REM 2030 driving profiles database

In the context of the project REM 2030, the Fraunhofer Institute for Systems and Innovation Research has been collecting primary data of driving profiles in commercial traffic since June 2011. The REM 2030 driving profiles database currently contains 522 driving profiles of commercially licensed vehicles in Germany and is continuously extended.

Codebook

The codebook explains all relevant variables and data formats of the database.

Sample files

The following sample files are an extract from the complete driving profiles database. The format of the database corresponds to the formatting of the sample files (in csv format).

Ordering of the data

You can order the database by filling out the order form.

After your order you will obtain the complete driving profiles database via login data that will be provided to your provided email address. In general, the database is free of charge if it is used for non-commercial purposes in research and education. However, a nominal fee is imposed if commercial use of the database is intended. In both cases, the use of the database is bound to stipulations and is only allowed with the approval of the data owner.

If you are already registered, please log in here.

Detailed description

With a share of 60% of the registration of new cars in Germany, commercial traffic is a relevant first user group for electric vehicles. Furthermore, the driving performance of commercial traffic is often much higher than the driving performance of public traffic. For this reason, the Fraunhofer Institute for Systems and Innovation Research has been collecting primary data of driving profiles in commercial traffic since June 2011. The REM 2030 driving profiles database currently contains 500 driving profiles of commercially licensed vehicles in Germany that were collected over a longer recording period and it is continuously extended. The database aims at being representative for different kinds of commercial sectors and their use of vehicles. It contains information about the trips (incl. departure and arrival times, as well as the distance), the vehicle size and the economic sector (according to WZ 2008), in which the vehicle is used. Moreover, data about the size of the community, where the vehicle is licensed, has been collected. If available, additional details concerning the size of the company and the use of the vehicle are provided. By means of this data and battery charging simulations, it is possible to determine the feasibility and profitability of an ecological alternative for the analyzed vehicles in the given economic sectors.

Further Questions?

For further questions, please contact Simon Funke, Till Gnann or Patrick Plötz.

 


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