依據2018年至2023年的交通事故死傷資料統計，大型車輛事故共造成2,314人死亡，其中約有7成為弱勢用路人（機車、慢車及行人），凸顯大型車輛於道路上行駛對弱勢用路人所產生的巨大威脅，因此政府與交通專家紛紛致力解決此問題。
本研究先回顧國內外大型車輛與弱勢用路人事故特性相關文獻，整理大型車輛管制措施及推動行車視野輔助系統等安全提升配備政策。再整理我國道路交通事故資料庫中大型車輛及弱勢用路人之傷亡資料，將大型車輛事故資料分類成全部大型車輛、大客車類及大貨車類，弱勢用路人分為機車類、慢車類及行人。為通盤概覽大型車輛與弱勢用路人間交通事故特性，本研究先以卡方檢定及逐步羅吉特迴歸，分析影響弱勢用路人事故致死風險的關鍵因子。另為發覺其他未被觀察到的事故潛在關係、降低組內的異質性，先透過潛在類別分析將事故資料分類，再使用逐步羅吉特迴歸方法鑑別肇事因子。
為合理評估推動行車視野輔助系統對大型車輛及弱勢用路人事故嚴重度之影響情形，本研究將推動大型車輛配備行車視野輔助系統的立法歷程，分為推廣、檢驗及執法三個政策階段，進行逐步羅吉特迴歸，細究該政策在各階段死亡事故的影響因子變化；另將肇事因素與行車視野輔助系統有相關之事故獨立取樣，使用變異數分析的費雪最小顯著差異檢定，分析不同政策時期事故的平均月件數、死亡人數及致死率，結果發現在政策開始實施罰則後，大型車輛及弱勢用路人雙車事故模型中，與行車視野輔助系統有關事故致死人數已達每年可降低31.28%。本研究結果可作為推動行車視野輔助系統政策及擬定大型車輛行車安全政策參考。

According to Taiwan's traffic accident dataset, heavy vehicles-related accidents resulted in a total of 2,314 fatalities from 2018 to 2023, and vulnerable road users account for approximately 70% of the total fatalities. This highlights the serious threat posed by heavy vehicles to vulnerable road users on the road.
This study utilized injury and fatality accident data. Heavy vehicles are composed of buses and heavy trucks (tractor, tractor trailer), while vulnerable road users included motorcyclists, cyclists, and pedestrians. To comprehensively overview the characteristics of accidents between heavy vehicles and vulnerable road users, this study first employed chi-square test and stepwise logistic regression to explore the key factors result in the death of vulnerable road users in heavy vehicles-related accidents. Additionally, to identify unobserved potential relationships in accidents and reduce intragroup heterogeneity, latent class analysis is used to classify accident data, and then applied the stepwise logistic regression model for each segment to identify contributing factors.
To explore the effects of equipping heavy vehicles with driving vision assistant system on the severity of accidents involving vulnerable road users, this study divides the legislative process of equipping heavy vehicles with assistant systems into three policy stages: promotion, inspection, and enforcement. Stepwise logistic regression is applied to examine the changes in key factors causing fatal accidents among these policy stages. Furthermore, accidents related to driving vision assistant systems were independently sampled for analysis by using Fisher’s least significant difference test. The results indicate that from the promotion stage to the enforcement stage, the fatalities of accidents involving heavy vehicles and vulnerable road users in double vehicles crash model related to driving vision assistant systems has been reduced by 31.28% per year. The findings of this study can serve as a reference for promoting driving vision assistant system policies and formulating driving safety policies for heavy vehicles.

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Transport for NSW (2022)，Fresnel Lens Trial Research，https://www.transport.nsw.gov.au/roadsafety/road-users/drivers/heavy-vehicles
Transport for London (2024)，Direct Vision Standard and HGV Safety Permit Scheme，https://tfl.gov.uk/info-for/deliveries-in-london/delivering-safely/direct-vision-in-heavy-goods-vehicles?intcmp=41259
United Nations Economic Commission for Europe (2022)，UNECE Adopts Two New Regulations to Improve the Safety of Vulnerable Road Users， https://unece.org/media/transport/Road-Safety/press/373454
World Health Organization (2018)，Global Status Report on Road Safety 2018，https://www.who.int/docs/default-source/searo/india/health-topic-pdf/global-status-report-on-road-safety-2018.pdf?sfvrsn=1de25920_2
World Health Organization (2022)，Road Traffic Injuries，https://www.who.int/zh/news-room/fact-sheets/detail/road-traffic-injuries
World Health Organization (2024)，Protecting Vulnerable Road Users，https://www.who.int/china/activities/protecting-vulnerable-road-users