Designing the Human Machine Interface to Address Range Anxiety

Abstract

It is essential that the interfaces of low carbon vehicles particularly fully Electric Vehicle (EV) support new users while they adjust to a different type of driving experience. Use of EV is not yet widespread and little is known about the user requirements for Human Machine Interfaces. One of the common concerns is driver anxiety about his/her vehicle’s ability to cover the distance required. However the problem is one of perception and driver experience in the context of new technologies, EV’s limited range and an immature charging infrastructure. Nevertheless eliminating range anxiety for the EV owner is one of a major design challenges for future Low Carbon Vehicle manufacturers. The current study found that drivers who had some experience of driving an EV have less anxiety than those who had never driven an EV. Experienced drivers develop strategies to ensure that they only undertake those journeys that they are confident about having enough range to complete and aware of the factors that could potentially impact on the range. It is clear from users’ feedback that estimated range of the vehicle is one of the most critical pieces of information for a driver. Combining this with battery state of charge information can provide the driver with a better understanding of the current range of their EV. However accuracy is a key factor to gain trust in range information. EV drivers need dynamic information on factors that influence available range. There is also a requirement for information that will enable drivers to drive economically. While designing the EV driver information system, designers must overcome the information complexity issue. Concerns were raised that complex information in current EVs could potentially lead to driver distraction and may increase anxiety further. In conclusion providing reliable, relevant and prioritise information can help to minimise range anxiety.