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This paper approaches the use of Hardware-in-the-Loop (HiL) test framework to perform automated verification test of Seatbelt Reminder Function in automotive Instrument Panel Cluster (IPC). The goal of this test was to verify if the Belt-Minder™ Feature performs its seatbelt warning function sounding a chime and illuminating a warning light when the user has his seatbelt unbuckled in compliance with safety standards and regulations. The manual execution of this test requires many resources like prototype vehicle, fuel, many engineers' work hours for each test, etc. However, testing dynamically with HiL system some of those mentioned resources are not required like the prototype vehicle and other are reduced, for example, the time taken to have report on hands. The most important among the advantages, was the possibility of testing with HiL earlier in the V-Diagram.

This paper approaches the use of machine vision as an automation tool for verification tests in automotive Instrument Panel Cluster (IPC). A computer integrated with PXI modular instruments, machine vision software and Integrated Development Environment (IDE) composes the test system. The IPC is verified in closed-loop using the Hardware-in-the-Loop (HiL) technique in which the HiL system simulates all Electronic Control Units (ECUs) that interact with the IPC. Every simulated ECUs signals are sent to the IPC over CAN (Controller Area Network) bus or hardwired I/O using PXI modules integrated with IDE and its responses are captured by cameras. Using machine vision such images are subjected to Digital Image Processing (DIP) techniques as pattern matching, edge detection and Optical Character Recognition (OCR), which can be applied to interpret speedometer, tachometer, fuel gauges, display and warning lights.

Cognitive Radio (CR) is an important technology for the evolution of wireless communications worldwide. Cognitive radio enables the verification of the electromagnetic spectrum availability. Consequently, it permits the modification of the transmission parameters through the interaction with the environment. By monitoring the available frequency band, cognitive users can opportunistically occupy spectral bands with no harming or interference to other users or applications. Cognitive vehicular networks represent a new tendency in the automotive market. New and future models are being released with pre-installed reconfigurable devices; software defined radio (SDR) offers new possibilities for the transmission of intra-vehicular commands as well as dynamic access to Wi-Fi and other wireless services while the car is in movement. In this context, this paper aims to describe the cognitive radio technology and its potential applications and perspectives in the automotive market.

The development of embedded systems in automotive environment has brought a strong expansion in the number of applications dependent of programmable devices. A failure in any of these systems may cause different types of damages. Therefore, it requires a high confidence in their operation. Many of these faults are inserted during the coding process. A tool for formal verification of the implemented code could allow the detection of possible errors that could not be encountered during the testing phase. In this paper, we propose a method for verifying software from the reduced model of the software built automatically with information from multiple traces of program executions. To illustrate the application of the proposed method a case study for an automotive electronic module that controls the windshield wiper is presented.