Citation

Madigan R, Lee YM, Merat N. Transp. Res. F Traffic Psychol. Behav. 2021; 81: 101-114.

Copyright

(Copyright © 2021, Elsevier Publishing)

DOI

10.1016/j.trf.2021.05.006

PMID

unavailable

Abstract

The successful deployment of automated vehicles (AVs) will depend on their capacity to travel within a mixed traffic environment, adopting appropriate interaction strategies across different scenarios. Thus, it is important to gain a detailed understanding of the specific types of interactions that are most likely to arise. The overall purpose of this paper was to present a methodology designed to facilitate the systematic observation of pedestrian-vehicle interactions, and to validate its use for both onsite and video based observations. A detailed observation protocol was developed to capture pedestrian and vehicle movement and communication patterns across four interaction phases. Onsite coders completed field observations of 50 pedestrian-vehicle interactions at a UK intersection, while video coders observed the same interactions recorded through a wireless camera mounted on a nearby rooftop.

RESULTS show that the observation protocol provides a reliable methodology for capturing patterns of pedestrian-vehicle interactions, with high levels of inter-coder consistency emerging across all categories of codes. A detailed examination of the specific descriptors selected suggests that onsite coding may be particularly beneficial in situations where the aim is to capture any explicit, and perhaps subtle, communication cues, whereas video based coding may be more appropriate in situations where exact sequences of behaviours or measurements of timings are desired. It is anticipated that this type of observation tool will be beneficial for AV developers to increase their understanding of how to interpret the movements of road users, along with increasing knowledge of when implicit and explicit communication techniques should be used.

Language: en

Keywords

Automated vehicles; Communication and interaction; External-HMI; Human factors; Human machine interface; Pedestrians; Road safety