News outlets and regional agencies have reported a rise in accidents in 13 regions since the start of the year in areas where stationary cameras monitor traffic violations. During the first nine months of 2022, more incidents occurred under camera surveillance in several regions, attributed to various factors:
- 19% in the Moscow region,
- 45% in the Chelyabinsk region,
- 71.4% in the Irkutsk region,
- 2.3% in the Ryazan region,
- 41.7% in Kamchatka,
- 300% in Crimea.
The Road Safety Knowledge Center of the Ministry of the Interior has suggested that the presence of restraint systems can trigger abrupt driver reactions when cameras are observed, potentially contributing to accidents. This view has drawn criticism from those who question the deployment and management of camera networks, including prosecutors and traffic police leadership.
Another perspective has been advanced by an expert from MADI, as reported in Za Rulem, a longstanding and widely read automotive publication in Russia.
Rinat Gematudinov, Associate Professor in the Department of Manufacturing Process Automation at MADI, notes that recent media reports claim more accidents occur in areas where photo and video recording complexes operate. These conclusions come from traffic police statistics for the nine months of the current year. In some regions, more incidents appear in locations with cameras, which can be misleading if the counting approach is not fully understood. This is a central point of concern.
How are accidents recorded under camera surveillance today? The method involves tallying all points where cameras are placed and compiling indicators of accidents, fatalities, and injuries at those points since the start of the calendar year. In effect, this means that all incidents since January 2022 may be counted, even if a camera was installed later in the year. This can create a misleading picture. Does it seem logical? Not exactly.
In practice, cameras are not deployed uniformly across all regions every year. The Moscow region, for example, explains that analysts continually identify new high-risk road segments. Once a hotbed is found, photo-video fixation systems are relocated to that area, sometimes mid-year. This approach makes sense from a safety standpoint: delaying action until year-end leaves too many people at risk in those spots.
The paradox lies in the traffic police’s method, which treats all cameras as if they were present from January. It implies that all accidents recorded since the start of the year are linked to those cameras, even if the camera appeared in August. In reality, the effect of a camera is not instantaneous; it typically takes about two months after installation for noticeable changes to occur. Consequently, the current figures may not accurately reflect the real impact of cameras on accident numbers.
So what would be a fair assessment? To determine whether installing a camera in a specific location has an effect, one should compare accident rates over at least one full year before and one full year after installation.
Consider a hypothetical scenario. A quiet road segment had never seen fatal accidents. Suppose that by December 2021, changes in traffic began to emerge—perhaps a nearby residential complex was built, leading pedestrians to cross more often toward a school and a supermarket, while drivers started turning left to access a nearby development project. This shift resulted in a monthly fatality in this segment. In March 2022, traffic authorities flagged the problem and decided to place a stationary camera complex for recording and enforcement. After a month devoted to approvals, TMP preparation, installation, and setup, the system became active in April 2022. The observed effect typically materializes about two months after activation, and by July the number of accidents at the site declined to zero.
Yet, the official calculations under existing traffic police methods might show a different story. At point X, where the camera was installed, one accident was recorded in 2021 and five in 2022. The increase would appear as 500%, suggesting that the camera was ineffective or even harmful. In reality, the camera fulfilled its mission and helped reduce accidents.
In this light, a more accurate assessment requires accounting for the timing of camera deployments and the lag before their effects become visible. Analysts argue that regional practice should be harmonized with assessment methods to provide a clearer picture of what cameras achieve in improving road safety.