Supervisor and control investigation in smart/autonomous vehicles: Environment recognition and objects detection ADAS application case study

Abstract

Research on autonomous and smart vehicles technology has been growing exponentially in recent years by integrating more and more smart software inside, those intelligent vehicles have several functionalities such as environment recognition, driver drowsiness detection and communication with other cars, etc. Thus, a supervisor is needed to control sensors and actuators, to manage the network and to process data tasks. In most of smart automobiles, embedded RTOS (Real Time Operating System) are used as supervisor to control all data coming from the different sensors, and to meet the real time requirements. In this paper, we investigate the real time software control in smart/autonomous through the design and prototyping of an ADAS (Advanced Driver Assistant System) real time application for vehicle environment recognition and objects detection. On one hand, we port the real time operating system FreeRTOS on the top of Multi/CPU-FPGA platform, and then we point out the advantages of the FreeRTOS to develop a real smart embedded system for environment car detection within a hardware prototype on a top of the FPGA Zynq hardware platform. On the other hand, a deep comparison between FreeRTOS and standard operating embedded Linaro/Linux, is presented. The entry point of our real time ADAS application system is a point cloud coming from LIDAR sensors as an input, and then several steps are defined in the application: data segmentation, objects searching, features extracts and classification. As a first step of validation, our ADAS application detects pedestrians using High-Definition range data.