Title

Bus Rapid Transit and Light Rail: Comparing Operating Costs with a Parametric Cost Model

Authors

Eric Bruun

Document Type

Journal Article

Publication Date

2005

Subject Area

economics - operating costs, mode - bus, mode - rail, mode - tram/light rail, mode - bus rapid transit

Keywords

Weekdays, Peak periods, Operating costs, Light rail transit, Fleet size, Dallas Area Rapid Transit, Cost of operation, Cost models, Case studies, Bus rapid transit

Abstract

A parametric cost model was developed to provide both average and marginal cost estimates and to compare annual operating costs for light rail transit (LRT) and bus rapid transit (BRT) under an assumption of additional peak service on weekdays. The model uses readily available data from the U.S. National Transit Database. For illustrative purposes, it is applied to a hypothetical service network simulating universal coverage of a medium-sized metropolitan area with either LRT or BRT operating on trunk lines. The Dallas [Texas] Area Rapid Transit agency is selected for a computational example because it has representative, contemporary performance statistics for both LRT and bus. High and low operating cost estimates based on articulated buses were used for BRT because of a lack of an operational history. For an agency with a similar cost structure to the Dallas agency, both BRT and LRT have lower operating costs on a per space kilometer basis during base periods than do regular buses. Both LRT and the lower BRT cost estimates are comparable for adding service during peak periods. With the higher cost estimate, peak BRT costs 24% more than LRT. For trunk line capacities below about 1,600 spaces per hour, the headway-versus-cost trade-off favors BRT. Above 2,000 spaces per hour, BRT headways become so short that traffic signal priority may not be effective and revenue speed may decrease. The marginal cost of adding off-peak BRT service is substantially less than the average cost of regular buses, and the cost of LRT is even less. Peak fleet size seems to be an important driver of costs. Research methods to verify this are suggested.