Use of Origin-Destination data for calibration and spatialization of synthetic travel demand

Abstract

Luxembourg’s high car ownership per household, combined with a strong population growth and high share of cross-border commuters, led to systematic traffic congestion issues all over the country. To address this problem, the government made public transport (PT) free in 2020 by eliminating second-class fares, a policy that attracted great interest but also led to controversial opinions on its real impact on car use. Notably, since free PT requires no ticketing, there is a problematic lack of passenger data that would allow assessing the policy impacts. Therefore, in this study a MATSim scenario was developed and used to evaluate the impact of this policy under realistic settings. The population was generated using data from a national travel survey collected in 2017 and the free PT scenario was compared against a benchmarking scenario where public transport was still not free, allowing to collect and analyse different KPIs. The simulation showed that the policy brought significant benefits in terms of Passenger Kilometer (PKT) and Hours (PHT) Travelled for PT, and a decrease in car usage in favor of PT especially for cross-border commuters for the parts of their journey that take place inside of Luxembourg. Nonetheless, this study found that the overall impact of Free PT was not significant enough to strongly impact the congestion levels, with the high car ownership rates being one possible reason for this resistance.