摘要: |
Traditionally, pavement inductive loop sensors are used to collect real time traffic data for passenger-freight movement in roadways. This method, however, is expensive to install and maintain. It requires significant cutting into the road for the inductive loop and also requires an electronic control unit that is connected to the induction loop. In the last decade, significant improvements have been achieved in michroelectromechanical sensors (MEMS) domain with respect to size, cost and accuracy. Moreover, extreme miniaturization of radio frequency (RF) Transceivers and low power micro-controllers motivated the development of small and low power sensors and radio equipped modules, which are now replacing traditional wired sensor systems. These modules which are often called "sensor mote" (size of a quarter) can communicate with other sensor nodes and build an intelligent sensing network. Because of the miniaturization and low power consumption, these sensor motes can remain functional year after year with low power budget. Motivated by these novel advances, the authors proposed a wireless MEMS sensor based passenger-freight interactions detection framework for Intelligent Transportation Systems (ITS). The authors' proposed system is mainly composed of two sub parts. Firstly, the sensor motes with possible energy scavenging privilege which contain Magneto-Resistive (MR) sensors to detect passenger-freight vehicles. Secondly, an Electronic Control Unit (ECU) which collects traffic data from sensor motes to calculate speed, length, volume and traffic congestion. The ECU contains RF transceiver to communicate with sensor motes and a GPRS (General Packet Radio Service) shield to send aggregated traffic data to the county or regional traffic data collection center. The authors' proposed solution will be significantly cost effective in comparison to traditional induction loop approach and it is scalable to cover millions miles of roadways all over the US. |