UBC Theses and Dissertations

UBC Theses Logo

UBC Theses and Dissertations

Distance based vehicle insurance : actuarial and planning issues Babiuk, Michelle


Distance based vehicle insurance (sometimes know as “Pay as you drive,” “Pay by the mile” or “Pay per-km” insurance) has long been advocated by transportation planners as a transportation demand management (TDM) strategy. In addition to reducing congestion and greenhouse gas emissions, it also has the potential to meet a number of planning goals, such as health and equity improvements. Despite the wide interest in and predicted benefits of distance based insurance, there is little consensus on the detailed design of a system that could be implemented. Five main distance based pricing schemes have been proposed: a flat per-km rate, temporal or “time of day” pricing, road-type pricing, demographic pricing and “differential” pricing, which prices low mileages at a higher per-km rate. Each of these systems treats risk differently and thus results in different cross-subsidies between drivers. The proposal’s design thus has implications for an insurance system’s fairness and equity. This report examines the distribution of crash risk across time, across space, and across the different demographic groups. It then compares the current annual insurance system’s treatment of risk with that of various proposals for distance based insurance. It evaluates each proposal, considering its treatment of risk and its potential for increasing fairness and equity of costs and of mobility. It also examines each proposal’s other impacts, such as effectiveness in maintaining privacy and in reducing health impacts, greenhouse gas emissions and congestion. The recommended model is a flat per-km rate. Each driver would pay the same rate for every kilometer driven, regardless of time or place. However, individual drivers’ per-km rates would vary, depending on current insurance rating factors, such as residential location, type of car and driving record.

Item Media

Item Citations and Data


Attribution-NonCommercial-NoDerivatives 4.0 International