INJURY PREDICTION MODELS FOR ONSHORE ROAD NETWORK DEVELOPMENT

Abstract

Integrating different modes of transport (road, rail, air and water) is important for port cities. To accommodate this need, new transport hubs must be built such as airports or sea ports. If ports are to grow, they must be accessible, a feature which is best achieved by building new roads, including fast roads. Poland must develop a network of fast roads that will provide good access to ports. What is equally important is to upgrade the network of national roads to complement fast roads. A key criterion in this case is to ensure that the roads are efficient to minimise time lost for road users and safe. With safety standards and safety management practices varying vastly across the EU, Directive 2008/96/EC of the European Parliament and of the Council was a way to ensure that countries follow procedures for assessing the impact of road projects on road safety and conduct road safety audits, road safety management and road safety inspections. The main goal of the research was to build mathematical models to combine road safety measures, i.e. injury density (DI) and accident density (DA), with road and traffic factors on longer sections, all based on risk analysis. The practical objective is to use these models to develop tools for assessing how new road projects will impact road safety. Because previous research on models to help estimate injuries (I) or injury density (DI) on long sections was scarce, the authors addressed that problem in their work. The idea goes back to how Poland is introducing procedures for assessing the effects of infrastructure on safety and developing a method to estimate accident indicators to support economic analysis for new roads, a solution applied in JASPERS. Another reason for the research was Poland’s insufficient and ineffective pool of road safety management tools in Poland. The paper presents analyses of several models which achieved satisfactory results. They are consistent with the work of other researchers and the outcomes of previous research conducted by the authors. The authors built the models based on a segmentation of national roads into sections from 10 to 50 km, making sure that they feature consistent cross-sections and average daily traffic volumes. Models were built based on the method described by Jamroz (Jamroz, 2011). Using the available road traffic volume data, each section was assigned variables defining geometric and traffic features. Based on studies conducted on road sections, the variables were either averaged over the entire length of the section or calculated as a percentage of the variable occurring over the entire length: related to traffic volume, roadside environment or cross section