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The Importance Of Data From Vehicle Driver Assistance Systems

Over the recent years, auto manufacturers like Tesla have reported several crashes related to their driver assistance systems. While these systems aim to make vehicles safer by automating some functions, they have also proven hazardous.

Driver assistance technologies have made travel safe, and more effortless for drivers. Features like lane departure detection and drowsiness detection have helped increase road safety. Additionally, these technologies have secondary tasks like obstacle detection, route planning, and location finding.

Generally, driver assistance systems include automatic braking, blindspot detection, adaptive cruise control, light vision, and intelligent speed control. However, they have yet to be fine-tuned and have caused several car crashes. This was the case with Tracy Forth, a driver whose autopilot system malfunctioned as she was driving.

Tracy’s Case

Tracy was rear-ended near Tampa, Florida, and slid into the median strip. During her statement, she explained that shortly before the accident, the autopilot system had suddenly activated her brake, and she could not control her vehicle.

Rear-end accidents are pretty common in the US, with thousands happening daily. However, this was a unique case involving a failed driver assistance system.

Though many automakers withhold this data from the public, it could be resourceful to insurance companies, regulators, law enforcement agencies, and other auto manufacturers as well.

Fortunately, Tesla has several sensors and cameras which capture every event right before impact. In Tracy’s case, the telemetry received from the sensors showed that she was traveling at 77 miles per hour 10 seconds before the crash. Shortly after, the autopilot system prompted a change of lanes.

Halfway through the lane transition, the obstacle detection system detected an obstacle and stopped the lane change, then rapidly decelerated, coming to a sudden stop. The rear cameras showed another vehicle approaching, ultimately colliding with the Tesla.

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Why This Data Is Important

“The data collected from these sensors is used to improve the functioning of driver assistance systems. Moreover, sharing this information with the relevant authorities could improve the regulations determining permitted technologies, and banned ones” says attorney Russell J. Berkowitz.

Ultimately, it will help government officials reverse the fatality trends, which have recently reached a 20-year high.

This information could also be used to differentiate between technology-related and human error accidents. The systems are comprehensive since they collect data each millisecond before, during, and after a crash.

Hence, the video footage in vehicles like Tesla has helped determine exact accident causes that data recorders may be unable to capture.

Matthew Wansley, a Cardozo School of Law professor specializing in vehicle technologies, urges auto manufacturers to share crash data to improve road safety.

Ms. Forth is using this data to sue the driver who rear-ended her, claiming that the car was moving at dangerous speeds. Even though this data could be used to determine at-fault parties during crashes, it has far more critical uses.

Therefore, sharing such information will help manufacturers and drivers understand and anticipate these malfunctions.

Complications With Sharing Data From Driver-Assistance Systems

That is easier said than done, as Tesla policies do not allow data acquisition without the user’s consent, raising a lot of privacy concerns from users.

There is also the concern of whether the data collected belongs to the manufacturer or the user. Regardless, data from these systems will help us understand car crashes, and improve safety.

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