Autonomy relies on GNSS/INS

September 30, 2019  - By

In transportation and machine control

It’s hard to overstate the importance of inertial sensors in the transportation and machine control markets. For the second year, using inertial navigation systems (INS) to augment positioning was selected by the most respondents (43%) as the best additional solution for positioning in GPS/GNSS-challenged environments.

Inertial measurement units are based on multi-axis combinations of precision gyroscopes, accelerometers and magnetometers using algorithms to determine location, direction and position. Other tech used to increase positioning accuracy includes signals of opportunity (cellular, radio, TV), visual indicators (such as lidar) and ultra-wideband.

Automakers are pushing hard to get autonomous vehicles on our roads and highways. Nissan and Renault (with Microsoft) plan to have 10 vehicles on sale by 2020 with “significant autonomous functionality.”

Ford plans to roll out autonomous vehicles by 2021, and Hyundai is targeting them for the highway by 2020 and urban driving by 2030. While industry experts debate the time frame, it’s clear autonomous vehicles are coming.

Every Tier 1 automaker has an autonomous navigation program, along with heavyweights such as Google, Apple an Amazon. Many automakers are teaming with tech companies on R&D, such as GM with Lyft, and BMW with Intel and Mobileye. Others are teaming with each other —Volkswagen and Ford partnered to acquire AI startup Argo. Daimler has joined Volvo to invest in the platooning concept, connecting trucks through wireless signals.

Stages of Autonomy. The move to autonomous won’t be a sudden jump, but will take place in incremental steps. Formerly only offered on luxury autos such as the Tesla or Mercedes, Honda has introduced semi-autonomous advanced-driver assistance systems (ADAS) options on its entry-level Civic, offering lane-keeping, automatic braking, and adaptive cruise control functionality for the mass market.

Automakers rely on SAE International’s J3016 standard, which defines six levels of automation from Level 0 (no automation) to Level 5 (full vehicle autonomy). The pivotal change occurs between Levels 2 and 3, when responsibility for monitoring the driving environment shifts from the driver to the system.

Chart: GPS World

Chart: GPS World

At Level 1 (driver assistance) is cruise control.

Level 2 (partial automation) includes Audi Traffic Jam Assist, Cadillac Super Cruise, Mercedes-Benz Driver Assistance Systems, Tesla Autopilot and Volvo Pilot Assist.

Level 3 (conditional automation) puts the car in the driver’s seat, but prompts the driver to intervene in a difficult encounter (Audi Traffic Jam Pilot).

At Level 4 (high automation), the car operates without human input, but only under select conditions (road type, geographic area). For instance, the driver might manage all driving duties on surface streets then become a passenger as the car enters a highway.

At Level 5 (full automation), the driverless car can operate on any road and in any conditions a human driver could negotiate. There are no Level 5 autos yet, but Waymo is using a fleet of 600 Chrysler Pacifica hybrids to develop Level 5 tech for production.

Machine Control. Not having to deal as much with traffic, except to navigate to the work site, machines in agriculture and construction are much more autonomous than the family car.

For liability reasons, fully autonomous machines have yet to be approved for field work in the U.S. Nevertheless, manufacturers such as Case IH, New Holland, John Deere and Komatsu are continuing to push the tech, and most tractors sold in the U.S. today include auto-steering systems.

At construction sites, GNSS technology installed in bulldozers, excavators, graders and pavers increase productivity and provide situational awareness to operators. GNSS increases the efficiency and accuracy of these machines, with the input used in task management, data management and theft-detection applications.

Operators rely on GNSS information to position the cutting edge of a bulldozer blade or an excavator bucket. GNSS enables comparison of the position against a 3D digital design to compute cut and fill amounts. Display systems provide the operator with the visual information to manually move the machine’s blade or bucket for highest accuracy.

Chart: GPS World

Chart: GPS World


About the Author: Tracy Cozzens

Senior Editor Tracy Cozzens joined GPS World magazine in 2006. She also is editor of GPS World’s newsletters and the sister website Geospatial Solutions. She has worked in government, for non-profits, and in corporate communications, editing a variety of publications for audiences ranging from federal government contractors to teachers.