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Security Concerns in Cooperative Intelligent Transportation Systems
Published in Georgios Kambourakis, Asaf Shabtai, Constantinos Kolias, Dimitrios Damopoulos, Intrusion Detection and Prevention for Mobile Ecosystems, 2017
Konstantinos Fysarakis, Ioannis Askoxylakis, Vasilios Katos, Sotiris Ioannidis, Louis Marinos
This heterogeneous networking infrastructure enables all parts of the C-ITS to share information, improving decision making and enabling the provision of novel, enhanced types of services. These enhanced services may include enhanced vehicle insurance models, whereby the driving behavior, distance, and areas travelled directly affect the insurance fees, providing novel usage-based insurance (UBI) schemes, and the associated pay as you drive (PAYD) and pay how you drive (PHYD) models. The real-time data link between road infrastructure and vehicles (types of which can be seen in Figure 16.2, presenting a view of a C-ITS deployment) can also enable numerous other services. The said services promise to reduce wait times and increase the efficiency of transport, by providing up-to-date information on mobile roadworks, wrong-way driver and pedestrian alerts, remaining red and green light times, and by enabling features such as the dynamic coordination green light phases, intelligent parking space management, and priority for emergency vehicles and public transport [25–27]. Figure 16.3 presents some indicative applications. While the potential and impact of these new cooperative traffic communications will reach its full potential with autonomous vehicles, considerable benefits can be earned even in these early stages.
Analysis of profitability of Pay-As-You-Speed scheme
Published in Traffic Injury Prevention, 2023
Sina Sahebi, Khashayar Khavarian, Habibollah Nassiri
The usage-based insurance plans (UBI) are an effort to provide a monetary incentive for driving safely where the premiums are based on how much the insured vehicle is used. It has the ability to offer personalized insurance rates based on individual driving behavior. These schemes are also implemented and still being tested in many countries (Stigson et al. 2014) to reduce driver crash risks through economic incentives or as a means of internalizing the driving externalities to aberrant drivers. Even the global plan toward a safer road developed through the decade of action for road safety movement, advices to implement the UBI to provide drivers with monetary incentives toward safe driving. It also recommends that governments help insurance companies establish these measures to make roads safer (WHO 2021).
Driver’s black box: a system for driver risk assessment using machine learning and fuzzy logic
Published in Journal of Intelligent Transportation Systems, 2021
The detection of risky driving behaviors can be useful in many domains, such as simulating traffic accidents, insurance, and fleet management. In the insurance domain, driver risk assessment can help insurance companies better calculate or adjust their insurance premiums. Drivers with high risk could pay more, while drivers with safe driving habits could pay less (usage-based insurance or pay as you go options). Integrating these systems into cars and enforcing their use by law may help us simulate accidents and understand how they occurred. This way, traffic officers can remotely connect to the system, observe the driving behaviors, and identify the guilty drivers.
Big data and reliability applications: The complexity dimension
Published in Journal of Quality Technology, 2018
Yili Hong, Man Zhang, William Q. Meeker
Usage-based insurance (UBI) is a type of insurance in which the cost of the insurance is based on the usage, use behavior, and product location. One important task is to assess future risk at the individual level to develop pricing plans. With some modifications and customization, reliability models that are used to assess product failure risks can be used to predict events for UBI. Thus, UBI will be an interesting area to apply reliability analysis techniques.