ABSTRACT: Non-motorized vehicles such as bicycles and e-bikes have gained great popularity in recent decades because of their high mobility and economy. Because these road users have a higher risk of injury in a crash, macro safety analyses have been conducted according to crash location. However, this strategy could be inefficient when comprehensive improvements such as traffic safety education programs are considered, due to differences between crash locations and the locations of the crash-involved road users’ residences. To improve implementation of such countermeasures, this study proposes a new analysis strategy of separately aggregating crashes for roadway engineering improvement and road users for education improvement. Roadway, socioeconomic and land use characteristics from 213 Shanghai sub-districts were collected as independent variables. The dependent variables of crashes and road users were divided into four subjects by crash severity level: fatal and injury (FI) and property damage only (PDO). A multivariate Poisson lognormal conditional autoregressive (CAR) model was developed to examine the relationships between regional characteristics and traffic safety, and potential safety improvement (PSI) was calculated for each sub-district based on model results. Hot-zone identification showed significant differences in distribution of sub-districts with urgent need for roadway versus education improvement. False positive and false negative indexes were developed to identify the differences quantitatively. Results indicated that nearly half the identified hot zones were inconsistent in unnecessarily prioritizing either engineering or education improvement. The findings of this paper are of great practical significance to better utilize resources for non-motorized vehicle traffic safety improvement.
Zhicheng Dai, Xuesong Wang, Wenbin Luo. Macro Safety Analysis for Non-Motorized Vehicles Based on Roadway and Safety Education Improvement Countermeasures. Transportation Research Board 100th Annual Meeting, Washington D.C., USA, 2021. 1.25-29.