Multivariate School Travel Demand Regression Based on Trip Attraction
Since primary school trips usually start from home,
attention by many scholars have been focused on the home end for
data gathering. Thereafter category analysis has often been relied
upon when predicting school travel demands. In this paper, school
end was relied on for data gathering and multivariate regression for
future travel demand prediction. 9859 pupils were surveyed by way
of questionnaires at 21 primary schools. The town was divided into 5
zones. The study was carried out in Skudai Town, Malaysia. Based
on the hypothesis that the number of primary school trip ends are
expected to be the same because school trips are fixed, the choice of
trip end would have inconsequential effect on the outcome. The
study compared empirical data for home and school trip end
productions and attractions. Variance from both data results was
insignificant, although some claims from home based family survey
were found to be grossly exaggerated. Data from the school trip ends
was relied on for travel demand prediction because of its
completeness. Accessibility, trip attraction and trip production were
then related to school trip rates under daylight and dry weather
conditions. The paper concluded that, accessibility is an important
parameter when predicting demand for future school trip rates.
[1] Barber, G. (1995). Aggregate Characteristics of Urban Travel, in The
Geography of Urban Transportation, edited by Susan Hanson, The
Guilford Press, New York.
[2] Hobbs, F. D. (1979). Traffic Planning and Engineering, Pergamon Press
Ltd, Oxford, England
[3] Meyer, J. R. (1974). The Future and Implications for Regional
Transportation Planning Perspectives on Regional Transportation
Planning edited by DeSalvo, J. S., Lexington Books.
[4] Muller, P. O. (1995). Transportation and Urban Form: Stages in the
Spatial Evolution of the American Metropolises. IThe Geography of
Urban Transportation edited by Susan Hanson, The Guilford Press,
New York.
[5] Buton, M. J. (1986). Introduction to Transportation Planning,
Hutchinson, London
[6] Ben-Edigbe J. ÔÇÿAssessment of Speed, Flow & Density Functions under
Adverse Pavement Conditions- International Journal of Sustainable
Development and Planning ISSN: 1743-7601- Volume 5, Issue 3 August
2010
[1] Barber, G. (1995). Aggregate Characteristics of Urban Travel, in The
Geography of Urban Transportation, edited by Susan Hanson, The
Guilford Press, New York.
[2] Hobbs, F. D. (1979). Traffic Planning and Engineering, Pergamon Press
Ltd, Oxford, England
[3] Meyer, J. R. (1974). The Future and Implications for Regional
Transportation Planning Perspectives on Regional Transportation
Planning edited by DeSalvo, J. S., Lexington Books.
[4] Muller, P. O. (1995). Transportation and Urban Form: Stages in the
Spatial Evolution of the American Metropolises. IThe Geography of
Urban Transportation edited by Susan Hanson, The Guilford Press,
New York.
[5] Buton, M. J. (1986). Introduction to Transportation Planning,
Hutchinson, London
[6] Ben-Edigbe J. ÔÇÿAssessment of Speed, Flow & Density Functions under
Adverse Pavement Conditions- International Journal of Sustainable
Development and Planning ISSN: 1743-7601- Volume 5, Issue 3 August
2010
@article{"International Journal of Business, Human and Social Sciences:55515", author = "Ben-Edigbe J and RahmanR", title = "Multivariate School Travel Demand Regression Based on Trip Attraction", abstract = "Since primary school trips usually start from home,
attention by many scholars have been focused on the home end for
data gathering. Thereafter category analysis has often been relied
upon when predicting school travel demands. In this paper, school
end was relied on for data gathering and multivariate regression for
future travel demand prediction. 9859 pupils were surveyed by way
of questionnaires at 21 primary schools. The town was divided into 5
zones. The study was carried out in Skudai Town, Malaysia. Based
on the hypothesis that the number of primary school trip ends are
expected to be the same because school trips are fixed, the choice of
trip end would have inconsequential effect on the outcome. The
study compared empirical data for home and school trip end
productions and attractions. Variance from both data results was
insignificant, although some claims from home based family survey
were found to be grossly exaggerated. Data from the school trip ends
was relied on for travel demand prediction because of its
completeness. Accessibility, trip attraction and trip production were
then related to school trip rates under daylight and dry weather
conditions. The paper concluded that, accessibility is an important
parameter when predicting demand for future school trip rates.", keywords = "Trip generation, regression analysis, multiple linearregressions", volume = "4", number = "6", pages = "906-5", }