現今交通科技的進步與行車用路安全意識的抬頭，交通安全的重視相較以往有很大幅度的改善，在科技變的更智能下希望更有效的降低意外事故的發生，甚至避免掉一些可預期的交通事故。本研究就是使用政府資料開放的平台，道路交通事故資料庫來分析過往交通事故容易造成的因素，希望達到有效預測或先知的方式來做預防。利用政府開放式資料(Open Government Data)來做本研究的分析與探討，主要是101年到105年臺北市交通事故資料分析其中造成意外事故的因素之關聯性，並以T-test、Anova加以深入探討。分析結果可知，青壯年族群肇事比例甚高，其他因素像是晴天、自小客車及普通重型機車的事故偏高，透過這樣的數據資料分析顯示來做後續可能的重點宣導及注意事項，也可以效法其他先進國家的經驗，對肇事者加重刑期與處罰條例，已達有效嚇阻之作用。 Nowadays, with the advancement of transportation technology and the rise of road safety awareness, the importance of traffic safety has been greatly improved compared to the past. Under the more intelligent science and technology, it is hoped that the occurrence of accidents will be reduced more effectively, and even some of the expectable traffic accidents can be avoided. This study uses government information open platforms to analyze the factors that are likely to be caused by accidents in the past and hopes to achieve effective prediction or prophetic methods for prevention. The use of Open Government Data for analysis and discussion of this research is mainly related to the analysis of traffic accident data in Taipei City from 2011 to 2016, and will be discussed considering both methods, T-test and Anova.The results of the analysis show a very high proportion of accidents among young and middle-aged ethnic groups. Other factors such as sunnyday, accidents involving cars and original heavy-duty vehicles are high as well. According to the results of the reviewed data, follow-up announcements and notes could be provided. It is also possible to imitate the experience of other advanced countries and impose more severe sentences and punishments on the perpetrators, in order to motivate drivers to a safer style of driving.
