Modal shift behavior of car users to light rail transit, some evidence from the field

Abstract

Growing population and car dependency in developing countries have led to congestion that adversely affects the environment, travel time, trip cost, accidents, and public transportation reliability. Through implementation of travel demand management (TDM) policies, governments and policymakers aim to reduce private vehicle dependency and encourage people to use public transportation. Light rail transit is an important part of an attractive public transport. Rail transportation systems, though offer many potential benefits, are a major financial challenge for governments because of the high capital and operation costs. Therefore, passenger behavior must be determined before a new system is introduced. Using a stated preference (SP) questionnaire, private car users' behavior in Tehran's universities has been investigated to determine the explanatory factors affecting the modal shift to urban light rail transit (LRT). A binary logit model estimation results showed that men are less likely than women to shift toward LRT because they rely more on their private cars. It was the provision of free on-street parking at destinations and the frequency of using private cars on a weekly basis that had the most negative effect on LRT modal shift, demonstrating the critical role that implementation of TDM policies could play. Moreover, reduction in travel time by LRT has the most positive impact on modal shift toward LRT among private car users. As an interesting finding, marginal effect values indicate that a 10% reduction in travel time (0.32) has a greater impact than the possibility of sitting 50% of the travel time (0.25) on the likelihood of modal shift to LRT. Furthermore, the probability of modal shift to LRT will be reduced by 0.12 units for each unit increase in car ownership. In addition, owning a driver's license was also negatively correlated with LRT modal shift and decreased the likelihood by 0.27. This research will facilitate the decision-making and planning for future transportation systems to increase LRT's utility for potential users.

Keywords

• binary logit model
• light rail transit
• modal shift
• stated preference
• travel behavior