Affiliations: [a] Department of Advanced Interdisciplinary Studies, Graduate School of Engineering, The University of Tokyo, Tokyo, Japan
| [b] Complex Systems and Artificial Intelligence Research Centre, University of Milano-Bicocca, Milan, Italy
| [c] Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo, Japan
| [d] Department of Aeronautics and Astronautics, Graduate School of Engineering, The University of Tokyo, Tokyo, Japan
Correspondence:
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Corresponding author: Claudio Feliciani, Department of Advanced Interdisciplinary Studies, Graduate School of Engineering, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8904, Japan. E-mail: [email protected].
Abstract: This paper presents a model to simulate non-signalized pedestrian crosswalks. Principal scope is to develop a tool to be used by decision-makers to evaluate the necessity of introducing a new crosswalk and/or switching to a traffic light and estimate the potential benefits of such a measure in terms of Level of Service. The model is based on empirical evidence gained during an observation of a non-signalized crosswalk. Pedestrian motion is simulated using a Cellular Automata model which is capable to simulate pedestrian dynamics at low density conditions, as observed in the considered scenario. Vehicles use a continuous car following model inspired on Gipps equations in which driver’s reaction time is considered. Pedestrian’s decision-making process on crossing attempt and model parameters are directly obtained from the analysis of pedestrian-vehicle interactions observed in reality. The model developed employs small time steps, thus allowing the consideration of different pedestrian speeds (intrinsically considering pedestrians with reduced mobility, such as elderlies) and smoothly reproducing car-pedestrian interactions. This aspect required the definition of distinct behavioral rules for vehicles and pedestrians that, in their dynamic interaction, implement an ad-hoc coordination model. In order to validate the model, delays (or waiting times) measured for both pedestrians and drivers were compared with simulated values. Results show a good agreement between empirically obtained time delay and values computed in the simulation.
