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Self-driving vehicles are cars or trucks in which human drivers are never required to take control to safely operate the vehicle. Also known as autonomous or “driverless” cars, they combine sensors and software to control, navigate, and drive the vehicle. Currently, there are no legally operating, fully autonomous vehicles in the United States. There are, however, partially autonomous cars and trucks with varying amounts of self-automation, from conventional cars with brake and lane assistance to highly-independent, self-driving prototypes.
Though still in its infancy, self-driving technology is becoming increasingly common and could radically transform our transportation system (and by extension, our economy and society). Based on the automaker and technology company estimates, Level 4 self-driving cars could be for sale over the next several years with Tesla and many other automakers taking the lead in this field.
The Society of Automotive Engineers (SAE) currently defines 6 levels of driving automation ranging from Level 0 (fully manual) to Level 5 (fully autonomous). These levels have been adopted by the U.S. Department of Transportation.
The SAE uses the term automated instead of autonomous. One reason is that the word autonomy has implications beyond the electromechanical. A fully autonomous car would be self-aware and capable of making its own choices. For example, you say “drive me to work” but the car decides to take you to the beach instead. A fully automated car, however, would follow orders and then drive itself. The term self-driving is often used interchangeably with autonomous. However, it’s a slightly different thing. A self-driving car can drive itself in some or even all situations, but a human passenger must always be present and ready to take control. Self-driving cars would fall under Level 3 (conditional driving automation) or Level 4 (high driving automation). They are subject to geofencing, unlike a fully autonomous Level 5 car that could go anywhere.
Autonomous cars rely on sensors, actuators, complex algorithms, machine learning systems, and powerful processors to execute software. Autonomous cars create and maintain a map of their surroundings based on a variety of sensors situated in different parts of the vehicle. Radar sensors monitor the position of nearby vehicles. Video cameras detect traffic lights, read road signs, track other vehicles, and look for pedestrians. Lidar (light detection and ranging) sensors bounce pulses of light off the car’s surroundings to measure distances, detect road edges, and identify lane markings. Ultrasonic sensors in the wheels detect curbs and other vehicles when parking. Sophisticated software then processes all this sensory input, plots a path, and sends instructions to the car’s actuators, which control acceleration, braking, and steering. Hard-coded rules, obstacle avoidance algorithms, predictive modeling, and object recognition help the software follow traffic rules and navigate obstacles.
Fully autonomous (Level 5) cars are undergoing testing in several pockets of the world, but none are yet available to the general public. We’re still years if not decades away from that. The challenges range from the technological and legislative to the environmental and psychological.
Lidar is expensive and is still trying to strike the right balance between range and resolution. If multiple autonomous cars were to drive on the same road, would their lidar signals interfere with one another? And if multiple radio frequencies are available, will the frequency range be enough to support mass production of autonomous cars?
What happens when an autonomous car drives in heavy rain or fog? If there’s a layer of snow on the road, lane dividers would disappear. How will the cameras and sensors track lane markings if the markings are obscured by water, oil, ice, or debris?
Will autonomous cars have trouble in tunnels or on bridges? How will they do in bumper-to-bumper traffic? Will autonomous cars be relegated to a specific lane? Will they be granted carpool lane access? And what about the fleet of private passenger cars still sharing the roadways for the next 20 or 30 years?
The regulatory process in the U.S. has recently shifted from federal guidance to state-by-state mandates for autonomous cars. Some states have even proposed a per-mile tax on autonomous vehicles to prevent the rise of “zombie cars” driving around without passengers (Uber, Lyft, Waymo etc.). Lawmakers have also written bills proposing that all autonomous cars must be zero-emission vehicles and have a panic button installed. But are the laws going to be different from state to state? Will you be able to cross state lines in an autonomous car?
Who is liable for accidents caused by an autonomous car? The manufacturer, the human passenger/owner? The latest blueprints suggest that a fully autonomous Level 5 car will not have a dashboard or a steering wheel, so a human passenger may not even have the option to take control of the vehicle in an emergency.
Human drivers rely on subtle cues and non-verbal communication, like making eye contact with pedestrians or reading facial expressions and body language of other drivers to make split-second judgement calls and predict behaviors. Will autonomous cars be able to replicate this connection? Will they have the same life-saving instincts as human drivers?
There are numerous autonomous vehicle organizations, but some stand out more than others. Based on published data and public statements made by various companies, a semi-consensus exists in the autonomous driving community as to which companies are at the most advanced stages of development.
1. WAYMO
Google and their Waymo spinoff is by far the most recognized leader in the area. They've been doing it longer than anyone else. Their fleet is significantly larger than any other company, they recently announced to consumers on their platform in Arizona that they're going to start launching actual autonomous rides, which is a significant step forward. I don't think anyone else is that close to being able to physically take the engineer out. Waymo used Phoenix, Arizona, as the site for testing Waymo One, a self-driving taxi service. These tests all had a human backup driver in their vehicles as a safety precaution, but a recent email was sent out to Waymo users claiming that completely autonomous rides were on the horizon.
According to Waymo, self-driving sensor suite consists of LiDAR, cameras, and radar, as well as microphones to detect sounds such as sirens. Like a person's own five senses, Waymo's self-driving technology is more powerful as a whole than the sum of its parts; each sensor complements the others. Waymo began developing its own hardware and sensors in-house in 2011 when it found nothing else on the market provided the functionality that would enable level-four vehicles and fully driverless cars.
2. GM CRUISE
A General Motors subsidiary, Cruise is also a big name in the autonomous vehicle game.
With billions of dollars in investments from SoftBank, Honda, GM, and T.Rowe Price Associates, GM Cruise has a significant number of vehicles on the road: 180 vehicles in testing, which is by far the second largest number of vehicles in testing. Perhaps a little too ambitious, recently pushing back the launch date for its driverless taxi service from late 2019 to early 2020, ZDNet reported. The Chevy Bolts may look like a regular retail model on the outside, but under the hood, 40% of its parts have been altered to facilitate autonomous driving. Unlike other autonomous vehicle companies, being deeply integrated with one of the world's largest automakers like General Motors positions Cruise to manufacture self-driving cars on an assembly line in Orion, Michigan, which is capable of producing hundreds of thousands of vehicles per year. The Cruise vehicles use machine learning techniques, cloud-based tools, and IoT sensors to gather data about their surroundings and make intelligent decisions based on that insight.
3. ARGO AI
A newer creation, Argo AI has a "very significant growing footprint in the United States with the number of cities that they are testing in, and also, with the recent partnership with Volkswagen, I think they have the potential to kind of take a leadership position. Argo AI is an independent company that started in 2017, with a $1 billion investment from Ford Motor Company. Volkswagen only recently joined the partnership, which is still undergoing regulatory review, investing another $2.6 billion. Argo AI specializes in a different platform than its competitors in that it isn't striving to develop a car or operate a service. Rather, the company's goal is to develop the self-driving system. The vehicles that are being used are Ford Fusions, but that's not necessarily the intent of what the final product will be, it's obviously up to Ford or Volkswagen to decide which vehicles they want to use. Argo AI is not developing a car, they’re not going to be the operators of the services. The benefit of close partnerships with car manufacturers is that Argo AI is able to focus on the technology, developing it at a much deeper level. The outside of Argo AI-equipped vehicles have a combination of sensors -- LiDARs, radars, and cameras. The LiDAR is used to locate the distance of objects, and cameras help with depth perception.
Between September 2014 and November 2015, Waymo’s (Google) autonomous vehicles in California experienced 272 failures and would have crashed at least 13 times if their human test drivers had not intervened, according to a document filed by Google with the California Department of Motor Vehicles (DMV). When California started handing out permits for the testing of self-driving cars on public roads, it had just a few conditions. One was that manufacturers record and report every “disengagement”: incidents when a human safety driver had to take control of a vehicle for safety reasons.
And then there was the most infamous Uber self driving car accident involving a human death. It took place in Arizona with a safety driver behind the wheel who was too distracted to avoid the crash.
In a hearing of the National Transportation Safety Board in Washington, DC on November 19th, the three-member panel heard from a team of investigators who had been sifting through the details of the crash for over a year now. At the end of the two-and-a-half-hour hearing, the board issued its determination of probable cause in the event that shook the autonomous vehicle industry.
The board cited the following as contributing to the fatal crash:
Driverless vehicles have the potential to provide significant road safety, economic, environmental and social benefits, including improved social inclusion. This technology will make driving easier and safer, allow people to be more productive and offer greater mobility to a wider range of people than ever before, reduce emissions, and ease congestion. In general terms, the benefits of driverless vehicles are reflected in the following categories.
The most important safety benefit from driverless vehicles is the potential to markedly reduce the number of accidents with international experts agreeing that 90% of all accidents could be eliminated through advanced driverless vehicle technology. This technology could also reduce the impact of human error in road crashes, which cost billions of dollars annually, on top of the cost of human lives.
Driverless vehicle technology will profoundly impact every single person in the community, and offer lifestyle benefits well beyond just being able to read a book, surf the web, watch a film or talk with passengers on a journey. One of the greatest benefits from self-driving vehicles will be enhanced mobility for people with a driving impairment or some type of license restriction, such as a medical condition or vision impairment.
Utilization rates of cars horrible with the average car being parked 95 percent of the time, a “mobility on demand” model would see fewer cars on the road, and the ones that are likely to be shared. That could result in around 80-90 percent fewer cars in a perfectly efficient mobility system. It’s likely that the car ownership model will change too, with more people opting to not own a vehicle. That means homes will use space normally needed for a carport or garage to expand their living areas, and on-road parking space could be used for other transport options such as cycling. Imagine using a smartphone to summon a driverless car to take you where you need to go, rather than pay for registration, maintenance and running costs that come with vehicle ownership.
The scenarios for convenience and quality-of-life improvements are limitless. But the real promise of autonomous cars is the potential for dramatically lowering CO2 emissions. In a recent study, experts identified three trends that, if adopted concurrently, would unleash the full potential of autonomous cars: vehicle automation, vehicle electrification, and ridesharing. By 2050, these three revolutions in urban transportation could:
RIDEGURU
Comments
Sergio
It’s a great article it seems you did your research pretty well however
“Reduce traffic congestion (30% fewer vehicles on the road)“
this comment is not what actual data shows Single and double occupied autonomous cars will not reduce number of car on the road base on many research it’s actually will be opposite because there will be less public transportation vehicles more ride share and private autonomous cars on the road (Hint hint 🛴) of course this only apply in US I am sure you realize during your research other industrial countys are not investing heavily this technology they are more interested electric cars and electric public transportation vehicles some of those countries see autonomous vehicle is actually luxury and not environmental friendly