This paper presents an autonomous driving experience platform for the purpose of improving the social acceptance of autonomous driving technologies. The platform includes two modules: a dangerous object detection (DOD) module and a lane keeping assist (LKA) module. The DOD module first employs an object detection convolutional neural network to locate the vehicle on the image, then the dangerous level is determined based on the corresponding location and geometrical relationship. The LKA module, which is based on reinforcement learning inputs the physical sensor measurements and outputs the steering command to control the vehicle in the lane center. The experiments validate the effectiveness of the proposed methods. The platform is exhibited in 2018 Beijing science and technology week¹.