Estimating the total mileage at the National Level for France 1990-2005 : KILOM 2 model Zehir Kolli Ariane Dupont.
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Estimating the total mileage and its evolution by types of vehicles is a corner stone of the understanding of the mobility at the national level ; estimating road demand and its externalitiies in terms of road risk and pollution
In France, we can estimate the road demand by two ways using the KILOM model and surveys as the NHS, Panels SECODIP and PARC AUTO, and also surveys on road sites.
1. Presenting the Kilom model: its aims, its conceptual architecture
2. Presenting the 5 modulus computing the monthly mileage at the National level: Fleet, Kilommoy, Conso, Fuel leak, Final modulus
3. The results for 1990-2005
What is estimated ?
A monthly estimation of the road demand i.e. the total mileage on any find of road networks and for all kind of road engines
For the whole French territory (excluding Corsica and the overseas territory
An estimation putting in balance fuel deliveries and actual consumption of fuel
An estimation for 1957 to 1994 by Laurence Jaeger as road risk exposure measurement for the TAG Model
An estimation for 1990 to 2005 (being updated to 2006) with a simplified architecture
For 5 categories of vehicles
1/ cars for personal and professional uses
2/ pick up weighted under 5 tones
3/ trucks weighted over 5 tones (a distinction being set up between the 5t to 10t lorries and the lorries over 10t)
4/ bus and coaches
5/ motorized two-wheels
KILOM 2 conceptual architecture
Two steps of computation
1/ to collect and compute the input series (annual and monthly)
2/ to compute the monthly estimation by 5 modulus (output series)
Fleet : CCFA for annual fleet + monthly registration
Kilommoy: CCTN for annual mileage, AFSA for monthly trucks mileage on higways, SECODIP for monthly mileage for light vehicles
Leak: CPDP, Oil bulletin, CCTN
Conso: SECODIP, Beauvais, CCTN, Ademe
1/ the FLEET modulus
2/ the KILOMMOY modulus which gives a seasonal index of mileage for each category of vehicles
3/ the leak modulus which computes the monthly correction of the fuel deliveries by the leak at the borders based on the monthly variation of prices
4/ the CONSO modulus
5/ the COMPUTATION modulus which gives a monthly mileage for each category of vehicles in France after calibration on fuel deliveries
Annual DATA for the 5 categories: CCTN
Monthly breakdown by computing seasonal coefficients with monthly data : SECODIP for cars and AFSA for trucks
Monthly breakdown of cars: Due to the fact that the Secodip data are not monthly but quaterly since 1995 we have computed infra-quaterly coefficient based on available data for before 1995 and assuming a stability of seasonal behaviour over time such as
Monthly breakdown of trucks: Due to the fact that the data are
annual from 1990 to 1991
Monthly from 1992 to 2002
Quaterly from 2003 to 2005
We have computed monthly coefficients for 1992-2002 and apply them to break down the series for the other years, according to the observed stability of the seasonal behavior of the series
Assumption : same seasonality for trucks and coaches
Fuel consumption at the National level =Livraisons - (Quantités sortantes – Quantités entrantes)
2 kinds of fuel: gasoline (price is weigthed according to the fleet size between super and super 95) and diesel
Variable to estimate : monthly fuel deliveries (CPDP data)
Explicative variables : Prices (Oil Bulletin data), Difference between French prices and fuel prices (oil bulletin data) in contant euros,temperature (CPDP-Météo France), evolution of the fleet,
Ѵ Ѵ12Logess=Ѵ Ѵ12 [μIpares + ξTemp + λd+ ρLog(Pxfess)]+ [Θ/Φ]*εt
Gasoline leaksIt represent in average 0,53% of all gasoline deliveries for the period 2000 to 2005. Elasticity price of deliveries 8,35% for gazoline.
Ѵ Ѵ12Logdies=Ѵ Ѵ12 [μIparc + ξTemp + λd+ ρLog(Pxfdies)]+ [Θ/Φ]*εt
Diesel escapesIt represents in average 0,37% of all diesel deliveries for the period 2000 to 2005. Elasticity price of deliveries 4,70% .