Cause analysis of Driving Infractions and Accidents in Taipei City by Data Exploration

• Main Authors: Chang,Fu-Jung, 張復榮
• Other Authors: Chiang,Tzu-Chiang
• Format: Others
• Language: zh-TW
• Published: 2018
• Online Access: http://ndltd.ncl.edu.tw/handle/rnv2sq

碩士 === 東海大學 === 資訊管理學系 === 106 === 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.