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The conventional radar modeling methods for automotive applications were either function-based or physics-based. The former approach was mainly abstracted as a solution of the intersection between geometric representations of radar beam and targets, while the latter one took radar detection mechanism into consideration by means of “ray tracing”. Although they each has its unique advantages, they were often unrealistic or time-consuming to meet actual simulation requirements. This paper presents a combined geometric and physical modeling method on millimeter-wave radar systems for Frequency Modulated Continuous Wave (FMCW) modulation format under a 3D simulation environment. With the geometric approach, a link between the virtual radar and 3D environment is established. With the physical approach, on the other hand, the ideal target detection and measurement are contaminated with noise and clutters aimed to produce the signals as close to the real ones as possible.

This paper presents a novel real-time virtual simulation environment for advanced driver assistance systems (ADAS). The proposed environment mainly includes a 3D high-fidelity virtual driving environment developed with computer graphics technologies, a virtual camera model and a real-time hardware-in-the-loop (HIL) system with a driver simulator. Some preliminary simulation and experiment have been conducted to verify that the proposed virtual environment along with the image generated by a virtual camera model is valid with sufficient fidelity, and the real-time HIL development system with driver in the loop is effective in the early design, test and verification of ADAS systems.

Lane detection is one of the most important part in ADAS because various modules (i.e., LKAS, LDWS, etc.) need robust and precise lane position for ego vehicle and traffic participants localization to plan an optimal routine or make proper driving decisions. While most of the lane detection approaches heavily depend on tedious pre-processing and great amount of assumptions to get reasonable result, the robustness and efficiency are deteriorated. To address this problem, a novel framework is proposed in this paper to realize robust and real-time lane detection. This framework consists of two branches, where canny edge detection and Progressive Probabilistic Hough Transform (PPHT) are introduced in the first branch for efficient detection.

Vision-based Advanced Driver Assistance Systems has achieved rapid growth in recent years. Since vehicle field testing under various driving scenarios can be costly, tedious, unrepeatable, and often dangerous, simulation has thus become an effective means that reduces or partially replaces the conventional field testing in the early development stage. However, most of the commercial tools are lack of elaborate lens/sensor models for the vehicle mounted cameras. This paper presents the system-based camera modeling method integrated virtual environment for vision-based ADAS design, development and testing. We present how to simulate two types of cameras with virtual 3D models and graphic render: Pinhole camera and Fisheye camera. We also give out an application named Envelope based on pinhole camera model which refers to the coverage of Field-of-Views (FOVs) of one or more cameras projected to a specific plane.