Safety and efficiency impact of pedestrian-vehicle conflicts at non signalized midblock crosswalks based on fuzzy cellular automata

Midblock crossing is very common in the high populated urban cities, especially in Southeastern Asia. To regulate unauthorized midblock crossing, Midblock Zebra Crosswalk (MZC) is applied to promote yielding behavior of drivers to pedestrians. It is necessary to set up a clear guidance for constructing MZC to help regulate the unlawful crossing, as well as analyzing the performance of existing MZCs. In this paper, a Fuzzy Cellular Automata (FCA) model is developed to analyze the safety and efficiency impact of pedestrian-vehicle interactions at non signalized MZCs, which explicitly explores the decision making process of individual drivers. In the proposed model, membership functions of conflict area gap and velocity of pedestrian in the fuzzy inference system are calibrated with field survey, in order to reason the output of each driver's filtering decision in front of the crosswalk. Furthermore, by employing safety and efficiency indicators, including Time Difference to Collision (TDTC) and Deceleration Occurrences caused by Conflicts (DOC), the FCA model is capable of evaluating safety and efficiency impact of pedestrian-vehicle conflicts under different proportions of obedient drivers and traffic flows. Finally, we deduce the minimum pedestrian flow for constructing MZC in the midblock from the FCA model and national guideline of setting traffic lights in China. (C) 2021 Elsevier B.V. All rights reserved.

Automated summary

This paper investigates the efficacy of using Midblock Zebra Crosswalk (MZC) to regulate unauthorized midblock crossing, utilizing a Fuzzy Cellular Automata (FCA) model to analyze the impact of pedestrian-vehicle interactions on safety and efficiency. The model explores the decision making process of individual drivers and evaluates safety and efficiency indicators under different scenarios of obedient drivers and traffic flows.