Road Safety Assessment Considering the Expected Fatal Accident Density
Network-wide road safety assessment throughout the whole network is one of the four road infrastructure safety management procedures regulated by Directive 2019/1936/EC of the European Parliament and of the Council of 23 October 2019 Аmending Directive 2008/96/EC on Road Infrastructure Safety Manage...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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RTU Press
2020-06-01
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| Series: | The Baltic Journal of Road and Bridge Engineering |
| Subjects: | |
| Online Access: | https://bjrbe-journals.rtu.lv/article/view/3982 |
| Summary: | Network-wide road safety assessment throughout the whole network is one of the four road infrastructure safety management procedures regulated by Directive 2019/1936/EC of the European Parliament and of the Council of 23 October 2019 Аmending Directive 2008/96/EC on Road Infrastructure Safety Management and one of the methods for determining the direction of investment in road safety. So far, the implementation of the procedure has been lightly regulated and adapted using various road safety indicators. The paper describes the evaluation of road accident data that is one of the criteria for conducting a network-wide road safety assessment. Taking into consideration that networkwide road safety assessment is a proactive road safety activity, the paper proposes to conduct road safety assessment considering the expected fatal accident density. Such assessment makes it possible to assess the severity of accidents, and the use of the predicted road accident data on calculating the introduced road accident rate contributing to the prevention of accidents. The paper describes both the empirical Bayes method for predicting road accidents and the application of one of the road safety indicators – the expected fatal accident density – to determine five road safety categories across the road network. The paper demonstrates the application of the proposals submitted to Lithuanian highways using road accident and traffic data for the period 2014–2018. |
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| ISSN: | 1822-427X 1822-4288 |