Ford Fusion Hybrid’s self-driving technology is crafted to combat winter obstacles

Article by Christian A., on March 14, 2016

Most people in the US have experienced the difficulty of driving in snow in one way or another. It has been a constant challenge because the roads become slippery and road visibility is often an obstacle. In line with this, self-driving vehicles need to be able to navigate through the roads during winter better than present models.

Ford, for example, has disclosed six facts about its self-driving technology that will enable vehicles to brave through the snow conveniently. Ford has built high-resolution 3D maps that will scan the area thoroughly before driving through it.

Ford Fusion Hybrid self-driving cars come with LiDAR technology to first create digital maps of the area where the cars will be driven. Using four LiDAR scanners that yield 2.80 million laser points per second, the vehicle will create digital models of the road and the infrastructures that surround it. The map will then serve as a baseline to identify the position of the vehicle when it is in self-driving mode.

This enables the vehicle to locate itself within the mapped coverage later in time when it is already covered in snow. Apparently, the self-driving technology of Ford requires more data in just an hour than the average mobile data used by one person in 10 years. Mapping the environment in high-resolution requires the vehicle to collect heavy and detailed data about the surroundings. This causes the vehicle to collect and process up to 600GB an hour.

Meanwhile, an average person in the US consumes 21.60GB of data a year, amounting to a total of 216GB for 10 years. The LiDAR sensors are extremely powerful. In fact, they can also identify raindrops and snowflakes falling. Because of this, the sensors may return a false impression that there is an obstacle along the way. However, of course, there is no need to steer around precipitation.

To deal with this dilemma, Ford, together with researchers from the University of Michigan, devised an algorithm that can recognize rain and snow. Consequently, they are filtered out of the vehicle's vision, allowing the self-driving car to continue driving. Ford's self-driving cars are built with navigation systems that are far better and more accurate than the average GPS. Present GPS can only be accurate up to slightly more than 10 yards.

Self-driving vehicles need more than that. Ford's self-driving cars can accurately locate themselves within a centimeter; thanks to the powerful technology that scans the environment and compares the acquired data to the stored 3D maps. The data from multiple, high-tech sensors, together with the smart monitoring of sensor health, are capable of keeping the self-driving car out of the blind. Aside from the LiDAR sensors, Ford's self-driving technology also includes cameras and radars that monitor the surroundings using the data from all the sensors fused together.

This process, which yields a robust 360-degree situational awareness, is called sensor fusion. This means that if any elements such as snow, ice, debris, and grime build up on a sensor lens, inactivating a sensor, the self-driving technology remains uncompromised. The camera and radar systems can still identify the deterioration of sensors, keeping them in ideal working order. Moreover, this might even enable the vehicles to perform self-cleaning and/or defogging measures in no time.

Astrophysics major Wayne Williams, the first person to perform a self-driving test in snow, never even thought about being in a self-driving vehicle. Before Williams joined the self-driving team of Ford, he used to work on remote sensing technology for the federal government.

As a self-proclaimed geek, he has always been interested in self-driving technology. However, Williams never dreamt of one day becoming part of a team that will develop the technology and bring it into materialization— let alone be the first to conduct a self-driving vehicle test in snow. According to him, it was all purely business with a coworker monitoring the system from the back seat. Williams said that everyone in the team was confident about the extensive development they had performed and worked on.

However, overwhelmingly, he expressed that it was not until after the test that the true victorious feeling began sinking in. Ford is the first automobile company to conduct a public self-driving vehicle test in the snow. It took place in Michigan, including at Mcity, which is the University of Michigan's 32-acre, real-world driving environment. The testing on the full-scale simulated urban campus is geared toward realizing Ford's mission to further advance the emerging self-driving realm.

Press Release

From Autonomy to Snowtonomy: How Ford Fusion Hybrid Autonomous Research Vehicle Can Navigate in Winter

Driving in snow can be a slippery challenge, with the potential for one blizzardy gust to white-out your field of view – a situation faced by the majority of people in the United States. So if self-driving cars are to become a reality – and they almost certainly will – they must be able to navigate snow-covered roads. In its quest to bring self-driving vehicles to millions of people around the world, Ford reveals six facts about its technology that allows for a car to drive itself in snow.

Mapping the way: Ford first creates high-resolution 3D maps using LiDAR technology to scan the area its autonomous vehicle will later drive in the snow.
To operate in snow, Ford Fusion Hybrid autonomous vehicles first need to scan the environment to create high-resolution 3D digital maps. By driving the test route in ideal weather, the Ford autonomous vehicle creates highly accurate digital models of the road and surrounding infrastructure using four LiDAR scanners that generate a total of 2.8 million laser points a second. The resulting map then serves as a baseline that’s used to identify the car’s position when driving in autonomous mode. Using the LiDAR sensors to scan the environment in real time, the car can locate itself within the mapped area later, when the road is covered in snow.

Better have an unlimited data plan: Ford’s autonomous vehicles collect and process significantly more mapping data in an hour than the average person uses in mobile-phone data in 10 years.
While mapping their environment, Ford autonomous vehicles collect and process a diverse set of data about the road and surrounding landmarks – signs, buildings, trees and other features. All told, the car collects up to 600 gigabytes per hour, which it uses to create a high-resolution 3D map of the landscape. In the United States, the average subscriber of a cellular data plan uses about 21.6 gigabytes per year, for a 10-year total of 216 gigabytes.

Super smart sensors: Ford uses LiDAR sensors that are so powerful, they can even identify falling snowflakes and raindrops.
Ford’s autonomous vehicles generate so many laser points from the LiDAR sensors that some can even bounce off falling snowflakes or raindrops, returning the false impression that there’s an object in the way. Of course, there’s no need to steer around precipitation, so Ford – working with University of Michigan researchers – created an algorithm that recognizes snow and rain, filtering them out of the car’s vision so it can continue along its path.

Not your average navigation: The way Ford’s autonomous vehicles identify their location is more accurate than GPS.
When you think about vehicle navigation, GPS usually comes to mind. But where current GPS is accurate to just more than 10 yards, autonomous operation requires precise vehicle location. By scanning their environment for landmarks, then comparing that information to the 3D digital maps stored in their databanks, Ford’s autonomous vehicles can precisely locate themselves to within a centimeter.

No need for glasses: Sensor fusion – the combination of data from multiple sensors – plus smart monitoring of sensor health help keep Ford’s autonomous vehicles out of the blind.
In addition to LiDAR sensors, Ford uses cameras and radar to monitor the environment around the vehicle, with the data generated from all of those sensors fused together in a process known as sensor fusion. This process results in robust 360-degree situational awareness. Sensor fusion means that one inactive sensor – perhaps caused by ice, snow, grime or debris buildup on a sensor lens – does not necessarily hinder autonomous driving. Still, Ford autonomous vehicles monitor all LiDAR, camera and radar systems to identify the deterioration of sensor performance, which helps keep sensors in ideal working order. Eventually, the cars might be able to handle ice and grime buildup themselves through self-cleaning or defogging measures.

Look Mom, no hands: The first person behind the wheel of a demonstrated autonomy test in snow is an astrophysics major who never dreamed he’d be in a self-driving car.
Before Wayne Williams joined Ford’s autonomy team, he worked on remote sensing technology on behalf of the federal government. A self-described “geek,” Williams was intrigued by autonomous vehicles. But he never envisioned one day being part of a team working to bring them to reality – let alone being behind the wheel of the auto industry’s first publicly demonstrated autonomous snow test. The mood in the car that day was all business, he recalls, with a coworker monitoring the computing system from the back seat. “Because of the extensive development work, we were confident the car would do exactly what we asked of it,” says Williams. “But it wasn’t until after the test that the achievement began to sink in.”
Ford is the first automaker to publicly demonstrate autonomous vehicle operation in the snow. The company's winter weather road testing takes place in Michigan, including at Mcity – a 32-acre, real-world driving environment at the University of Michigan. Ford’s testing on this full-scale simulated urban campus is aimed at supporting the company’s mission to learn about and advance the emerging field of autonomous driving.


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