Use cases for rider assistant mobile application evaluation using travelling simulator

Today's personal mobility vehicles have been considered as a solution for solving the last/first mile problem of a rider in big cities. It is important to investigate the rider factors, rider behavior, and rider-machine interface while using personal mobility vehicles in order to propose useful and safe personal mobility systems (including vehicles and software for the rider assistance). These factors can be evaluated using a simulator that attains realistic environments. The paper presents use cases for the rider assistant using a personal mobile application and their evaluation using the developed travelling simulator. The mobile application for the rider assistant is generated recommendations for the rider based on detected dangerous situation during the riding to prevent an accident. Dangerous situations detection is based on images analysis of the rider face taken from the front camera of the rider's mobile device mounted in the personal mobility vehicle.