ABSTRACT
The overall function of intelligent transportation system (ITS) is to improve decision-making, often in real time, improving the operation of the entire transport system. For this study, the research focuses on evaluating the use of smartphones (SP) as an intermediate step to accelerate the implementation of vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I), which could be used to prevent collisions. To evaluate whether smartphones can properly predict a future trajectory and be considered as a possible solution to fill in the V2V/V2I implementation gap, the position estimation error between the vehicle-mounted (VM) sensors (UConn) and the SP sensors was selected using the same KF models and IMM framework. The Multi-Sensor Data Fusion (MSDF) techniques are used in many diverse fields, although most of the literature addresses the fields of military target tracking or autonomous robotics. The MSDF is required to combine and process data, which has been traditionally performed by some form of Kalman or Bayesian filters.
