Effects of Automated Vehicles on Traffic Flow With Different Levels of Automation

Highly automated vehicles are regarded as the next revolution of the transport system. Automated vehicles include a spectrum from vehicles with driver assistance systems through to highly automated vehicles. These vehicles will only gradually appear in the overall vehicle fleet. Their impact as part of future traffic is of reference value for transport decision-makers. The present paper starts from assumptions for the shares of vehicles with different levels of automation in 2030 and 2050 (representing the near and far-distant future) and compares the effects of these automated vehicles on traffic flow using microscopic traffic simulations. The simulated vehicles include non-assisted vehicles, semi-automated vehicles with driver assistance systems, and fully autonomous vehicles. To obtain a more realistic result, a traffic scenario of the city of Duisburg is used in this thesis. With the support of the city administration, existing data of the origin/target matrix, detector data including induction loops, and cameras were available. Thus, the data of the origin/target matrix are used to generate the real traffic scenario and the detector data to investigate the accuracy of the generated traffic. The result shows that automated vehicles would have a positive impact on traffic, a proportion of automated vehicles can reduce the average travel time. For areas with different traffic conditions, the degree of impact of automated vehicles can be very different.