Vaisala Xweather Case Studies Embark's Autonomous Trucks Overcome Weather Challenges with Advanced On-Road Testing

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	Embark's Autonomous Trucks Overcome Weather Challenges with Advanced On-Road Testing Vaisala Xweather

Embark's Autonomous Trucks Overcome Weather Challenges with Advanced On-Road Testing

Vaisala Xweather

Technology Category	Robots - Autonomous Guided Vehicles (AGV) Sensors - Autonomous Driving Sensors
Applicable Industries	Automotive Transportation
Applicable Functions	Logistics & Transportation Quality Assurance
Use Cases	Autonomous Transport Systems Experimentation Automation
Services	Testing & Certification
Challenge	Road logistics operators in the United States often face revenue loss due to the inability to operate in severe weather conditions, particularly in Northern states. Autonomous trucks, such as those developed by Embark Trucks, have the potential to transform the industry, but they face their own challenges. Autonomous vehicles (AVs) rely on sensing technologies like LiDAR, radar, and optical cameras to collect visual data from their surroundings, which is then combined with maps and algorithms to make decisions. However, even the most advanced sensing technology can struggle with accurate detection and interpretation of road conditions in adverse weather. Embark needed not only on-road testing but also accurate and complete historical weather datasets to fully understand the implications of such conditions on its self-driving solution. Read More
About Customer	Embark Trucks is the longest-operating self-driving truck program in the United States, having been a forerunner in autonomous vehicle technology for trucks since 2016. Their software powers safe, commercially viable autonomous long-haul trucks, trusted by investors, Fortune 500 shippers, and some of the nation’s largest carriers. Embark's autonomous trucks use sensing technologies such as LiDAR, radar, and optical cameras to collect visual data from the surrounding environment, which is then combined with maps and algorithms to make decisions while on the road. Read More
Solution	Embark turned to an AerisWeather Flex subscription to obtain granular weather data, pulled on location-based intervals frequently throughout the day. This allowed Embark to develop a comprehensive weather model comprised of over eight billion historical weather data points dating back over 10 years for major routes across the United States. The model increased Embark's confidence in its autonomous trucks' ability to assess and react to the impact of snow at a lane level. The data was also combined with highway requirements, such as the requirement for highways to be cleared within three hours of snow stopping. This enabled Embark to estimate when highways would be cleared at any given location. Trucks were test-driven in snowy conditions and data from the truck’s sensors was cross-referenced with AerisWeather’s interpolated conditions, allowing Embark to determine the possible business implications of snowy conditions. Read More Log in to view content
Contents

Technology Category

Robots - Autonomous Guided Vehicles (AGV)

Sensors - Autonomous Driving Sensors

Applicable Industries

Automotive

Transportation

Applicable Functions

Logistics & Transportation

Quality Assurance

Use Cases

Autonomous Transport Systems

Experimentation Automation

Services

Testing & Certification

Challenge

Road logistics operators in the United States often face revenue loss due to the inability to operate in severe weather conditions, particularly in Northern states. Autonomous trucks, such as those developed by Embark Trucks, have the potential to transform the industry, but they face their own challenges. Autonomous vehicles (AVs) rely on sensing technologies like LiDAR, radar, and optical cameras to collect visual data from their surroundings, which is then combined with maps and algorithms to make decisions. However, even the most advanced sensing technology can struggle with accurate detection and interpretation of road conditions in adverse weather. Embark needed not only on-road testing but also accurate and complete historical weather datasets to fully understand the implications of such conditions on its self-driving solution.

About Customer

Embark Trucks is the longest-operating self-driving truck program in the United States, having been a forerunner in autonomous vehicle technology for trucks since 2016. Their software powers safe, commercially viable autonomous long-haul trucks, trusted by investors, Fortune 500 shippers, and some of the nation’s largest carriers. Embark's autonomous trucks use sensing technologies such as LiDAR, radar, and optical cameras to collect visual data from the surrounding environment, which is then combined with maps and algorithms to make decisions while on the road.

Solution

Embark turned to an AerisWeather Flex subscription to obtain granular weather data, pulled on location-based intervals frequently throughout the day. This allowed Embark to develop a comprehensive weather model comprised of over eight billion historical weather data points dating back over 10 years for major routes across the United States. The model increased Embark's confidence in its autonomous trucks' ability to assess and react to the impact of snow at a lane level. The data was also combined with highway requirements, such as the requirement for highways to be cleared within three hours of snow stopping. This enabled Embark to estimate when highways would be cleared at any given location. Trucks were test-driven in snowy conditions and data from the truck’s sensors was cross-referenced with AerisWeather’s interpolated conditions, allowing Embark to determine the possible business implications of snowy conditions.

Impact #1	The on-road testing and performance review conducted in February 2022 represented a significant milestone in the development of autonomous trucking technology. Embark’s trucks traveled on a 60-mile round-trip route on public roads in Montana, in varying intensities of winter weather. The testing process enabled Embark to determine the possible business implications of snowy conditions, specifically, how often a truck would be able to run a particular route in the snow based on historical data. The results indicated that Embark's software works within tolerance thresholds for safe operation in a majority of snowy weather conditions.

Impact #1

The on-road testing and performance review conducted in February 2022 represented a significant milestone in the development of autonomous trucking technology. Embark’s trucks traveled on a 60-mile round-trip route on public roads in Montana, in varying intensities of winter weather. The testing process enabled Embark to determine the possible business implications of snowy conditions, specifically, how often a truck would be able to run a particular route in the snow based on historical data. The results indicated that Embark's software works within tolerance thresholds for safe operation in a majority of snowy weather conditions.

Benefit #1	Embark developed a comprehensive weather model comprised of over eight billion historical weather data points dating back over 10 years.
Benefit #2	Embark's software works within tolerance thresholds for safe operation in snowfall rates up to one-sixth of an inch per hour, and with snow accumulation of one inch on the road over 3 hours.
Benefit #3	Embark estimates its software will operate within acceptable shipper delivery windows approximately 90% of the time on delivery runs under such weather conditions.

Benefit #1

Embark developed a comprehensive weather model comprised of over eight billion historical weather data points dating back over 10 years.

Benefit #2

Embark's software works within tolerance thresholds for safe operation in snowfall rates up to one-sixth of an inch per hour, and with snow accumulation of one inch on the road over 3 hours.

Benefit #3

Embark estimates its software will operate within acceptable shipper delivery windows approximately 90% of the time on delivery runs under such weather conditions.

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Overview

Embark's Autonomous Trucks Overcome Weather Challenges with Advanced On-Road Testing

Operational Impact

Quantitative Benefit