Research and development of autonomous functions for a road vehicle becomes increasingly active in recent years. However, the vehicle driving dynamics performance and safety are the big challenge for the development of autonomous vehicles especially in severe environments. The optimum driving dynamics can only be achieved when the traction torque on all wheels can be influenced and controlled precisely. In this study, an advanced torque vectoring controller for an autonomous vehicle with four direct-drive in-wheel motors is designed and developed to generate and control the traction torque and speed quickly and precisely, thus to improve the stability and safety of the autonomous vehicle. A four in-wheel motored autonomous vehicle equipped with LIDAR, monocular /depth camera, and ultrasonic sensor is modelled in Panosim environment. Vehicle-to-Vehicle (V2V) and Vehicle-to Infrastructure (V2I) communications are used in this software platform to avoid collision. Individual in-wheel motor control systems are integrated and networked together using a high-level advanced vectoring control system. The proposed vectoring control system can monitor and manage the behavior of the individual subsystems, assigning appropriate tasks to each of them according to the driving maneuver and road conditions. The performance and effectiveness of the proposed vectoring control system is evaluated using standard test maneuvers, such as double-lane-change, step-steer response and brake-in-turn in Panosim. Performance tests in severe environments response such as extreme obstacle avoidance at high speed, driving on low-friction road surfaces etc. are also carried out in the simulation. Simulation results show that the proposed advanced torque vectoring controller can enhance the performance of the autonomous vehicle in terms of handling, yaw stability, path-following and longitudinal dynamics compared with the conventional central motor controller particularly for severe environment conditions.