The past decade has seen a rapid development of advanced driver assistance systems (ADAS). Through the development
of intelligent systems based on detection onboard detection and perception,
engineers aim to significantly improve road safety. When these systems are
fully developed, advanced driver assistance systems (ADAS) can detect potential
unsafe conditions early and avoid the possibility of a crash. One of the big advanced
driver assistance systems (ADAS) applications currently in use is the Adaptive
Cruise Control system (ACC) (Padhi, 2019).
The Adaptive Cruise Control system is usually detected through the
Radar and Lidar sensor suite that is installed in front of the vehicle. The
radar sensors help the Adaptive Cruise Control maintain the speed that the driver
sets as long as the road in front are free of any vehicle or obstacles and then
gently slows down by engaging the brake system when the vehicle detects slowing vehicles
at a predetermined range (Bosch, 2018).
One challenge facing the Adaptive cruise control is that it works
well when a car directly follows another car but often fails to detect
stationary objects. Adaptive cruise control is programmed to
focus on maintaining a safe distance from other moving vehicles and to
ignore stationary objects as the human operator should be able to steer clear
of stationary objects. The result is not always the case. This situation is most likely going to result in a
crash. The software to complement and utilize the full potential of
autonomous-vehicle hardware still has a way to go. Development timelines have
stalled given the complexity and research-oriented nature of the problems (Padhi, 2019).
The ability to detect both moving and stationary vehicles and objects will be
the major update to the Adaptive Cruise Control. The field of advanced driver
assistance systems still has a long way to go due to the complexity of
developing the necessary software technology.
References
Bosch.
(2018). Adaptive cruise control. Retrieved from https://www.bosch-mobility-solutions.com/en/products-and-services/passenger-cars-and-light-commercial-vehicles/driver-assistance-systems/adaptive-cruise-control/
Padhi, A.
(2019). Autonomous-driving disruption: Technology, use cases, and opportunities
| McKinsey. Retrieved from https://www.mckinsey.com/industries/automotive-and-assembly/our-insights/autonomous-driving-disruption-technology-use-cases-and-opportunities
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