From Newsgroup: rec.bicycles.tech
TheyAre robo-cops.
Santa Monica has become the first city in California to crack down on
bike lane violations using security cams powered by artificial
intelligence.
The initiative targets vehicles that illegally park that stop or park
illegally in the cyclistAs side of the road, forcing peddlers into the
street where the risk of an accident goes up exponentially, according to
City Of Santa Monica Blog.
To prevent this, the city mounted AI-powered cams on enforcement
vehicles, so they can bust violators by recording the time and location,
as well as video and photos of the incident.
When the program initially debuted on May 1, vehicle owners received a
60-day grace period and a warning. Starting on July 1, violators were
subject to fines of $93, Secret Los Angeles reported.
Before deciding to issue a financial penalty, the evidence is reviewed
and verified by an officer, who then mails a citation to the vehicles
owner.
Nonetheless, tickets and hundred of warning violations have been issued
since the ordinance went into effect, per the city.
This marks the culmination of a multi-year effort to get psychopaths to
stay in their lanes.
During a six-week dry run of the campaign in 2024, just two enforcement vehicles flagged nearly 1,700 potential bike lane violations.
oMaking bike lanes safer and more accessible encourages people to choose
active transportation, helping reduce traffic congestion and improve air quality in Santa Monica,o the city wrote in their blog.
This isnAt the cityAs first attempt to improve road safety via getting commuters to pick a lane.
In fact, this latest campaign was inspired by the cityAs Automated Bus
Lane Enforcement initiative launched in September , which helped curb
bus lane parking violations by 67% and bus stop violations by 40% within
just months
https://nypost.com/2026/07/20/lifestyle/southern-california-taps-ai-to-is sue-hefty-street-parking-fines/
It's total bullshit to make drivers pay for scumbag bike riders who do not
pay any taxes.
It is 100% theft by deception.
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