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篇名
先進駕駛輔助系統納入汽車保險費率影響因素之研究
並列篇名
RESEARCH ON ADVANCED DRIVER ASSISTANCE SYSTEMS AS FACTORS AFFECTING AUTOMOBILE INSURANCE RATES
作者 周文生徐岷瓘
中文摘要
隨著科技進步與駕駛人對車輛安全觀念提升,國內外車輛配備先進駕駛輔助系統(ADAS)普及率提高。ADAS得輔助駕駛人操控車輛,提升道路安全性並降低肇事率,進而減少車輛出險頻率及保險公司賠償率,爰考量ADAS使車輛安全性提高,車險費率以實際影響交通安全情形計算較合適,故本研究探討我國汽車保險費率以ADAS作為風險考量係數之可行性。針對配備不同ADAS車輛之事故資料統計分析,並以問卷調查駕駛人對ADAS與行車安全性及汽車保險費率關聯性之看法,再根據上述結果,與保險專業人員進行半結構式訪談,了解保險業者對ADAS影響交通事故與汽車保險理賠之看法,藉以研擬ADAS影響汽車保險費率結構之調整方式及因應措施,給予保險業者調整汽車保險制度R及費率結構之建議。
英文摘要
With the advancement of science and technology and the improvement of drivers' awareness of vehicle safety, the popularity of domestic and foreign vehicles equipped with Advanced Driver Assistance Systems (ADAS) has increased. ADAS can assist drivers in controlling vehicles, improve road safety and reduce accident rates, thereby reducing the frequency of vehicle accidents and insurance company compensation rates. Considering that ADAS can improve vehicle safety, it is more appropriate to calculate auto insurance rates based on the actual impact on traffic safety. Therefore, this study explores the feasibility of using ADAS as a risk consideration factor for automobile insurance rates in Taiwan. Based on statistical analysis of accident data of vehicles equipped with different ADAS, and using a questionnaire to survey drivers’views on the correlation between ADAS and driving safety and automobile insurance rates, based on the above results, semi-structured interviews were conducted with insurance professionals to understand the insurance industry views on the impact of ADAS on traffic accidents and auto insurance claims are used to develop adjustment methods and countermeasures for the impact of ADAS on the auto insurance premium rate structure, and provide insurance companies with suggestions for adjusting the auto insurance system and rate structure.
起訖頁 75-101
關鍵詞 先進駕駛輔助系統車體損失險保險費率影響因素Advanced Driver Assistance SystemsAutomobile Physical Damage InsuranceInsurance Rate Factor
刊名 運輸計劃季刊  
期數 202603 (55:1期)
出版單位 交通部運輸研究所
該期刊-上一篇 以ADAS警示為基礎之國道大客車高風險駕駛行為辨識與預測
 

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