1. Comparison of key parameters of EU WLTP database and WLTC version 5
Heinz Steven 1

2. Introduction
The WLTP development methodology was originally proposed by Japan. A reviewed version (reviewed by UK, JRC and Steven) was discussed and agreed in the DHC subgroup meeting at 11. and 12. January 2011 in Geneva (see WLTP-DHC-06-03).
The basis of the cycle development was the derivation of a reference database consisting of representative in-use data from the participating regions weighted by statistics on light duty vehicle use (annual mileage) in the regions.
The overall process of the driving cycle development is described in figure 1. Two main elements were essential for the derivation of the reference database:
Collection of in-use driving data,
Collection of statistics on light duty vehicle use 2

3. Introduction Task of DHC Group Work See page 6 of WLTP-DHC-06-03
Figure 1 3

4. European in-use data
As a consequence, initiatives in the EU-WLTP mirror group were started in order to collect the necessary data and the member states were asked for support.
Concerning the in-use data the following member states contributed by the delivery of in use-data:
Belgium (2 different datasets, 22 vehicles),
France (2 different datasets, 42 vehicles),
Sweden (6 M1 and 2 N1 vehicles),
UK (12 N1 vehicles).
This data was completed by data collected on behalf of JRC in the following member states:
Germany (8 different vehicles),
Italy (8 different vehicles), 4

5. European in-use data Poland (9 different vehicles),
Slovenia (17 different vehicles),
Spain (10 different vehicles),
UK (10 different vehicles)
In addition to that some in-use data from Switzerland was also included.
It is important to mention that all this data is customer data and that it was delivered from the participating partners as being representative for the member state.
The mileage of the in-use data after deletion of faulty or inconsistent data is listed in table 1 together with corresponding data from other regions in the world.
Europe has by far the highest mileage share and Belgium and France are the main contributors within Europe. 5

6. European in-use data
Table 1a 6

7. European in-use data
Table 1b 7

8. EU WLTP database
The EU WLTP database covers 9 of the 27 member states representing 82% of the total mileage. The total mileage of the in-use database is more than km. This is by far the biggest database so far, used for type approval cycle development.
It was also agreed in the EU-WLTP mirror group, to use the mileage statistics from TREMOVE for the derivation of the necessary weighting factors.
TREMOVE is a policy assessment model, designed to study the effects of different transport and environment policies on the emissions of the transport sector in the EU.
The model estimates for policies as road pricing, public transport pricing, emission standards, subsidies for cleaner cars etc., the transport demand, modal shifts, vehicle stock renewal and scrappage decisions as well as the emissions of air pollutants and the welfare level (see 8

9. EU WLTP database
It was also agreed in the EU-WLTP mirror group, to use the mileage statistics from TREMOVE for the derivation of the necessary weighting factors
For the establishment of a unified EU database as well as
For the establishment of the worldwide reference database.
The agreed approach was as follows:
The weighting factors for the unified EU database were established by a 50% contribution of the delivered in-use data mileage and another 50% contribution of the individual TREMOVE member state mileage for light duty vehicles.
The weighting factors for the worldwide reference database are based on TREMOVEs annual mileage for the EU 27 member states and Switzerland. 9

10. EU WLTP database
For both cases 2005 was chosen as reference year. An excel file with this statistics was made available to all DHC subgroup members.
In order to double-check the analysis results for the EU in-use data, a re-analysis of the data from the different contributors was performed recently, using the original but consistency checked data rather than the short trip and stop phase databases.
This data contains also all incomplete short trips that do not start from standstill and/or go not back to standstill.
In order to get a first overview, all data was analysed as it is, without further speed class or road category binning.
The results are summarised in table 2. The corresponding values for the WLTC version 5.3 are shown for comparison. 10

11. Key parameter of the EU in-use data
Table 2 11

12. EU WLTP database
The average speeds vary between 27,9 km/h (Poland) to 62,2 km/h (2nd dataset from Belgium), but the average values for the biggest data contributors (> km) are close to or higher than the averages over the whole dataset (see figure 2).
The same accounts for the stop percentages, but in this case the biggest contributors have values close to or lower than the averages (see figure 3).
Average speed and stop percentage of WLTC version 5.3 fits quite good to the average values for the EU database.
The weighting factors for the combined approach are shown in figure 4. 12

13. Average speeds
Figure 2 13

14. Stop percentages
Figure 3 14

15. Mileage share comparison for the EU database
Figure 4 15

16. EU WLTP database
More than 3/4 of the in-use database mileage was delivered with road category indicators representing urban, rural and motorway.
Table 3 shows the key values of the database for the 3 road categories.
The average speed values and stop percentages for the French data are close to the averages of the whole database, except for the motorway part, while the average speeds in the Italian database are higher and the stop percentages are lower than the averages of the whole database.
There is no significant difference between the overall key values (v_ave, p_stop) for the whole database and that part of the database with road category indicators. 16

17. Key parameter for 3 road categories
In [1] Michel Andre, one of the most experienced French traffic experts, states in paragraph 3.2 „National data“, „France“ in table 35 the following average speeds per road category:
Urban: 23 km/h, rural: 56 km/h, motorway: 108 km/h.
Table 3 17

18. Speed class shares within a road category
It was agreed in the DHC subgroup to base the cycle development on the so called „short trip and stop phase“ analysis.
A short trip is a speed sequence starting from standstill and going back to standstill.
A stop phase is the time period between two consecutive short trips.
The speed phase classification was based on the maximum speed of a short trip as follows:
Low: v_max <= 60 km/h,
Medium: 60 km/h < v_max <= 80 km/h,
High: 80 km/h < v_max <= 110 km/h,
Extra high: v_max > 110 km/h. 18

19. Speed class shares within a road category
For the WLTC the speed phase durations are set in a way so that the distances represent the mileage distribution of the reference database.
The in-use data with road category indicators was used for the conversion of urban, rural and motorway into the agreed speed class system low, medium, high and extra high on the basis of these short trips.
Tables 4a and 4b show exemplarily the mileage and duration values for the 2 datasets from France distributed over the 3 road categories and the 4 speed classes within the road categories.
It must be mentioned that a significant percentage of short trips belonging to the „urban“ category are classified as extra high speed short trips. This reflects the fact that some „hybrid“ short trips consist of a predominantly urban speed trace but contains also an extra urban part. 19

20. Speed class shares for different road categories
Table 4a 20

21. Speed class shares for different road categories
Table 4b 21

22. Speed class shares within a road category
On the other hand, short trips belonging to congested traffic on motorways are classified as low speed short trips (see table 6, Belgium 1).
That means, the two classification systems road category versus speed phases cannot be compared directly.
The following tables (table 5 to table 8) show the results of the transformation from urban, rural, motorway to low, medium, high and extra high in terms of mileage percentages.
Table 9 and figure 5 show the summary for all contributing member states.
There are significant differences between the different data sets but one cannot conclude that extra high speed driving is overrepresented and low speed driving is underrepresented in the WLTC version 5.3.
This is especially valid for the French and Italian data. 22

23. Speed class shares for different road categories
Table 5 23

24. Speed class shares for different road categories
Table 6 24

25. Speed class shares for different road categories
Table 7 25

26. Speed class shares for different road categories
Table 8 26

27. Speed class shares for different member states
Table 9 27

28. Speed class shares for different member states
Figure 5 28

29. Speed class key values
The transformation of the data from urban, rural and motorway into low, medium, high and extra high results in average speed and stop percentage values for the different data sources as listed in table 10.
Once again there is a good agreement between the average database values and the WLTC 5.3 values and the values for France and Italy are also close to the WLTC values. 29

30. Speed class key values for different member states
Table 10 30

31. Summary and Conclusion
The basis of the WLTP cycle development was the derivation of a reference database consisting of representative in-use data from the participating regions weighted by statistics on light duty vehicle use (annual mileage) in the regions.
As a consequence, initiatives in the EU-WLTP mirror group were started in order to collect the necessary data and the member states were asked for support.
The EU WLTP in-use database covers 9 of the 27 member states representing 82% of the total mileage. The total mileage of the in-use database is more than km. This is by far the biggest database so far, used for type approval cycle development.
It is important to mention that all this data is customer data and that it was delivered from the participating partners as being representative for the member state. 31

32. Summary and Conclusion
It was also agreed in the EU-WLTP mirror group, to use the mileage statistics from TREMOVE for the derivation of the necessary weighting factors.
In order to double-check the analysis results for the EU in-use data, a re-analysis of the data from the different contributors was performed recently, using the original but consistency checked data rather than the short trip and stop phase databases.
Average speed and stop percentage of WLTC version 5.3 fits quite good to the average values for the EU database.
More than 3/4 of the in-use database mileage was delivered with road category indicators representing urban, rural and motorway. 32

33. Summary and Conclusion
The average speed values and stop percentages for the French data are close to the averages of the whole database, except for the motorway part, while the average speeds in the Italian database are higher and the stop percentages are lower than the averages of the whole database.
There is no significant difference between the overall key values (v_ave, p_stop) for the whole database and that part of the database with road category indicators.
The average speeds for the French in-use data for the road categories urban, rural and motorway fit quite good to corresponding values for France, reported in a deliverable of the ARTEMIS project.
Therefore, it can be concluded that the delivered in-use data was appropriate for the cycle development. 33

34. Summary and Conclusion
The in-use data with road category indicators was used for the conversion of urban, rural and motorway into the agreed speed class system low, medium, high and extra high on the basis of these short trips.
It must be mentioned that a significant percentage of short trips belonging to the „urban“ category are classified as extra high speed short trips. This reflects the fact that some „hybrid“ short trips consist of a predominantly urban speed trace but contains also an extra urban part.
On the other hand, short trips belonging to congested traffic on motorways are classified as low speed short trips.
That means, the two classification systems road category versus speed phases cannot be compared directly. 34

35. Summary and Conclusion
It cannot be concluded from the analysis results that extra high speed driving is overrepresented and low speed driving is underrepresented in the WLTC version 5.3.
On the contrary, there is a good agreement between the average database values and the WLTC 5.3 values and the values for France and Italy are also close to the WLTC values. 35

36. Literature [1] Michel ANDRÉ, Catherine FANTOZZI, Nadine ADRA,
Development of an approach for estimating the pollutant emissions from road transport at a street level, ARTEMIS - Assessment and reliability of transport emission models and inventory systems, Report INRETS-LTE 0628 July 2006. 36

37. Thank you for your attention!
End
Thank you for your attention! 37