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Amid a race to market, the promoters who say a self-driving future is just around the corner rarely disclose one important thing—the price of outfitting an autonomous car. That extra cost, according to one of the few experts prepared to discuss the subject openly: about $250,000 per vehicle.

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You've seen the video on YouTube: Steve Mahan, a visually impaired, conservatively dressed, white-haired gentleman with a walking cane and Ben Hogan-style hat on his head, climbs behind the wheel of one of Google's nautical blue-colored self-driving Toyota Prius. He makes a "Run for the Border." Then Mahan, who has lost 95% of his eyesight, picks up his dry cleaning, takes a joy ride around his middle class looking community while munching on tacos. Then he returns to his driveway, exits the car (tacos in hand), and heads off camera toward the house, safe and sound, never having touched a steering wheel, brake or accelerator.

The clip is amusing and tremendously uplifting-showing how autonomous driving technology can empower a person, giving them a sense of independence and freedom to do whatever they want, when they want to do it. Problem is, most Americans (disabled or not) can't afford such a vehicle, even if one were available, let alone the advanced driving assist systems that are available to the public now, and serve as the building blocks of autonomous automobiles.

According to the National Automobile Dealers Association, the average American spends around $30,000 on a new car or light truck. In contrast, Interest.com's 2013 Car Affordability Study says that the average American can only afford to spend $20,806 on a car. The featured Prius, which starts at around $24,000, is optioned up with a $75,000 to $80,000 Velodyne LIDAR system, visual and radar sensors estimated to cost about $10,000, and a nearly $200,000 GPS array. Not to mention the cost of the driving computer and software. Put into context: The staid-looking Toyota Prius Mahan "drove" around in the video costs more than a Ferrari 599. At $320,000, that's an exclusive purchase, and well above the mean cost of a car, truck or SUV.

So, who, exactly are self-driving cars for? Proponents to make fantastic claims about autonomous vehicles and ADAS technologies, then automakers and other advanced safety system developers turn around and charge exorbitant prices for their creations, failing to factor in the need for mass adoption in the plan for success.

Fairness aside, cost will be an issue for driverless and self-driving car technologies well into the future. To provide all the vehicle electronic functionality, automakers must add complexity and unnecessary weight (wires, sensors and other components/modules) to a car. This can affect the cost of the vehicle, its performance, and how much it costs to keeping the vehicle on the road.

According to a recent study, "Emerging Technologies: Autonomous Cars-Not If, But When," IHS Automotive forecasts that the price for the self-driving technology will add between $7,000 and $10,000 to a car's sticker price in 2025, a figure that will drop to around $5,000 in 2030 and about $3,000 in 2035, the year when the report says most self-driving vehicles will be operated completely independent from a human occupant's control.

"It's a chicken and egg thing, the have's versus the have not's," says John Absmeier, director for Delphi's Silicon Valley Innovation Center. "When people start buying the technology the cost will come down, but the cost has to come down before most people will buy it. Consequently, [SDC technology] will come in through the luxury, high-end market and penetrate down as economies of scale kick in."

The incremental decreases in cost are projected based on the adoption of the technology (i.e., projected increases in sales of cars with SDC technology). IHS predicts that annual sales between 2025 and 2035 will jump from 230,000 to 11.8 million. That's about 9% of all the world's auto sales in 2035. Seven million of those 11.8 million vehicles will rely on a mix of driver input and autonomous control, with the remaining 4.8 million vehicles relying entirely on computers to get around. Combined with vehicles from previous model years, IHS also forecasts that there will be 54 million autonomous vehicles on the road by 2035. When will sales of autonomous cars outnumber those of conventional cars? IHS expects this tipping point to occur by 2050. By then, IHS says the majority of vehicles sold and those in use are likely to be autonomous, with conventional vehicles becoming increasingly rare.

Companies like Audi, BMW and Mercedes-Benz have a leg up on the competition in this case simply because their clientele is more affluent. "Our customers demand the latest technologies and are willing to pay for them, especially when it comes to safety technologies," says Rupert Stadler, Chief Executive Officer and Chairman of Audi AG. "We are simply giving them what they want, and anticipating what the customer of tomorrow will demand from us."

However, more mainstream brands, such as Ford, are looking more pragmatically at the bottom line. "We are not jumping into the self-driving arena simply to prove we can make a vehicle that can pilot itself under controlled situations," says Paul Mascarenas, Chief Technical Officer and Vice President of Research and Advanced Engineering at Ford. "We know we can do that. We need to deliver it in the most efficient, cost-effective way possible, and still have an excellent user experience."

The consensus in the automobile industry is that Google's idealistic approach to the driverless car won't bring the price of these technologies down far enough in price to make its car a mass-market proposition. So most outfits are working on less exotic but much cheaper approaches to the driverless problem: They're looking at ways to consolidate and simplify the hardware.

"We are looking into miniaturization, sensor fusion and integration of controllers, [to name a few technologies]," explains Ford's Mascarenas. "Anything that will make the technology more accessible."

Delphi's has been working on a new type of controller that takes into consideration all three of Ford's concerns. Its "multi-domain controller" is designed to take all of the data collected-from the body and security of the vehicle up through the active safety systems - and aggregate it into one controller, one processor that will then make the driving decisions and direct all the subsystems and sub-controllers in the vehicle. By combining all of the sensor inputs and processors into box, instead of hundreds, Delphi's controller will bring down the weight of the vehicle (improving fuel efficiency and performance) as well as complexity of the system (making it easier to maintain.) In addition, it makes the vehicle cheaper to build; fewer ECUs and the corresponding wire harnesses to drive the costs up.

Another popular target for most ADAS developers is the sensor array. Tesla's Elon Musk believes the LIDAR/RADAR sensor approach is too expensive. "It's better to have an optical system, basically cameras with software that is able to figure out what's going on just by looking at things," he recently told Bloomberg.

Mobileye, a technology firm headquartered in the Netherlands, is aiming to get most of the functionality into cars for much less, with equipment that cost hundreds of dollars, rather than the tens of thousands. It currently focuses on helping cars avoid collisions and pedestrians, as well as drifting out of lanes - most of the advanced safety features currently rolling out in higher end autos. The longer-term goal, is more ambitious: a semiautonomous vehicle that can handle many, but not all, driving functions without driver input. To that end, it has developed a low-cost alternative to expensive sensor arrays that uses a single camera and a "system-on-chip." It works as a third eye for the driver by supporting them in performing routine driving tasks (e.g., distance keeping, pedestrian identification, traffic-sign recognition) and provide timely warnings (e.g., lane departure warning, forward collision warning) in dangerous situations. Though he wouldn't discuss exact prices has not been announced, Ziv Aviram, a co-founder and the company's chief executive, told the New York Times that it is the "most cost-efficient system that's out there." One thing is for certain, the optical approach is currently more accessible, and Mr. Aviram is working with three powerhouses in the autonomous business: BMW, General Motors, and Volvo.

Driverless, self-driving, and autonomous driving technologies do have the potential to deliver improved safety and comfort for the driver and passengers, while reducing the vehicle's impact on the environment around it and reducing the cost to the driver. But don't expect to see a scene the like the one in Google's video-where a blind neighbor drives by while munching a taco-anytime soon in your neighborhood. In reality, most people in Steve's positionb who were head of household reported an annual household income of $25,550, according to the 2010 U.S. Census. Currently, the technology package in the Infiniti Q50 that includes adaptive cruise control, blind spot monitoring, lane keeping systems, and adaptive steering, costs an additional $6,600 above the base sticker price of around $37.000. Mercedes-Benz driver assist package costs around $3,000, but the base car costs just north of $92,000.

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Will You Ever Be Able To Afford A Self-Driving Car?

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Proponents of self-driving cars are sure they'll help save the planet and empower large groups of people with the freedom of mobility. But will the people who need the technology the most ever be able to afford it? Not anytime soon.

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This website says that there are many reasons driverless cars could fail.
One that is really worrying is that driverless cars could get hacked!

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In my last post, 7 Wonders of the Driverless Future, I listed seven magical societal benefits that driverless cars might deliver.

While I am optimistic about driverless cars, skepticism abounds about whether driverless cars can actually work and, even if they are technically possible, whether they should be allowed.

In the interest of facilitating a robust conversation, I want to offer seven of the most pressing concerns. Effective decision making, as Peter Drucker observed, depends on the dialogue between different points of view and a choice between different judgments.

The following differing points of view and judgments cover a wide range of potential issues, including technical viability, operational resiliency, and even fears that driverless cars might work too well and thus unleash a host of unwanted secondary effects.

Please feel free to reiterate, refute or add to the items on this list.

1. There are too many "corner cases." While driverless cars have demonstrated remarkable proficiency in many aspects of driving, some contend that many driving scenarios will remain unsolved. MIT's John Leonard, for example, points to left hand turns into heavy traffic, adverse weather, changes to road surfaces, and eye and hand gestures as open technical questions for which solutions " might be a very long way away." Leonard should know, he has been a central figure in the field for years, including a stint as the leader of MIT's autonomous car team in the famed 2007 DARPA Urban Challenge. (Watch this excellent presentation for Leonard's detailed assessment.)

2. The technology is not robust enough. Even if theoretical solutions are found, it might be hard to reliably translate them to the real world. Robustness would depend on a myriad of electronic, mechanical and software components operating with little tolerance for error under adverse (freezing, wet, boiling) conditions, long duty cycles, less than perfect maintenance (car owners being human), fender benders, network and electrical outages, and so on. Dr. Louise Cummings, for example, made a well-reasoned argument along these lines during a recent U.S. Senate committee hearing.

3. They will cost too much. The cost of sophisticated electronics, including lidar, radar, sensors, cameras, computing and networking devices, on top of the cost of additional development, maintenance, and liability, will price driverless cars out of reach of most consumers.

4. They will not mix well with human drivers. Even if driverless cars can learn to interact with human-driven cars, human drivers will not be able to deal with driverless cars. The resulting confusion would lead to more accidents and congestion, rather than less.

5. Regulatory and liability hurdles will long delay the technology. Legal and regulatory frameworks are all built around the assumption of human drivers. This encompasses expectations about who is liable for what and when, what components are required in cars, and so on. Sorting through the maze of necessary changes will take decades, and will offer ample points for entrenched interests to delay the approval process. Product liability might be a showstopper.

6. They will be hacked. Beyond the unintentional vagaries of the real world, driverless cars will suffer from attacks by hackers, hooligans, hijackers, thieves and terrorists. Risk range from invasion of privacy to the specter of driverless cars being used as precision bomb delivery vehicle.

7. They will cause economic devastation. By some estimates, 10% of all jobs are driving related. Driverless vehicles could put millions of Americans out of work, including taxi, Uber, bus and truck drivers. And, the list of jobs at risk do that stop there. Add auto suppliers, new car dealers, collision and repair shops, tow truck operators, insurance agents, adjustors, call-center operators, ambulance drivers, emergency medical personnel, traffic police, and untold other jobs related to how cars and trucks are designed, manufactured, sold and operated today.

These are serious issues and mandate that we approach the deployment of driverless cars with caution and deliberation.

Some issues embody technical challenges that developers must adequately address. Policy makers and regulators will have much to say, too, about acceptable standards and levels of verification.

Other issues, such as cost and user acceptance, will be decided in the market place. Driverless technology will enable tremendous business and service-level innovation. Customers, however, will have the last word on whether the products are good enough.

The hardest issues will be those that require making the societal tradeoffs between wonderful benefits and tremendous cost.

As with every major technological transition, driverless cars will result in winners and losers. There can be no neutral decisions. Whatever decisions are made (or not made) will result in gain to some and loss to others.

If you could choose, how would you decide?
(This article was updated and revised on April 9, 2016, including title, which was previously "7 Driverless Car Doomsday Scenarios.")
--
For a list of my other articles on driverless cars, see "Primers On Driverless Car Innovation And Disruption."

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In my last post, 7 Wonders of the Driverless Future, I listed seven magical societal benefits that driverless cars might deliver. While I am optimistic about driverless cars, skepticism abounds about whether driverless cars can actually work and, even if they are technically possible, whether they should be allowed.

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should self driving cars be aloud in a big city?

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should self driving cars be aloud in a big city?

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personally i think they shouldn't be aloud in the city because there is a high risk of frailer and could cause fatality's because there is a lot of pedestrians on the side walks.

how ever this website has a different opinion to this subject.

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You don't look for the essence of a city in its monuments or its museums. You look for it in its streets, where the covenant at the core of urban life-the sharing of space-plays out. For the past century, the personal car has dominated that arena, shaping the streets and environments around it. Roads are straight and wide for faster travel; intersections are regulated to protect distracted humans; businesses are located near open spaces for better parking. But as cars start to drive themselves, we have some ideas for how urban planners of the future might reimagine those outdated layouts-and transform the city into a joyful mess of throughways and byways optimized not for cars but for people.

Major Arteries

While main thoroughfares will still exist (so self-driving buses and trams can quickly get people where they need to go), there won't need to be as many. Autonomous tech will never be perfect, but limiting the places where cars can go fast should mitigate crashes.

Green Space

Even little bits of green-a tree here, a parklet there-can improve mental health. Great news: With less space needed for everybody's personal cars, nature can be everywhere. Also, why not move water runoff above ground as streams, for pedestrians to enjoy?

Nest Stops

Imagine: no need for curbside parking or sprawling garages. But parking won't go away entirely. It'll be too expensive for taxi companies to operate their driverless vehicles during off-peak hours, so cities will scatter small "nests"-pit stops for autonomous vehicles-throughout their streetscapes. Larger "hives" will house facilities for vehicle maintenance and charging.

Zombie Tax

With parking meters and traffic enforcement cops off the streets (no more towing!), the city will need new ways to raise funds. One idea: a per-minute tax on driverless cars with empty seats-zombie- mobiles only congest roadways.

Designated Stations

In roads optimized for self-driving taxis, ride hailers won't have to dash across lanes to catch cars-pickup and drop-off stations will be strewn throughout cities.

Zoning Free-for-All

Building height restrictions meant to reduce traffic and parking space requirements lose their justification in the self-driving city, so zoning laws can chill out.

Less Signage

Speed limits, stop signs, traffic lights: These are the trappings of a streetscape built for needy human drivers. In this future, cars will know the rules. The only street signs you'll see will provide ETAs for public transit. No delays, hopefully.

Call Centers

Self-driving cars won't be infallible. In case they get stuck or stumped by things like road construction, humans in call centers (maybe former Uber and Lyft drivers) will be ready to take control and get them out of jams.

Winding Roads

Side streets will serve people first, not cars. They'll meander around buildings and restaurants, stores and schools. Everyone's welcome: self-driving cars, cyclists, skateboarders, pedestrians. (Jaywalking, as crime and concept, has disappeared.)

Specialization

Large self-driving vehicles will serve different functions at different times: take kids to school in the morning, make some deliveries during the day, take kids home in the evening, assist with birthday bar crawls late into the night.

Lobby Boom

When cars don't park, no one enters buildings through the garage-they'll always enter through the lobby. Architects expect that everything from apartment complexes to dreary office buildings will have more elaborate entrances. Time to invest in that koi pond startup.

Delivery Bots

Street droids will make house calls for mail, groceries, and supplies, while fleets of flying drones handle bigger orders. At the end of their shifts, the delivery bots return to the mothership-a self-driving van.

Senior associate editor Alex Davies (@adavies47) and staff writer Aarian Marshall (@aarianmarshall) cover transportation for WIRED.
This article appears in the May issue. Subscribe now.
More Great WIRED Stories

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Lots of Lobbies and Zero Zombies: How Self-Driving Cars Will Reshape Cities

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You don't look for the essence of a city in its monuments or its museums. You look for it in its streets, where the covenant at the core of urban life-the sharing of space-plays out. For the past century, the personal car has dominated that arena, shaping the streets and environments around it.

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This website says that...

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Driverless cars used to be the sort of thing you'd see in sci-fi films - but in 2018 they're becoming a reality. Autonomous car technology is already being developed by the likes of Lexus, BMW and , and we've even tested Tesla's driverless Autopilot system on UK roads. Across the Atlantic, Google is developing its automated technology in the wild, and Apple is rumoured to be working with BMW on its own - probably automated - car.

Fully-driverless tech is still at an advanced testing stage, but partially automated technology has been around for the last few years. Executive saloons like the BMW 7 Series feature automated parking , and can even be controlled remotely.

Autonomous tech is also enjoying heavy investment around the world, especially in the UK. In 2015, the government announced new laws for testing driverless vehicles on our roads and, with them, an unprecedented £20 million investment into the technology.

With so much investment and interest in driverless technology, it's easy to assume that self-operating cars are imminent, but they're much further away than we might think. Before our roads are flooded with driverless vehicles, manufacturers must tackle a range of technical and ethical challenges, and combat the biggest threat to autonomous technology: humans.

The Google Car

Autonomous vehicles rely on a range of sensors to interact with the world around them, with the prototype coming equipped with eight.

The most noticeable is the rotating roof-top LIDAR - a camera that uses an array of either 32 or 64 lasers to measure the distance between objects, building up a 3D map at a range of 200m and allowing the car to "see" hazards. The car also sports another set of "eyes", a standard camera that points through the windscreen. This looks for nearby hazards like pedestrians, cyclists and other motorists, as well as reading road signs and detecting traffic lights. Speaking of other motorists, bumper-mounted radar, already used in intelligent cruise control, tracks other vehicles in front of and behind the car .

Externally, the car has a rear-mounted aerial that receives geolocation information from GPS satellites, and an ultrasonic sensor on one of the rear wheels monitors the car's movements. Internally, the car has altimeters, gyroscopes and a tachometer (a rev-counter) to give even finer measurements on the car's position, all of which combine to give it the highly accurate data needed to operate safely.

Using these arrays, the Google Car can read the road like a human, but these sensors come with their own limitations. Autonomous cars simply replace the human eye with a camera, leaving them vulnerable to extreme sunlight, weather or even defective traffic lights. In current autonomous cars, the way this selection of pixels is analysed could be the difference between a safe journey and death.

Since Google unveiled it s self-driving car, it has spun off this part of the business into a separate arm under the name Waymo. The name comes from Google's mission to find "a new way forward in mobility."

Connected Cars

Many believe a connection between cars and traffic infrastructure is needed to combat this problem. "Car-to-car and car-to-infrastructure communication is essential for enabling autonomous driving," says Christoph Reifenrath, senior manager in technology marketing of Harman's infotainment division, who supply in-car tech to the likes of Audi, BMW and Mercedes .

"Car-to-infrastructure communication is essential for enabling autonomous driving."

"For example, as your car approaches a red light, we'll give you information. How can we provide this information in every car at every red light? There has to be a solution for that for if you want to enable autonomous driving in areas with traffic lights."

The German automotive industry is one of the most powerful advocates of a connected car-traffic infrastructure. Earlier this week, manufacturers including Daimler, BMW and Audi paid $3.1 billion for the Nokia Here mapping service, which will be used as a platform for a connected-car environment. A joint statement released by the consortium reads:

"[Nokia] Here is laying the foundations for the next generation of mobility and location based services. For the automotive industry, this is the basis for new assistance systems and ultimately fully autonomous driving. Extremely precise digital maps will be used in combination with real-time vehicle data in order to increase road safety and to facilitate innovative new products and services."

To become a viable solution, these systems will be required in every vehicle, including those still used by humans. It's likely that emergency vehicles like ambulances and police cars will continue to use human drivers, so they'll need a method of communicating with the autonomous cars around them.

"You have to know where [an emergency vehicle] comes from and when it will be there, so the information is shared between this car and your car," adds Reifenrath.

The human problem

Although autonomous cars will need better, more connected infrastructure to function effectively, they still face a larger, more unpredictable factor - us. Humans present problems for autonomous cars as both drivers and pedestrians, and dealing with our unpredictable behaviour represents a significant challenge for the technology.

"Humans present problems for autonomous cars as both drivers and pedestrians"

The Google Car is one of the most experienced autonomous vehicles, and its interaction with human drivers has exposed one of driverless cars' main weaknesses. The first injury involving the Google Car wasn't due to a fault in its system, but human-error.

Revealed by Google earlier this month, an incident in July was caused by a human driver's failure to stop. While correctly waiting at traffic lights, Google's self-driving car was hit by an inattentive driver and, despite its sophisticated array of sensors, there was little it could do to avoid the incident. Luckily, the accident only resulted in whiplash for a few of the passengers, but it's a reminder that autonomous cars are at risk when surrounded by human road users.

Google Car's project leader Chris Urmson was one of the people involved in the accident, and his subsequent Medium post describes the event in detail. "The light was green, but traffic was backed up on the far side, so three cars, including ours, braked and came to a stop so as not to get stuck in the middle of the intersection," he writes. "After we'd stopped, a car slammed into the back of us at 17mph - it didn't brake at all."
READ NEXT: The slow self-driving cars of Greenwich
Despite their sophisticated systems, self-driving cars currently have no plan B for human road users. Human drivers are able to interact with each other and make allowances, but also make countless, small mistakes when driving - mistakes to which current self-driving cars simply can't adapt. Although there was little that could be done to avoid the Google Car's latest accident, it's a stark reminder of autonomous technology's biggest hurdle.

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Driverless cars of the future: How far away are we from autonomous cars?

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Driverless cars used to be the sort of thing you'd see in sci-fi films - but in 2018 they're becoming a reality. Autonomous car technology is already being developed by the likes of Lexus, BMW and Mercedes, and we've even tested Tesla's driverless Autopilot system on UK roads.

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driver less cars

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1. will driver less cars take off in 2020?

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You can find me on Twitter @bhutanisanyam1, connect with me on Linkedin here

Here are my Garage Projects
Here and Here are two posts on my Learning Path to Self Driving Cars

The MIT Deep Learning for Self-Driving Cars course just released their F irst lecture video (alternatively Here are the lecture notes if you want a quick read)

The Lecture is an overview of Deep Learning techniques and has some discussions on the future of Self Driving Tech as well, and a brief warning about the Gaps of current systems.

Here is the take on how far away are we from an Autonomously Driven Future and a brief touch on Ethics:

By 2017, Computer Vision has reached 97.7%+ accuracies! (ImageNet challenge) Amazing isn't it?

So how far are we from a fully autonomous World?

97.7% sounds good enough. Is it?
After all driving involves a lot of Computer Vision and it is indeed better than human high scores-so are we close?

The ImageNet Challenge involves classifying 14M images into one of 22,000 possible classes.

How good is this accuracy when its extrapolated to the real world?

Now yes, the classes involved in the challenge wouldn't all be involved in the SDC scenario but they do point out to one thing, Computer Vision, although it's more accurate than Humans now, is still not perfect. It isn't a 100% accurate.

That coupled with the dynamics of the real world suggest that there is a small chance of the Autonomous systems behaving in unexpected ways. Would you trust the system completely in under all scenarios? To handle every situation better than a Human Driver?

The argument made in the lecture is that SDCs as of now will work as tools that would help us drive better. They might even drive better than us, but at points, Humans would need to intervene. We have a Semi-Autonomous year as of 2018.

Roughly, in 90% of the Cases, the Car will drive itself better than us, but for the remainder of 10% cases, Human intervention/control would be required.

A 100% accuracy would have a universal approval, which would require a generalisation over all the unexpected cases too, for example: A situation of 1 in a Million, where a Deer would cross the road and the situation has to be handled.

Lex Fridman argues in the Lecture that the 'perfect system' would require a lot more research efforts and increase in Efficiency of Deep learning algorithms. Which as of now are highly inefficient as well (Computationally speaking).

By the perfect case- I'm not referring to the case that a car that can drive itself. The perfect case is where, we'd be so confident about the systems that we would no longer have steering wheels in our vehicles. That human driving would be considered more dangerous than the automated one.

Till then SDCs would definitely appear on the road, we might not have to hold the steering wheels for long durations, no doubt. But there will definitely be moments when Human control would be required. Hence, the term Semi-Autonomous.

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How Far Are We from a Fully Autonomous Driving World?

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You can find me on Twitter @bhutanisanyam1, connect with me on Linkedin here Here are my Garage Projects Here and Here are two posts on my Learning Path to Self Driving Cars The MIT Deep Learning for Self-Driving Cars course just released their F irst lecture video (alternatively Here are