Automated enforcement

The essence of automated enforcement systems is the use of cameras and/or radar incorporated into roadside sensor units. For automated speed enforcement, cameras and/or radar are used to determine the speed of the vehicle to within 3%, while an image of the vehicle license plate is captured for identification purposes. In some cases, the distance from the vehicle to the measurement device is also recorded .  An image of the driver. Can also be captured, although in some jurisdictions, it is not legal to retain this image. 

For red light enforcement, the position of the vehicle is determined at the time that the traffic signal turns red .  The measurement system is connected to the local traffic signal controller in order to obtain signal timing information. 

In both approaches the data and images are stored in a secure vault and then transferred to a back-office analysis system using USB, SDD cards, wireless, or wire line telecommunication technologies. In many jurisdictions, a police enforcement officer must take the decision with regard to the issue of the violation notice. In other jurisdictions, traffic engineering staff or private contractor staff can support this task.

The first red light camera was introduced in 1965, the first radar for use with road traffic in 1971 and the first mobile speed traffic camera in 1982. The use of automated enforcement systems is well-established with the effects well proven and documented. Safety has always been a primary concern for those involved in the transportation service delivery process. 

Of late, the focus on safety has increased with the adoption of vision zero policies in both Canada and the USA. Plans are being developed for the application of a number of different technologies and infrastructure improvements to move towards the goal of avoiding fatalities and severe accidents. While automated enforcement systems are endorsed by national and provincial governments, the use of such technologies is a decision taken at the local level by communities and municipalities.

While automated enforcement systems are well proven, there is some hesitancy at political levels to implement the technology. Drivers tend to support the safety effects of AES but are suspicious that the true reason for implementation is revenue generation, while the stated objective for all implementations is an improvement in road safety, agency actions suggest otherwise. 

Automated enforcement systems operate under the auspices of a self-defeating business model with respect to revenue. Once installed, driver behavior quickly adapts, and the amount of revenue generated by violations falls significantly. This can be considered as a successful outcome from a safety perspective as reduced speeds and compliant driver behavior reduces the number of violations. However, the reduction in generated revenue can make it uneconomical to continue operation of the automated enforcement system at the particular location. In many cases, the agency relocates the system to raise revenue generation.

Another dimension of the business model is that revenue generated from the system is typically entered into a general fund that is available to subsidize the entire budget for an agency. The revenue generated is not typically ring fenced for further improvements in road safety. This reinforces the driver’s perception that the primary objective of implementation is revenue generation to support the agency budget. 

In response to this, many agencies restrict the use of automated enforcement systems to school safety zones and construction work zones. However, there are many agencies that have a wider approach to the application of automated enforcement systems on a region or city-wide basis.