Abstract
Automobile manufacturers, alongside technology providers, researchers, and public agencies, are conducting extensive testing to design autonomous vehicles (AVs) algorithms that will provide a complete understanding of road users, specifically pedestrians. Pedestrian behavior and actions determination are highly unpredictable depending on behavioral beliefs, context, and socio-demographic variables. Context includes everything that potentially affects one’s behavior; in AVs–pedestrian interaction, context may consist of weather conditions, road structure, social factors norms, and traffic volume. These influencing elements, therefore, need to be focused on during the development of pedestrian interaction algorithms. For this purpose, the pedestrian behavior questionnaire for FAVs (PBQF) is designed based on the theory of planned behavior (TPB). A total of almost 1000 voluntary participants completed this multilingual survey. As socio-demographic values and physiological perception varies with local norms, regions, and ethnicity, participants from 27 countries were therefore chosen to account for this variation. One of the key findings of this study is the influence of pedestrian attributes and the context on pedestrian behavior. Pedestrian action cannot be understood without visual observation of the pedestrian themselves and their context. The findings showed that pedestrians build communication with vehicles based on their driving styles. The vehicle’s driving style leads pedestrians to think that the vehicle is human-driven or autonomous. The results also revealed that pedestrians use several cues to show their intention. The general perception of AVs was also analyzed, and the communication between AVs and pedestrians with different displaying options was investigated.
Highlights
Many enormous challenges remain to be overcome in terms of general perception, policies, and traffic management prior to the deployment of autonomous vehicles (AVs)
Exploratory Factor Analysis (EFA) is a type of multivariate statistical correlation analysis that can be used to test the validity of variables [56]
CFA was applied by the partial least squares structural equation modeling (PLS-SEM) method to test the model of the study
Summary
Transportation is one of humanity’s most essential needs, and it has evolved with the passage of time. Automobile manufacturers, researchers, and government officials have all been working on and allocating resources to this new technology. More than fifty companies in the United States have been granted permits to test their AV in California [1], with six autonomous driving companies, Cruise, Waymo, Nuro, Zoox, AutoX, and Baidu, currently in the testing phase. Many enormous challenges remain to be overcome in terms of general perception, policies, and traffic management prior to the deployment of AVs. As a result, automobile manufacturers have made no plans to commercialize AVs. Environmental perception is one of the critical challenges from a technical standpoint [2–5]
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