Average unit cost of installing light rail in street/arterial alignments

Left: Phoenix LRT in arterial alignment. Right: Houston LRT in street alignment. Photos: L. Henry.

Left: Phoenix LRT in arterial alignment. Right: Houston LRT in street alignment. Photos: L. Henry.

Increasingly, interest has been growing in the use of street and arterial roadway rights-of-way (ROW) as alignments for new light rail transit (LRT) segments – either new-start systems or extensions to existing systems. As planners, other professionals, advocates, and civic leaders consider such projects, it’s useful to have reliable data on the installation costs.

Unfortunately, many available “average unit cost” methodologies present averages based on various types of alignment — such as re-purposed railroad ROW – rather than exclusively or predominantly street/arterial corridors, which present quite specific needs, challenges, and costs with respect to installation of LRT. For example, while railroad ROWs typically need rehabilitation, much of the necessary preparation for LRT tracklaying is usually in place; space and installations costs for overhead contact system (OCS) infrastructure and stations are often easier to deal with. On the other hand, installing LRT tracks, stations, and electrical systems in streets/arterials typically requires extra (and more costly) tasks such as pavement removal, subsurface utilities relocation, traffic management and reconfiguration, and other measures.

The brief study described in this post has been undertaken as an effort toward fulfilling the need for reliable total-system unit cost data for street/arterial LRT project installations. It has focused on predominantly (or exclusively) street/arterial LRT projects, drawing upon data from eight specific projects in five U.S. cities (Salt Lake City, Houston, Portland, Phoenix, and Minneapolis) as listed in the table further below.

Also, this study (conducted by LRN technical consultant Lyndon Henry) has endeavored to avoid carelessness as to what is designated as “light rail”. As it has been most pervasively considered since the 1970s, LRT is regarded to be an electrically powered mode, not a light diesel-powered regional railway. For the purposes of this study, LRT has been considered as both electrically powered and operating predominantly in exclusive or reserved alignments (i.e., streetcar-type systems have been excluded).

Analysis of this data has yielded an average capital cost of $85.5 million per mile ($53.0 million per kilometer) for construction in these kinds of alignments. This figure might be considered appropriate for approximating system-level planning cost estimates for corridors considered possible candidates for LRT new starts or extensions. (Capital costs, of course, may vary significantly from corridor to corridor depending on specific conditions, infrastructure needs, service targets, and other factors.)

It should be noted that these data have been primarily drawn from Federal Transit Administration resources (particularly New Start profile reports), supplemented where necessary by data from Light Rail Now and Wikipedia. Because these figures present final total capital cost data, they represent final year-of-expenditure costs, including infrastructure and vehicle requirements, and incorporate other typical ancillary cost items such as administration, engineering, contingencies, etc.

Capital costs for the eight projects were tabulated as shown in the table below.


Relevant data for 8 LRT segments used in study. (Click to enlarge.)

Relevant data for 8 LRT segments used in study. (Click to enlarge.)


NOTES

Portland: Interstate (Yellow) line data include section at outer (northern) end on viaduct over Columbia Slough and flood plain. Phoenix: Initial project data include new LRT bridge over Salt River, and short section on abandoned Creamery Branch of Southern Pacific Railroad. Minneapolis: Green line data include adaptation of roadway bridge over Mississippi River.

It should also be recognized that the design requirements and installation costs of streetcar-type LRT projects average significantly lower than those of rapid or interurban-type LRT, particularly because of several factors. For example, streetcar alignments predominantly share street/arterial lanes with existing motor vehicle traffic. Stations often consist of simple “bulge-outs” from adjacent sidewalks, and are typically designed for single-car trains (i.e., single vehicles) rather than multi-car LRT trains. Also, the lighter static and dynamic loading requirements of some streetcar configurations facilitate the use of lower-cost “shallow slab” construction rather than the deeper excavation more typical of “heavier” LRT designs.

Capital costs and line lengths were aggregated for all eight LRT cases studied. Results are presented in the table below:


Data and calculation of average LRT project cost in street/arterial alignments.

Data and calculation of average LRT project cost in street/arterial alignments.


Hopefully, the information from this study will be helpful in developing realistic cost estimates for new LRT projects in these types of alignments. ■

New U.S. light rail transit starter systems — Comparative total costs per mile

LEFT: LA Blue Line train emerging from tunnel portal. (Photo: Salaam Allah.) RIGHT: Norfolk Tide LRT train on single-track railroad roght-of-way. (Photo: Flickr.)

LEFT: LA Blue Line train emerging from tunnel portal. (Photo: Salaam Allah.) RIGHT: Norfolk Tide LRT train on single-track railroad right-of-way. (Photo: Flickr.)

This article has been updated to reflect a revision of the LRN study described. The study was revised to include Salt Lake City’s TRAX light rail starter line, which was opened in late 1999.

What’s been the been cost per mile of new U.S. light rail transit (LRT) “starter systems” installed in recent years?

The Light Rail Project team was curious about this, so we’ve reviewed available data sources and compiled a tabulation comparing cost-per-mile of “heavy-duty” LRT starter systems installed in or after 1990, all adjusted to 2014 dollars for equivalency. (“Heavy-duty” distinguishes these systems from lighter-duty streetcar-type LRT projects.)

This is shown in the figure below, which presents, for each system, the year opened, the initial miles of line, the cost per mile in millions of 2014 dollars, and comments on significant construction features. (“RR ROW” refers to available railroad right-of-way; “street track” refers to track embedded in urban street pavement, almost invariably in reserved lanes or reservations.)

2_LRN_US-LRT-starter-lines-cost-per-mi_rev2

Major data sources have included TRB/APTA 8th Joint Conference on Light Rail Transit (2000), individual LRN articles, and Wikipedia.

Averaging these per-mile cost figures is not meaningful, because of the wide disparity in types of construction, ranging from installation of ballasted open track in railroad right-of-way (lowest-cost) to tunnel and subway station facilities (highest-cost). These typically respond to specific conditions or terrain characteristics of the desired alignment, and include, for example:

Seattle — While Seattle’s Link LRT is by far the priciest system in this comparison, there are explanatory factors. Extensive modification of existing Downtown Seattle Transit Tunnel (and several stations) previously used exclusively by buses; tunneling through a major hill, and installation of a new underground station; extensive elevated construction to negotiate hilly terrain, major highways, etc.

Dallas — This starter system’s costs were pushed up by a long tunnel beneath the North Central Expressway (installed in conjunction with an ongoing freeway upgrade), a subway station, a new viaduct over the Trinity River floodplain, and significant elevated construction.

Los Angeles — The Blue Line starter system included a downtown subway station interface with the Red Line metro and a short section of subway before reaching the surface of proceed as street trackage and then open ballasted track on a railroad right-of-way.

St. Louis — While this system’s costs were minmimized by predominant use of former railroad right-of-way, a downtown freight rail tunnel was rehabilitated to accommodate the system’s double-track LRT line, with stations; an existing bridge over the Mississippi River was adapted; and significant elevated facilities were installed for access to the metro area’s main airport.

Hopefully this cost data may be helpful to other communities, in providing both a “ballpark” idea of the unit cost of new LRT, and a reality check of any estimated investment cost already rendered of such a new system. ■

How rail public transportation has been a leader in the Analytics and Big Data revolution

Diagram from Digi International illustrates some of the multiple ways that Analytics and Big Data may be involved with rail public transport operation.

Diagram from Digi International illustrates some of the multiple ways that Analytics and Big Data may be involved with rail public transport operation.

In a paper presented this past June (2013) to the annual Rail Conference of the American Public Transportation Association (APTA) in Philadelphia, Light Rail Now Project technical consultant Lyndon Henry (also an independent transportation planning consultant with Urban Rail Today and a blog columnist for Railway Age magazine) emphasized the leading role that rail public transportation has been playing — actually for a number of decades — in the Analytics and Big Data revolution that has been sweeping through both the private and public sector of global economies. (Lyndon is also a blog writer for the All Analytics online forum, sponsored by business analytics provider SAS.)

The paper — titled Analytics and Big Data — Rail Public Transportation is a Leader — not only highlighted a wide variety of applications of the newly emerging capabilities of this technology, but also the long developmental legacy in which rail public transportation has been a pioneer.

So, what are Analytics and Big Data, anyway? This is best explained in the paper’s introduction itself:

Two concepts currently at the leading edge of today’s information technology (IT) revolution are Analytics and Big Data. Analytics is high-technology applied to data processing, complex calculations, and automation; Big Data is the current term referring to significantly large volumes of data, on virtually every facet of human activities and characteristics, that can be rapidly processed via Analytics, yielding a broad spectrum of highly useful results. Recent technological advances have sparked what amounts to a “revolution” in the application of these cognitive and informational tools.

“Apparently without realizing it,” observes the paper, “the public transportation industry, has, for many decades, been at the forefront in utilizing and implementing Analytics and Big Data, from ridership forecasting to transit operations.” As it goes on to explain:

Rail transit systems have been especially involved with these IT concepts, and tend to be especially amenable to the advantages of Analytics and Big Data because they are generally “closed” systems that involve sophisticated processing of large volumes of data. In virtually any American city, on any normal weekday, one is likely to see the results of analytics literally in motion — the operation of transit buses and trains that are essential to maintaining the mobility of the metro area.

The more that public transportation professionals and decisionmakers understand the role of Analytics and Big Data in their industry in perspective, the more effectively they will be able to utilize its promise. Furthermore, it is useful for both the public and the industry to realize how significantly public transportation has been a leading pioneer in the rich and extensive historic development of these tools, the roots of which in some cases extend back to 19th century rail technology.

The paper then details a number of the major general applications of Analytics and Big data in modern rail passenger and rail transit systems:

Travel Demand Modeling — how analytics has actually been used for decades in planning new public transportation services and infrastructure

Train Signal and Control Systems — involving components and technologies such as automatic block signaling (ABS), cab signaling system (CSS), centralized traffic control (CTC), automatic train stop (ATS), automatic train control (ATC), communications-based train control (CBTC), automatic train operation, or ATO, and positive train control (PTC)

Route Planning and Scheduling — involving analytics-based software for tedious tasks such as routing, developing timetables, blocking (developing bus and train schedules),runcutting, and essential component tasks such as rostering

Automatic Vehicle Location (AVL) — this transit operating mechanism deploys analytics to track vehicles in operation and and provide information to passengers via passenger information display (PID) monitors or digital signs in stations, or apps on smartphones

Automated Fare Collection (AFC) — typically relying on ticket vending machine (TVM) devices in stations that can receive cash or process credit card swipes, thus also instantly updating a central database

Automated Passenger Counting (APC) — tallies how many passengers are boarding or deboarding each vehicle, and precisely where this happens, and relays this information continuously to a central database

To illustrate some of these applications, a number of case studies are highlighted from actual operating systems:

Bay Area Rapid Transit (BART) — focusing on agency’s operational analytics providing delay analysis, passenger flow modeling (PFM), system performance analysis, and operational forecasting.

Salt Lake City TRAX — focusing on CTC train tracking and dispatching system, the GPS-based passenger information system, and the AFC system.

Austin – Capital Metro’s MetroRail — focusing on operational analytics involved with the ABS (automatic block signal) system overseen by CTC (central traffic control), the GPS-based AVL and passenger information system, and APC.

Philadelphia – SEPTA Regional Rail — focusing on the system’s signaling-dispatching technology, mainly involving a combination of CTC, ABS, and ATC, plus CSS and PTC via compatibility with Amtrak’s Advanced Civil Speed Enforcement System (ACSES).
In addition, Analytics is being utilized in the form of APC, as well as planning and scheduling, plus a passenger information system utilizing both PIDs with train arrival/departure onfprmation and a smartphone app providing bus and train status information to passengers’ personal devices.

Philadelphia – SEPTA Suburban Trolley Lines — focusing on these lines’ signal systems, currently ABS-based, but with planned conversion to CBTC is being planned.

Seattle – Sound Transit’s Link and Sounder — focusing on these operations’ enhanced AFC system utilizing the new regional, trans-agency ORCA payment card.

Tacoma – Sound Transit’s Tacoma Link Streetcar — focusing on how this very small, simple, extremely bare-bones system integrates its APC system with onboard GPS, and provides on-train passenger announcements triggered by wheel pulses from the cars’ propulsion sensors that gauge distance traveled.

The paper concludes with an overview of some of the most salient current issues and trends in Analytics and Big Data, and their relevance for rail public transportation. Topics include:

Data Mining

Cloud Computing

Sentiment Analysis

Security issues

Privacy Concerns

Predictive Analytics

Robotics

Check out the full paper for a more detailed discussion of these topics.

A PowerPoint slide show presented at the conference is also available online.