# Application of the Theory of Planned Behavior in Autonomous Vehicle-Pedestrian Interaction
## 3 Theoretical Framework  
As mentioned earlier, auto manufacturers are currently targeting the commercialization of AVs globally; hence, cross-country research is required to understand the effect of social norms, demographic variations, and ethical values on pedestrian behavior. The theory of planned behavior is one of the most dominant theoretical frameworks applied to predict human behavior from the last three decades [34]. An extended version of the theory of planned behavior was applied as the base model for this purpose. The theory of planned behavior [35; 36] was developed by [PERSON] to predict human behavior. According to this theory of planned behavior, the most influential predictor to determine someone's behavior is the individual intention to perform a behavior; intention wholly depends upon attitude, social norm, and perceived behavioral control. The theory of planned behavior has been extensively applied in a variety of research domains, including healthcare [37; 38; 39; 40], environmental science [41; 42; 43], supply chains [44; 45; 46], \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Reference/Study** & **Survey/Analysis Approach** & **Research Objective** & **Main Finding** \\ \hline \multirow{3}{*}{[27]} & \multirow{3}{*}{International survey Multilevel structural equation modeling} & Perceptions of AV safety & Young males have more optimistic and positive perceptions of AVs. \\  & & Awareness of AV & \\  & & Cross country/cultural & \\  & & comparison & \\ \hline \multirow{3}{*}{[28]} & \multirow{3}{*}{Nation-based survey Basic statistical analysis} & Pedestrian behavior analysis & Safety concerns were \\  & & Trust and intention to adopt & observed in an occluded \\  & & Modality of communication & pedestrian environment. \\ \hline \multirow{3}{*}{[31]} & \multirow{3}{*}{Nation-based survey Principal Component Analysis} & Trust and Intention to adopt & People who are familiar with AVs \\  & & Perceptions of AV safety & advanced assisted systems believe \\  & & Perceptions of AV safety & that AVs are more useful and safe \\ \hline \multirow{3}{*}{[32]} & \multirow{3}{*}{Nation-based survey Factor Analysis/ Regression Analysis} & \multirow{3}{*}{Pedestrian behavior analysis Perceptions of AV safety} & Males reported a significantly \\  & & & higher frequency of unsafe \\ \cline{1-1}  & & & behaviors on the road \\ \cline{1-1}  & & & than females \\ \hline \multirow{3}{*}{[33]} & \multirow{3}{*}{Nation-based survey Factor Analysis} & \multirow{3}{*}{Perceptions of AV safety Trust and Intention to adopt} & Pedestrians believe \\ \cline{1-1}  & & & AV-pedestrians are less risky \\ \cline{1-1}  & & & compared to \\ \cline{1-1}  & & & human-operated cars \\ \hline \multirow{3}{*}{[30]} & \multirow{3}{*}{International survey Graphical Analysis} & Trust and intention to adopt & The respondents are most \\ \cline{1-1}  & & perceptions of AV safety & concerned about crashing, \\ \cline{1-1}  & & Cross country/cultural & malfunctioning, purchase price, \\ \cline{1-1}  & & comparison & liability for incidents, interaction \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Comparison table of related work on AV-pedestrian behavioral studies. and transportation [47; 48; 49]. For predicting pedestrian behavior, [PERSON] [50] compared the theory of planned behavior and prototype willingness model (PWM) in pedestrian violations. Previous researchers suggested that social behavior is the dominant factor in pedestrian violation rather than planned behavior. [PERSON] [51] researched college students' road crossing behavior while using a mobile phone. A questionnaire-based survey was conducted to collect responses, where 4878 crossing instances were observed, and significant distraction was found by the pedestrian while using a mobile phone. In other research, [PERSON] [52] investigated pedestrian behavior while using crossing facilities. A questionnaire was used as an experimental tool, and a structural equation model (SEM) model and factor analysis were performed for data analysis.