Fangqi Zhang

Contract strategy design in early stage of implementing pay-how-you-drive policy with traditional commercial vehicle insurance coexisted

Pay-how-you-drive (PHYD), which is a driving behavior related premium rate setting method in usage based insurance (UBI), has drawn widespread attention in commercial vehicle insurance as well as internet-of-vehicle (IoV) industry nowadays, for it can not only help insurance companies to fully master the driving information of all insured vehicles, but can help to establish a corresponding premium rate setting strategy according to that as well. However, as the implementation of PHYD may undergo a complicated process, a stage with PHYD contract and traditional contract coexisted in vehicle insurance market will surely be went through, therefore, certain contract strategy should be given so as to eliminate the potential risk caused by information asymmetry which might be used to exploit an advantage by the speculative contract holders. In this paper, an “either-or” contract implementing strategy is proposed, and via theoretical analysis, its capabilities of providing the maximum utility for insured vehicles and ensuring reliable profit for insurance companies are demonstrated.

A Novel Set of Driving Style Risk Evaluation Index System for UBI-Based Differentiated Commercial Vehicle Insurance in China

Usage based insurance (UBI) for vehicles, or sometimes pay-how-you-drive (PHYD) as it is usually called, which fuses information and telecommunication technologies, can not only enhance the accuracy of underwriting, solve the severe homogeneity problem in vehicle insurance products for insurance companies, but can eliminate the cross-subsidies from vehicles of low risk to those of higher risk, as well. However, till now, researches of driving style evaluation method are mainly for fuel consumption control or to analyze road traffic conditions. It is hard to find reports on dedicated methods for UBI premium actuary purposes. Consider that China is a country which has a huge territory with different city landforms and traffic situations. There is an urgent requirement to establish a theory structure based on UBI implementations, and to establish a theory system for autonomous driving style evaluation methods. In this paper, a novel set of risk evaluation index systems of driving style for the UBI based differentiated commercial vehicle insurance for cities on the plains in China has been proposed. d via a real vehicle driving example analysis, the objectiveness and effectiveness the proposed dynamic driving evaluation index system has been proved.

Mathematical Verification for Transmission Performance of Centralized Lightwave WDM-RoF-PON with Quintuple Services Integrated in Each Wavelength Channel

Wavelength-division-multiplexing passive-optical-network (WDM-PON) has been recognized as a promising solution of the “last mile” access as well as multibroadband data services access for end users, and WDM-RoF-PON, which employs radio-over-fiber (RoF) technique in WDM-PON, is even a more attractive approach for future broadband fiber and wireless access for its strong availability of centralized multiservices transmission operation and its transparency for bandwidth and signal modulation formats. As for multiservices development in WDM-RoF-PON, various system designs have been reported and verified via simulation or experiment till now, and the scheme with multiservices transmitted in each single wavelength channel is believed as the one that has the highest bandwidth efficiency; however, the corresponding mathematical verification is still hard to be found in state-of-the-art literature. In this paper, system design and data transmission performance of a quintuple services integrated WDM-RoF-PON which jointly employs carrier multiplexing and orthogonal modulation techniques, have been theoretically analyzed and verified in detail; moreover, the system design has been duplicated and verified experimentally and the theory system of such WDM-RoF-PON scheme has thus been formed.

Effective presenting method for different driving styles based on hexagonal eye diagram applied in pay-how-you-drive vehicle insurance

Pay-how-you-drive (PHYD), which is an advanced product form in usage based insurance (UBI) for vehicle, takes not only driving habit and behavior into consideration in its actuary process, but geographical factors, sociological factors, psychological factors, and even meteorological factors as well. PHYD insurance product is supported by refinement and analysis based on raw driving data of insured vehicles, and the very analysis process, which is based on big data algorithms, helps to recognize the risk level of each driving behavior by finding the relationship between them. Even if studies on risk level determination have been done adequately, research on feedback and presenting of risk evaluation results for the drivers of insured vehicles have not been reported much. In this paper, an effective presenting method for different driving styles based on hexagonal eye diagram which can be applied in PHYD insurance based driver vehicle interface (DVI) has been proposed, six key style evaluation indices have been chosen in such eye diagram. Evaluation examples have shown that by employing different colors which represent the occurrence frequency of certain evaluation results in such eye diagram, the hexagonal eye diagram proposed can describe the most representative driving style for a certain insured vehicle, even if there might be style changing from time to time.

Fuzzy risk mode and effect analyasis based on raw driving data for pay-how-you-drive vehicle insurance

Pay-how-you-drive (PHYD), which has already been recognized as the most promising differentiated commercial vehicle insurance product in usage based insurance (UBI), can objectively analyze the risk level of each insured vehicle by analyzing its driving style from raw data collected by on-board diagnosis (OBD) module set up on it. Finding certain kinds of driving styles, or risk modes from raw data for insured vehicles, is very important for the insurance companies to get a rough understand of the types of each contract holders and to do the preliminary premium actuary work. Consider that there is a lack of theory basis for driving styles, or risk modes identification and their effect analysis in quantity, in this paper, in order to quantify the effect of different risk modes, and consider that the effect evaluation might be under fuzzy or uncertainty conditions, a fuzzy risk mode and effect analysis (FRMEA) method which can be applied in the early stage of premium actuary for PHYD insurance product is proposed, by setting 4 key indices including occurrence, severity, testability and preventability, and by referencing the grading results from a group of experts, the effect grades of several different risk modes have been given and described via fuzzy triangular numbers.

A Prognosis Method Evaluating Fault Tendency Percentage for Key Equipment in Urban Rail Transit Signal System Based on Enhanced Naive Bayesian Classifying

Signal System is the most important partof urban rail transit system and serves as the neural nervous part of the network. It is a thorny issue to enhance the surveillance of the key equipment in the urban rail transit signal system, and to do the accurate fault diagnosis and prognosis for them so as to realize active and accurate system equipment maintenance. In order to realize that, certain fault analysis methods, which should be not only able to determine whether certain kind of faults would take place, but be able to forecast the tendency of the fault as well, is needed. Naive Bayesian Classifying (NBC), which is widely used in big data analysis and data mining, is regarded as the basic method in fault diagnosis for the key equipment in urban rail transit; however, it is rarely used in fault prognosis, or it is only used in it combined with other data mining and analysis methods. By thoroughly analyzing the steps in Naive Bayesian Classifying, an intermediate parameter appears in the processing steps that can characterize the tendency if a certain class has been found. Utilizing this intermediate parameter Enhanced Naive Bayesian Classifying (ENBC) method proposed in this paper, the fault tendency percentage for the key equipment in urban rail transit signal system can be realized. By integrating ENBC into the maintenance and management system (MMS) of Shanghai Metro Line 8, and by analyzing a set of one week-long operating data sets, the effectiveness of the fault prognosis method has been proved.