Toyota Research Institute-Advanced Development (TRI-AD), Maxar Technologies, and NTT Data announced they will collaborate on a proof of concept building automated high-definition (HD) maps for autonomous vehicles using high-resolution satellite imagery.
According to TRI-AD analysis, currently HD maps cover less than 1% of the global road network, and there is a need to broaden the coverage of urban areas and local roads before autonomous vehicles can become a mainstream mobility technology. The company says that an HD map created from the accurate satellite imagery allows the driving software to compare multiple data sources and signal the car to take action to stay safe.
In this proof of concept, the three companies will work together to process satellite imagery into vehicle-friendly HD maps. Leveraging Maxar's cloud-based Geospatial Big Data platform (GBDX), imagery from Maxar's optical satellite imagery library will be fed into NTT Data’s specialized algorithms using artificial intelligence to extract the necessary information to generate the detailed road network. Based on the above information, TRI-AD will make HD maps available for delivery from TRI-AD's cloud into Toyota test vehicles. The group is focusing first on creating an automated HD map for a predefined area of the Tokyo metropolitan region, opening up the future possibility of supporting automated mobility on all roads.
Mandali Khalesi, Vice President, Automated Driving at TRI-AD, said, "Recent advances in electronics and aerospace engineering are leading to higher resolutions and more frequent updates of global imagery from space-based assets. Additionally, machine learning is helping automate the discovery and integration of semantic relationships between road elements within image data. We're excited to collaborate with Maxar and NTT Data to revolutionize automated driving mobility for all."