Speed and speed variation are closely associated with traffic safety. There is, however, a dearth of research on this subject for the case of urban arterials in general and in the context of developing nations. In downtown Shanghai, the traffic conditions in each direction are very different by time of day, and speed characteristics during peak hours are also greatly different from those during off-peak hours. Considering that traffic demand changes with time and in different directions, arterials were divided into one-way segments by the direction of flow in this study and time of day was differentiated and controlled for. In terms of data collection, traditional fixed-based methods are widely used in previous studies, which fails to capture the spatio-temporal distributions of speed along a road. A new approach is introduced to estimate speed variation by integrating spatio-temporal speed fluctuation of a single vehicle with speed differences between vehicles using taxi-based high frequency GPS data. With this approach, this paper aims to comprehensively establish a relationship between speed, speed variation and traffic crashes for the purpose of formulating effective speed management measures, specifically using an urban dataset. From a total of 234 one-way road segments from eight arterials in Shanghai, mean speed, speed variation, geometric design features, traffic volume, and crash data were collected. Because the safety effects of mean speed and speed variation may vary at different segment lengths, arterials with similar signal spacing density were grouped together. To account for potential correlations among these segments, a Hierarchical Poisson Log Normal model with random effects was developed. Results show that a 1% increase in mean speed on urban arterials is associated with a 0.7% increase in total crashes, and larger speed variation was also associated with increased crash frequency.
Xuesong Wang*, Qingya Zhou, Quddus M, Tianxiang Fan. Speed, Speed Variation, and Crash Relationships for Urban Arterials, Transportation Research Board 96th Annual Meeting, Washington D.C., USA, 2017. 1.8-12.