The technology is being displayed at the 2016 Consumer Electronics Show in Las Vegas next month and uses data from on-board cameras and GPS devices to gather road images and vehicle position information. This information is sent to data centres where it is used to create maps that cover a wide area and are said to be highly accurate.

Previously such information has been obtained using specially built vehicles equipped with 3D laser scanners, such as those run by Google, where the data needs to be manually edited to add information on road features such as kerbs, divides and signage. As this is also cost-intensive, data collection is infrequent and the maps are not updated regularly.

Toyota said there is a higher risk of error with a system that relies on cameras and GPS in this way, compared to one which uses 3D laser scanners, but positional errors can be mitigated by using image matching technologies that integrate and correct the road image data from multiple vehicles, as well as high-precision trajectory estimation technologies. This restricts the margin of error on straight roads to a maximum 5cm. By using production vehicles and existing infrastructure to collect information, this data can be updated in real time. It can also be implemented and scaled up at relatively low cost.

The carmaker added that it plans to include this system as a core element in the automated driving systems that will be available in production vehicles by around 2020. Initial use is expected to be limited to motorways but functionality will be expanded to cover ordinary routes.