Testing of traffic reduction policies using a transport demand model

Abstract

This thesis aimed to test the impact of various transport demand management (TDM) measures on traffic road assignment in transport demand macro model developed for the city of Coimbra in software VISUM 12.0. The policies tested in the model were parking policy, carpooling incentives, urban road tolling policy and improvement of public bus transit, as well as strategic combinations of all of those policies. The study measures the impact on aggregated values for private vehicle volumes, fossil fuel consumption and CO2 emissions from the traffic in the city of Coimbra with complementary geographical representation. The strategic policy scenario consisting of combination of all the measures that were tested resulted in a 4% reduction of CO2 emissions (19.76 tonnes), 4% reduction of fuel consumption (6.34 tonnes) and 506’969 vehicles per km in 24 hours of a non-eventful working day. It was able to target the zones with the highest demand for commuting represented as reduction of 2.1% of trip origins and 5% of trip destinations in the zones. These policies were also able to target the most congested or the most polluted roads in the inner city and reduce CO2 emissions and private vehicle volumes. It was found that road tolling, higher parking fees and extended paid areas can lead to a different route choice of private vehicle instead of shift to public transport or walking. Thus their effectiveness in reducing CO2 emissions and private vehicle volumes can be lower. Additionally a road slopes in the city influence the results of policies aiming to reduce CO2 emissions. It was concluded that the macro model simulation plays important role in obtaining the aggregated results with macro projection of the traffic situation after a TDM policy. In the same time, careful multi-criteria policy modelling and a complementary micro simulation of traffic situation in the city will be necessary part when testing the effect of TDM policies.