ABSTRACT
The use of logit models for predicting mode-choice decisions for travels has gained in recent years.
The prime advantage of this lies in its to allocate travel demand among many modes at the same time, as opposed to the traditional binary mode-choice models developed in the early sixties.
Journey to work is vital in any aspect of land use and transport planning. Transport remains a vital component of the urban economy that enables the populace to move freely between their homes and place of work. This study examines the factors that influence modes of travel of civil servants in Minna.
administrations are used in establishing the modes of travel and factors influencing them were evaluated. The survey results showed that a large split of the workers (25.4%) use taxis as the dominant mode of transport to work.
Statistical regression analysis using SPSS was used to derive the utility function and a multinomial logit model was used to calculate the probability of occurrence of each particular model.
TABLE OF CONTENTS
Title page i
Dedication ii
Declaration iii
Certification iv
Acknowledgements v
Abstrac vi
Table of contents vii
List of Tables viii
List of Figures ix
List of Appendices X
Chapter One: Introduction
- Background 1
- Types of Modal Split Models 3
- Aim and Objectives 4
- Justification for the Study 4
- Scope of study 6
- Description of the Study Area 7
Chapter Two: Literature Review
- Mode choice 10
- Factors influencing the choice of Mode 11
- Factors Affecting Mode choice Decision 12
- Theoretical Development in Mode choice Models 16
- Transport policies and mode choice decision 16
- Urban Travel Patterns 17
- Approaches and Strategies use in planning for a journey to work 20
- Factors Affecting the Attractiveness of Transportation Mode 22
- Cost 22
- Speed and Reliability 23
- Factors that Affect Journey to Work 24
- Transport Cost and Residential Location 24
- Modal choice 26
- Socio–Economic Status of Workers 27
- Survey Area 28
- Selection of Variables 28
- Discrete Choice Models 30
- Multinomial Logit Models (MNL) 31
Chapter Three: Methodology
- Survey Design 33
- Derivation of Multinomial Logit Model 33
- Modelling the Logit 36
- Modelling the Probabilities 37
- Statistical Package for the Social Science (SPSS) 38
- Utility Function 38
Chapter Four: Results and Discussion
- Sample Size and Response Rate 39
- Cross Tabulation Results in 42
- The influence of Personal income on Mode choice 42
- Influence of Workers position in Household on Mode Choice 48
- Influence of Travel Time on Mode Choice 50
- Effect of Home Location on Travel Mode 56
- Regression Analysis using SPSS 57
Chapter Five: Conclusion and Recommendations
- Conclusion 60
- Recommendation 60
References 61
Appendix 64
INTRODUCTION
1.1 Background
Modal split can be defined as the proportionate division of the total number of person trips between different modes of travel. The modal split model predicts how people choose different modes of travel for different trip purposes.
Built environment influence the utility of travel both directly and indirectly but the utility gains are different for a different group of travellers, for different trip purposes and different modes (Reilly and Landis, 2003). A widely adopted approach for modal split analysis is the logit model (Ben- Akiva and Lerman, 1985).
A recent experiment using logit models /spatial interaction models in order to map out the freight transport in Europe has been carried out by Tavasszy (1999), who showed the sustainability of logit models also for the goods transport sector.
Transportation modes include walking, bicycling, transit, and using a vehicle (either as a driver or passenger). Modal split can be expressed numerically as a fraction, ratio or percentage of the total number of trips.
Many different procedures have been developed to derive this split in the transportation planning process, all based on the assumptions that, of a given total travel demand the proportion carried by bus, tube, surface railway or private motor car will depend on the standing of each mode of transport in relation to its competitors.
REFERENCES
Alhassan, D. (1995): A Functional Transportation Plan for Effective Work Trip in Kaduna Metropolis: An unpublished M.Sc thesis, Ahmadu Bello University, Zaria.
Banister, D and Hall, P. (1981): Transport and Public Policy Planning: Mansell, London.
Beesley, M. E and Malvi, M. Q. (1977): Spatial Equilibrium and Journey to Work: Journal of Transport Economics.
Ben-Akiva, M. and Martin, G. R, (1976): Disaggregate Multinomial Model for Work Trips in Netherlands-Transport Research Record No.569
Ben-Akiva, M. and Lerman, S. R, (1985): Discrete Choice Analysis: Theory and Application to Travel Demand, MIT Press, and Cambridge Massachusetts
Black, J. (1981): Urban Transport Planning, Theory and Practice. London, Crom Holon. Carol, T. D (1952): The relationship of home to workplaces and the spatial pattern of cities- Social forces, vol. 30, pp271-282
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