Skip to main content

Toyota developing new map generation system

To aid the safe implementation of automated driving, Toyota is developing a high-precision map generation system that will use data from on-board cameras and GPS devices installed in production vehicles. The new system will go on display at CES (Consumer Electronics Show) 2016 in Las Vegas from 6-9 January.
December 24, 2015 Read time: 3 mins

To aid the safe implementation of automated driving, 1686 Toyota is developing a high-precision map generation system that will use data from on-board cameras and GPS devices installed in production vehicles. The new system will go on display at CES (Consumer Electronics Show) 2016 in Las Vegas from 6-9 January.

Toyota's new system uses camera-equipped production vehicles to gather road images and vehicle positional information. This information is sent to data centres, where it is automatically pieced together, corrected and updated to generate high precision road maps that cover a wide area.

An understanding of road layouts and traffic rules (including speed limits and various road signs) is essential for the successful implementation of automated driving technologies. Additionally, high precision measurement of positional information requires the collection of information on dividing lines, curbs, and other road characteristics.

Until now, map data for automated driving purposes has been generated using specially-built vehicles equipped with three-dimensional laser scanners. The vehicles are driven through urban areas and on highways and data are collected and manually edited to incorporate information such as dividing lines and road signs. Due to the infrequent nature of data collection, maps generated in this manner are seldom updated, limiting their usefulness. Additionally, this represents a relatively cost-intensive method of gathering data, due to the need to manually input specific types of data.

Toyota's newly developed system uses automated cloud-based spatial information generation technology, developed by Toyota Central R&D Labs, to generate high precision road image data from the databanks and GPS devices of designated user vehicles. While a system relying on cameras and GPS in this manner has a higher probability of error than a system using three-dimensional laser scanners, positional errors can be mitigated using image matching technologies that integrate and correct road image data collected from multiple vehicles, as well as high precision trajectory estimation technologies. This restricts the system's margin error to a maximum of 5 cm on straight roads. By utilising production vehicles and existing infrastructure to collect information, this data can be updated in real time. Furthermore, the system can be implemented and scaled up at a relatively low cost.

To support the spread of automated driving technologies, Toyota plans to include this system as a core element in automated driving vehicles that will be made available in production vehicles by around 2020. While initial use of the system is expected to be limited to expressways, future development goals include expanding functionality to cover ordinary roads and assist in hazard avoidance. Toyota will also seek to collaborate with mapmakers, with the goal of encouraging the use of high precision map data in services offered by both the public and private sectors.

For more information on companies in this article

Related Content

  • Measuring the effectiveness of winter VMS
    August 5, 2013
    A survey into the effectiveness of weather-related variable message signs on a trans-mountain highway has some interesting results, as Alexis Bacelar told ITS Europe. A study in the Massif Central region of France evaluating the usefulness of winter weather warning signs has highlighted the effect of variable message signs on driver behaviour. During the winter of 2009-2010, road operator Massif Central Direction Interdépartementale des Routes (MC DIR) started installing bad weather-specific variable messag
  • ITS needs data highways
    November 18, 2014
    Transport and traffic data is on the increase but there must be an integrated data highway to derive the maximum ITS benefits, argues Deutsche Telekom. From public transport operators recording increasingly precise and comprehensive data on their vehicle’s position and driving behaviour to local authorities using RFID and video systems to control traffic on their streets and highways, the amount of traffic data is growing rapidly.
  • Top 5 trends in vision technology
    June 24, 2021
    Artificial intelligence and deep learning algorithms are among the major trends having an impact on road traffic enforcement, according to leading companies in the vision sector
  • Value of time – the key decider
    March 4, 2014
    The ‘value of time’ concept can be a vital decider in prioritising transport projects, as Lorenzo Casullo and Serbjeet Kohli of Steer Davies Gleave explain. How much do travellers value their time and how much would they be willing to pay for a better and faster transport option? For many years Steer Davies Gleave (SDG) has been collecting this type of information from thousands of people across the world as it researches travellers’ behaviour. And given the importance of this parameter for transport mo