A Roadmap to the Driverless Future of Autonomous Vehicles
The driverless future of autonomous vehicles is set to transform society by reinventing the transportation industry and changing consumer behaviors forever. As a result of this seismic shift, autonomous driving technology is expected to generate up to $400 billion in new revenue by 2035, according to recent research by the McKinsey Center for Future Mobility.
When AV technology is fully developed, driverless cars and trucks will provide immense benefits for society. Imagine the roadways when nearly all serious accidents and fender-benders can be eliminated and long-haul trucks can transport goods around the clock without needing to stop for sleep.
Applications for advanced driver assistance systems (ADAS) will replace the average human reaction time, lowering it from 1.6 seconds to just 0.5 seconds using sensors and algorithms, saving countless lives in the process.
The knock-on effects of autonomous driving should lead to further gains in human productivity and economic growth.
Hairpin-Turn Challenges for Autonomous Driving
Most public officials support the inclusion of capabilities for advanced driver assistance systems in regulatory frameworks and statutes. Regulations already are in place to govern pilot robotaxis and robo-shuttle services in many cities across the U.S., China, Israel and Europe.
Yet the share of consumers who support government regulation of fully self-driving cars has declined 15% over the past year, and trust in the safety of autonomous vehicles is down 5%, according to McKinsey. To address these ongoing safety concerns, extensive public education and outreach programs will be needed. In addition, regulatory controls will be critical for creating a trusted ecosystem that can balance the needs of drivers, pedestrians, businesses and law enforcement.
A vehicle with ADAS features is not autonomous, because drivers can take control of some ADAS driving functions when necessary. ADAS features continue to improve with cameras and sensors that can alert drivers about other vehicles and pedestrians on the road. They can also perform adaptive cruise control and activate the brakes in an emergency.
Unlike autos with ADAS, fully autonomous vehicles are designed to manage every aspect of driving without support from a human driver whatsoever. An AV requires much more complex hardware, software and computing power, as well as testing on the road and in the lab to accommodate millions of miles of driving scenarios.
SAE International has developed different Levels of Driving Automation for the industry, ranging from Level 0 (minimal autonomy) to Level 5 (fully autonomous). Mercedes has introduced its first Level 3 autonomous system, which can drive the vehicle under limited conditions, while Tesla’s Full Self-Driving (FSD) system is at Level 2, featuring some autonomous support for drivers.
Following a series of recent AV crashes, a group of six U.S. senators issued a stern letter to NHTSA. The senators urged the agency to use its regulatory powers to address the dangers of automated driving systems. “Public roads are not a sandbox for manufacturers or operators to play in, and regulatory agencies like NHTSA should be highly cautious about providing lax pathways onto the road for dangerous vehicles,” the senators wrote.
Autonomous vehicles should not be regulated by the same rules that govern standard passenger vehicles, because those regulations do not address the unique safety challenges for AVs. To address these concerns, the industry will need to continue building public trust through the improved performance of AV systems, especially in controlled environments.
Next-Gen Technology for Autonomous Driving
Reaching a totally hands-off and eyes-off autonomous driving experience will require a range of next-generation technologies that are still being developed. Automakers will continue to increase the safety of autonomous vehicles by applying new technologies such as artificial intelligence and machine learning to improve the performance of infrared sensors and sensors that use radio and light waves to help detect road users in all weather conditions. These technologies combine a variety of sensors that can recognize their surroundings, such as thermographic cameras, radar, lidar, sonar, GPS, odometry and inertial measurement units.
New applications for simulation, design, manufacturing, and maintenance, repair and overhaul are also creating a strong need for digital twin technology. Using a digital twin to replicate and test difficult scenarios in the real world is called edge case testing. Manufacturers are adopting emulation software and digital twin technology to accurately test and measure automotive components in the lab before launching them in the real world, helping to develop and deliver autonomous vehicles to market sooner.
The technical brain of an AV system relies on software systems that actively protect passengers. As this market grows, the costs will steadily fall for these new sensors and high-performance computers, just as safety standards will continue to make progress around the country and the world. To help build confidence in AVs, the industry will need to generate a common set of testing standards, similar to crash safety standards, that AV developers can evaluate their systems against.
The winding road to a driverless future still holds many twists and turns ahead as autonomous driving evolves. Over the next decade, our car-crazy society will be realigned through major changes to workforce commuting, car ownership and parking practices, new mobility options for seniors and the disabled, and possibly even large-scale demographic shifts away from large cities to more suburban and rural areas. It should be an exciting and wild ride for years to come as the auto industry reinvents itself with ever-increasing levels of automation.