What does the future hold for personal transportation? For one, you’ll be spending a lot less time behind the wheels. Self-driving cars are now a reality and their availability is just around the corner. Today’s cars already have multiple semi-autonomous features, like assisted parking and self-braking systems. Completely autonomous vehicles, which are able to operate without human intervention, are rapidly coming to the fore. The advantages of autonomous cars are many. Autonomous driving is a key element of the global transportation industry’s drive toward making roads safer. With driver errors causing over 90% of accidents, there is every reason to believe that self-driving cars will bring down their frequency and severity, which in turn will lower insurance costs drastically.
What technologies make self-driving cars possible? There’s three – sensors, connectivity, and automotive cameras. Most of the sensors required for autonomous driving are used in advanced safety features such as blind-spot monitoring, lane-keeping assistance, and forward collision warning. Sensors such as radars and cameras help cars navigate safely. Connectivity and cameras in self-driving cars enable access to information on traffic conditions, weather, maps, adjacent cars, and road conditions.
Research on Global Markets conducted an in-depth assessment of the global self-driving car market, along with its driver, challenges, trends, and the technology components that are impacting the industry.
- Demand for global self-driving cars’ products and services
- Major drivers and challenges affecting the adoption of self-driving cars
- Key trends in the self-driving vehicle industry
- Historical, current and forecasted values for the global self-driving car market
- The global self-driving car market is expected to be worth USD 155.59 by 2024, expanding at a CAGR of 50.9%.
- The growth of the global self-driving car market is expected to drive the demand for infotainment and connectivity services
- Technological advancements in the fields of artificial intelligence and machine learning will further augment the capabilities of self-driving cars
- Car manufacturers are investing heavily in artificial intelligence to be a step ahead in the era of self-driving cars
- Rise of the Mobility as a Service (MaaS) sector is anticipated to provide an impetus to the autonomous car's market
- Demand for driverless cars is on the rise owing to increased government regulations around the world
- North America is slated to hold the largest share in the self-driving car's market, with the U.S. witnessing the highest adoption of driverless technology
Autonomous Cars Scheduled for 2019 Roll Out?
Following the hype around autonomous cars over the last few years, 2019 is tentatively earmarked as the year when the world will witness cars that can drive themselves independently. Automotive behemoth General Motors is set to put out its fourth-generation of autonomous vehicles by 2019, which won't have steering wheels, pedals, or any instrument panels. Not far behind is Google-owned Waymo, which announced at the Google IO conference that the company will roll out robo-rides in 2019.
General Motors and Waymo have already invested huge amounts into getting the technology to its current state. Testing their own autonomous vehicles on roads provides it an exemplary opportunity to gather more data to further enhance these systems as they strive towards achieving commercialization of these vehicles.
Another big automotive player, Tesla, is lagging in developing its first fully self-driving car, despite touting its Autopilot system as self-driving. The automaker seems to be struggling with mass-production — a problem that doesn’t faze a company like GM, which has been rolling out cars the assembly line for more than a century.
Automaker Ford has set up its autonomous car division within the company - Ford Autonomous Vehicles LLC. This division handles all aspects of self-driving vehicle business operations in a bid to accelerate vehicle automation and capitalize on market opportunities. The company is set to launch a self-driving car without a steering wheel, a brake pedal or an accelerator, by 2021.
Automakers are investing heavily in self-driving technology and are looking to align more closely, their self-driving platforms, with their mobility solutions team. In the next three years, almost all automakers will be able roll out cars capable of navigating city streets at casual speeds on firmly fixed routes. This can give an impression of the parity and uniformity. Despite the market being in its initial stages, potential market leaders are beginning to emerge.
Impact of Autonomous Cars
Car crashes account for tens of thousands of deaths across the world, resulting in millions of dollars in forgone economic contributions. The advent of autonomous vehicles can significantly transform the scenario with respect to reducing road accidents significantly. Typically, computers react quicker than humans, owing to their enhanced cognitive intelligence, and the best part is, computers do not text, drink, or daydream while driving. Autonomous vehicles has the potential to reduce accident rates by over 80%, thus contributing significantly to public safety. Following the widespread adoption of autonomous technology, nearly five million fatal road accidents are likely to be avoided by 2035.
Given fewer traffic-related deaths, insurance premiums are likely to shrink. With the impending roll-out of autonomous cars, insurance companies could enjoy significantly lower claims. Further, with more sensors on vehicles collecting data, accidents should be easier to predict, giving insurers the ability to adjust rates on a real-time basis.
Like insurance, autonomous cars may be a boon for other industries as well. By 2030, autonomous vehicles could be beneficial for the supply chain and logistics industry, as managing fleets will be much easier without the need to constantly monitor the whereabouts of drivers. The smart sensors integrated in vehicles will facilitate real-time tracking of fleets, thereby enhancing operational efficiency within the industry. Further, by 2030, the emergence of autonomous taxi services (pioneered by Uber) could boost advertising and subscription revenues for the global entertainment industry.
Levels of Automation: From adaptive cruise control to full automation
The quest for autonomous cars began a few decades ago when automakers started introducing semi-autonomous technologies in personal cars. Over time, the technology that is set to eventually take autonomous driving mainstream is being continually restructured. The application of Advanced Driving Assistance System (ADAS) is being put through its paces to make it commercially viable in cars plying on the road today. ADAS includes intelligent systems aimed at proactively helping drivers avoid accidents, improve driving efficiency, and reduced driver fatigue.
In 2013, the U.S. National Highway Transportation Safety Administration (NHTSA) issued a policy statement on automated vehicles to define the four levels of automation:
The sensing technologies integrated in autonomous vehicles include laser-based lidar, ultrasonic and motion-based sensing, cameras, and communications between vehicles, and from vehicles to the Internet. Data generated by these sensors are interpreted and cross-analyzed with other pertinent data, resulting in a particular action.
The strategic implementation of autonomous driving is taking shape, subject to road classes. The first stage of implementation has begun on highways, where driving conditions are generally far more predictable. As the technology is evolving to become more sophisticated, the implementation will eventually make its way to urban roads. This is expected to be the real test for self-driving cars as navigating urban settings like buildings, traffic lights, pedestrians, cyclists, and road turns, among others, require more precise safety functionalities.
What’s the impetus for adopting autonomous technology?
Human error is reportedly the cause of 90% of all road accidents. Safety is the primary reason behind the push to embrace autonomous driving. Advocates believe that the number of accidents, injuries, and fatalities could drop dramatically, when the risk of human error is removed by networks of sensors, cameras, radar, lidar, and GPS receivers.
Safety is expected to emerge as an even more critical factor in the future, since the number of vehicles with autonomous driving features is expected to increase. People with disabilities or limited mobility are likely have access to autonomous vehicles, and may be inclined to use their cars for trips, as opposed to taking a plane or train. Even though autonomous vehicles are expected to improve the utilization of road capacities by allowing vehicles to run faster, the net increase in vehicles due to increased adoption may defeat the purpose altogether. Another major advancement in autonomous driving and safety is cars’ ability to communicate with each other. Vehicle-to-vehicle communication is expected to enhance situational awareness by sharing information such as location, speed, and direction, while communicating necessary updates and warnings. This will aid in tackling situations that are likely to result in forward collisions, blind spots, and abrupt lane changes.
Technologies Leveraged by Self-driving Cars:
Automotive Vehicle Cameras
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