The Costs of Traffic Accident Hotspots
| Autor: | Shu Liu, Kevin Koch, Felix Wortmann, Bernhard Gahr, Junhan Wen, Katherine M. Caves |
|---|---|
| Jazyk: | němčina |
| Rok vydání: | 2019 |
| Předmět: |
Standards
costing Natural resource economics high-accident-density locations Road accidents data analysis pattern clustering traffic engineering computing computer science road vehicles 03 medical and health sciences 0302 clinical medicine road traffic accident hotspots 0502 economics and business Hotspot (geology) Spatial databases 030212 general & internal medicine density-based spatial clustering of application with noise Law enforcement Activity-based costing traffic accident costs 050210 logistics & transportation Injuries Traffic accident 05 social sciences road traffic data mining DBSCAN Roads spatial data analysis data mining clustering road safety Switzerland |
| Zdroj: | ITSC |
| Popis: | Despite efforts to reduce them, traffic accidents continue to increase and bypass reduction targets. The costs of traffic accidents are enormous, killing 1.35 million people every year and costing 3% of most countries’ GDP. Recent research aims to target interventions at high-accident-density locations, called accident hotspots. New methods and technologies can systematically identify hotspots, but it remains unclear whether hotspots contribute to accident costs as well as volume. This paper investigates the monetary and human costs of accident hotspots. We analyze a dataset of all accidents from 2011 - 2017 in Switzerland. We identify hotspots, then analyze their contributions to traffic accident costs. We find that hotspot accidents are not different in monetary costliness or injury rates from non-hotspot accidents, so hotspots drive costs along with accident volume. However, hotspot accidents are less fatal, so hotspot targeting might not be best for fatalities. If hotspots are reduced to normal road conditions, total monetary costs can be reduced by up to 5% per year as a theoretical upper bound. Targeting the top 10% most frequent, costly, injurious, or deadly hotspots yeilds different results for different cost types, with accident number and monetary cost targets creating the highest reductions overall. |
| Databáze: | OpenAIRE |
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