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With the increasing complexity, dynamicity and uncertainty of traffic, motion planning of automatic driving is getting more difficult and challenging. This paper focuses on the real-time motion planning problem of CAVs (connected and automated vehicles) in complex traffic scenarios. To effectively solve this problem, a general driving risk model is presented, which contains the following two essential parts: i) collision risk, i.e., the collision risk between the SV (subject vehicle) and other surrounding vehicles, pedestrians, buildings etc.; ii) non-collision risk, such as violation of traffic regulations, the deviation from the intention of driver, etc. To achieve the real time collision detection, the SV is approximated to a point and its shape is considered by extending the dimension of obstacles considering their relative position and velocity.