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ADAS features development involves multidisciplinary technical fields, as well as extensive variety of different sensors and actuators, therefore the early design process requires much more resources and time to collaborate and implement. This paper will demonstrate an alternative way of developing prototype ADAS concept features by using remote control car with low cost hobby type of controllers, such as Arduino Due and Raspberry Pi. Camera and a one-beam type Lidar are implemented together with Raspberry Pi. OpenCV free open source software is also used for developing lane detection and object recognition. In this paper, we demonstrate that low cost frame work can be used for the high level concept algorithm architecture, development, and potential operation, as well as high level base testing of various features and functionalities. The developed RC vehicle can be used as a prototype of the early design phase as well as a functional safety testing bench.

In this work, the functional development of motion planning and control for SAE level-4 autonomous urban pilot is presented, including its architecture design, algorithm development, software implementation and hardware prototype. First, a completely AVL in-house designed, modular and generic Advanced Driver Assist System (ADAS) and Automated Driving (AD) application architecture is deployed, such that the motion planning and control modules can communicate with decision making, environment modeling and localization modules. Second, A road-navigation-oriented, sampling-and-searching-based iterative spatial-temporal motion planning algorithm is developed and integrated with classical motion control algorithms, via a ©MATLAB/Simulink implementation platform. Finally, the integrated motion planning and control subsystem is prototyped in ©Speedgoat hardware, via a real-time multi-core multi-thread deployment methodology.