Car telematics big data analytics for insurance and innovative mobility services
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ORIGINAL RESEARCH
Car telematics big data analytics for insurance and innovative mobility services Leonardo Longhi1 · Mirco Nanni2 Received: 24 July 2019 / Accepted: 30 October 2019 © Springer-Verlag GmbH Germany, part of Springer Nature 2019
Abstract Car telematics is a large and growing business sector aiming to collect mobility-related data (mainly private and commercial vehicles) and to develop services of various nature both for individual citizens and other companies. Such services and applications include information systems to support car insurances, info-mobility services, ad hoc studies for planning purposes, etc. In this work we report and discuss some of the key challenges that a car telematics pilot application is facing within the EU project “Track and Know”. The paper introduces the overall context, the main business goals identified as potentially beneficial of big data solutions and the type of data sources that such applications can rely on (in particular, those available within the project for experimental studies), then discusses initial results of the solutions developed so far and ongoing lines of research. In particular, the discussion will focus on the most relevant applications identified for the project purposes, namely new services for car insurance, electric vehicles mobility and car- and ride-sharing. Keywords Mobility · Big data analytics · Car insurance · Mobility services · Carpooling
1 Introduction Mobility data generation and analysis is at the core of the business of many mobility–related companies, including car insurances and associated technology providers. Indeed, providing fresh and detailed information about the mobility of vehicles and single users can be fundamental in optimizing services. This is the case for car insurances, where a good knowledge of the driving attitude of the customer allows to identify the most appropriate contractual conditions, typically associated with the risk of causing accidents. Indeed, risky customers create risks both for their safety and for the car insurance profit, and the best customers for car insurance providers are indeed the safe ones. For this reason, in the long term the business objectives of the company should include not only identifying the risky subjects, but also providing them useful feedbacks to correct their risky behaviours. Similarly, services aiming at supporting alternative transportation solutions, such as car pooling or electric * Mirco Nanni [email protected] 1
Sistematica S.p.A, Via G. Peroni 400/402, Rome, Italy
ISTI-CNR, Via G. Moruzzi 1, Pisa, Italy
2
vehicles, require to know which kinds of mobility needs the user has, and then infer what kind of changes to her daily routines are needed to fit the requirements of the new solution. In case of car pooling, that means aligning with the mobility of other users; in the case of electric vehicles, we have to take into consideration the limited autonomy of current batteries, the relatively low availability of recharging points, and the relatively lon
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