Navigant Research Blog

Most Developed Automated Vehicle Tech Doesn’t Equate to a Best Solution Today

— June 21, 2018

An interesting Twitter thread sprung up recently discussing the merits of Tesla’s AutoPilot partially automated driving system relative to competitors. This came in the wake of a preliminary report from the National Transportation Safety Board that was examining a March 2018 crash that killed an Apple engineer in a Tesla Model X. One of the commenters raised the concept of which automated driving systems are most developed, citing how far back Tesla ranked in Navigant Research’s Automated Driving Leaderboard report.

How to Interpret Leaderboard Rankings

While it is true that Tesla had the lowest score in this year’s ranking, it’s important to understand both what is being ranked and how most developed may relate to best developed for automated driving.

This Navigant Research Leaderboard is intended to provide a snapshot of where analysts believe companies rank in their ability to successfully commercialize automated driving technology. To do that, the Leaderboard goes well beyond just the core automation technology, with individual subscores assigned for 10 different criteria including vision, go-to market strategies, partnerships, manufacturing capability, product quality, and financial strength. While Tesla has always ranked high on vision, it often lags in many other areas, leading to its low overall score.

Scoring for Vision

The vision score is based in part on where a company sees its business going in the coming decade as well as what it hopes to achieve. In Tesla’s case, its score was boosted by its belief that automated driving technology should be deployed as far and wide as possible as soon as possible.

That is a fantastic idea. In an ideal world, it would save many of the tens of thousands of lives lost annually in American traffic accidents and the more than one million lost globally. Unfortunately, we don’t live in an ideal world. Putting insufficiently developed technology in the hands of untrained consumers on public roads can be a recipe for disaster.

The Gap between Most and Best

AutoPilot may indeed be the most developed system on the market today in terms of the manufacturer’s willingness to stretch its capabilities and extract all it can from the available sensor suite. That does not necessarily make it the best developed system in terms of what should be in production based on safety requirements and consumers’ current abilities and understanding of the technology.

Humans Like Consistency

Early in my engineering career, working on anti-lock braking systems, I learned the value of ensuring that the technology performed with as much consistency and predictability as possible. For all our flaws, humans are remarkably adaptable if we understand the conditions. Most people tend to drive the same vehicle every day for years. Even if a vehicle has limitations or quirks, as long as they are consistent, drivers will adjust how they use the vehicle. If a vehicle has a longer stopping distance, drivers will brake sooner. If the steering response is slower, a larger angle will be used.

The problem comes when the system responds differently every time you use it, as many voice control systems have done. That’s when people stop using it or get caught unawares when they do. That likely contributed to Walter Huang ignoring warnings to hold the steering wheel in his Tesla. There are other systems on the market, that while not as capable as they could be in certain conditions, are indeed better developed for the real world.

Acknowledging Room for Improvement

As we move to higher levels of automated driving in the next several years, we need to encourage manufacturers to acknowledge what their products can’t do yet, while working to make available functions the best they can be.


Advanced Driver Assist System Vehicles May Require Pricier Repairs

— May 31, 2018

Bosch, the world’s largest automotive supplier, held a media event this May at its Flat Rock, Michigan proving grounds to demonstrate its latest technologies including new advanced driver assist systems (ADAS). In addition to all the components and systems that Bosch sells to most of the world’s automakers, Bosch also provides a wide range of service and repair tools for factories, dealers, and independent repair shops.

One of the static displays at the recent event was showing off equipment used to calibrate the cameras used for ADAS and automated driving. The calibration equipment includes a stand with checkerboard panels for aiming and focusing cameras, gauges for checking ride height, and electronic diagnostic tools to actually make adjustments to the sensors. While Bosch declined to discuss the price of all this equipment, given the cost of professional tools, a complete set capable of handling all the different sensors would likely run into the tens of thousands of dollars.

Let’s Talk about Repairs

For a repair facility, buying tools has always been the cost of doing business. But for consumers and insurance companies, life happens and this equipment designed to save lives can also lead to substantial repair costs for damage that has nothing to do with crashes. The chances of actually being in a crash for any vehicle, including those without ADAS technology, are surprisingly small. The 6.3 million crashes in 3.1 trillion vehicle miles driven in the US in 2015 equals about one crash every half a million miles. The frequency of crashes for vehicles with ADAS should be even lower, resulting in fewer trips to the body shop. A far more likely occurrence is a pebble thrown up by one vehicle striking the windshield of another. At 70 mph, even a small projectile has a surprising amount of energy, and can lead to the formation of a crack.

Smarter Cars Can Mean More Expensive Car Work

Such a crack happened 2 years ago to one of the cars then in my household, a 2010 Volkswagen Jetta with no ADAS. A national vendor that does auto glass repair came to my home and replaced the cracked windshield in my garage in less than 30 minutes for under $250.

The Jetta was replaced by a 2017 Honda Civic last year. The latter has lane keeping assist, adaptive cruise control, and other ADAS features including a camera mounted on the windshield.

A windshield repair estimate from the same vendor for the newer car came to $559, more than double the earlier cost. That new price does include calibrating the camera. However, not all local facilities have the equipment required to do calibrations in the field, so depending on location and the type of vehicle a customer may need to take the time to go to a repair facility.

If Smart Features Are Integrated in Common Ones, Expenses Increase

When Ford launched the current generation F-150, it featured a blindspot monitor with rear corner radar sensors integrated into tail light clusters. A broken tail light with the radar sensor cost more than $887 to replace. Ford has since redesigned the system to separate the radar sensor, reducing repair costs. However, that’s not always possible with all sensors.

Non-Crash Vehicle Repairs May Negate Savings

As manufacturers move to make ADAS features like forward collision alerts and automatic emergency braking the standard, damage caused by the vagaries of driving in the real world will offset some but probably not all of the savings that should result from reduced crash frequency. Nonetheless, consumers should be aware that when those non-crash related repairs are needed, they will likely be a lot pricier than they have been in the past.


HD Maps Might Help Teslas Stop Running into Fire Trucks

— May 24, 2018

Recently, a Tesla in Utah ran into the back of a stationary fire truck at high speed. This is the second such incident this year and the National Transportation Safety Board is already investigating the earlier incident. Incidents involving Teslas get news coverage because of the strident safety claims made by Elon Musk for his company’s AutoPilot driver assist system, but such accidents can happen with many vehicle brands. Relying on a single sensor for active safety control is often inadequate, but high definition (HD) maps may actually turn out to be part of the solution.

Teslas, and many millions of other vehicles, are equipped with forward-looking radar sensors that are used for adaptive cruise control (ACC). The radar is used to detect a vehicle moving ahead while ACC is active and measures the gap to that vehicle. If the lead vehicle slows down, the ACC vehicle will automatically slow to maintain a safe gap.

Forward-Looking Sensors Not Seeing Everything

You might think that if ACC detects a stopped vehicle it would automatically slow to a stop, but as the two recent crashes indicate, this isn’t always true. When ACC is used at highway speed, the assumption is that the other vehicles on the road will also be moving. To prevent false positives that would cause the brakes to erroneously engage, these systems are designed to ignore static objects like road signs, light poles, etc.

When another static vehicle that was outside of the radar range comes within view of the sensor while moving at highway speeds (as both vehicles in these crashes were), it is not assumed to be a vehicle and thus it is ignored. Some vehicles also include a combination of automatic emergency braking and/or forward collision warning safety systems to prevent crashes, but these systems are not optimized for identifying stationary vehicles in the roadway when the vehicles are traveling at highway speeds. Refinements in the coordination between these systems will continue.

How Does Mapping Fit into This?

Today, increasingly detailed maps are being used not just for routing but also as inputs to hybrid propulsion systems and long-range sensors in partially automated vehicles from GM and Mercedes-Benz. In the coming years, HD maps with detailed locations of static objects will be used for precision localization. If a vehicle has HD maps with the locations of fixed roadside objects, it may be possible to fuse this with the real-time radar data to better understand which objects can safely be ignored. The addition of image data from the camera used for lane keeping assist and it should be possible to recognize legitimately stopped vehicles and respond accordingly.

Companies such as San Francisco startup Mapper and incumbent map providers like HERE and TomTom have begun building HD maps. Mapper has developed a low cost, multi-camera-based data collection system that can be installed in vehicles used for ride-hailing providers or in other fleets. By the end of 2018, up to 2 million vehicles from Volkswagen, BMW, and Nissan are expected to be on the road globally with Mobileye’s latest EyeQ4 image processor. These vehicles will also be collecting data that feeds into Mobileye’s Road Experience Management system and then into maps from providers including HERE.

The sooner we start augmenting existing driver assist systems with new data sources such as HD maps or fusion of other sensors in the vehicle, the sooner object classification should improve to help prevent more crashes. The Tesla crashes are getting the attention, but these are problems that afflict virtually every manufacturer and the technology needs to be improved in order to save more lives.


Lack of Automated Vehicle Test Standards Is an Oversight

— May 3, 2018

In a capitalist economy, companies have a fiduciary responsibility to maximize the returns for their shareholders. That can often be at odds with the general public good. Ideally, political and regulatory leaders can find ways to strike a balance between the two that helps the economy grow and allows the populace to be safe. When it comes to the automated vehicle industry, in the past few years those leaders have abdicated their responsibilities.

Vehicles today are safer than they have ever been. While we have seen an uptick in traffic fatalities in the past couple of years, the overall trend has been downward for nearly half a century. In large part, that is due to leaders having the courage to impose safety and emissions regulations since the early 1970s. Automakers complained vociferously every step of the way, but in the end, they have largely complied. We are now safer while automakers remain very profitable.

Regulations created some speed bumps, but the world did not come to an end. In virtually every business sector, companies faced with new rules whine about it, but ultimately, they adapt.

From a societal good perspective, 37,000 deaths on the nation’s roads every year is not acceptable. On the other hand, when considered against the 3.2 trillion miles we travel annually, that’s about 1.1 death for every 100 million miles. Over the long haul, a shift away from human drivers toward automated mobility will almost certainly slash those numbers dramatically. However, engineers still have a lot of development to do to prove that the technology we have available is better than us flawed humans.

We Need Real World Testing

The vast majority of the testing will probably be done in ever more sophisticated simulation environments. But we also need real world testing, and it seems reasonable to begin with the same tests we apply to humans that want to drive. Before a teenager can get their first driver’s license, they have to take a vision test to demonstrate that they can see and recognize pedestrians, signs, and other objects in the driving environment. They also have to demonstrate a basic knowledge of rules of the road.

In the US, the federal government is responsible for motor vehicle safety standards like occupant crash protection. The states are responsible for licensing and registration of drivers and vehicles.

Human test drivers have to pass those aforementioned evaluations. So too should the virtual drivers that many hope will someday replace us. The death of a pedestrian struck by an automated Uber test vehicle demonstrates the failure of the laissez-faire approach taken by Arizona and many other states to automated vehicle testing.

We Also Need Standards

SAE International has for decades provided a platform for industrywide standards development. The oft-quoted (and misquoted) automation levels are the product of an SAE standards committee. Now would be a good time for SAE to develop standards for testing that a sensor system can detect a pedestrian or cyclist at a minimum distance in various lighting and weather conditions. With those standards in hand, every state should require that any company wishing to test automated driving systems on public roads must demonstrate that they can pass those tests and respond appropriately when other road users are detected.

The standards should be technology agnostic, but would demonstrate the most basic functionality, just as a human must do. We will undoubtedly have more fatal crashes along the way to some hoped-for automated utopia, but requiring automated cars to pass a driving test is a minimum today.


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