Influence Analysis of Deep Discount Policy on Public Transit Ridership

To encourage the use of public transit modes and/or discourage the use of auto for the commuter trip, deep discount policy was provided and implemented in May 2006 in Beijing. To estimate responses of urban travelers to Deep Discount policy, the choice behavior survey was carried out in Beijing, including passengers' individual characters, trip behavior and their choices to railway and bus under certain conditions. And the influence factors of mode split are analyzed. Then traveler mode choice model considering different ticket ratio between railway and bus was established and the mode choice behavior are specified and estimated. The estimation results suggest that ticket cost and ticket cost ratio between bus and railway are the most cited factors in explaining ridership growth and shift. The conclusion will provide an analysis tool for an evaluation of the effectiveness of deep discounts actions. Also the result can provide the Deep Discount policy sustain for the increasing of the trip proportion of public traffic.