Smart driven by estimation of delay and energy consumption in urban road traffic

摘要

Energy efficiency in transportation is today an important issue in urban road traffic. In fact, energy prediction along a specified route in an urban road is necessary to reduce the energy consumption. In this paper, we present a dynamic and a modular method to estimate the energy consumption in real-time while driving. In the proposed model, we use internet of things concept to predict the energy consumption and time travel between two chosen points source and destination. In fact, each car sends the state of the road to the data center: accidents, crowded streets, road works, etc. Based on the real-time traffic information and the state of roads, the application calculates the estimation of energy consumption, to aid the driver in piloting the truck in a safe and economical manner. Drivers then, choose the optimal route that reduce the energy consumption which may be the longest one. The speed profile contain information about the individual driving style and the prevailing traffic situations. Proposed model considers the individual driving style and other effects on energy consumption. The proposed system architecture is discussed with its requirements to ensure smart and safe driven.