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


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