Johan Wahlström
ABSTRACT
Insurance telematics programs are continuously gaining market shares in the automotive insurance industry. By recording data on drivers' behavior, the information asymmetry between the policyholder and the insurer is reduced, enabling a granular risk differentiation based on the true risk levels of the drivers. However, the growth of the insurance telematics industry is being held up by large logistic costs associated with the process of acquiring data. As a result, several market participants have started looking towards smartphone-based solutions, which have the potential of easing and improving the data collection process for both policyholders and insurers.
In this paper, we present a unified framework highlighting the challenges of smartphone-based driver behavior analysis. Since all driver behavior analysis relies on access to accurate navigation data, we first address the intermediate step of smartphone-based automotive navigation. The considered topics include estimation of the smartphone's orientation with respect to the vehicle, classification of the smartphone owner as a passenger or driver, and navigation in GNSS-challenged areas. Once a driver-specific high-performance navigation solution has been obtained, it can be used to extract information on the driver's behavior. We review the most commonly employed driving events, and discuss some of the difficulties inherent in detecting these events.
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Index Terms
- Driving Behavior Analysis for Smartphone-based Insurance Telematics
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