Development Of Accident Prediction Models For Chinese Rural Roads

Following on earlier work, the development of additional models for estimating the accident potential of rural road sections is described. In the modelling procedure presented, Ontario data are used to develop regression model estimates of a section's accident potential based on its traffic and geometric characteristics, and an empirical Bayesian procedure is used for refining these estimates using the section's accident count. These refined estimates are shown in a validation exercise to be superior estimates based on accident counts or regression models only. This method of estimating accident potential is recommended for use in the identification of accident blackspots and in the evaluation of safety treatments on rural roads. To facilitate this use, detailed exmple applications are presented.

This pilot study covers the second stage of a three-stage research project that aims to quantify the impact of all key road features on the safety of two-lane rural roads. This stage of the study involved the collection of road alignment, roadside environment, traffic flow, and crash data for 200 sections of rural road, each one 400m long, throughout the Waikato region of New Zealand. The data was used to develop preliminary crash prediction models for two-lane rural roads, using generalised linear regression model techniques developed by Beca. The data collection exercise covered a total of 28 predictor variables used for developing the preliminary model. The preferred model showed that the crash rate was most influenced by five predictor variables- namely, traffic volume, absolute gradient, distance to non-traversable hazards, skid resistance (SCRIM), and number of accessways.

In India, the primary mode of transport is road transport which plays an important role in the conveyance of goods and passengers and linking the centers of production, consumption and distribution. It is also a key factor for promoting socio-economic development in terms of social, regional and national integration. The motor vehicle population is growing at a faster rate than the economic and population growth.

This book presents comprehensive research and analyses on road traffic safety in China, discussing individual, vehicle, road and environmental factors to improve road safety in the country. It also sheds light on the development of similar (adjusted) measures to reduce traffic violations and/or accident fatalities and injuries, and to promote road safety in other countries and regions. As such, it is a valuable resource for anyone wanting to understand the characteristics and patterns of road traffic safety, the risk factors affecting traffic violations and traffic injuries, as well as road safety policies and practices in China.

"Dynamic route guidance systems (DRG) aid drivers in choosing the best routes based on real time conditions in networks. Whether for the evaluation of DRG's impact on a whole-network traffic safety or for determination of the safest routes by DRG, suitable accident prediction models are required. However, such models are not available for links of all kinds of roads. The objective of this research is to develop an accident prediction approach for links on freeways and urban streets suitable for DRG. Firstly, datasets were established by collecting accident data from police reports, link geometric and traffic data from a simulation network. Then, based on a concept we call "link neighbors", a model form was set up. The model performance was measured using the standard deviation of the model's outputs, and through model optimization, model parameters were determined."--Abstract.