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Developing a risk model to explore factors affecting the occurrence of bicycle accidents

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Abstract
為了掌握自行車騎乘市區道路未來的安全狀況,透過有效的控制各種影響因素,減少交通事故,增進自行車行駛於道路的安全性,依據路口與路段劃分以及相關影響因素分析的基礎上,利用實地調查與收集全台北市近3年自行車肇事數據,建立了廣義線性迴歸的事故預測模式,透過比較卜瓦松、負二項兩種風險分布模式回歸之結果、最後確定了負二項分布自行事故預測模式,分為事故次頻與事故嚴重度兩模式,以最大概似法校估均達顯著水準0.01,校估結果顯示天橋、機車專用道、車流分向處、車道數、路口面積與尖峰時段,對事故次頻與嚴重度有顯著相關之影響;特別式圓環、禁止超車處、禁止變換車道處、阻隔式導引分向設施、有標記之車道線、和分隔島寬度涉及較高之事故次頻;而照明程度、市區道路、速限、自行車穿越設施之路口、大量汽機車混合之交通環境、路緣高度、視距阻礙程度、無號誌路口及分向設施影響了自行車肇事之嚴重度。最後,並提出自行車肇事防制對策可供做未來改善自行車交通安全的參考。
For protecting the safety of cyclist driving on urban roads, there are efficient ways to reduce the number of relevant bicycle accidents by control all of the fatal or influent factors. To enhance the cyclist’ safety, this research has analyzed there years of field bicycles accident data in Taipei City according to categories of occurring on segment or junction and to build up a set of linear-regression bicycle accident evaluation model. This model had compared the Poisson to Negative-Binominal Risk distribution and found the Negative-binomial distribution has the better ability to forecast bicycle accidents. The model based on two indexes—accident frequency and accident severity and all of two indexes reveal level of significance great than 0.01. All significant factors includes road facilities and traffic situation, such as overpass, exclusive motorcycle lane, traffic diverse location, lanes of road, square measure of intersection, peak hour duration. One most significant items represented on accident frequency are roundabout, place of prohibiting overtaking and lane-changing, marked lane, width of isolated land. The other most important ones for accident severity include level of illumination, urban road, speed limit intersection include bicycle pass-through facilities, high mixture ratio of traffic stream, height of curb, level of barrier on sight distance, etc. Finally, in terms of the factors’ outcome of discussion, the paper makes some suggestions providing for traffic managers or traffic engineers about how to make relevant strategies to improve the cyclist’ safety.
Keywords
Accident risk, negative binomial distribution,Bicycle safety

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Chicago
Wang, Hwa-chyi, and Tienpen Hsu. 2010. “Developing a Risk Model to Explore Factors Affecting the Occurrence of Bicycle Accidents.” In Proceedings of the 2010 Annual Conference for the Chinese Institute of Transportation, 1–24.
APA
Wang, Hwa-chyi, & Hsu, T. (2010). Developing a risk model to explore factors affecting the occurrence of bicycle accidents. Proceedings of the 2010 annual conference for the Chinese Institute of Transportation (pp. 1–24). Presented at the 2010 annual conference for the Chinese Institute of Transportation.
Vancouver
1.
Wang H, Hsu T. Developing a risk model to explore factors affecting the occurrence of bicycle accidents. Proceedings of the 2010 annual conference for the Chinese Institute of Transportation. 2010. p. 1–24.
MLA
Wang, Hwa-chyi, and Tienpen Hsu. “Developing a Risk Model to Explore Factors Affecting the Occurrence of Bicycle Accidents.” Proceedings of the 2010 Annual Conference for the Chinese Institute of Transportation. 2010. 1–24. Print.
@inproceedings{6982502,
  abstract     = {為了掌握自行車騎乘市區道路未來的安全狀況,透過有效的控制各種影響因素,減少交通事故,增進自行車行駛於道路的安全性,依據路口與路段劃分以及相關影響因素分析的基礎上,利用實地調查與收集全台北市近3年自行車肇事數據,建立了廣義線性迴歸的事故預測模式,透過比較卜瓦松、負二項兩種風險分布模式回歸之結果、最後確定了負二項分布自行事故預測模式,分為事故次頻與事故嚴重度兩模式,以最大概似法校估均達顯著水準0.01,校估結果顯示天橋、機車專用道、車流分向處、車道數、路口面積與尖峰時段,對事故次頻與嚴重度有顯著相關之影響;特別式圓環、禁止超車處、禁止變換車道處、阻隔式導引分向設施、有標記之車道線、和分隔島寬度涉及較高之事故次頻;而照明程度、市區道路、速限、自行車穿越設施之路口、大量汽機車混合之交通環境、路緣高度、視距阻礙程度、無號誌路口及分向設施影響了自行車肇事之嚴重度。最後,並提出自行車肇事防制對策可供做未來改善自行車交通安全的參考。},
  author       = {Wang, Hwa-chyi and Hsu, Tienpen},
  booktitle    = {Proceedings of the 2010 annual conference for the Chinese Institute of Transportation},
  keywords     = {Accident risk,negative binomial distribution,Bicycle safety},
  language     = {chi},
  location     = {Taiwan, Taipei},
  pages        = {1--24},
  title        = {Developing a risk model to explore factors affecting the occurrence of bicycle accidents},
  year         = {2010},
}