When there are many sensors in the car need to be managed, the point-to-point wiring complexity and cost will be greatly improved. By connecting multiple sensors to the ECP5 at the rear of the car, you can use a single cable Sensor to quickly and efficiently deliver data to the front of the car, reducing weight and cost and simplifying maintenance.

    ECP5 can also be used to preprocess video. As the automotive industry began to adopt mobile processors, design engineers had to face a variety of new interfaces. Although the handset processor typically has a single DSI output connected to the display, LVDS is used on the mainstream display in the automotive market. FPGA can achieve different resolution of the video signal preprocessing and bridging between different interfaces. ECP5 can be used to build video bridge solutions between application processor DSI or FPD-Link output and most automotive display LVDS inputs. In addition, the ECP5 can be used for in-car infotainment applications, dividing one video output into two outputs Fuel Rail Pressure Sensor for the rear panel display, or cutting and formatting individual video outputs at specific video resolution requirements. Radar and laser radar are not only suitable for autopilot vehicles, but also as a driving aid. Specifically, it is used to detect dangerous targets and conditions, so that the car to inform the driver or when necessary to take measures to protect the safety of passengers. While these systems are still evolving, it is foreseeable that future cars will not be confined to image processing of images received by cameras, but will also use proximity sensors based on radar and terrain sensors based on lidar. Radar and laser radar systems take full advantage of the high-speed MIPI interface and use CSI-2 output data. Once the situation is considered in conjunction with the processor's resources, the design engineer will once again face the challenge of a limited number of MIPI CSI-2 interfaces or different interface types. Car-level CrossLink devices can be used to aggregate data from multiple sensors, or simply use as a bridging solution to convert CSI-2 data into a format acceptable to the application processor interface.

  ADAS also requires expensive image signal processing (ISP) resources to identify objects or focus on specific objects rather than normal images. As the machine learning algorithms used for decision-making continue to evolve and automotive automation is increasing, FPGAs provide design engineers with the flexibility they need. When the decision-making power is attributed to the computer, it must decide how to handle the road condition, the object on the road, and in any case to ensure the safety of the driver. Lattice ECP5 has a full HDR ISP Pressure Sensor from Helion Vision, GmbH that can be used to improve the quality of images captured. Based on higher quality images, the use of microprocessor soft core can easily achieve the target recognition function.