Evidence-based transport policy analysis driven by agent-based simulation: the case of mobility in Ústí nad Labem

Abstract

There is a raise in public awareness on environmental and health issues in recent years, therefore many municipalities changed their transport policy direction to become more sustainable, especially active mobility based. This study makes use of an activity-based demand model to simulate urban mobility and policies for sustainable transport modes in the Usti nad Labem district using an agent-based model simulator driven by a co-evolutionary algorithm. Two policy scenarios were created by considering the transport literature and analyzing the characteristics and behaviors of citizens as well as the properties of the study area. Three scenarios—the actual situation, a cycleway-infrastructure case, and a bus priority case—were simulated for the study area with MATSim software. Both policy scenarios resulted in a decrease in car usage, with a higher drop seen in the cycleway-infrastructure scenario. 9.11% higher public transport ridership and 2.45% more of public transport modal share are observed in the bus priority compared to the actual situation, however the car-related emissions did not decrease. 6.36% more of cycling modal share was also noticed in the cycleway-infrastructure scenario which, the transport modal shift is enhanced by 2.6 more times than in the bus priority scenario. Car driving hours were significantly reduced in the cycleway scenario (5535 h less in a day) where 445.3 tons of car-related CO2 emissions would be saved annually, therefore environmental benefits of cycling modal share increase in the study area is undoubtable in long-term.