Abstract:
Increase in automobile ownership in last decade has prompted congestion, delays and environmental pollution on urban road network. Though, infrastructure interventions have proved effective, but can potentially cause inefficient corridor progression due to improved infrastructure/ segment mobility triggering rapid accumulation of traffic at intersections/ bottlenecks. A comprehensive policy and planning is needed to overcome the urban congestion and meet future transportation demand with sustainable solutions taking due cognizance of the traveler’s behavior/ mode choice. This research is designed to investigate and develop a travel behavioral model for work trip mode using revealed and stated choice data collected through a questionnaire survey. Different model specifications were tested to predict the demand for the competing modes in order to analyze the effect on the mode choice due to the change in attributes such as income, cost, and travel time. Multinomial Logit (MNL) model specification was found best suited to develop a disaggregated modal-split model, and build the traveler’s perceived expectation utility functions. Direct and cross elasticities were computed and pricing variable was found invariably elastic for all the considered choice models. The developed model was also used to calculate value of time and demand response to the policies of improvement in transit/ Bus Rapid Transit (BRT) and implementation of congestion pricing on major arterials of an urban road network. It is concluded that improvement in transit services by introducing BRT alone, do not induce major change in share proportion of auto demand, however on the other hand, congestion pricing has significant effect on reduction of auto demand. Also, combination of two policies has induced more modal-split than congestion pricing alone do. This research highlights traffic congestion pricing as one of the means of traffic demand management by demonstrating its contribution to releasing the urban traffic congestion.
