Encouraging Public Transport Use to Reduce Traffic Congestion and Air Pollutant: A Case Study of Ho Chi Minh City, Vietnam

Traffic congestion and transportation-related environmental pollution are identified as the severe problems in many countries all over the world, especially in the developing countries, and Vietnam is also not an exception. In the context of Ho Chi Minh City, the biggest city located in Southern Vietnam, millions of students and employees annually immigrate there to live, work and study; therefore, encouraging them to use bus service to reduce pressure on urban environment and traffic and transport is significant. The goal of this study was to recognize the behaviour of mode choice among students and employees using disaggregate model. To achieve this goal, binary logit model was used under disaggregate choice method. The findings indicated that, for students, ‘Gender’, ‘Motorcycle ownership’, ‘Travel time’, ‘Travel distance’, ‘Migrant status’, ‘Convenience’, ‘Safety’, and ‘Awareness’ affected their mode choices; for employees, ‘Married’, ‘Income’, ‘Children’, ‘House ownership’, ‘Motorcycle ownership’, ‘Migrant status’, ‘Travel cost’, ‘Travel distance’, ‘Convenience’, ‘Safety’, ‘Awareness’, and ‘Social norms’ played vital roles in their choices of means of transport. Besides, although motorcycle was the premier transport mode for both employees and students every day, they showed their perceptions of the negative sides of motorcycle to environment and community, and also expressed their willingness to switch to travel by bus if public transportation infrastructure and quality were upgraded.

[1]  Mark W Burris,et al.  Examination of Student Travel Mode Choice , 2007 .

[2]  S. Schwartz Normative Influences on Altruism , 1977 .

[3]  Jiangping Zhou,et al.  Sustainable commute in a car-dominant city: Factors affecting alternative mode choices among university students , 2012 .

[4]  Christian A. Klöckner,et al.  A multi-level approach to travel mode choice – How person characteristics and situation specific aspects determine car use in a student sample , 2011 .

[5]  Jeffrey Brown,et al.  Waiting for the Bus , 2004 .

[6]  Patricia L. Mokhtarian,et al.  What Affects Commute Mode Choice: Neighborhood Physical Structure or Preferences Toward Neighborhoods? , 2005 .

[7]  Chandra R. Bhat,et al.  A generalized multiple durations proportional hazard model with an application to activity behavior during the evening work-to-home commute , 1996 .

[8]  Riza Atiq Abdullah O.K. Rahmat,et al.  Modeling of Intercity Travel Mode Choice Behavior for Non-Business Trips within Libya , 2014 .

[9]  Banihan Gunay,et al.  Using GIS to visualise and evaluate student travel behaviour , 2011 .

[11]  Max Bulsara,et al.  Active commuting in a university setting: Assessing commuting habits and potential for modal change , 2006 .

[12]  Sofia Martin-Puerta,et al.  Commuting mode choice: Motivational determinants and road users profile , 2014 .

[13]  Xueming Chen,et al.  Statistical and activity-based modeling of university student travel behavior , 2012 .

[14]  Lee Schipper,et al.  Energy trends in the Japanese transportation sector , 1996 .

[15]  Moshe Ben-Akiva,et al.  Discrete Choice Analysis: Theory and Application to Travel Demand , 1985 .