Last week, police in Tempe, Arizona, released dash cam footage showing the final seconds before an Uber self-driving vehicle crashed into 49-year-old pedestrian Elaine Herzberg, who died at the hospital shortly afterward.

While Herzberg is visible for less than two seconds in the camera footage, she might have become visible earlier to a human driver, since human eyes are better at picking out details in low-light situations. The police also released internal dash cam footage showing the car’s driver, Rafaela Vasquez, in the seconds before the crash. Vasquez can be seen looking down toward her lap for almost five seconds before glancing up again and realizing what is about to happen.

This is not the first collision involving a self-driving vehicle. Other crashes have involved Ubers in Arizona, a Tesla in ‘autopilot’ mode and many others in California. While it is still not clear as to who is to be blamed for the latest incident, most of the other crashes were due to human error.

Image source: ReadWrite

Why do autonomous vehicles crash? The first cause is when the sensors don’t detect what is happening around the vehicle. In the case of Herzberg, she was walking with a bicycle across a poorly lit roadway. About 1.4 seconds elapse between the time when Herzberg starts to become visible and the video’s final frame. Each car and each sensor works differently. In some, GPS may work only with a clear view of the sky or the camera may function properly only with ample light. Researchers aren’t clear about the ‘ideal’ set of sensors in an autonomous vehicle, and can’t keep adding more and more to the fleet because of cost limitations.

The second cause is when the vehicle encounters a situation that the software didn’t plan for. Much like human drivers, self-driving cars also make many decisions at any given second. So, when a self-driving car sees something it’s not programmed to handle, it becomes difficult to assess what is going to happen next. So, the challenge for programmers is to combine information from all sensors to create an accurate representation of the surroundings. If that doesn’t happen, the vehicle can’t take a call.

Before we can release autonomous vehicles on the road completely, they need to be programmed with a whole set of instructions about dealing with the out-of-the-ordinary, and plan for extreme adverse situations. A human driver, for instance, might even break a few traffic rules to save lives. The autonomous car needs to be taught how to do the same instead of waiting or the situation to pass.

Additionally, self-driving cars must be taught to understand their surroundings and the context. In the crash involving Herzberg, the car should have been tested and rated based on how well it performed difficult tasks, including assessing danger in fraction of a second. This is a lot like a human driving test, but that is how it should be if the two have to co-exist safely on the road.

Another approach to this could also be explicitly stating rules in formal logic, like how nuTonomy, which is running an autonomous taxi pilot in cooperation with authorities in Singapore, is doing. NuTonomy’s approach to controlling autonomous vehicles is based on a rules hierarchy. Top priority goes to rules such as “don’t hit pedestrians”, followed by “don’t hit other vehicles” and “don’t hit objects”. Rules such as “maintain speed when safe” and “don’t cross the centreline” get a lower priority.

Image source: The Verge

Learning how to drive is an ongoing process for both humans and their autonomous cars, as both adapt to new situations, road rules and technology. Time will tell the better approach, but for now, the research still has a long way to go.

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Waymo, the autonomous car development company, recently made history by launching cars on public roads without any safety drivers behind the wheel. The tests aren’t limited to one or two routes, and the cars are able to go anywhere within a defined space, in this case, the space being Chandler in Arizona.

Driverless cars have the potential to completely transform the way we travel. In his most recent TED talk, even Elon Musk, co-founder of Tesla, said that “by the end of this year, an autonomous car will be able to leave a parking space in Los Angeles, navigate all the way across America, and park in a space in New York.” With this shift, there will also arrive a plethora of benefits; from reduced travel costs, to increased road safety and more efficient trips.

We all have, at some point of time in our lives, faced the nightmare of holiday traffic. Long weekends and holidays like Christmas and New Year’s are considered to be some of the most popular and busiest travel days of the year, with many travellers driving to their destinations by car. The advent of self-driving cars could reduce, if not fully eliminate, all this holiday traffic. Self-driving vehicles will be able to travel quickly, instead of being stuck in traffic on congested highways. They will be able to drive closer to the cars in front of them, at faster speeds, and navigate narrow lanes than are generally prone to human error.

Image source: EnergyKids

Self-driving cars may even help travellers plan ahead for increased efficiency. Once the vehicle knows the destination, it could suggest an alternate route based on the expected number of vehicles on the usual route. The car could then also recommend that travellers leave a day earlier or late, or even at two in the morning, to avoid getting stuck.

Autonomous cars could be a game-changer for the airline and rail industry as well. With increased efficiency and reduced costs, people may choose to travel by car than planes or trains. This, in turn, could drastically cut down flying costs, as the airline industry tries to keep up with the advent of this new technology and changing passenger demands. Additionally, self-driving cars allow for point-to-point transportation, which means no more wasted time travelling to a bus or train station or the airport.

Self-driving cars are all set to alter the landscape of mobility and revolutionize the automotive industry, public transport and swathes of the global population. While there is still a lot that needs to be sorted in terms of acceptance and readying our infrastructure for such cars, the excitement in the air is tangible with a faster and more efficient future of travel on the way.

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Auto companies are more open than ever to look beyond what they are doing and explore what they see as the future of transportation. However, in order to move quickly, they are looking outside for allies to build on the strengths of each other. Taking another step in the same direction, Volvo is making progress with the partnership with Autoliv called Zenuity announced earlier. Building on Nvidia’s PX in-car AI computing platform, they plan a commercial rollout of cars with Level 4 autonomy by 2021.

Autoliv is a leading automotive safety company while Nvidia has been aggressively moving ahead in this space. Previously the company announced partnership with Baidu to work on development of autonomous vehicles. Nvidia’s Drive PX already powers autonomous vehicles on testing currently.

This partnership highlights how large corporations are more open to collaborations and the trend will continue in the time to come. While the software they are developing will be unique to Volvo in ways, Autoliv will have right to make the software available to other automakers through its existing relationships. Nvidia too will gain from this partnership as adoption by other automakers will give its PX platform a push across a wider range of vehicles.

“This cooperation with NVIDIA places Volvo Cars, Autoliv and Zenuity at the forefront of the fast moving market to develop next generation autonomous driving capabilities and will speed up the development of Volvo’s own commercially available autonomous drive cars,” said Hakan Samuelsson, president and chief executive of Volvo Cars.

Jan Carlson, chief executive of Autoliv, said: “With NVIDIA, we now have full access to the leading AI computing platform for autonomous driving. Autoliv, Volvo Cars and NVIDIA share the same vision for safe, autonomous driving. This cooperation will further advance our leading ADAS and autonomous driving offerings to the market.”

To work towards safer autonomous vehicles, Nvidia also signed up ZF and Hella to build additional safety standards into its autonomous vehicle program. In another development, Nvidia also announced partnership with VW to leverage AI in variety of mobility services beyond autonomous vehicles. Together, they are also looking to support startups in the space with VW Data Lab.

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We have been witnessing Samsung vs Apple in the smartphone industry for years now. That battle isn’t going away anywhere however, a new one is just beginning. Soon after reports of Apple testing its self-driving cars started appearing, it is being reported that Samsung has received permissions to test self-driving car.

South Korea’s Ministry of Land, Infrastructure, and Transport has granted Samsung the required permissions to test its self-driving car. It is reported that Samsung will use South Korean carmaker Hyundai’s vehicles for the testing and the vehicles will be equipped with Samsung’s hardware and software. Hyundai itself is working in the same direction, or at least has plans to do so, and was the first one to obtain South Korean government’s approval to test self-driving vehicles. Samsung becomes the first tech company to do the same.

Samsung has previous tried its hands in the auto industry and with this development, there were speculations that Samsung might consider the same again. However, the tech giant quickly dismissed the rumours claiming that the test run approval is to run pilot for developing the software.

The company statement said, “The test run approval does not mean that Samsung is making a self-driving car. The pilot run is being carried out for software and solution development for an autonomous car, nothing more.”

The bankrupt Samsung Motors was sold to Renault in 2000 with Samsung holding 19.9 percent of the resulting Renault Samsung Motors. However, as auto industry begins its shift towards becoming transportation industry, an increasing number of tech companies are trying to be a part. Samsung recently acquired Harman, which has a range of in-car connectivity solutions, for USD 9 billion and has been registered presence across auto shows over the past few years.

For its self-driving endeavours, Samsung will use off the shelf laser and radar systems manufactured by other companies with its own software algorithms and AI. With this, Samsung joins the ever expanding list of companies working towards developing self-driving vehicles. What role the South Korean tech giant is looking to assume in the transportation ecosystem of future is something only time will tell.

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The Chinese search giant Baidu has taken another step towards supporting the development of self-driving vehicles. The tech giant has announced a new autonomous vehicle platform called Project Apollo to help car companies accelerate their self-driving car developments. With the platform, Baidu will be offering the partners both tech and open source code needed to operate autonomous vehicles.

Baidu plans to open up Project Apollo for testing in closed environments in July and then offer it for vehicles operating in urban conditions later this year. Baidu set an optimistic goal for itself to deliver self-driving vehicles to the market by the year 2018. The company got permissions to test the vehicles in California last year and also partnered with Nvidia to work together towards the common goal.

Baidu initially started working on driverless cars with German car manufacturer BMW which has been working on the technology for well over a decade. However, the partnership was called off last year reportedly due to different pace of both the companies. The new project, Project Apollo will also help Baidu find new partners to work with, including car manufacturers from its home country.

Last year, BMW, in association with Intel and Mobileye announced a platform to create common technology standards and bring together multiple brands working in the same direction. According to Intel chief executive Brian Krzanich, the platform would play a critical role in advancing the safety aspects of driverless cars.

A survey last year indicated that Chinese were more open to the idea of using a car with autonomous functions compared to Germans and Americans. And while Baidu has got the tech and data to build for its home market, it won’t be easy to beat Waymo (Google) in other parts of the world because of its deep map data and years of head start.

Source: MarketWired

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NuTonomy, the autonomous car startup spun out of MIT will soon begin testing its autonomous vehicles in Boston. The company beat Uber to public streets in the race for autonomous cars by rolling out driverless taxis in Singapore. It announced that it has signed an agreement with officials in Boston to roll out driverless cars to the city streets and the testing will begin in an industrial park in South Boston later this year.

Similar to Singapore, their autonomous Renault Zoe electric cars will be operated in public area but somewhat removed from the whole urban chaos an average driver deals with. Initially only company engineers will be riding the cars in Boston however, there could be plans to open it up for public like the Singapore program.

“These tests in the city of Boston will enable our engineers to adapt our autonomous vehicle software to the weather and traffic challenges of this unique driving environment,” company CEO and co-founder Karl Iagnemma said in a statement. “Testing our self-driving cars so near to nuTonomy’s home is the next step towards our ultimate goal: deployment of a safe, efficient, fully autonomous mobility-on-demand transportation service.”

According to company statement, there are plans to have a dozen cars on the roads in Singapore as this year approaches a close. In Singapore, the cars are picking and dropping passengers through a partnership with Grab. nuTonomy will have to put together a similar partnership in Boston which is highly unlikely considering the fact that it would cause conflict of interest as both Uber and Lyft are working on their own versions of self-driving cars. Uber is already running tests in Pittsburgh which kicked off a short while after nuTonomy launched the program in Singapore.

The race for autonomous vehicles is getting competitive as almost all the players in the space are registering good progress. Alphabet (Google) seems to be much further ahead of the others but it is still a long way to go before any one of these players could actually start affecting the ground transportation.

Source: WSJ

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Road travel is going to be much safer, or at least there is a promise, when fully autonomous vehicles arrive. You can go much longer without fatigue and with minimum risks. Even local commute would be much safer and less frustrating, probably making the whole world more efficient. But all that is still a while away. Google has been testing its self-driving car for years now and every month there is a report on the project.

During August, the Google vehicles travelled 126,000 miles in autonomous mode, close to what an average human driver drives in 10 years. The number of miles driven have been doubled over the last year to prepare the system with as much learning as possible. They are now being subjected to testing in new areas including dusty desert conditions.

But the most important thing to watch for are the collisions. Minor accidents are inevitable for any vehicle and with more time spent on road, it is more likely. We have been observing the accidents that Google shares in its monthly report and on almost all the occasions, it is the human driver at fault. Over all these years, there have been one or two incidents where the driverless vehicle failed to understand the situation and got involved in an accident. While the incidents involving human errors are just far too many. Even this month, there were two incidents of slow speed crashes, in both the cases the car was rear ended while standing. Another crash in manual mode involved a vehicle that ran a red light.

The Google self-driving vehicles are performing much better than an average driver in the region already. And this while also dealing with the different response the Google vehicles get from other road users. Earlier this year, Google highlighted how people are leapfrogging in front of these vehicles. Another crash that month was because a disoriented driver rear ended a Google vehicle.

These are all minor incidents and it is very likely that many of them would have gone unreported. However, this reinforces the idea all the self-driving car projects begun with. We really need them for a safer, better ground transport in future.

You can find the report for August here.

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