# Application of the Theory of Planned Behavior in Autonomous Vehicle-Pedestrian Interaction
## 2 Related Work  
The origin and study of transportation are probably as old as human beings. Before the advent of vehicles, animals were used for transportation over long and short distances. Recognizing and identifying pedestrian actions and intentions started at that time. Pedestrian studies can be divided into categories, classical pedestrian studies and pedestrian studies involving AVs [13]. Pedestrian classical studies started in the early 1950s. At that time, the focus was on the factors that influence pedestrian behavior, such as environmental factors and pedestrian factors [14]. Pedestrian studies started after the invention of the first AV [15]. In the beginning, studies focused were on AV safety perception, choices, and \begin{table}
\begin{tabular}{c c} \hline \hline
**Questions** & **Motivations** \\ \hline Is it essential to consider context while & It plays a vital role in pedestrian attitude, and \\ designing and developing an & its consideration will help in building a robust \\ AV–pedestrian system? & vehicle–pedestrian system. \\ \hline Is it necessary to understand regional norms, & Understanding variations is essential, as it \\ social demographic variations, and adoption of & highly affects attitude. \\ traffic rules? & Pedestrian and driver actions entirely depend \\  & upon their visual communication. \\ \hline How many people are aware of an AVs, what is & Both awareness and safety perception is the \\  & their safety perception? & criteria of any technology acceptance. \\ \hline Is it required to investigate communication & Knowing communication mode will help auto \\  & made between pedestrians and AV? & manufacturers in building a suitable \\  & communication model. \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Research questions and motivations. attitude towards AV adoption [11], but now after successful testing and deployment of AVs in urban public transportation, researchers are focusing on pedestrian AVs interaction [16]. Currently, AVs have dedicated movement zones and specific routes because pedestrian behavior is not yet fully explored. This section discusses related work in behavioral studies in the context of AVs. Different strategies have been adopted for this purpose; surveys and field experiments were mostly applied to understand the effect of technology on human behavior. As mentioned earlier, initial studies focused on participant's preferences, attitudes, and choices, and data were collected by survey or by presenting hypothetical scenarios. [PERSON] [17], in his research, examined individuals' attitudes toward AVs by considering trust and sustainability concerns by applying the technology acceptance model (TAM). Two variables, namely perceived usefulness (PU) and perceived ease of use (PEOU), were added to existing models. Participants showed their intention to adopt the AVs based on their usefulness rather than their easiness. [PERSON] [18] concluded that the willingness to adopt AVs and opinion about adoption depends on users' mobility profiles. It is possible to identify distinct classes of users with unique mobility profiles through Latent class cluster analysis (LCCA). Public safety perception is considered a crucial factor in the adoption of AVs. [PERSON]'s [19] study indicated that the safe interaction experience of AVs will positively affect public perception and help in the long-term adoption of AVs. Due to the different operating regulations of AVs in different regions, different public experiences were observed. [PERSON] [20], in his research, explored the safety perceptions of the general public in terms of their potential roles as pedestrians, bicyclists, and drivers of conventional vehicles on shared roadways. It was observed that previous experience, testing, and knowledge of recent progress were positively correlated with perceived safety about AVs; on the other hand, awareness of the crashes and other safety-related incidents fueled safety concerns about AVs.