APPROXIMATION OF PEDESTRIAN EFFECTS IN URBAN TRAFFIC SIMULATION BY DISTRIBUTION FITTING

For a proper simulation of urban traffic scenarios, besides cars other road users, namely bicycles and pedestrians, have to be modeled. In scenarios where a whole city is modeled, a detailed actor-based simulation of pedestrians leads to expensive extra computational load. We investigate to what extent it is possible to capture traffic effects imposed by simulated pedestrians and then perform simulations without pedestrians. We propose to collect information about pedestrian impacts in a simulation with pedestrians, estimate underlying probability distributions and finally, use a simplified model where only these effects are generated probabilistically. We investigate two approaches a best-fit distribution fitting and a histogram-based distribution approximation using synthetic data as well as simulated traffic scenarios. The experiments show that using the proposed approximations can lead to similar average cars' travel times.