Trajectory Estimations Using Smartphones

This paper investigates whether the smartphones' built-in sensors can accurately predict future trajectories for a possible implementation in a vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) system. If smartphones could be used, vehicles without the V2V/V2I technology could use them to tap into the V2V/V2I infrastructure and help to populate the gap of vehicles off the V2V/V2I grid. To evaluate this, we set up a dead-reckoning system that uses Kalman filters to predict the future trajectory of a vehicle, information that could be used in a V2V/V2I system to warn drivers if the trajectories of vehicles will intersect at the same time. Then, we use a vehicle with accelerometer, GPS, and speedometer sensors mounted on it and evaluate its accuracy in predicting the future trajectory. Afterward, we place a smartphone securely on the vehicle's dashboard, and we use its internal accelerometer and GPS to feed the same dead reckoning and Kalman filter setup to predict the future trajectory of the vehicle. We end by comparing both results and evaluating if a smartphone can achieve similar accuracy in predicting the future trajectory of a vehicle. Our results show that some smartphones could be used to predict a future position, but the use of their accelerometer sensors introduces some measurements that can be incorrectly interpreted as spatial changes.