Risk assessment of vehicle cornering events in GNSS data driven insurance telematics

Abstract

Abstract-We propose a framework for the detection of dangerous vehicle cornering events, based on statistics related to the no-sliding and no-rollover conditions. The input variables are estimated using an unscented Kalman filter applied to global navigation satellite system (GNSS) measurements of position, speed, and bearing. The resulting test statistic is evaluated in a field study where three smartphones are used as measurement probes. A general framework for performance evaluation and estimator calibration is presented as depending on a generic loss function. Further, we introduce loss functions designed for applications aiming to either minimize the number of missed detections and false alarms, or to estimate the risk level in each cornering event. Finally, performance characteristics of the estimator is presented as depending on the detection threshold, and on design parameters describing the driving behavior. Since the estimation only uses GNSS measurements, the framework is particularly well-suited for smartphone-based insurance telematics applications, aiming to avoid the logistic and monetary costs associated with e.g., on-board-diagnostics or black-box dependent solutions. The design of the estimation algorithm allows for instant feedback to be given to the driver, and hence, supports the inclusion of real time value added services in usage-basedinsurance programs.

Survey of smartphone‐based sensing in vehicles for intelligent transportation system applications

“…Among the millions of M2M devices that will be deployed world-wide in the coming years, smartphones will be the most mobile, versatile and powerful devices that can be used as sensors and M2M gateways [12]. Therefore much research has been done on smartphone sensing applications in recent years [12,13,14,15,16,17,18,19,20,21,22,23].…”

“…Händel et al [42] provides a detailed investigation into the necessary characteristics of a smartphonebased insurance telematics system. Wahlström et al [21,22], developed two systems that detect and quantify the risk level of cornering events using GPS measurements. These risk classifications are used for data driven insurance telematics.…”

“…Wahlström et al [21, 22], developed two systems that detect and quantify the risk level of cornering events using GPS measurements. These risk classifications are used for data driven insurance telematics.…”

Driving Behavior Analysis for Smartphone-based Insurance Telematics

“…Appropriate test statistics can be derived based on the dynamics of skidding and rollovers [29]. Choosing the threshold for detection of dangerous events determines the tradeoff between making accurate detections (easier at lower thresholds) and making relevant detections (easier at higher thresholds).…”