The following is a press release from the City of Santa Monica.
Beginning Sept. 1, the Santa Monica Department of Transportation, in coordination with the Police Department, will begin automated enforcement of vehicles parked illegally in both bus lanes and bus stops in Santa Monica, marking the official launch of its Automated Bus Lane and Bus Stop Enforcement, or ABLE, program.
Under the program, two front-facing cameras mounted inside Big Blue Bus’s fleet, including a license plate recognition camera, will automatically detect and record illegally parked vehicles. Registered owners will receive a $293 citation for violations.
The formal launch of the program follows a 60-day warning period that began July 1, 2025, in which violators were mailed both a warning notice and information about the ABLE program. During the warning period, ABLE detected 352 instances of illegal parking in bus lanes and 777 instances at bus stops.
“The number of violations detected by ABLE during the warning period is eye-catching, yet not surprising,” Department of Transportation Director Anuj Gupta said. “It underscores the urgent need for programs like ABLE that help enforce existing laws designed to keep our communities moving safely and reliably. Clear bus lanes and stops will help us deliver more efficient service for thousands of Big Blue Bus riders every day.”
A single vehicle obstructing a bus lane or bus stop can delay up to 60 riders, create accessibility challenges for those boarding and exiting, and cause safety risks for other pedestrians and motorists. These impacts disproportionately affect individuals who rely on public transportation, particularly seniors, students, people with disabilities, and those with limited access to private vehicles.
By reducing the illegal use of bus lanes and stops, ABLE supports Big Blue Bus’s commitment to an efficient, equitable, and sustainable system while advancing Santa Monica’s strategic priority of clean streets and safe neighborhoods by investing in tools that support a high-quality multimodal transportation network.
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