APRR

Avoid collision between vehicles and workers

Collision between vehicles and workers

Collision between vehicles and workers is one of the most expensive and serious incidents on a work site (such as construction site).

Even when they happen at low speed (very often lower than 5 Km/h), collision can cause serious injury to operators or site workers, even not talking about loss of productivity and financial compensation, if not the company brand being bashed.

A tough challenge

Low visibility and lack of situational awareness (due to fatigue, alcohol or drug) are known problems in the field.

Another problem comes from the dynamic nature of most of the construction sites, meaning that you cannot rely on static sensors and/or equipment to monitor. The number of vehicles increases the co-activity intensity.

False positive detection rate can quickly be a poison and lead to safety system rejection among teams, managers and workers.

Collision conditions and consequences differ from one context to another one. For instance, a collision in a supply-chain house is often pretty different from a collision in a large construction area. Thus, preventing multiple collision context (i.e finding the perfect candidate for one size fits all) is difficult.

Last but not the least, surrounding noise and vibrating environment make very difficult for a driver and/or for a worker on the field to perceive the danger.

Poor existing solutions

Existing solutions to prevent collision between vehicles and workers do not solve the problem.

For instance, camera-based systems assume that the driver can see and act accordingly anytime anytime, which is wrong assumption.

Other type of solutions require the worker to wear an extra specific device but it can be forgotten and/or workers can have issue in getting the message.

Some solutions can display or generate a loud noise to inform the driver and/or the worker, but again those solutions assume that the brains will listen to the signals, which is wrong assumption.

The worst solution might be smartphone-based as the tool is not only poor in terms of power autonomy (low power when you need it) but also very fragile and unable to notify in noisy environment.

An innovative solution leveraging smart PPE-based collision detection

APRR (managing motorways and toll structures under concessions awarded by the French State, fourth player in Europe), a subsidiary of EIFFAGE (the third largest construction group in France and fifth in Europe) has been collaborating with Intellinium to develop a new disruptive way of looking at things to prevent collision between vehicles and workers.

The basic idea is to use an vibration-enabled equipment that is always worn by both the driver and the worker at risk AND to notify both the driver and the worker at risk about an imminent collision.

Intellinium innovative smart PPE add-on attached to any safety shoes (or boots) is the keystone to efficiently notify a driver and a worker at proximity.  A beacon located in the driver cabin will detect the driver presence and provides better accuracy for relative positioning as well as ensure a proper detection bubble to lower false positive (for instance, workers walking besides the vehicles will not get notifications while workers in front and/or behind the vehicle will get immediate signal).

There are several benefits to our innovative solution.

As you notify simultaneously both the driver and the worker by powerful vibration signal located at foot level (which is a very sensitive body area), the solution :

  • Is immune to external noise
  • Can protect the worker and/or the driver (man-down, panic button, all…) while also preventing collision
  • Is always worn by both the driver and the worker and is not an extra device
  • Can be up during several days without any power charging
  • Can fit any static and/or dynamic site

The solution will be ready for pilot testing in April 2019 and is planned for mass production in September 2019.

Leave a Comment





This site uses Akismet to reduce spam. Learn how your comment data is processed.