Work

Alteration in delay time considering different pedestrian's crossing characteristics in the era of autonomous vehicles

Year: 2025

Type: article

Abstract: Delay is one of the most crucial factors for both pedestrians and car drivers around pedestrian crossings. Drivers often do not yield to pedestrians, which may result in both delay and impatient pedestrian behaviour. This tendency may alter after introducing autonomous vehicles as the vehicles will follow the traffic rules in all cases. This study aims to estimate the delay time alteration at a simple zebra crossing using on-site measures and simulation. Roadside video recordings were carried out in Budapest, Hungary, to obtain the crossing decisions of pedestrian groups based on the approaching vehicle distance. We have determined the accepted vehicle distance vales for pedestrian groups that served as input data for microsimulation modelling. The novelty of the study is that the simulation involved autonomous vehicles that hold preset headways from the leading vehicle. The simulation was designed based on the traffic share of autonomous vehicles and the headways they kept. The main findings are that the travel time and stopping time for cars are higher if the modal share of autonomous vehicles is high. For pedestrians, however, we found a slight decrease in both travel times and stopping times. Moreover, we have proposed modifications to the simulation software (Vissim) to handle distance-dependent pedestrian decisions and drivers' failure to give priority. The results can be useful for road operators to estimate the road capacity in the era of autonomous vehicles and for software developers to formulate the simulated and real driving mechanism for autonomous vehicles. • Modelling travel time alteration at a pedestrian crossing after introducing autonomous vehicles. • Simulation of scenarios for different autonomous vehicle penetrations and headways. • Average stop time and stops per pedestrian fell by 43.72% and 22.13% in the best case. • An increase between 1.98% and 10.14% was measured in vehicle travel times. • Travel time for cars may increase due to autonomous vehicles' rule-following habits.

Source: Journal of Traffic and Transportation Engineering (English Edition)

DOI: 10.1016/j.jtte.2024.03.007

Authors: Szilárd Szigeti, Dávid Földes, Attila Aba

Institutions: Budapest University of Technology and Economics, Institute for Transport Sciences

Language: English

Topic: Traffic control and management

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Sustainable cities and communities, Industry, innovation and infrastructure

Open Access status: diamond

Funder: Magyar Tudományos Akadémia