of more dual carriage ways. Meanwhile, Onokala (1976), in her own journey to work in Edmonton, Canada has investigated the relationship between residential locations on place of work in Edmonton. She also noticed that parking cost at destination is not a strong deterrent to worktrip making to major employment centers in the city. She added that
a transit system adequate to deal with worktrips will have more than enough capacity to deal with shopping, business, social and recreational trips.
Car ownership modeling has received considerable attention in the travel demand analysis literature because of the important role it plays in the overall transportation and land use planning process. It is now well recognized that car ownership is one of the key determinants of the activity – travel behaviour of individuals and households.
Finally, although mode characteristics are less relevant in this part of the analysis, the author decided to keep the variable “travel time” in the set of explanatory variables to represent the notion of distance in a broader sense. Not only this variable closely related to the physical distance from home to work but it also encompasses the performance of the network.
i. The gravity model was used to determine relationship or the interaction between places of the residence in the study area – Warri and Environs. However, the two basic factors considered here are population and distance between the residential zones. This is in line with finding out how distance affects the volume of work trips. Algebraically, the model is written as
……………..…………………… Equation (I)
r = n∑XY – (∑X)( ∑Y) i
iii. The multiple correlation is used to complete the combined effects of these measures of spatial separation on work trip. The multiple correlation coefficient technique is written as;
Results and Discussions
Table 1: The Gravity Model Calculation
Source: Field survey
This procedure applies to all the 6 zones.
It can be deduced that traffic flow in any zone is neither sequal with the size of the zone nor with the total length of roads in that zone. Zone 9, the second largest zone offer zone 1 with 0.52km2 and 0.86km2 in area respectively has network density than the largest zone 1 which attracts 10,689 or 11.35% of the total traffic in all the zones with one of the smallest zones (see Table 2).
Table 2: Traffic Volume Analysis Via the Road Network Density of Each of the Ten (10) Traffic Zones in Warri and Environs.
Total area of zones = 12.82km2
Total volume of traffic trough zone = 94,168
This was calculated for all the ten (10) zones.
Having said this much, it was observed that the degree of association between the volume of trip generated and the travel distance using the correlation statistics was -0.80 which carries a negative value indicating an inverse relationship between two variables tested. What this result implies is that so long as travel distance increases the volume of worktrips equally reduces.
Time was also taken to check for the significance of the correlation coefficient between the volume of worktrips generated in relation to travel cost. It was also observed that an inverse relationship was recorded accounting for a value of -0.79. The argument here is that both volume of worktrips in these residential zones and the transportation cost to work places will continue to go in opposite directions indicating that as long as transport cost increases, there will always be a decrease on the number of work trips with respect to such residential
zones as the case may be. Again where travel cost of individual worktrip is allowed to influence the travel distance, it was seen that the direction of influences is positive, with a magnitude of 0.94 and coefficient determination (r2) of 88.36%. In other words, travel cost explains 88.34% of the decisions made by work tripmakers into Warri metropolis, leaving only 11.64% to be explained by other factors.
However, when the combined influence of these variables on work journeys into Warri and environs is sought for, the multiple correlation revealed that the multiple effect of the variables R is 0.82 (See Appendix A). In other words, they can together only define 82% of the behaviour of working journeys into Warri metropolis. This means that only 18% is left undefined and is thus under the determination of other factors which may include trip-makers economic status’, some may find other means of getting to work in Warri and environs etc.
Policy Implications and Conclusions
Adidjaja, C. (1999) “Analysis and Comparison between 1980 and 1990 Journey to work data”. New York Metropolis Transportation Council.
Atubi, A.O. and Onokala, P.C. (2004b) “The Accessibility of Centres to the Road Networks: The Case of Lagos Island, Lagos, Nigeria, International Journal of Ecology and Environmental Dynamics. Vol.2, pp. 140 – 151.
Atubi, A.O. and Onokala, P.C. (2005) “The Effects of Traffic Congestion on Road Accidents in the Niger-Delta: The Case of Warri Metropolis, ” Journal of Nigerian Academic Forum Vol.9, No.5.
De Palma, A. and Rochat, D. (2000) “Mode Choices for Trips to Work in General: An empirical Analysis Journal of Transport Geography Vol.8. pp. 43 – 51.
Kim, Y.T. and Heo, E. (2003) Bayesian Estimation of Multinomial probit models of work trip choice”. Transportation 30: 351 – 365.
Kingham, S.J.; Dickson, S. and Copsey, C. (2001) “Travelling to Work: will people move out of their cars”, Transport Policy, 8: 151 – 160.
Lekan, E. (1999) “Socio-demographics, activity participation and travel Behaviour, Transportation Research 33 (1): 1 – 18.
Myers, K. and Mauch, M. (2002) “Public Transportation and Work-trip length” Traffic quarterly, 44 (6) 508 – 515.
Ogunsanya, A.A. (2002) “Issues and Problems in Nigerian Transport System”, The Trainer. Journal of the Nigerian Institute of Transport Technology, Vol. 1, No. 1, pp. 4 – 10.
Onokala, P. C. (1976) “Journey to Work Patterns in Edmonton, Canada”. Unpublished M.Sc. Thesis, University of Alberta, Canada.
Pooley, C. and Turnbull, J. (2001) “Modal Choice and Modal Change: The Journey to Work in Britain since 1890”, Journal of Transport Geography 8(1) 11 – 24.