Simulation and analysis of the performance of a traffic network in Zurich

Abstract

Motorized individual transport in Zurich is expected to grow about 20% by 2030. Moreover, the expansion of the global self-driving vehicle industry is estimated at up to 16% each year and is expected to grow even more. The purpose of this study is to analyze the performance of a traffic network in the city of Zurich during morning rush hour and to evaluate the effects of a hypothetical increase of demand as well as the impact of autonomous vehicles in future cases. For the baseline data, own measurements of traffic flows and signal timings were utilized. After the design of the network in Aimsun, different scenarios were simulated and compared to each other. The results show that an increase of 20% in traffic flows reduces speed about 8% and increases travel time about 19%. By replacing cars with autonomous vehicles, the performance measures show improvement, as speed increases about 29% and travel time reduces about 41%. In order to quantify the impact of autonomous vehicles into the traffic network, different subcases were simulated, in which the penetration rate of the autonomous vehicles was modified at a 25% increment. A penetration rate of 25% AV has a low impact on the network, whereas a shared road with at least 50% AV may perform quite as efficiently as one entirely occupied by autonomous vehicles.