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For intelligent driving systems, the ability to recognize different driving styles of surrounding vehicles is crucial in determining the safest, yet more efficient driving decisions especially in the context of the mixed driving environment. Knowing for instance if the vehicle in the adjacent lane is aggressive or cautious can greatly assist in the decision making of ego vehicle in terms of whether and when it is appropriate to make particular manoeuvres (e.g. lane change). In addition, vehicles behave differently under different surrounding environments, making the driving styles identification highly challenging. To this end, in this paper we propose a dynamic clustering based driving styles identification and profiling approach where clusters vary in response to the changing surrounding environment. To better capture dynamic driving patterns and understand the driving style switch behaviours and more complicated driving …