Early user participation in the identification of use case scenarios for 'Connected cruise control'

Connected Cruise Control (CCC) aims to improve throughput in dense commuter traffic on motorways by advising drivers on speed, headway and lane-use via a nomadic human-machine interface. The advice is generated from a prediction of future traffic flow, based on actual traffic-loop data and is transmitted to the in-car platform via 3.5G communication. The systems advantage compared to Cooperative Adaptive Cruise Control (CACC) lies in its potential for rapid implementation and its additional support of lateral driver behaviour. It is important to note that CCC will not have direct control over the car movement. Its beneficial effect is dependent on the driver‘s willingness to comply with the advice. In turn, willingness to comply, in the long term, is also dependent on the perceived benefit of using the system. It is assumed, that to increase both the driver‘s initial willingness to comply and the perceived benefit of using the system, CCC has to reduce the frequency of situations that are seen as most unpleasant by drivers during peak hour traffic. Therefore it is important to understand what these situations are. This study determines the level of frustration caused by driver behaviour in dense motorway traffic, at a lane drop and at an on-ramp/off-ramp. The results help to identify use cases scenarios for driving simulator experiments to ensure that CCC can have a beneficial effect in these situations.