Segment Trees based Traffic Congestion Avoidance in Connected Cars Context

Nowadays traffic congestion in cities is one of the main challenges that drivers are facing. Cities administration doesn't always manage to handle this challenge with success and the increasing number of cars makes the situation worse. Navigation Systems, besides generating routes between a starting and ending point, can be used to predict and avoid traffic congestion. In this paper we propose a novel solution for traffic information representation in connected cars context. The strategy is based on segment trees data structure and was integrated into an industry navigation system by enhancing routing algorithm to support traffic congestion prediction and avoidance. The experimental results proves that connected cars information can be used to predict and optimize traffic flow in a city.