Reducing accidents by improving roads - Demonstration on TARVA evaluation tool Harri Peltola VTT Technical Research Centre of Finland Harri.Peltola@vtt.fi
2 How to use safety evaluation tools? To find the dangerous locations: - that need road improvements most urgently - where road users should be warned To help in selecting the most appropriate safety measures To evaluate the safety effects of roads improvements (or building up new roads) To make cost-benefit analyses of road improvements To enhance transfer of traffic safety knowledge between countries
3 Estimating safety effects of road improvements Accidents after a measure= CMF(s) * Accidents if no measures are implemented CMF = Crash Modification Function (e.g. 0,9 = 10% reduction). Internationally good estimates available. Accidents if no measures are implemented = a prediction that needs to be done nationally. Accident history alone is very bad prediction of the accidents if no measures are implemented. Best practice prediction: combining accident model and accident history estimates using Empirical Bayesian method.
4 Evaluation of safety effects of road improvements Injury accidents on a road section (5 years) Average accident rate and its variation on a road section Current number Change in safety of accidents situation (1 (2 TARVA= A TOOL FOR ESTIMATION OF TRAFFIC SAFETY EFFECTS OF ROAD IMPROVEMENTS USING IMPACT COEFFICIENTS Forecast of the number of accidents Measure and its impact coefficient Accident reduction Average accident severity in road conditions in question and its change 1) Reliable estimate of current safety situation 2) For example, traffic or land use change Traffic fatality reduction
5 Results from the safety evaluation tool, TARVA Accidents if no measures are implemented: injury accidents, fatalities Safety situation after the measures Safety effects of each measure and measures all together Costs of the road improvements Effectiveness of each measure and measures all together
6 All Finnish public roads Different versions of TARVA about 72 000 km, in Finnish language Significant Lithuanian roads about 21 000 km, in English/Lithuanian languages All highway-rail level crossings on Finnish state rails about 3 000 level crossings, in Finnish/English languages E18 (in Russia road M10), St. Petersburg Finnish border and St. Petersburg Ogonki Pargalova Tolokonnikova (A122) a demo on about 85 km to be demonstrated now
7 Building up a short demo, Tarva RU Review of the available road, traffic and accident data Building up the database homogenous road sections Simple injury accident and fatality (killed people) models, (mileage, road, speed limit) Accident model and accident history estimates combined using statistical methods Translation of key phrases Demonstration/Test use
8 Accident numbers and risks on demo roads Number of accidents in 2009 2011 Section Injury accidents Fatalities Road length, km Vehicle Ped+Bic (1) Vehicle Ped+Bic (1) M10 71,9 173 23 68 14 A122 13,0 126 16 33 7 Total 84,8 299 39 101 21 Mileage, Accident risk per vehicle mileage (2) million Injury accidents Fatalities Road km/year Vehicle Ped+Bic (1) Vehicle Ped+Bic (1) M10 656 8,8 1,2 3,5 0,7 A122 132 31,7 4,0 8,3 1,8 Total 788 12,6 1,6 4,3 0,9 (1) Pedestrian and bicycle accidents (2) Accidents or killed people/100 million vehicle kilometres
9 Rough safety comparison between countries Accident risk per vehicle mileage (2) Injury accidents Fatalities Country Vehicle Ped+Bic (1) Vehicle Ped+Bic (1) Russia 12,6 1,6 4,3 0,9 Lithuania 8,2 2,7 1,9 0,7 Finland 4,4 0,2 1,0 0,1 (1) Pedestrian and bicycle accidents (2) Accidents or killed people/100 million vehicle kilometres
10 Demonstration on Tarva RU Only two road sections, 85 km Simple models, accidents in 2009 2011 Safety measures and their impact coefficients as in Lithuanian Tarva, Tarva LT A link to the Tarva RU demo: http://tarvaru.myapp.info/tarvadb/tarva/tarva.html Also an accident database analysis tool ONHA is available A link to the ONHA (Finnish or Lithuanian data): http://onha.myapp.info/onha2/onha-client/onhaclient.html
11 An example: Accident type distribution of casualty accidents and fatalities in 1991 2012 30 27,3 26,0 25 24,4 20 15 16,8 Percentage 10 5 3,9 10,1 3,4 7,4 8,0 2,1 5,4 10,5 9,6 7,2 5,3 5,5 4,3 4,3 10,0 8,6 0 0 Same direction, no turning 1 Same direction, turning 2 Opposite directions, no turning 3 Opposite directions, turning 4 Crossing, no turning 5 Crossing, turning 6 Pedestrian on zebra crossing 7 Pedestrian, non zebra 8 Running off road 9 Other accident Killed people 3,9 3,4 27,3 2,1 10,5 4,3 4,3 9,6 26,0 8,6 Casualty accidents 10,1 7,4 8,0 5,4 16,8 7,2 5,3 5,5 24,4 10,0 Accident type
12 Thank you! Questions? Injury accidents on a road section (5 years) Average accident rate and its variation on a road section Current number Change in safety of accidents situation (1 (2 Forecast of the number of accidents Measure and its impact coefficient Accident reduction Average accident severity in road conditions in question and its change 1) Reliable estimate of current safety situation 2) For example, traffic or land use change Traffic fatality reduction More information: harri.peltola@vtt.fi Mobile: +358 40 506 9064