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Cost of a Ride: The Effects of Densities on Fixed-Guideway Transit Ridership and Capital Costs

Abstract

The cost of building rail transit facilities in the United States has skyrocketed in recent decades. Sections of Los Angeles’s Red Line subway cost more than $750 million per mile to build and even less pricey light-rail systems can cost more than $200 million per mile. Soaring capital investment costs are today’s biggest deterrent, both political and financial, to constructing new transit infrastructure. It stands to reason that high-cost transit projects need high ridership levels. Without sufficient numbers of riders and the fares they generate, new rail investments will inevitably incur huge deficits. Nor will environmental benefits accrue. Transit only reduces traffic congestion and tailpipe emissions when it draws former motorists – and particularly single-occupant drivers – to trains and buses. A system with few riders and a high price tag is a poor investment compared to a system with many riders and a low price tag.

Through the investigation of more than 50 transit investment projects built in the U.S. since 1970, we find a strong correspondence between costs and ridership. As one would expect, capital costs and ridership are positively correlated. Moreover, both ridership and capital costs typically rise with job and population densities. By clustering trip ends near stops, concentrated development tends to average far more transit trips per square mile than less concentrated development. But density often increases construction costs as well – via increased costs for right-of-way acquisitions and building demolitions, more complicated route alignments, utility relocation expenses, and higher labor costs.

This symbiotic relationship between density and both ridership and costs begs the question: are there densities that offer the most “bang for the buck” in terms of the number of riders for the investment costs? If so, what minimum densities should municipalities zone for around existing or planned stations in different settings or for different types of investments? These are among the most frequently asked questions in the urban planning field today – questions for which there are surprisingly few good answers or widely accepted benchmarks. This paper aims to help fill this knowledge gap.

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