2 items tagged "self-driving car"

  • Big data and the future of the self-driving car

    Big data and the future of the self-driving car

    Each year, car manufacturers get closer to successfully developing a fully autonomous vehicle. Over the last several years, major tech companies have paired up with car manufacturers to develop the advanced technology that will one day allow the majority of vehicles on the road to be autonomous. Of the five levels of automation, companies like Ford and Tesla are hovering around level three, which offers several autonomous driving functions but still requires a person to be attentive behind the wheel.

    However, car manufacturers are expected to release fully automatic vehicles to the public within the next decade. These vehicles are expected to have a large number of safety and environmental benefits. Self-driving technology has come a long way over the last few years, as the growth of big data in technology industries has helped provide car manufacturers with the programming data needed to get closer to fully automating cars. Big data is helping to install enough information and deep learning in autonomous cars to make them safer for all drivers.

    History of self-driving cars

    The first major automation in cars was cruise control, which was patented in 1950 and is used by most drivers to keep their speed steady during long drives nowadays. Most modern cars already have several automated functions, like proximity warnings and steering adjustment, which have been tried and tested, and proven to be valuable features for safe driving. These technologies use sensors to alert the driver when they are coming too close to something that may be out of the driver’s view or something that the driver may simply not have noticed.

    The fewer functions drivers have to worry about and pay attention to, the more they’re able to focus on the road in front of them and stay alert to dangerous circumstances that could occur at any moment. Human error causes 90 percent of all crashes on the roads, which is one of the main reasons so many industries support the development of autonomous vehicles. However, even when a driver is completely attentive, circumstances that are out of their control could cause them to go off the road or crash into other vehicles. Car manufacturers are still working on the programming for autonomous driving in weather that is less than ideal.

    Big data’s role in autonomous vehicle development

    Although these technologies provided small steps toward automation, they remained milestones away from a fully automated vehicle. However, over the last decade, with the large range of advancements that have been made in technology and the newfound use of big data, tech companies have discovered the necessary programming for fully automating vehicles. Autonomous vehicles rely entirely on the data they receive through GPS, radar and sensor technology, and the information they process through cameras.

    The information cars receive through these sources provides them with the data needed to make safe driving decisions. Although car manufacturers are still using stores of big data to work out the kinks of the thousands of scenarios an autonomous car could find itself in, it’s only a matter of time before self-driving cars transform the automotive industry by making up the majority of cars on the road. As the price of the advanced radars for these vehicles goes down, self-driving cars should become more accessible to the public, which will increase the safety of roads around the world.

    Big data is changing industries worldwide, and deep learning is contributing to the progress towards fully autonomous vehicles. Although it will still be several decades before the mass adoption of self-driving cars, the change will slowly but surely come. In only a few decades, we’ll likely be living in a time where cars are a safer form of transportation, and accidents are tragedies that are few and far between.

    Source: Insidebigdata

  • The data management issue in the development of the self-driving car

    The data management issue in the development of the self-driving car

    Self-driving cars and trucks once seemed like a staple of science fiction which could never morph into a reality here in the real world. Nevertheless, the past few years have given rise to a number of impressive innovations in the field of autonomous vehicles that have turned self-driving cars from a funny idea into a marketing gimmick and finally into a full-fledged reality of the modern roadway. However, a number of pressing issues are still holding these autonomous vehicles back from full-scale production and widespread societal embrace. Chief amongst them is the data management challenge wrought by self-driving vehicles.

    How should companies approach the dizzying data maze of autonomous vehicles? Here’s how to solve the data management of self-driving cars, and what leading automotive companies are already doing.

    Uber and Lyft want to release self-driving cars on the public

    Perhaps the most notable development in the creation of autonomous vehicles over the past few years has been that Uber and Lyft have both recently announced that they’re interested in releasing self-driving cars to the general public. In other words, these companies want autonomous vehicles that are navigating complex city environments by themselves and without the assistance of a human driver who can take over in the event of an emergency.

    Uber has already spent a whopping $1 billion on driverless cars, perhaps because the ridesharing app relies heavily on a workforce of freelancers who aren’t technically considered full-time employees. It could be that Uber and other companies see a financial imperative in automating their future workforce so that they don’t have to fret about providing insurance and other benefits to a large coterie of human employees. Whatever the company’s motivations, Uber has clearly established itself as a leader in the self-driving car space where investments are concerned and will continue to be a major player for the foreseeable future.

    Other companies like Ford may have the right idea, as they’re moving in the opposite direction of Uber and trying to take things slowly when debuting their autonomous vehicles. This is because Ford believes that solving the data management challenge of self-driving cars takes time and caution more than it does heavy spending and ceaseless innovation. Ford’s approach opposite to Uber's approach to self-driving cars could pay off too, as the company has avoided the disastrous headlines that have followed Uber everywhere when it comes to testing and general brand PR.

    We can learn from Ford in one regard: haste. Though important when delivering a product to market, it often results in shoddy production that leads to costly mistakes. The company is deciding to take things slow when it comes to collecting and managing data from auto insurance companies, which is a standard others should be following if they don’t want to get in over their heads. Ford’s focus on creating data 'black boxes' not dissimilar to those on airplanes, which can be consulted in the event of a major crash or incident for a data log of what occurred, is going to become a standard feature of autonomous vehicles before long.

    It’s a matter of trust

    It’s going to become increasingly obvious over the next few years that solving the data management challenges wrought by the advent of self-driving cars is going to be a matter of trust. Drivers need to be certain that their cars aren’t acting as surveillance devices, as does society broadly speaking, and manufacturers need to be taking steps to build and strengthen trust between those who make the car, those whose data the car collects, and those who analyze and utilize such data for commercial gains.

    The fierce competition between Tesla and Waymo is worth watching in this regard, largely because the profit incentives of the capitalist marketplace will almost assuredly lead both of these companies to throw caution to the wind in their race to beat one another via self-driving cars. We will only be able to solve the data management challenge issued by autonomous vehicles if we learn that sometimes competition needs to be put aside in the name of cooperation that can solve public health crises like deaths resulting from self-driving vehicles.

    The data management challenge posed by self-driving cars demands that that auto and insurance industries also take ethics into consideration to a hitherto undreamt-of extent. Modern vehicles are becoming surveillance hubs in and of themselves, with Tesla’s newest non-lidar approach to self-driving car data collection proving to be more accurate, and thus necessarily more invasive, than nearly any other technique that’s yet been pioneered. While this may help Tesla in the sense that it’s propelling the company ahead of its adversaries technologically speaking, it poses immense ethical questions like what the responsibility of the market leader is when it comes to fostering innovations which necessarily surveil the public in order to function.

    It’s a self-driving world now

    The data management challenges being generated by the ceaseless advance of self-driving vehicles won’t go away anytime soon, as we’re now in a self-driving world where automation, data collection (another term for surveillance), and programmatic decision-making is the new standard. While we’ve grown so used to always being the one doing the driving, humans are now being put in the backseat and must trust in the capacity of machines to deliver us to a brighter future. In order to arrive at our destination unimpeded, we need a new focus on ethics across the automotive and insurance industries that will ensure this new technology is primarily used for good.

    Additional regulation will be needed in order to protect the privacy of everyday people, and modern infrastructure must be constructed in order to alleviate the sensory-burden being placed on autonomous vehicles if they’re to succeed in the long-term. The good news for those who love self-driving cars is that the profit incentive is enough to make companies plow ahead regardless of the data management challenges they’re facing. This could result in huge ethical dilemmas later on, though, so those interested in self-driving cars can’t allow humans to become unmoored from the driver’s seat if we want our values to be represented on the roads of tomorrow.

    Author: Steve Jones

    Source: SmartDataCollective

EasyTagCloud v2.8