The road to driverless cars
Gartner, Inc.
Connected cars made big news at the Consumer Electronics Show in Las Vegas this month. It’s not surprising with this year’s buildup of buzz surrounding autonomous and connected vehicles, and the ecosystem of technology that is feeding them. Gartner forecasts 21 million new automobiles will be equipped with data connectivity, either through a built-in communications module or tethered to a mobile device in 2017.
However, amidst the opportunities for a range of technologies to merge our various worlds of data and to sense both vehicular and human conditions, several hurdles remain before connected cars become mainstream.
Ogi Redzic, senior vice president for connected vehicles at the Renault-Nissan Alliance, stands next to the Nissan Motor Co. Intelligent Mobility IDS Concept electric vehicle during the 2017 Consumer Electronics Show (CES) in Las Vegas, Nevada, U.S., on Thursday, Jan. 5, 2017. Nissan is betting that regulators will find it easier to approve vehicles that have all the capabilities of a self-driving car but are supervised by humans miles away. Photographer: Patrick T. Fallon/Bloomberg
Regulatory hurdles
The biggest hurdle will likely be regulatory. Governments will need to feel comfortable with the rules put in place before these cars are released to the general public.
The current state of autonomous vehicle development is still fragmented as automobile manufacturers, large technology providers, chip companies and lesser-known tech innovators vie for a seat at the table. The critical capabilities for automated driving cluster around sensing technologies, 3D mapping and data analytics, and algorithms for computer vision, localization and path planning. Until clear leaders and standards begin to emerge in each of these areas, we will continue to see different alliances forming around the autonomous vehicle initiatives of leading car companies.
Extract value from data
The development of data analytics algorithms has progressed rapidly in the IT industry, and these technologies are being adopted in the automotive industry to extract value from the streams of data generated by the connected-vehicle fleet. We are only beginning to scratch the surface of understanding and putting to work all of the data that cars produce. We expect that by 2020, 50% of motor vehicle manufacturers will apply advanced analytics to connected-vehicle data to identify and correct product defects.
This trend presents an unprecedented opportunity for the automotive industry to accelerate the process of locating product defects and identifying root causes. Using data, problems in a whole fleet can be looked at, and the data can help guide engineering decisions and repairs. Additionally, problems that might not have been previously noticed can be identified. Automotive companies are eager to see the impact of these innovations such as reduced costs from recalls, service bulletins and settlements, along with improved customer satisfaction.
Biometric and sensing abilities
Imagine a scenario where a car senses that a driver is having a heart attack and takes over the vehicle from the driver. Biometrics technologies hold life saving potential for drivers and passengers of autonomous vehicles.
Ford has patents on systems that can tell when a driver is in an agitated state and will hold incoming phone calls. Preventing people from getting into dangerous situations is opening up many interesting technology avenues. We are also seeing driver monitoring systems – enabled by a camera watching the driver – which are designed to make sure he is not falling asleep or distracted while behind the wheel.
As cars become more automated, they are being equipped with an increasing array of sensing technologies, including cameras, radar and lidar systems. Many automobiles will use image detection as the primary means to identify and classify objects in the vicinity of the vehicle so they can provide more sophisticated responses and even have autonomous control. The captured images can be correlated with time, geolocation and other sensor information for contextual analysis to improve predictive accuracy and enrich the user experience.
Mike Ramsey is a research director in Gartner's CIO Research Group. Mike covers smart mobility and the evolution of the automotive industry, including advanced manufacturing, the rise of vehicle autonomy, connected vehicles, suppliers and future technology.
via Forbes
