Dyn TAG-RIM : a DRAG -type Structural Road Safety Model [ D emand for R oad use, A ccidents and their G ravity ] Ar

1. Dyn TAG-RIM :a DRAG-type Structural Road Safety Model[Demand for Road use, Accidents and their Gravity]Ariane Dupont-KiefferLaurence Jaeger

2. CONTENTS of the presentation • 1/ TAG belongs to the DRAG family • 2/ Structure and data of TAG • 3/ Main results INRETS

3. 1. TAG belongs to the DRAG models family • Any model investigating the road risk must be driven by 2 principles: • 1/ regarding the failure of the system of circulation as the origin of road risk and that is a random phenomenon; • 2/ as it is a random phenomenon whose central tendency depends on various factors (economic, climatic, etc.), it is necessary to develop a multivariate analysis of this central tendency [whether the data used are time series or cross sections, aggregate or disaggregate]. INRETS

4. 1. TAG belongs to the DRAG models family • How to analyse safety on road: the road fatalities are the result of a combination of 3 components: • DR-road demand , • A- the frequency of accidents and • G-the gravity of accidents. INRETS

5. TYPICAL MULTI-LEVEL STRUCTURE Damage Function: VI = DR .A . G • AlcoholSpeed Behaviour: Y ← ( --, --, Xy ) Risk Taking ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------- • Veh-km GAsoline • Veh-Km Diesal Demand Road: DR ← ( --, Y, Xdr ) • Exposure Risk • Fatal • Injury Accidents: A ← ( DR, Y, Xa ) Frequency Risk • Materiel • Mortality • Morbidity Gravity: G ← ( DR, Y, Xg ) Severity ======================================================And NOT: • Killed Victims ← ( DR, Y, Xa , Xdr , Xg , Xy) • Injured INRETS

6. 1. TAG belongs to the DRAG models family • One has to develop a two stages analysis: • An analysis of the exposure to road risk through the measure of mobility by type of users (cars, pick-up, trucks, coachs, motorised two-wheels and pedestrians if data are available), networks (highways, local roads where the number and the gravity of accidents are different) and environment (urban or non urban areas, what are the consequences of the urban sprawl on road demand and accidents); • An analysis of the risk itself: frequency and severity (and the substitution between injured and killed victims, ex: France where the number of killed is decreasing but the number of severe accidents is increasing : why ? How shall France plan its health policy in the long term taking account of this new fact?) INRETS

7. 1. TAG belongs to the DRAG models family • Modeling is necessary for analysing and estimating the weighted impact of the 4 groups of factors of risk, namely: • Infrastructure characteristics (separation between lines or not) • Vehicle characteristics (air bag, safety belt have impact on the gravity) • Driver behaviour (speed increasing or not when new legislative rules are implemented, alcohol drinking when driving) • Levels and nature of the activities that determine road demand (ex: the impact of the gravity is different when trucks are loaded with timber, fuel, or paper; ex: when the road demand increases in a context of economic growth, what is the impact on the frequency and the severity of accidents? Ex: what is the consequence of the increasing price of energy on road demand?) INRETS

8. 2. The TAG model - DRAG : national and regional models built up since 1984: Canada, Norway, Sweden, Belgium, Spain, Sweden, (Spain, Switzerland and Algeria: work in progress) - TAG : an econometric model for estimating the road risk for France for the 1957-1993 period (published in 1999) INRETS

9. 2. The TAG model • To explain the damage as a function of • Exposure to risk (mileage driven) • Risky behaviour (average inter-urban speed) • Risk of an injury accident (number of injury accidents) • The risk of injury (number of casualties per injury accident) Each of these dimensions becomes an element to be explained INRETS

10. 2. The TAG model • Two kinds of factors that may influence the performance of the road system: • Internal factors as the characteristics of vehicles, drivers and road infrastructure (ex: proportion of front-seat passengers in private cars who fasten their seat belt…surveys) • External factors (proportion of young drivers, prices, climatic system, govt system) INRETS

11. 2. The TAG model • The Tag model= a structure of • 7 non-linear , simultaneous equations • In which an endogenous variable of one equation appears as an explanatory variable of another equation (recursive model) INRETS

12. 2. The TAG model • The TAG model allows: • To identify the direct and indirect (via ceteris paribus assumption) effects of the explanatory variables of the road accident tool (through risk exposure and average speed); • To analyse the subsitution/compensation effects between the numbers of fatal and non-fatal injury accidents, or between the numbers of dead and injured INRETS

13. 2. The TAG model • Data=the monthly statistical series for: • The total mileage (computed via the KILOM model) • The average speed (harmonic average) (computed ex post by aggregating the data from surveys carried on the main road networks) • The numbers of accidents and casualties • from 1967 to 1993 (324 observations) • (actually updated to 2006) INRETS

14. Typical nation-wide data: France Vehicle-kilometers (Jan.1967-Dec. 1993) INRETS

15. Typical nation-wide data: France Injury accident frequency (Jan.1967-Dec. 1993) INRETS

16. France Typical nation-wide data: France Deaths per 100 injury accidents (Jan.1967-Dec. 1993) INRETS

17. 3. The TAG model: some results • Model of road transport demand: identifying factors affecting road demand and evaluating the direction and intensity of their effect; • Model of average speed • Analysis of the results by risk indicators • Analysis of the results by explanatory factor INRETS

18. 3. The TAG model: some results/road demand • Factors having a positive influence: • Home-to-workplace journeys (proxy=employment index), • the stock of private and commercial vehicles per unit of work, • the consumption of wine per adults (strong correlation between the frequency of social outings and the consumption of wine) • Temperatures • Holiday travel INRETS

19. 3. The TAG model: some results/road demand • Factors having a negative influence: • Technical inspections (1992) • Price of fuel • Proportion of small cars INRETS

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21. 3. The TAG model: some results/ average speed • Factors having a positive influence: • Motor vehicle price index (+0.2%) • Rate of safety belt wearing (+0.08%) • Proportion of motorway traffic (+0.07%) • Percentage of private motorcars rated at 11 fiscal horsepower or more (+0.06%) INRETS

22. 3. The TAG model: some results/average speed • Factors having a negative influence: • Laws relating to speed limits , both in urban (-2.9%) and the countryside (-2.5%) INRETS

23. 3. The TAG model: some results/risk indicator • Factors having a significant positive impacts on accidents (fatal and non-fatal injury accidents): • Average speed • Number of motorised two-wheelers • Total mileage • Industrial activity INRETS

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25. 3. The TAG model: some by explanatory factor • Incidence of road transport demand= an increase of 10% mileage has a significant impact on injury and fatal accidents • Risk taking (seat belts, wine consumption) • Structure of vehicle fleet INRETS

26. 4. Concluding remarks • Further developments - national level vs regional level; - combining models of LEVELS (time series data) and models of SHARES (cross-section data, panel data, surveys data) by a QDF (Quasi-Direct Format) procedure. INRETS

27. Typical Quasi-direct FormatProduct of:-- a model of Level [e.g. of all accidents in a region]-- by a Share (or Probability) model [e.g. by type of road]: INRETS

28. Concluding remarks • It is a work in progress (depending on the funds): • Data collection, especially at the disaggregated level; • International collaborations are required to discuss theoretical issues (aggregation…) through an international seminar (two meetings in 2007) INRETS

29. Thank you for your attention INRETS