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Positioning reference
Photo: Magnus Herbertsson

Validation of Mapping and Localization for Autonomous Vehicles

The goal of the project is to create a varied, validated and open dataset in the form of an HD-map which should be available for future research. This will enable academy, developers and researchers to use a HD-map with known measurement uncertainties, together with collected sensor data for future research in for example decision algorithms.

The goal of VAMLAV is to develop a high definition map (HD-map) of the test track Rural Road at AstaZero based on the existing infrastructure. Data collection will be made under all seasons, time of day and in different weather conditions to achieve a varied dataset.

Validation of the HD-map will be done by using road signs and rails as references in the map creation. The reference objects will then be monitored during the project to estimate their short- and long-term stability. The monitoring of the objects will be performed with measurement technology for large volumes such as GNSS and laser systems. These systems typically have lower measurement uncertainty than vehicle sensors as they benefit from being stationary.

To go one step further, and to gain a better understanding of how the objects stability will affect the map, at least one purpose-built reference object will be constructed. It will be designed for long-term stability, possibility of vehicle sensor validation and will be monitored more closely. This will establish a primary reference which can be used to validate both individual sensors, the vehicle positioning system and possible HD-map drift.

After the project has been completed VAMLAV plans to enable other parties to contribute to the dataset created during the project, to promote research in map creation and data sharing. This could benefit research in areas such as Mobility as a Service, Path Planning and Crowdsourcing.


Summary

Project name

VAMLAV

Status

Active

Region

Västra Götaland Region

RISE role in project

Participant

Project start

Duration

2 years

Total budget

11 MSEK

Partner

AI Innovation of Sweden, Zenseact

Funders

Vinnova - Traffic safety and automated vehicles - FFI

Project website

Coordinators

Project members

Supports the UN sustainability goals

9. Industry, innovation and infrastructure
Carl-Henrik Hanquist

Contact person

Carl-Henrik Hanquist

Ingenjör

Read more about Carl-Henrik

Contact Carl-Henrik

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