Factors Contributing to Freeway Crashes and Collisions: Some Measures and Findings along TDM Implementation

Abstract

Freeway plays an important role in economic and social development, especially for developing countries such as China, which is also an essential issue in TDM strategy. Therefore, proper infrastructure maintenance and management are significantly necessary. Currently, accident related factors and exact effect degree are mostly conducted by human observation. Automated operation would substantially improve the processing speed and accuracy of the key processing tasks, factor detection, classification and degreeing, since the human observation of the large amount of data is tedious, error-prone and time-consuming. 20032005 accident data is surveyed from two typical freeways, Jiqing and Dongqing, and then rear-end collision accident is divided into two patterns, namely rear-collision and stationary object collision. PCA (Principal Component Analysis) is induced to identify the effect level of different factors on above mentioned two types of collisions, which reduces the dimension of the image as well as keeping the most important features, and significant effect factors are identified by charting analysis and clustering research. The final investigation result indicates that fatigue driving, over-speeding, environmental factor, unsafe following, truck overload, and trunk driving, over-speeding, overcrowd, fatigue driving illegal overtaking, are main effect factors on rear collisions and stationary vehicle collisions, respectively. Preliminary experimental result presented in the following demonstrates that such a proposed method has potential to solve the identification and classification problem of factors contributing to freeway crashes and collisions.