With the support of new information technologies such as the Internet of Vehicles (IoV) and cloud computing, the Intelligent Transportation System (ITS) has begun a new stage role as Cooperative ITS (C-ITS). Moreover, featuring the collaboration of vehicles, roads, clouds and humans, it becomes possible to scientifically mitigate several serious phenomena in the traditional ITS, including traffic congestion, blocked emergency vehicles, etc. While focusing on optimizing the Quality of Transportation Service (QoTS) requirements from vehicles with different types of tasks, covering emergency vehicles (fire engine, police vehicle and ambulance), shuttle buses, and others, this paper studies and proposes a new service-oriented and cloud-based cooperative path planning mechanism for such heterogeneous vehicles. First, the architecture of service-oriented cooperative path planning is established, where the types and QoTS of traffic tasks are illustrated. Then, a hybrid traffic impedance model is put forward, in which three influencing factors of traffic impedance are concluded and combined through the entropy weight method. On this basis, a service-oriented cooperative path planning mechanism with load balancing strategies named SoCPPLB is designed. The main principle of SoCPPLB is to provide different levels of path planning service for vehicles according to their QoTS requirements per the constraint of the QoTS of vehicles and traffic equilibrium. Finally, all these proposed models and algorithms have been implemented within the Simulation of Urban MObility (SUMO), and further verified under several typical traffic scenarios. The experimental results show that, this new mechanism can effectively improve the QoTS of emergency vehicles and traffic equilibrium performance obviously.