Abstract
State-of-the-art collision avoidance and collision mitigation systems predict the behavior of pedestrians based on trivial models that assume a constant acceleration or velocity and heading. Additional information received from external sources, for e.g. consumer electronic devices, can enhance pedestrian behavior models, which can in turn improve the accuracy of the predicted pedestrian trajectory. The crossing behavior of pedestrians is dependent on personal and external factors, which likely differ between cultures and countries of residence. For the design of enhanced pedestrian safety systems it is important to know the willingness of pedestrians to share personal data with other traffic participants and if it differs between cultures and countries. Based on an identification of prediction-relevant data, an online survey was conducted in India and Germany to evaluate the acceptance and cultural differences for data sharing based on different levels of aggregation shared for V2P based collision avoidance systems. In view of future development of V2P based collision avoidance systems, conditions for data sharing and their influence on data sharing willingness were also investigated in this survey. The results show that German participants in general show a lower acceptance towards higher detailed data sharing, i.e. when low anonymity is provided, as compared to Indian participants. Willingness to share data is further influenced by general conditions for data sharing such as data storage duration, location and activation of data sharing.