Automated Urban Parking and Driving

Project Information

UP-Drive

Grant agreement ID: 688652

DOI

10.3030/688652

Project closed

EC signature date 10 November 2015

Start date 1 January 2016

End date 31 December 2019

Funded under

• INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT)

Total cost

€ 7 604 893,75

EU contribution

€ 4 671 896,25

Coordinated by

VOLKSWAGEN AKTIENGESELLSCHAFT
Germany

Periodic Reporting for period 3 - UP-Drive (Automated Urban Parking and Driving)

Reporting period: 2018-07-01 to 2019-12-31

Summary of the context and overall objectives of the project

The project UP-Drive aims at pushing the state of the art of automated driving and focuses on urban environments. Automotive experts expect the automated driving technology to radically improve the safety, comfort and affordability of individual mobility. Whilst many driver assistance systems - addressing mainly highway-like environments - are being introduced into the market and successively propagated from the premium car segment down to economy vehicles, automation of urban traffic remains an open research topic. The main goal of UP-Drive is therefore to push forward the perception, localization and reasoning abilities of autonomous vehicles. In the course of the project, we will build a prototype car system capable of driverless operation in complex urban environments. Our focus is placed on residential areas and speeds up to 30 km/h.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

During the second period, the project has focused on building up the second vehicle platform and bringing closure to the first development and integration cycle in terms of environment perception, life-long localization and mapping, scene understanding and decision-making and navigation. Integration and testing of all relevant components have been successfully completed at a system level

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

Project has already provided novel contributions to the fields of perception, localization, scene understanding and motion planning for automated vehicles. Further developments and contributions are expected in the final phase of the project. We believe that such contributions will eventually lead to turning the vision of automated vehicles into reality and thus to radical improvement of the safety, comfort and affordability of individual mobility.

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