Mode Choice Modeling of Work Trips: A Case of Hetauda Sub-Metropolitan City
Student: Swastika Bhattarai
Supervisor: Er. Rajesh Khadka
Submitted Date:
September, 2024
Abstract
Transportation planning is essential in modern society, particularly for urban areas facing
challenges such as traffic congestion during peak hours. Mode choice modeling is a crucial
component of transportation planning, as it allows planners to predict the behavior of
travelers and make informed decisions regarding transportation policies. This study focuses
on the work trips of commuters in Hetauda Sub-Metropolitan City, Nepal, and develops a
mode choice model to predict the utility of different transportation modes. Data for this
study were collected through Revealed Preference survey with questionnaire. The analysis
was conducted in mlogit package of RStudio software, employing a nested logit model to
evaluate the factors influencing mode choice.
Two-Wheeler is found to be most used mode of transport by working commuters. Gender,
age, marital status, occupation, monthly income, vehicle ownership, distance, travel cost
and travel time are determined to be significant variables using Chi-square test. Travel time,
travel cost, age, occupation, vehicle ownership and trip distance are statistically significant
variables on mode choice of Auto in relation to Two-Wheeler. Travel time, travel cost,
occupation, income and trip distance are statistically significant variables on mode choice
of Four-Wheeler in relation to Two-Wheeler. Similarly, travel time, travel cost, age, vehicle
ownership and trip distance are statistically significant variables on mode choice of Magic
Van in relation to Two-Wheeler. The result of inclusive value parameters showed that Public
mode nesting structure has high dissimilarity in comparison to Private mode. Most of the
working commuters depend on private mode for travel within city, so there is need for
policies that enhance the attractiveness of public modes to ensure effective and efficient
future urban transportation planning.
Keywords
Mode choice, Work trip, Revealed Preference, Nested logit model, RStudio