Understanding real-world driving conditions in the form of driving cycles is instrumental in the design of efficient powertrains and energy storage systems for electric vehicles. In addition, driving cycles serve as a standardised measurement procedure for the certification of a vehicle's fuel economy and driving range. They also facilitate the evaluation of the economic and lifecycle costs of emerging vehicular technologies. However, discrepancies between existing driving cycles and real-world driving conditions exist due to a number of factors such as insufficient data, inadequate driving cycle development methodologies and methods to assess the representativeness of developed driving cycles. The novel aspect of the work presented here is the use of real-world data from electric vehicles, over a six month period, to derive a driving cycle appropriate for their assessment. A stochastic and statistical methodology is used to develop and assess the representativeness of the driving cycle against a separate set of real world electric vehicle driving data and the developed cycle performs well in that comparison. Although direct comparisons with internal combustion engine driving cycles are not that informative or relevant due to the marked differences between how they and electric vehicles operate, some discussion around how the developed electric vehicle cycle relates to them is also included. (C) 2016 Elsevier Ltd. All rights reserved.