The machine vision-based assisted driving system is designed to improve the driver's environmental awareness, monitor the external environment through the auxiliary system, and provide early warning to the driver in non-safe situations, thus making the human-vehicle-road system more stable, safe and reliable. Improve the safety of the car.
When developing a machine vision-based assisted driving system, you need to face the following difficulties:
(1) The system algorithm is complex and the code is numerous. Machine vision mainly uses the camera to collect external information and convert it into digital image signals for processing. Facing different external environments and detection purposes, the system needs to deal with different points. Therefore, the whole system is extremely complicated in algorithm. The development process is slow.
(2) The test environment is demanding. In the later stages of system development, testing its performance and rectifying it is one of the key steps in the entire development process. Compared with other automotive electronics, machine vision-based assisted driving technology products need to consider two factors when testing: First, whether the driver's safety can be guaranteed during the actual vehicle test; second, the test process needs to be effective, It is credible and reusable, so that problems can be discovered and rectified in time.
In the process of developing a machine vision-based assisted driving system, if the above problems can be solved smoothly, it will pave the way for the development of machine vision-based assisted driving technology products, improve the development efficiency of assisted driving technology products, and promote the assisted driving technology products as soon as possible. Put into mass production, and ultimately improve the safety performance of the car.
In view of the above problems in the development and testing of the machine vision assisted driving system, taking into account the excellent image processing capabilities and powerful real-time simulation test functions of NI's EVS and PXI platforms, the LabVIEW programming language is used to integrate the simulation through the VeriStand development platform. Test model, designed a machine vision-assisted driving development system based on NI EVS and PXI.
With the NI EVS platform, machine vision-based assisted driving can be quickly implemented, which is based on the following features of the NI EVS platform:
(1) High-performance multi-core processor, 2GB RAM for fast detection and large image processing;
(2) Connecting multiple cameras for simultaneous detection (Gigabit Ethernet vision and IEEE1394 standard), which can be used for the development of various driver assistance functions;
(3) High-speed I/O channels are suitable for industrial communication and have powerful expansion capabilities;
(4) Automatic detection by means of visual generator configuration, without the design and development of the underlying driver and interface circuit;
(5) Vision Development Module (VDM) integrates a large number of common machine vision processing basic modules, developers will focus on integration and application, and quickly realize various types of detection and recognition functions;
(6) Using graphical programming, it is more convenient for developers to develop and debug complex algorithms.
When designers have new ideas, the system can be used to quickly implement ideas and improve the efficiency of system development. Among them, the visual development module (VDM) allows designers to pay more attention to the effects of different algorithms, reduce the energy investment in programming, and further improve the performance of the system through comprehensive comparison.
With the NI PXI platform, you can test your system in an efficient, trusted, and versatile environment to identify problems and rectify them early. The NI PXI platform has unique advantages in the following areas:
(1) Provide a graphical software development environment and good human-computer interaction elements, focusing on application development, without paying attention to the underlying driver, and the human-machine interface is easy to develop;
(2) Good real-time performance, ensuring the timing requirements and real-time performance of data acquisition and testing, and capable of running complex vehicle models;
(3) High system reliability, high integration, and good scalability;
(4) It has good openness and scalability, and can integrate various models developed by other software platforms.
Combining the advantages of NI EVS and PXI, a set of machine vision assisted driving system based on NI EVS and PXI was developed by using the LabVIEW programming language and integrating the simulation test model with the VeriStand development platform.
3 system technology principles and design architectureFor the problems faced by the development of machine vision assisted driving systems and the corresponding solutions, the designed system should have the following two functions:
(1) Rapid development and implementation of machine vision systems. With the NI EVS platform, pre-configured requirements are implemented programmatically and the entire hardware system is guaranteed to meet functional needs.
(2) Trustworthy, efficient and repeatable testing of machine vision-based driving assistance functions. With the NI PXI platform, a virtual test system is built to test the problems in the machine vision development part so that it can be rectified in time to improve system security performance.
According to the above ideas, the system design principle architecture is shown in Figure 1.
Figure 1 System design principle architecture diagram
As shown in Figure 1, the entire platform is divided into two parts: a virtual test system and a machine vision system. The two parts are composed of their respective hardware and software.
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