Video has been the industry standard technique for surveys such as Turning Movement Counts (TMC) for about 15 years now. Technology over that time has been developing at an increasingly rapid rate. This section will outline some of the ways in which technology is being used in Traffic Engineering projects as well as demonstrating some of the more manual data entry processes which are still valid.
Origin-Destination surveys using number plate cameras is still the best way to obtain a high quality dataset through capturing a high sample rate through a strategically placed cordon.
Whilst permanent ANPR cameras are able to capture a significant amount of high quality data, it is much more challenging to capture similar data in temporarily deployed sites. Video technology has fairly quickly gone from post-survey manual number plate extraction, to Optical Character Recognition (ANPR) to ANPR with vehicle classification. The image below shows some sample output from a video feed which includes make and model of vehicle.
The key to successfully undertaking Origin-Destination surveys is to engage a survey consultant early and determine how the available technology can best be deployed to achieve the study objectives.
The processing of traffic count video can be done in numerous ways. Video Analytics extracts classified vehicle movements from pre-recorded video and outputs the data in a text or csv files format.
One of the key benefits of this technology is that, with standardised field work techniques and quality video analytics setup the data at each site (for a study with multiple sites) with also be highly accurate. There is no human error involved if each of these components are appropriately managed. TTM works with Miovision Technologies (Canada) on the processing of video.
Video Analytics can be used to extract classified turning movements at an intersection. The data extracted includes turning movements by type of vehicle (up to 5 classes) as well as direction pedestrian crossings and cyclists.
The physical characteristics of the intersection and the data required will determine whether Video Analytics is the most appropriate technology to use at a site.
Video Analytics can also be of significant benefit to highway studies. Whilst tube counters, such as Metrocount are the industry standard for mid-block and speed studies, high speed sites and multi-lane sites can also be effectively captured by deploying video cameras to mid-block locations.
TTM uses the Miovision Scout cameras for the majority of highway studies, with Analytics undertaken within their cloud-based software. Video Analytics can effectively capture multiple lanes of traffic (up to 4 lane carriageways).
The decision to deploy cameras over tube counters depends on the lane configuration and speed of a site, along with the duration of the required count. Risk is also another determining factor. Lastly, cost is considered including the deployment of the equipment and the processing costs.
Despite the presence and fast pace of technological change, many projects still have data requirements that are more effectively processed through data entry staff. Some example are:
As technology continues to evolve it can be assumed that some of these manual processes will also be able to be completed by AI.