California’s Tesla crash victim praised ‘Autopilot mode’ in TikTok, FB videos
A Tesla Model 3 driver, who was involved in a fatal crash in California on May 5, had praised the EV maker’s ‘full self-driving feature’ in videos posted on his apparent TikTok account. The California Highway Patrol’s Multidisciplinary Accident Investigation Team (MAIT) is still trying to determine if the victim had engaged the Autopilot system at the time of the accident.
35-year-old Steven Hendrickson of Running Springs in California had posted two videos of a main driving with his hands off the wheel on his alleged TikTok account. A message on one of the videos said, “What would do I do without my full self-driving Tesla after a long day at work.” In the other one, a comment read, “Coming home from LA after work, thank god, self-drive… Best car ever!”
On his Facebook account, in an earlier video he shot while driving on Tesla Autopilot, he said, “Don’t worry. I am on Autopilot.”
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On May 5, the man died after his Model 3 crashed into an overturned truck on a highway in Fontana. The incident also caused injury to the truck driver and a motorist who had stopped to help them. As per the Associated Press, in the police’s preliminary investigation, it was determined that the Tesla’s driver assistant system Autopilot was engaged prior to the crash. However, on Friday, the police corrected its statement, saying, “There has not been a final determination made as to what driving mode the Tesla was in.”
Though Tesla has dubbed its driver assistant feature ‘Autopilot’ as ‘Full Self-driving’, its website mentions that the Autopilot feature does not make the vehicle autonomous. However, experts say the name could mislead consumers into believing the car can drive by itself.
Tesla’s ‘Autopilot’ feature has been under scrutiny by the US National Highway Traffic Safety Administration, that has been investigating more than two dozen crashes of Tesla vehicles. Since 2016, at least three Tesla vehicles operating on Autopilot have been involved in fatal crashes.
(with inputs from agencies)