AI News, Japan’s Upgraded Mobile Mapping Technology Aims to Make Autonomous Driving Safer

Japan’s Upgraded Mobile Mapping Technology Aims to Make Autonomous Driving Safer

A consortium of 15 Japanese automakers andmanufacturers that make components and systems for cars—including Toyota, Honda and Nissan, as well as Mitsubishi Electric, map makers, and others—have come together to create detailed, high-definition 3D maps to help usher in safe autonomous driving.

As the vehicle cruises atspeeds of around 40 km an hour, the system uses a laser-scanning point cloud technique to gather 3D positioning data of roadside features such as traffic signals, road signage, and lane markings.

“The MMS 3D maps will provide such additional information as noise barriers, lane divisions and their widths and surface conditions,as well as the location of traffic lights, road signs and other useful information to help improve the safety of autonomous driving,”says Kuriaki,

The system, which is gathering the myriad bits of information needed to subsequently allow vehicles to traverse Japan’s roads without human intervention,is designed to be operated by a person with a notebook PC in the passenger seat.

“Some special specification versions of our MMS have already been applied to inspection of tunnel linings and road surface conditions,” says Kuriaki.“And we are also studying how to apply the technology to other fields, such as inspection of railway tracks and underground areas.” With Mitsubishi ready to export its road-scanning technology, it can expect to compete with Google in the United States, and with several companies in Europe.


Using the point cloud data acquired with the MMS, and software (MMS browser) that generates triangulated irregular network (TIN) models quickly and accurately, the visual distance of the road can be confirmed.

Automotive navigation system

An automotive navigation system is part of the automobile controls or a third party add-on used to find direction in an automobile.

Dead reckoning using distance data from sensors attached to the drivetrain, a gyroscope and an accelerometer can be used for greater reliability, as GPS signal loss and/or multipath can occur due to urban canyons or tunnels.

Mathematically, automotive navigation is based on the shortest path problem, within graph theory, which examines how to identify the path that best meets some criteria (shortest, cheapest, fastest, etc.) between two points in a large network.

Vendors who used this format include: The Navigation Data Standard (NDS) initiative, is an industry grouping of car manufacturers, navigation system suppliers and map data suppliers whose objective is the standardization of the data format used in car navigation systems, as well as allow a map update capability.

The NDS effort began in 2004 and became a registered association in 2009.[14] Standardization would improve interoperability, specifically by allowing the same navigation maps to be used in navigation systems from 20 manufacturers.[15] Companies involved include BMW, Volkswagen, Daimler, Renault, ADIT, Aisin AW, Alpine Electronics, Navigon, Navis-AMS, Bosch, DENSO, Mitsubishi, Harman International Industries, Panasonic, Preh Car Connect formerly TechniSat, PTV, Continental AG, Clarion, Navteq, Navinfo, TomTom and Zenrin.

Many original systems also contain a gyrocompass and/or an accelerometer and may accept input from the vehicle's speed sensors and reverse gear engagement signal output, thereby allowing them to navigate via dead reckoning when a GPS signal is temporarily unavailable.[16] However, the costs can be considerably higher than other options.

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