A team of high-profile AI\/ML engineers at Intellias has developed a pedestrian tracking and collision prediction module as an R&D project. Harnessing advanced technologies<\/a> for road and pedestrian safety has long been one of our focuses, and our new solution addresses the rising need for safe mobility in big cities.<\/p>\n Urban populations are growing alongside the number of personal, public transportation, and last-mile delivery vehicles. These vehicles share increasingly crowded streets with pedestrians and cyclists, who are the most vulnerable road users. Globally, pedestrians accounted for 25% of all road traffic fatalities in 2018 according to the WHO Global status report on road safety 2018<\/a>.<\/p>\n Besides street congestion, blind spots of large buses and heavy vehicles are another cause of incidents. Drivers must maneuver quickly and accurately while staying alert to any nearby movement. Workers on foot can also be exposed to potential harm on industrial storage sites from forklifts. With a full load completely blocking the view, forklift drivers may have more blind spots than areas of clear vision.<\/p>\n All these pedestrian safety issues encouraged us to work on a pedestrian collision prediction module. Our skills in machine learning and AI<\/a> along with experience in object detection solutions<\/a> led to the success of our R&D project for predicting pedestrian collisions.<\/p>\n Our approach to developing a pedestrian collision prediction module involved analyzing data about the position of pedestrians, their predicted locations, and road coordinates. The module we developed comprises the following components:<\/p>\nSolution delivered<\/h2>\n
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