Brake-Signal-Based Driver’s Location Tracking in Usage-Based Auto Insurance Programs

Abstract

In this paper, we demonstrate that by using a temporal sequence of applied brake signals collected from a vehicle, attackers can still possibly infer the vehicle’s route over the period, even though brake signal data does not reveal any specific location information. Our route inference is basically composed of three steps: At first, we categorize brake signal sub-sequences into four different driving maneuvers (i.e., stopping from a certain speed, reducing speed to adjust with the traffic flow, and taking left and right turns). Second, we estimate the number of intersections traversed by the vehicle using the applied brake signals and their corresponding maneuvers. Finally, we design a graph-based route-selection algorithm to find a list of (paths) routes from the regional map using the predicted driving maneuvers and the speed profile. We evaluate our approach using over 450km of transportation data, which has been collected from 25 individuals. The experimental results demonstrate that, by resorting to our solution, 92.04% of the original drivers’ trajectory can be successfully recovered from their brake data regardless of driver and vehicle models.