Navigant Research Blog

Google’s Autonomous Vehicle Crashes Are Misunderstood

— May 18, 2015

There’s been a fair amount of coverage in the media around the 11 reported accidents with Google’s autonomous vehicles. While some headlines about self-driving cars crashing may confuse the public about the merits of autonomous vehicle safety, the facts on the 11 accidents should ease any cause for worry: all of the 11 minor accidents were a result of driver error (from drivers of other vehicles) and had nothing to do with the autonomous vehicle functionality.

Seven of the accidents reportedly involved another vehicle rear-ending Google’s car, two were sideswipes from other vehicles, and a car running a red light was the cause of another. This information helps confirm what we already know: 94% of accidents are attributed to human error, and autonomous vehicles offer drastically improved safety capabilities that are expected to reduce the number of accidents on the road by enormous proportions. With 360-degree visibility; 100% attention in all directions at all times; and sensors keeping track of other vehicles, cyclists, and pedestrians out to a distance of nearly two football fields, autonomous vehicles use much safer and more advanced driving techniques than humans—and they won’t ever be caught texting at the wheel.

Accident Rates

Google released figures on the accident rates for their autonomous vehicles to clear up any confusion that may have been going on in the media: there have been 11 accidents in over 1.7 million miles of driving over the course of 6 years. While this is actually higher than the national average of 0.3 damaging incidents per 100,000 miles, Google has noted that the higher rates are largely due to the company’s full reporting of accidents, a practice most drivers ignore. Most importantly, director of Google’s self-driving program Chris Urmson has said that not once was the self-driving vehicle the actual cause of the accident. Thus, the at-fault accident rate for Google’s autonomous vehicles’ through nearly 2 million miles of driving is 0%.

Benefits of Automation

Autonomous vehicles have benefits that extend far beyond fewer traffic accidents. In early 2015, the International Transport Forum at the Organisation for Economic Co-operation and Development (OECD) published a report titled Urban Mobility System Upgrade: How shared self-driving cars could change city traffic. This report found that autonomous vehicles could provide the same mobility we have now (using a mid-sized European city as an example) with just 10% of the cars. Additionally, a network of autonomous vehicles could completely remove the need for on-street parking spaces while also removing 80% of off-street parking, opening vast new public and private opportunities for alternative uses of valuable city space. Considering that driver error accounts for the vast majority of vehicle accidents and Google’s autonomous cars have racked up a total of zero at-fault accidents over the course of 6 years of driving, it’s clear that the potential long-term benefits of autonomous vehicles are well worth the associated risks—even if there were one or two accidents in the process.

 

Uber Expanding into Electric and Autonomous Vehicles

— April 7, 2015

Since Uber’s creation in 2009, the adoption of the company’s mobile app-based transportation service has exploded and the service is now available in 56 countries and over 200 cities worldwide. In fact, it was recently reported that there are now more Uber cars than yellow cabs in New York City. With nearly $3 billion in total funding raised by 2015, Uber is looking to expand its business into the growing electric vehicle (EV) and autonomous vehicle markets.

Offering local customers emissions-free transportation options, Uber has partnered with BYD to provide electric e6 taxis in Chicago. Uber drivers have the option to rent the e6 taxis from the Green Wheels USA dealership for $200 a week, and Uber customers will be able to choose an EV through the smartphone app when booking a vehicle. This new option gives users added flexibility in their riding choices, and more cities around the United States can expect Uber EVs as an option in the near term.

So Long, Driver

Likely to be more disruptive than the introduction of EVs, autonomous vehicles could have a much more notable impact on Uber’s business. In February 2015, Uber announced that it is setting up a laboratory in Pittsburgh to develop self-driving technology. In partnership with Carnegie Mellon University, the company will reportedly be developing the core autonomous technology, the vehicles, and associated infrastructure at the Pittsburgh facility. Uber CEO Travis Kalanick has stated in the past that he would gladly replace human drivers with a self-driving fleet of vehicles, as Uber drivers reportedly take home about 75% of every fare.

Beyond massive savings on costs for Uber, and potentially its customers, autonomous vehicles would make Uber a much safer service—not just in terms of smoother running vehicles with (likely) fewer accidents, but also in terms of the well-being of the passengers. Uber has come under intense scrutiny as of late, as accusations of assaults on passengers by Uber drivers have come from numerous customers from a variety of countries. While Uber does conduct background checks on its drivers, prosecutors in California are suing the company for alleged exaggeration regarding the rigor of its background checks.

Navigant Research’s report, Autonomous Vehicles, projects that globally, close to half of all new vehicles sold in 2035 will have some form of autonomous driving capability installed. Uber may have autonomous vehicles on the road even sooner, which would go a long way toward ensuring safer driving and safer environments for customers who would no longer have to consider the possibility of a dangerous driver.

 

Volvo Pioneers Autonomous Vehicles

— March 17, 2015

Volvo has long sold cars that are considered among the safest in the world. Since the 1940s, Volvo has been at the forefront of introducing innovations that include laminated safety glass, crush zones, three-point seatbelts, and more recently, pedestrian detection with automatic braking. As Volvo prepares to launch its first all-new production vehicle since being acquired by China’s Geely Group, the company has announced plans for a test of highly automated vehicles on public roads near its Gothenburg, Sweden headquarters.

Self-Driving Cars a Reality

Self-driving vehicles from automakers, suppliers, and technology companies have become commonplace recently on Silicon Valley roads. However, all of those vehicles are under the control of the engineers trying to refine the complex control software required to make them work reliably. Beginning in 2017, Volvo plans to put a fleet of 100 autopilot-equipped XC90 SUVs into the hands of regular Swedish drivers.

Reiterating its oft-stated goal of achieving sustainable mobility and a crash-free future, Volvo has worked to design the autopilot system it is building into the XC90 to be robust enough to let ordinary drivers give  complete control.

“Making this complex system 99% reliable is not good enough, you need to get much closer to 100% before you can let self-driving cars mix with other road users in real-life traffic,” Erik Coelingh, technical specialist at Volvo, told me. With that in mind, Volvo has recognized the limitations of current technology, so the XC90 will be equipped with a combined array of radar, lidar, ultrasonic, and camera sensors.

Sensor Array on Autonomous Volvo XC90

(Source: Volvo)

Coelingh acknowledges that there are some fundamental problems that cannot be overcome. For example, lidar sensors cannot see through fog or rain and cameras cannot see lane markers that are obscured by snow. In addition to using multiple sensor types, Volvo is taking care in packaging the sensors to minimize the risk of obstruction from the elements such as snow and salt buildup.

The goal is to allow drivers to spend time on secondary tasks without constantly monitoring the system. The vehicles will be able to execute automatic lane changes and enter and exit a limited access highway. Soft degradation of the system will extend the time between the driver being alerted and when they have to take over. If the driver does not respond by taking over control in a timely manner, the vehicle will attempt to pull over and come to a safe stop.

Fully Autonomous vs. Self-Driving

Despite all of that, there is an important distinction between vehicles that are capable of fully autonomous operation and those that are entirely self-driving. The Volvo falls into the former category, with the ability to handle the driving when conditions permit, while reverting to human control in many scenarios. Google’s prototype pod car, which was designed without a steering wheel or pedals, is in the latter category. For the foreseeable future, driverless vehicles are likely to remain restricted to closed environments where they don’t need to interact with traditional vehicles.

As detailed in Navigant Research’s report, Autonomous Vehicles, 40% of new vehicles will have some form of automated driving capability by 2030. The bulk of those are likely to be similar in concept to what Volvo will be testing on Swedish roads in 2017. Although consumer surveys have indicated strong interest in autonomous vehicles, it’s too early to tell how much of that interest will be retained as consumers become aware of the real-world limitations of autonomous technology. Volvo’s test program in Sweden might give the first real feedback on this topic.

 

Cloud Connections Bolster In-Vehicle Systems

— January 26, 2015

With the average transaction prices of new vehicles in the United States hitting nearly $35,000 at the end of 2014, drivers can be grateful that the cars they purchase are also more durable and reliable than ever before. The average age of the more than 200 million vehicles on the road in the United States today is now nearly 11.5 years.  However, that longevity has a big potential downside: as computing and communications technology marches on to improve safety, efficiency, and reliability, many of those existing cars will be incapable of participating in these advances.  Luckily, cloud computing could come to the rescue.

According to Navigant Research’s report, Autonomous Vehicles, full-function self-driving vehicles aren’t expected to be available in significant volumes until late in the 2020s.  Until the fully self-driving car arrives, we’ll have a steady stream of incremental improvements in advanced driver assistance systems.  Thanks to increasing connectivity in vehicles, we’re also less likely to be stuck with the capability that was built-in when the vehicle rolled off the assembly line.

No Car Left Behind

General Motors (GM) and Audi are among the manufacturers that are already building 4G LTE radios into many of their new vehicles.  When this capability is combined with advanced new microprocessors from companies like NVIDIA and Qualcomm, vehicles will be able to leverage cloud computing infrastructure to get smarter as they age, rather than being left behind.

At the 2015 Consumer Electronics Show in Las Vegas, NVIDIA unveiled a new generation 256-core processor, called the Tegra X1, along with electronic control units powered by this advanced chip.  One of the problems that driver assistance and autonomous systems have to solve is being able to recognize and distinguish the objects detected by all of the sensors on new vehicles.  The human brain is remarkably adept at distinguishing the nuances between an animal and pedestrian or an ambulance and a delivery van.

Detection before Failure

This sort of image recognition is far more difficult for a computer, so the Tegra X1 is designed to collect image data from its 12 camera inputs and transmit it back to data centers where it can be aggregated with information from other vehicles.  By combining data from many vehicles, the object recognition can be dramatically improved, and updated image libraries can be fed back to vehicles for improved onboard sensing ‑ even without changing hardware.

GM is also harnessing the power of the cloud to provide drivers with predictive diagnostic information for their vehicles using OnStar.  Available for more than a decade, OnStar provides subscribers with vehicle health reports when faults are detected.  Now, by monitoring critical systems such as the battery, starter, and fuel pump and sending this information back to the cloud, OnStar is able to detect subtle changes in performance that have previously been shown to be precursors to component failures.  The OnStar Driver Assurance system can then notify the driver so that an impending problem can be corrected before the driver is left stranded on the side of the road.  This predictive diagnostic system will be available on several of GM’s 2016 model year vehicles.

As automakers roll out new infotainment interfaces, such as Apple CarPlay and Google’s Android Auto, drivers will also benefit from improved voice recognition that leverages massive data centers run by these technology companies.  More robust and reliable voice control will help reduce driver frustration and keep their attention on the road ‑ at least until the car can take over completely.

 

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