Simulation Study on Automated Vehicles in Munich, Germany Found That at Full Penetration, the Total Number of Conflicts Decreased by Around 25 Percent Compared to a Fully Human-Driven Vehicle Scenario.
Increasing the Penetration Rate of Automated Vehicles Reduced the Total Number of Conflicts Due to These Vehicles’ Fast Reactions in Conflict Situations.
Germany
A Simulation-Based Impact Assessment of Autonomous Vehicles in Urban Networks.
Summary Information
Automated vehicles (AVs) are expected to bring significant mobility and safety changes to the transportation system. This study modeled and simulated the car-following behavior of AVs under different penetration rates and conducted a network-wide impact assessment under various demand scenarios.
METHODOLOGY
This simulation-based impact assessment evaluated the effects of AVs on efficiency and safety in an urban network. An optimization algorithm that enables groups of agents exploring and learning from each other to gradually find the best model settings was used for model calibration. The researchers selected traffic capacity, waiting time, queue length, and total travel time as the main performance indicators, as well as the number of conflicts.
FINDINGS
- The total number of conflicts was around 25 percent less in a fully AV setting in comparison to the base scenario (a fully human-driver setting).
- With 20 to 40 percent penetration rates, the results showed around a 10 percent increase in travel time, where this figure reduced gradually for penetration rates ranging from 40 to 100 percent.
- Network-level results showed that differences in AV driving behavior have limited impact on urban traffic efficiency. In a fully AV scenario, the network travel time was almost the same as in the base scenario. The same findings were found for the average number of stops per vehicle, average time loss per vehicle, and average time loss per vehicle per intersection.
