Abstract
Original language | English |
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Publication status | Published - 2013 |
MoE publication type | Not Eligible |
Event | 17th IRF World Meeting & Exhibition - Riyadh, Saudi Arabia Duration: 9 Nov 2013 → 13 Nov 2013 |
Conference
Conference | 17th IRF World Meeting & Exhibition |
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Country | Saudi Arabia |
City | Riyadh |
Period | 9/11/13 → 13/11/13 |
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More effective road safety work with proper tools. / Peltola, Harri; Rajamäki, Riikka.
2013. 17th IRF World Meeting & Exhibition, Riyadh, Saudi Arabia.Research output: Contribution to conference › Other conference contribution › Scientific
TY - CONF
T1 - More effective road safety work with proper tools
AU - Peltola, Harri
AU - Rajamäki, Riikka
PY - 2013
Y1 - 2013
N2 - Developing and using proper road safety evaluation tools is essential to further enhance road safety work. These are also requested e.g. by a directive from the Member States of the European Union. However, science-based safety evaluation tools are not widely available or used. Comparing different ways of predicting future accidents revealed that accident model estimates combined with accident record gives essentially better predictions than those based on accident history alone. In fact, estimation based on accident record only seems to give in many cases predictions that are not worth more than a guess. Hence, TARVA, one example of tools will be demonstrated. The aim of it is to provide reliable current safety estimates as well as predictions of safety effects of improvements for roads and level crossings. Separate versions have been created for Lithuanian and Finnish roads and Finnish level crossings. Principles and use of the tool will be explained, including Finnish and Lithuanian examples. Using the tool one can rank the safety of existing road network or level crossings. Ranking is done using the expected accident numbers received by combining accident history data with accident prediction model data. In addition to comparing the safety of individual roads, examples will be presented on comparing road safety among areas. In addition to selecting roads to be improved, the tool can be used for estimating safety effects of improvements. Crash modification factors (CMF) of about 100 safety measures have been defined based on internationally recognised safety research results. Using the expected accident figures, CMF’s and the implementations costs of measures, one can estimate the cost-effectiveness of alternative ways of improving safety.
AB - Developing and using proper road safety evaluation tools is essential to further enhance road safety work. These are also requested e.g. by a directive from the Member States of the European Union. However, science-based safety evaluation tools are not widely available or used. Comparing different ways of predicting future accidents revealed that accident model estimates combined with accident record gives essentially better predictions than those based on accident history alone. In fact, estimation based on accident record only seems to give in many cases predictions that are not worth more than a guess. Hence, TARVA, one example of tools will be demonstrated. The aim of it is to provide reliable current safety estimates as well as predictions of safety effects of improvements for roads and level crossings. Separate versions have been created for Lithuanian and Finnish roads and Finnish level crossings. Principles and use of the tool will be explained, including Finnish and Lithuanian examples. Using the tool one can rank the safety of existing road network or level crossings. Ranking is done using the expected accident numbers received by combining accident history data with accident prediction model data. In addition to comparing the safety of individual roads, examples will be presented on comparing road safety among areas. In addition to selecting roads to be improved, the tool can be used for estimating safety effects of improvements. Crash modification factors (CMF) of about 100 safety measures have been defined based on internationally recognised safety research results. Using the expected accident figures, CMF’s and the implementations costs of measures, one can estimate the cost-effectiveness of alternative ways of improving safety.
M3 - Other conference contribution
ER -