학술논문

Brake-Signal-Based Driver’s Location Tracking in Usage-Based Auto Insurance Programs
Document Type
Periodical
Source
IEEE Internet of Things Journal IEEE Internet Things J. Internet of Things Journal, IEEE. 10(12):10172-10189 Jun, 2023
Subject
Computing and Processing
Communication, Networking and Broadcast Technologies
Brakes
Roads
Vehicles
Internet of Things
Prediction algorithms
Insurance
Trajectory
CAN-bus network
driving maneuver detection
location tracking
OBD-II port
random forest classifier
usage-based insurance
vehicular network
Language
ISSN
2327-4662
2372-2541
Abstract
In this article, 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 subsequences 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 450 km 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.