In 30% of accidents with fatalities or serious injuries, the infrastructure played a significant role, either causing the accident or worsening its consequences. An accident black spot is defined as a section where several accidents have already occurred, but on our roads we can find multiple risk sections and locations with very serious consequences in the event of an accident. These two cases require a comprehensive analysis of the infrastructure, which would help prevent the emergence of new black spots and, of course, save lives.

The presentation published at the ITS Europe conference shows how to detect both potential black spots and locations with serious consequences in the event of an accident, using various Computer Vision and data analysis techniques.

This presentation was prepared in collaboration with the Department of Traffic of the Basque Government, the authority responsible for traffic management in the Basque Country. Its responsibilities cover the roads in the three historical territories of Bizkaia, Gipuzkoa, and Alava, although its responsibilities are limited to traffic and not road maintenance, which is the responsibility of the Regional Councils, one for each historical territory.

Recognizing the possibilities of generating infrastructure data thanks to the Autonomous Road Inspector, the Basque Government’s Traffic Department decided to cover the third pillar of road safety, infrastructure, through it. This way, it could complement the information already obtained through other means related to vehicles and drivers. Previously, the Department managed Traffic Flow indices, information from telecommunications operators, navigation data, and other data to analyze accidents. But black spots are infrastructure black spots, and this is a point that can only be analyzed with information from infrastructure assets.

The assets data were collected through automated geofence-based recordings scheduled at locations requested by the Traffic Department. In this way, information was collected on:

  • Vertical and horizontal signs, including defects in them
  • Protection barriers, including measurements of guardrail heights and defects
  • Pavement condition and its impact on vehicles traveling on that section
  • Geometric data of the road, such as gradient, radius of curvature, and lane width

With this data, a factor-combination analysis was applied, allowing the following circumstances to be automatically assessed:

  • Presence, absence, and suitability of safety barriers at points with certain geometries
  • Degree of danger at road exits in the absence of safety barriers at curves
  • Visibility limitations of traffic signs at specific traffic signals (e.g., yield or stop)
  • Visibility limitations of lane markings
  • Inconsistencies between vertical and horizontal signage
  • Presence of unprotected hazardous elements near the road

Traffic and Road Safety departments now have a tool at their disposal, very useful for detecting dangerous spots on the road and potential black spots.

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