A Car Owner Said He Won’t Park His Vehicle Next To Cars That Are In Bad Shape
by Matthew Gilligan
TikTok/@turbochargejay
Do you pay a lot of attention to where you park your car or what kind of vehicles you park next to?
Well, I guess it depends on the person and what kind of car they drive…
But this guy isn’t messing around!
His name is Jay and he took to TikTok to explain why he’s very picky about where he parks his car.
TikTok/@turbochargejay
Jay told viewers he only parks next to nice cars and said, “If I can tell that you care about your car, then you all good.”
He added, “The people with them ****** up cars that are parked next to your *** ding the **** out of your door.”
TikTok/@turbochargejay
Jay then said, “Anytime somebody with a ****** up car parked next to you, you come back and your **** gonna randomly have a ding in it or a scratch in it.”
TikTok/@turbochargejay
Here’s the video.
And this is what viewers had to say on TikTok.
This person chimed in.
Another TikTokker spoke up.
And this viewer shared their thoughts.
He’s protecting his car like it’s a member of his family…
If you liked that story, check out this one about a delivery driver who gave two weeks notice… so his employer disabled his truck when he was 300 miles from home!
Man arrested after shooting at 3 people in suspected ding dong ditch prank gone wrong in Frisco, officials say
The man was arrested on complaints of aggravated assault, officials say.
More Videos
- Next up in 5In The Feed: Weather Impact Alert in Dallas-Fort Worth | January 24, 2026 (Morning)
- North Texas Tollway authorities give an update on road conditions
- Fort Worth snow and sleet conditions: Snow and ice accumulate
- Snow fell heavily near the Red River in North Texas, bringing icy conditions
- Snow conditions in Collin County: Latest sleet and ice conditions
Author: Rachel Snyder
FRISCO, Texas — A man was arrested after allegedly shooting at three people in a vehicle who he believed had knocked on his door in a ding-dong ditch prank gone wrong last month, officials say.
Police were called to a home in the 6500 block of Scottsdale Way in Frisco shortly before 11 p.m. July 28, where the suspect, Damon Wolfe, 58, told police he’d shot at someone who’d tried to kick in his door, a press release states.
After hearing the noise at his door, Wolfe said he fired multiple shots at a passing vehicle he believed to be involved, police say.
Officers responded after reports of a vehicle with three people inside being shot at as they were driving northbound on Legacy Drive later that same night, police said. The three in the vehicle told police a man shot at their vehicle as they drove by.
“However, during subsequent interviews, all admitted to ding, dong, ditching in a random neighborhood when they were confronted by a male with a firearm,” police said in a press release.
Officers saw what appeared to be bullet holes on the vehicle, officials say.
Wolfe was arrested on complaints of aggravated assault, a second-degree felony, by Frisco police on Aug. 7. He faces between two and 20 years in prison and a fine of up to $10,000 if convicted.
“Parents please talk to your kids about the dangers of participating in these types of Tik Tok challenges,” said Frisco Police Chief David Shilson. “The teens involved in this case are very fortunate they were not shot and killed or seriously injured. For homeowners, it is important to understand that there are legal and criminal consequences for running outside and shooting at a vehicle fleeing the scene. The bullets fired in this offense could have easily struck neighbors’ houses and had deadly consequences. This entire incident is completely senseless and avoidable had better decisions been made by all involved.”
AI Trouble At Hertz: Alleged Damages And A Customer Revolt
A deep dive into the growing backlash against Hertz as renters accuse its AI of flagging false damage and ignoring disputes.
- Hertz’s AI scanner is flagging damage some customers say doesn’t exist.
- One renter filmed “damage” that wasn’t visible, but got no real help.
- Users are now sharing tips to avoid UVEye and dispute bad claims.
Hertz is facing mounting scrutiny over a new AI-powered camera system that was supposed to improve how vehicle damage is assessed, but has instead sparked widespread customer frustration and confusion. The company hoped automation would remove the subjectivity and human error from post-rental inspections, but it’s now being criticized not just for how the system operates, but also for how it handles disputes.
In fact, public opinion is so heavily focused on it right now that it’s drawing flack when human damage assessments seem unfair to customers. On top of that, customers are theorizing about how to avoid the AI system. It’s all kind of a mess, and we’re here to sort some of it out for you.
Read: Hertz AI Complaints Are Spreading Faster Than The Damage It Flags
We’ve covered several examples of the damage that Hertz’s new AI camera system, UVEye, catches. The rental car company has openly discussed the situation with Carscoops. It’s said that 97 percent of renters return cars without any damage to speak of. In addition, the system allegedly only flags damage that measures one inch or larger.
Hertz pointed out that the system is meant to be objective. That means you won’t get charged for a ding created by the previous renter because nobody caught it until you dropped it off. In theory, that’s a great idea and it could incentivize folks to be more careful when they rent a car. In reality, the situation is far from perfect.
An Example We Haven’t Seen Before
Over the weekend, one long-time Hertz customer said the brand has lost his business. It’s not just about alleged damage either. Their anger stems also from a lack of communication, they say. That’s nothing new, we’ve seen plenty of folks complain about these issues since the UVEye system came out. What we haven’t seen is someone document the damage they’re accused of creating quite so meticulously.
Reddit user Akkasca says that they’ve rented from Hertz for 10 years and have always returned the cars in great shape. After dropping a car off at the airport in Houston, Texas, though, they received a message: “Damage Detected”.
“Concerned, got off the shuttle with all my luggage and went back downstairs to inspect the vehicle. The supposed damage area? Completely fine. No visible damage whatsoever. I even recorded a video on the spot to document the condition of the car,” they say.
That’s right, they went to the car after the scanner took photos and recorded their own video. Based on that video, it certainly doesn’t appear that there is any damage where UVEye says it should be. Take a gander for yourself.
Video Reddit/u Akkasca
With the above video in hand, the customer felt confident about disputing the issue even though the employees on hand couldn’t help.
“Employees and managers all pointed fingers at the ‘AI scanner’ and told me to contact customer support – they claimed they had no control over the damage claim,” they noted. Sadly, the renter was wrong. As we’ve pointed out, the app doesn’t allow users to communicate directly with a human. Hertz says it’s working on that, but that clients have other ways to reach out.
According to this customer, the one with no visible damage in the video they recorded, those other channels didn’t work well either. Representatives on the customer support helpline reportedly said they had no ability to do anything. Since then, things haven’t improved.
Strategies For Avoiding UVEye
The same customer claims that he found damage on the car from a previous rental that the AI actually missed. If indeed the system did get this wrong, then how many other similar situations was it wrong about? That kind of question has several people wondering how to avoid this type of situation.
The New York Post recently covered strategies on this exact topic. It suggests avoiding locations with UVEye. As of this writing, Hertz uses the system at no less than six locations, all airports. They include Atlanta Hartsfield-Jackson, Charlotte Douglas, Houston George Bush, Newark Liberty, Phoenix Sky Harbor and Tampa International.
That only helps a little, though, because Hertz plans to roll it out to 100 locations by the end of the year. Reddit users are posting about the system as it goes up in some places like Boston, so there’s no telling where it’ll be tomorrow or next week, much less next month.
The Post also suggests using your own insurance or credit card coverage to handle charges for damage. The issue there is that you might be accepting liability for something that you didn’t cause. In most cases, you’ll also have to decline coverage through Hertz as well.
Other suggestions include taking your own photos and video before and after the rental. At least one AI-powered app, Proofr, is available for Apple users. It uses machine learning to evaluate vehicles before and after a rental. This isn’t a full-proof plan, either, though, because there’s no promise that Hertz values such input.
If the customer from the incident above is any sort of indication, Hertz not only doesn’t care about the video they took, but also doesn’t provide a clear, simple way to submit such documentation.
In reality, no strategy is perfect. While UVEye does seem to be capable of making mistakes, humans are too. In fact, in our last coverage of this whole situation, some of the images of minuscule we initially thought were from UVEye turned out to be from human damage assessments.
In other words, if you return the car with a ding, there’s a decent chance that you’ll get charged for it. In fact, at Hertz locations without UVEye, there’s likely a larger chance that you’ll get dinged for damage that happened before you picked it up just due to human imperfection.
Hertz, like all other rental car companies, has a duty to hold those who damage vehicles responsible for that damage. Of course, any associated policy can go too far or be too lenient.
For now, the only (almost) surefire way to avoid a charge from Hertz seems to be to return the car in the same condition. And return it with enough time to document any alleged damage after the AI scan. Sooner or later, that kind of proof will very likely be beneficial.
