When a location has been flagged for a road safety concern, either through network screening or a public complaint, the next step is often a diagnostic study.
These diagnostic studies are often called in-service road safety reviews or road safety audits. The goal of a diagnostic study is to identify key risks and appropriate countermeasures. These countermeasures can then be programmed into an HSIP or similar road safety program.
MicroTraffic was started by engineers who performed hundreds of these diagnostic studies. Our concern before starting MicroTraffic was that historical crash data, which is usually relied on heavily, does not reveal latent risk factors and as a result is an inadequate diagnostic tool.
A latent risk factor is a risk that has not yet been expressed in the collision data, but which has the potential to result in serious injuries or fatalities.
The image below compares a risk profile from 72 hours of road safety video analytics (the vertical columns in the chart) to a risk profile from 5 years of crash data (the numerical data labels above the columns are crash counts).
The crash data, when broken down by configuration, is mostly a sequence of 1's and 0's, with one discernable pattern (6 north left vs east through crashes). The near miss data from video analytics, however, shows a higher resolution picture of the actual risk. The near-miss data reveals significant latent risk factors that have not yet been expressed in the crash data.
If diagnostics at this location stopped at collision data and did not dig into latent risk factors using video analytics, the engineers performing the study would have done so with a very incomplete intersection risk profile.
At this intersection, the most serious latent risk factor, resulting in dozens of high risk near-misses every single day, had not yet resulted in a collision. By using road safety video analytics, latent risk factors can be identified and corrected proactively before they turn into serious and tragic outcomes.