حمیدرضا فوری

Today,transportationdemandmanagement(TDM)policy tools are accepted as practical solutions for decreasing the costs of congestion in urban regions, and more ecient using of transport infrastructures. This paper investigates the role of a \time-of-day congestion pricing scheme" as a pull TDM policy and two push TDM policies including \bus travel time reduction" and \bus access time reduction" in user's car use behavior. The main goal of this research is to estimate the impacts of these policy-tools on the probability of choosing car at morning peak, when they are applied separately or simultaneously. The analysis is based on the results of a stated preferences survey developed through the experimental design approach and was completed by 231 users, who travel intoTehranseven-oddzoneforworkbycar. Theadvantage of data gathering in even-odd zone was that these commuters were familiar with the boundaries of pricing area and so, they could make a more realistic decision(forexample, decisionaboutchoosingpark-and-ride mode). For considering a time-of-day congestion pricing policy, we introduced a cordon pricing scheme from 6:30 AM with a discount on entering after peak period (in this case study, between 6:30 AM to 9 AM). Like other policies, the discount policy has three levels containing 50%, 25% and 0% of peak period tolls. The independent and interaction eects of these policies are assessed by developing a two-level mode choice nested logit model and estimating marginal eects. This model has 8 alternatives, three of which are related to driving a car: drive before 6:30, drive between 6:30 and 9, and drive after 9 AM. Results show that cordon pricingschemefrom6:30AMhasthelargesteectandcould decrease share of drive between 6:30 and 9 AM by 0.408. Congestion charging scheme at 6:30-9 AM and bus access time reduction, are also the most eective policytools with a 0.49 decrease in car share when applied simultaneously.