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Method and system for road traffic accidents prevention

IP.com Disclosure Number: IPCOM000253597D
Publication Date: 2018-Apr-16
Document File: 4 page(s) / 39K

Publishing Venue

The IP.com Prior Art Database

This text was extracted from a PDF file.
This is the abbreviated version, containing approximately 53% of the total text.

Road safety became a major public health concern when the statistics showed that thousands

of people around the world succumb to death daily due to road traffic injury. In addition,

road crashes lead to the global economic losses with an estimated cost in the order of many

billion dollars per year.

A large number of measures to reduce road accidents have been taken but the problem is still

present. The events analysis obtained from crash investigation highlights as human factor and

road and environment factors are crucial in road accidents. Often, an inaccurate risk assess-

ment produces an incorrect judgment and decision-making, as well as, the visibility, lane

markings, surface condition, and street light facilities have a potential influence on the driv-

ers and other automatic systems, to perceive and react in a dynamic driving condition. In [1]

authors describe a system for automatic cruise control to maintain vehicle speed at a preset

value, in [2] is presented an apparatus of predicting the future behavior of an object i.e. a ve-


In [3] authors propone a system similar to the one we propone, but that differs for the

kind of elaboration unit, we use a Cloud System instead of a Raspberry PI and the fact our

solution uses Cognitive Services. Another previous art that propone a System to avoid

incident can be found in [4], where authors use a GPS and a network of satellites to prevent


Disclosed is a Cognitive System realized using a remote system and one or some devices

installed on the crossroad or blind bend, with a camera pointing to every road direction in

order to monitor all vehicles; for additional information, additional sensors can be used, like

a directional microphone pointing in the same direction of the camera (fallback system in

case of camera failure, and identify an alarm from ambulance, police, etc.), and a weather

sensor to get the temperature, humidity, etc. (in order to assess the condition of the road).

The retrieved data will be elaborated by an Artificial Intelligent System that identifies

approaching vehicles and predicts all risks, like the possibility that the vehicle will not stop

in time; the predicted data will be sent to all the drivers approaching the crossroad, using a

radio wave system. The drivers will receive the message by a dedicated device that will

communicate with another device able to give back an alert, and providing the corrective

action to perform. The alert system can provide a message on windscreen or a vocal internal

advice, communicate directly with a self-driving car system, etc.

The cognitive system must as a minimum be able to identify the type of vehicle (truck, car,

bike, etc.), and ideally identify the model of the vehicle in order to match it with the

capabilities (ABS pre...