Running Head: Lab 1 – Current ITS Product Description
Lab 1 – Current ITS Product Description
Red Team
Brian Dunn
CS411W
Professor Brunelle
10/18/2012
Current ITS - 1
Lab 1 – Current ITS Product Description
Current ITS - 2
Table of Contents
1.
2.
INTRODUCTION .................................................................................................................. 2
PRODUCT DESCRIPTION ................................................................................................... 5
2.1 Key Product Features and Capabilities ............................................................................ 5
2.2 Major Components (Hardware/Software) ........................................................................ 7
2.3 Target Market/Customer Base ....................................................................................... 10
3. PROTOTYPE DESCRIPTION ............................................................................................ 13
3.1 Functional Goals and Objectives.................................................................................... 13
3.2 Architecture (Hardware/Software) ................................................................................. 14
3.3 Features and Capabilities ............................................................................................... 16
3.4 Development Challenges................................................................................................ 17
A. GLOSSARY ......................................................................................................................... 20
B. REFERENCES ..................................................................................................................... 21
List of Figures
Figure 1. Major Functional Component Diagram........................................................................... 8
Figure 2. Prototype Major Functional Component Diagram ........................................................ 15
List of Tables
Table 1. Prototype vs. Real World Product Table ......................................................................... 16
Lab 1 – Current ITS Product Description
1.
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Introduction
Despite efforts by Hampton Roads Transit (HRT) to show off their early success with
their light rail system, The Tide, there is still much room for improvement. The biggest problem,
lack of information, is very prevalent as in one survey that revealed 70% of downtown workers
did not even know the station locations for The Tide (Southeastern Institute of Research, 2011).
This poses a direct problem for revenue, as evidenced in the downward trend in ridership that has
been in place since the start of the light rail (Hampton Roads Transit, 2012).
Along with this, communication is also lacking within the system. HRT currently has no
way to accurately track trains throughout the system. Even in the event of failures such as
derailments, the only way to spread this information at present is by manually calling in to relay
the information through the control center (Messina, 2011). These delays and closures are never
communicated with riders either, which leaves them with the possibility that a train may simply
fail to arrive on time without warning.
Current Intelligent Transport System (ITS) is a product designed to solve these problems
and improve public opinion. The first feature is an enhanced communications platform that
allows Tide Operators to not only send out alerts and updates to each other, but also to local
business owners and riders. With communication throughout the light rail system, all users who
interact with the system will benefit from this readily accessible information. HRT will be able
to warn users about possible problems such as derailments or maintenance delays, while riders
will be able to submit feedback about any problems they have experienced.
In addition to receiving important updates, riders can also access real-time information of
ridership and train locations, along with reports based on data trending and predictive algorithms
designed to estimate travel times. While this information will give riders an incentive to use the
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product, it has the additional benefit of creating an easy way to advertise to a targeted audience.
Using Current ITS, local businesses will be able to promote their stores by purchasing
advertisement space and listing upcoming events.
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Lab 1 – Current ITS Product Description
2.
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Current ITS Product Description
The main goal of Current ITS is to connect the three parties involved in light rail systems:
the operators (Hampton Roads Transit), the end-users (Tide riders), and local businesses owners.
All three of the user subsets will access the same system, which will simplify communication
between them; however, only the appropriate information, layout, and options provided will be
presented to each user class. This system will also be accessible from different platforms, with
the real world product featuring applications for mobile devices, a website interface, and
software to run on station hardware.
All of the overlap in benefits provides benefits to every party involved. The tracking of
trains allows riders to make accurate plans for their travel, while also giving HRT the tools
necessary to make sure the system is running smoothly. This GPS system also optimizes the
advertising platform for businesses, allowing owners to select specific stops to target for display.
The prediction algorithms help to anticipate potential problems before they happen, which can
save riders time, but also allows HRT to use the information to make decisions that will avoid
losing riders and thus revenue.
2.1
Key Product Features and Capabilities
The product experience will be different for each class of user, starting with the lowest
access level: the rider. This experience will be focused around helping them to find the
necessary information to fully utilize The Tide’s route and stations. The first option will be a
search function that will break down into three categories: destination (for those that know where
they are going but not where to get off), business (for those that want to find a specific business
or search categories such as restaurants), and event (for those that are looking for special events
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going on near The Tide such as parades or baseball games). This option will appeal to both
novice users who do not know where they are going and to veteran users looking for something
new to try along The Tide. The next option will be trip planning, which will aid riders in
determining the train that will have the best arrival time. The third option will be an easy-to-use
ticket-purchasing interface that will give riders an efficient way to buy their ticket from
whichever platform they are using to access the system. Finally, a simple feedback system will
be available where users can report problems, comments, or suggestions that will be delivered to
the light rail operators in an efficient manner.
The next authentication level will be for local business owners to access the system and
according product features. The primary focus here will be on advertising for local companies.
All businesses and approved events will be listed for riders regularly, but business owners can
choose to purchase advertising space on the system for even more promotion. In addition to
purchasing and launching ad campaigns, the business owners will use this interface to view
metric data for the campaign’s performance. Not only will this provide standard data for
impressions and clicks, local business owners will also be able to view information about
passengers boarding and leaving the train at the closest station. The trend and prediction
algorithms will generate reports that can be used to find relationships between time of day, day
of week, and months between ridership as well as estimations for future ridership that will allow
businesses to adjust their marketing accordingly.
The final level will be for the operators who work for Hampton Roads Transit and help to
run The Tide. The two main focuses on this level will be pushing alerts throughout the system to
all users and using ridership data to make better decisions about The Tide’s operation. The alert
system will primarily be used to update riders about delays or interruptions in service routes. All
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three parties will benefit from this feature as it will provide an easy form of communication
between operators, give users real-time updates on trains they are expecting, and even provide
business owners with knowledge of potential delays for reservations or appointments. The
second focus of the system’s interface for operators will be providing extensive information
regarding rider trending and forecasting. Combining historical information with current trends
and upcoming events, the Current ITS algorithms will provide operators with insight to ridership
so that any necessary adaptions, such as increasing the number of cars for an event, can be
planned in advance.
2.2
Major Components (Hardware/Software)
As seen in Figure 1, the start of the data flow will go from the sensors on the train
through the Onboard Unit to a centralized database server where all of the data will be stored.
The Onboard Unit will need to poll the sensors regularly in order to meet the goal of having realtime information. Transmission will then be sent through a 3G GSM modem and network, using
the Google Transit Specification Feed for formatting. The database server will run Red Hat
Enterprise and store basic information such as train locations and occupancy numbers will be
stored along with timestamps. The schemas for the database will also cover the basic
authentication and access levels for users and their profiles, as well as information such as names
and coordinates for the stops, trains, events, and businesses. All of this will be stored using the
Google Transit Feed Specification, for the sake of compatibility and standardization.
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Figure 1. Major Functional Component Diagram
With reports and raw data both available now, the remaining software will focus on
delivering the information to users. The center of this will be the Web Application Engine
(WAE), which will provide the user GUI’s with the necessary information to display. Software
will be required for each of the platforms that will connect to the server; the first being a website
interface that can be accessed from popular web browsers such as Mozilla Firefox, Microsoft
Internet Explorer, and Google Chrome among others. The second will be an Android application
designed for users that want to access information on the go from their mobile phones. The third
end-user GUI will be a similar version of the Android application that is optimized to run on
kiosks using the Android operating system. All three of these end-user GUI’s will have to
request and transmit authentication for the user to the Web Application Server, which will then
determine which data to deliver and work with the end-user software to provide users with all
necessary information. The final form of data delivery will come in a simple form: a Google
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Transit Feed Specification (GTFS) based feed that will allow external applications to access the
data collected by the Current ITS system.
The major part of making the system’s hardware work will be the interfaces that connect
them all together and provide an easy way to adjust as the system’s requirements change. The
central part of the interfacing process will be the embedded on-board application, which will
have to take the data from the sensors and transmit it back to the database server in real-time.
However, to make proper use of the data collected by all of this hardware, Current ITS will make
the information presentable through multiple interfaces.
The exact hardware required for the real world product will vary some due to the modular
nature of our product. If a customer, such as HRT, already has sensors or an onboard unit,
Current ITS will interface with them to make use of the existing solutions. In addition, the
server hosting will need to scale with demand both in terms of the number of users accessing the
system and the number of trains being monitored through the system. The basic hardware
breakdown, however, will consist of one IRMA Matrix Automatic Passenger Counter per train,
one Garmin GPSP 18x antenna per train, one Habey BIS-6620-IV-Z530 Embedded Computer
System per train, Dell R710 servers to use for the Database, Web Application Server, and
Decision Engine, and finally any requested hardware for the stations such as electronic signage
or kiosk booths. During the development of the product, Current ITS will also require
workstations to be used for software development.
Once all of this information is stored in a logical manner, the Decision Engine will be
able to run algorithms to analyze the masses of data. The first major function will be using the
training set to generate trend reports, which will require associating ridership data with various
factors that impact it including the date, time, and any relevant events or service interruptions
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that occurred. The second major function of the Decision Engine will be generating predictive
data for train locations and ridership numbers through the use of machine learning. While some
of these occurrences, such as accidents, may be entirely random in nature, other delays such as
capacity issues may be predicted through an algorithm based on historical data being compared
to real-time data and the upcoming schedule.
2.3
Target Market/Customer Base
The Current ITS product was designed specifically with Hampton Roads Transit in mind.
The Tide light rail system will work as both the first customer and essentially a trial run of the
system. While the prototype is designed to mitigate implementation risks, the feedback and
experience from the real world product in this first incarnation will help to modify and optimize
the product and its deployment for future customers.
The reason HRT works so well as the initial customer is that the area has seen a lot of
recent growth and the light rail system is still relatively new. As the light rail system enters its
first new fiscal year, the budget required to operate it will no longer be padded by the initial
investment grants that HRT received to get The Tide up and running. Instead, the company will
need to generate more revenue from other sources, most notably ticket sales. Studies have
shown that real-time information is so valuable to riders that providing these updates reduces
perceived wait times by 10% (UK Department for Transport, 2010). Station information
availability was ranked as an important problem by 69% of those in the SIR survey on Hampton
Roads, which further shows that the ability to easily find destinations through Current ITS will
boost ridership.
Two other studies show 30% increases in sales at businesses local due light rail systems
around the country (Cagney, Crossley, Crossley, & Wells, 2006 2. Brown & Victor, 2010), while
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everyone in the localized area benefits from increased property values and new job openings.
This is already great for showing return on investment to taxpayers, but by using Current ITS,
the impact can be boosted further through increased information flow and communication about
these local businesses and the advantages of property located near The Tide. Additionally, one
study shows that by 2030, Virginia will need to spend $3.1 Billion on an estimated 989 new lane
miles just to keep up with growing traffic (Hargten & Fields, 2006). Nationally traffic and
congestion cost over $115 Billion per year in lost productivity (Texas Transport Institution,
2011). The Tide can help alleviate this problem, but only if riders learn to trust the alternative
method of travel, which is provided by giving the users reliable, real-time information about the
system status.
The final direct benefit of implementing Current ITS will be the revenue directly
generated by the advertisement program being run for local businesses. As such, a targeted
medium for advertising the option will be very attractive for any company looking to reach new
customers, which will provide HRT with another source of funding that will continue the
snowball effect started by the increased ridership numbers.
The use of Current ITS will also help Tide proponents to achieve their goal of expanding
the light rail system to new areas. Through collecting more thorough data, better analysis can be
done to show which areas would benefit the most from an expansion, while the overall goal of
boosting ridership will ensure that future expansions are not met by dwindling numbers by
unhappy customers.
After the initial deployment of Current ITS for Hampton Roads Transit, the next targets
will be areas featuring several key characteristics that made The Tide an easy choice. The first is
that an area must be undergoing a lot of new development, as the benefits of the search function
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and increased communication will be much more effective in an area where people are still
exploring and learning. The second is the length of time the light rail system has been in place
and its recent expansions. Long established light rail systems should not have as much trouble
earning a reputation as a reliable means of transit and have had time to be woven into the area’s
mass transit network, but in areas with newly developed systems, our goal is to assist in building
the reputation.
Finding these areas should not be hard, as there are currently over 35 light rail systems
running in the United States alone (Dickens, 2011), with 60 more systems now in development
or proposal stages (Light Rail Now, 2011). This gives many options, while allowing the product
to stay within the country where language barriers and other complications can be avoided while
focusing on the first wave of expansion. Once this stage is complete, however, even more room
for expansion can be seen in the global market, where over 8000 miles of track can be found in
Europe alone (Global Industry Analysts, Inc., 2010). This global market is estimated to be worth
$7.5 Billion by 2015 and is quickly growing, so there will be no fear of finding future customers
any time soon (Global Industry Analysts, Inc., 2010).
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3. Current ITS Prototype Description
The objective of the prototype will not change much from the real world product. Since
the data will be simulated instead of coming from a live light rail system, the focus will be more
on what is done with the data instead of the details in how the sensor system works. The
collection of data will provide HRT with the invaluable opportunity to generate performance
reports and trend reports to aid them in improving the system. The proof of concept will also
show that riders would be able to view data that allows them to plan trips based off of real-time
updates regarding schedules and delays.
3.1
Prototype Functional Goals and Objectives
The first interface, the HRT GUI, will have a fully functioning prototype version, using
simulated monitoring of trains and ridership in place of actual data. The main change from the
real world product will be the missing algorithms for re-routing and prediction. The real-time
data will give them constantly updated information for train positions, train occupancy, ridership
trends, delay impacts, and on-time performance.
The second interface will be the Business GUI, which provides business owners with a
hub for viewing ridership information for their local stop and the ability to submit advertisements
and events for promotion through Current ITS. In the prototype we will be leaving out the
requirement for these submissions to be approved, as well as the payment portion of the
advertisement campaign module. The focus will be on simplicity, as one of the goal’s for
Current ITS is to get local businesses to participate and that requires uses being willing to adopt
the system quickly.
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The final interface will be for the actual riders of The Tide. The key differences between
the prototype version and real world product will be the lack of ticket purchasing and user
favorites. This means that riders will never have any login information, simplifying the use of
the interface. Still, they will be able to see a system overview displaying real-time information
of train locations and occupancy levels. Additionally they will be presented with a list of
upcoming local events, while advertisements will be displayed for simulated local businesses.
All of the data used here will need to be artificially simulated in a realistic manner. This
will allow for meaningful reports on trends and occupancy, displaying the use of the interfaces
for each user level. In addition to pre-populated data, the test harness will allow for input and
modification of data to use for test cases to ensure the system functions properly in all possible
scenarios.
3.2
Prototype Architecture (Hardware/Software)
The biggest change from the real world product to the prototype in the architecture will
be the replacement of the onboard sensors and computers with simulated data. This will result in
less required hardware and thus less cost; in addition, the hardware required to host the three
servers will not be as strict as the real world environment. Instead of purchasing hardware,
Current ITS will make use of ODU’s Computer Science Department resources for workstations
and virtual servers to use in the development and testing stages of the prototype.
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Figure 2. Prototype Major Functional Component Diagram
Since the prototype will not be using sensors or any onboard equipment, the need for
physical hardware interfaces will disappear, and the architecture simplified as seen in Figure 2.
In terms of software, the biggest change will be in the smaller scope of functions available on the
Decision Engine, which will be focused more on trend analysis than true machine learning or
predictive algorithms. The database server will see no change in the software side aside from a
few missing fields for the features previously described as missing in the prototype (such as
ticket purchasing). Most parts of the Web Application Engine will remain the same as well, with
the biggest change being the reduced complexity of the Decision Engine and the lack of a ticket
purchasing function for rider level users to access.
The biggest addition to the prototype will be the test harness. This will be used to run
test cases through the system, and will have to be able to manipulate all of the fields in the
database in real-time. This will be crucial as the product must not only be able to handle regular
pre-populated data but must also handle scenarios outside of the normal as well. For example,
since we have no actual sensors to test real malfunctions, the test harness will allow us to
simulate data that needs to be marked as erroneous when it reaches realistic thresholds.
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3.3
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Prototype Features and Capabilities
With an emphasis on ease-of-use and effective tools for the users in the Current ITS
prototype, the testing focus will be on the interfaces used by the three different levels of users.
Each will have their own set of information to display, but will need to remain intuitive for the
sake of acceptance by users. While some of the platforms used to display this information will
be left out of the prototype, the functionality will remain the same and will simply be ported to
the new platforms in the real world product. These changes can be seen in Table 1.
Hardware
RWP
Prototype
Functionality
APC
IRMA Matrix
Simulated
Partial
GPS
Garmin GPS 18x
Static Android Data
Partial
Embedded CPU
Habey BIS-6620-IV-Z530
Omitted
N/A
3G Modem
Novatel MC935D
Omitted
N/A
Electronic Signage
US Stamp & Sign LED
Omitted
N/A
Physical Server
Dell R710
Virtual Machine
Full
Virtualization
RHEL KVM
Omitted
Partial
Operating System
Red Hat Enterprise
CentOS
Full
Table 1. Prototype vs. Real World Product Table
For the rider interfaces, the main way to focus on ease-of-use will be through the
navigation options. As shown in the sitemap for the mobile application in Figure 5, there are
very few layers of complexity to the overall system. Each category is relatively self-contained
and guides the user through the necessary steps, while options are kept simple so as not to leave
a rider feeling lost and unable to find the information he needs. Since the prototype will not
feature actual riders using the tools, testing must be done to ensure best practices are followed
and the tools work as expected. Finally, the rider’s feedback tool needs to be an extremely
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simplistic submission that allows them to submit feedback to HRT without having to go through
any hassle.
The business owner interface will be slightly more complicated, as business owners will
have more relevant data that needs to be displayed. However, the key here will be to make sure
the ability to create ads and monitor campaigns remains intuitive. Since the prototype will not
feature any actual business owners, it will simulate their presence by generating realistic, yet
fake data in the business owner backend to test the system thoroughly. In order to generate an
ad, the interface will require a business associated with a station, and an image or text string to
use as the advertisement display.
The final interface will be for The Tide operators, the users that need to see the most data
about riders and the trains. Since the full version of the Decision Engine will not be running in
the prototype, most of the analysis will be limited to trend reporting that shows which factors
lead to the highest ridership peaks. This historical data can still be used to determine potential
peaks in upcoming usage, so there will be plenty of reports to display for The Tide operators
nonetheless. The goal will be to simplify the data for users by providing these detailed reports
one at a time, but still offer many options for viewing different data sets or altering the
parameters of the current display. Finally, the alert broadcast system’s performance will be
crucial, as operators will need to have a simple tool that allows them to get out information fast
and the network will need to make sure that everyone else receives the alerts promptly.
3.4
Prototype Development Challenges
The most difficult challenge in the prototype development will be the accuracy of the
simulated data. Because real-time data from The Tide’s actual sensors will not be available in
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this stage, the prototype will need to use simulated data that is as close to real as possible. In
order to adequately serve its purpose to users, Current ITS must be able to verify the data that it
is processing. The prototype will also need to be able to handle outlier data, such as bad
coordinates being reported from sensors in a way that does not cause glitches in the system. For
example, if a GPS sensor were to malfunction and report coordinates outside of The Tide’s
service area, the Decision Engine should not use this data in its estimates for future train arrivals.
Likewise limits will be set, and then tested, for the occupancy data being simulated from
Automatic Passenger Counters.
This will mean that our simulated data must include both realistic sets gathered from
actual GPS coordinates that The Tide follows, but also erroneous data generated by the test
harness in order to ensure the system’s integrity. Once the data is all confirmed to be accurate,
bounds will need to be set for the latency at which it is transmitted. If data from a train or sensor
is delayed, the Decision Engine will need to consider it outdated. In order to simulate this in the
prototype, Current ITS will use timestamps on all data, while the test harness will be able to
generate timestamps to simulate data that has been delayed or lost due to network congestion or
any other possible technical difficulty.
As with most projects, meeting development requirements will also be crucial. With
particular specifications being necessary to make the system work and a tight time frame to get
the system up and running, the development schedule will be very unforgiving. One of the most
difficult, yet crucial, algorithms will be the learning algorithm used in the trend reports. The
amount of historical data used, combined with real-time data coming in, will require a lot of
testing to ensure accuracy.
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In the prototype we will not have to worry specifically about HRT and local business
integration since they’re being simulated, but the goal will be for the prototype to encourage their
participation in the real world product. This will be one of the key parts to making the project
innovative and will guarantee proper information flow through the product. Doing this requires
a very practical and helpful interface that will not overwhelm viewers of the demonstration, yet
will still aim to provide proof of concept for how powerful the tool will be.
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A.
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Glossary
3G GSM: Wireless technology that is in use by many devices today, ex. cell phones.
Android: A widely-used, open-source platform for mobile applications.
Automatic Passenger Counter (APC): Sensor that uses 3D cameras to count passengers above the
vehicle door.
Automatic Vehicle Location (AVL): System that can send track locations of vehicles.
CentOS: Community Enterprise Linux.
Database Server: Hardware that stores information in an organized manner.
Decision Engine (DE): Component of Current ITS that can generate predictions of ridership and
delays.
Global Positioning System (GPS): Satellite-based navigation system that provides location and
time information from space.
Google Places: Third-party source for local business locations.
Graphical User Interface (GUI): Presentation of information, ex. a web page.
GTFS (Google Transit Feed Specification): An industry standard in transit reporting.
Intelligent Transportation System (ITS): Blanket term for advanced applications in
transportation.
Linux: A free, widely-available open-source operating system.
Machine Learning: A branch of artificial intelligence concerned with programming computers to
change behaviors based on historical data, and make predictions based off many types of
algorithms.
Structured Query Language (SQL): Language used to interact with a database server.
Tables: Logical collections of data stored on a database server.
Training Set: A collection of historical, actual data used to make predictions about future events.
Web Application Engine (WAE): The main interactive component of Current ITS that can
process various requests including DE predictions, checking delays, etc.
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B.
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References
Brown, D., & Victor, J. (April 2010). The Business of Light Rail: A Compilation of Local
Business Interviews. Retrieved from http://www.friendsoftransit.org/The-Businesses-ofLight-Rail.pdf
Cagney, R., Crossley, D., Crossley, J., & Wells, G. (August 2, 2006). The Impact of Light Rail
on Local Businesses. Retrieved from http://www.gulfcoastinstitute.org/university/
LightRail_BusinessImpact.pdf
Dickens, M. (December 6, 2011). Transit Ridership Report. Retrieved from
http://apta.com/resources/statistics/Documents/Ridership/2011-q3-ridership-APTA.pdf
Global Industry Analysts, Inc. (July 14, 2010). Global Light Rail Market to Reach $7.5 Billion
by 2015. Retrieved from http://www.prweb.com/releases/light_rail/light_rail_transit/
prweb4253534.htm
Hampton Roads Transit. (2012). Ridership Levels for Rail [Data file]. Retrieved from
http://www.gohrt.com/public-records/Operations-Documents/Rail/MonthlyRidership/Rail-Ridership-Current.pdf
Hargten, D., & Fields, M. (August 1, 2006). Building Roads to Reduce Traffic Congestion in
America's Cities. Retrieved from http://reason.org/news/show/126773.html
Light Rail Now (2011). New Rail Transit Systems Proposed, Planned, or in Development.
Retrieved from http://www.lightrailnow.org/success2.htm
Southeastern Institute of Research, Inc. (February 25, 2011). Hampton Roads Transit: Light Rail.
Retrieved from http://www.gohrt.com/publications/reports/sir-light-rail-summary.pdf
Texas Transportation Institute (September, 2011). What Does Congestion Cost Us? Retrieved
from http://mobility.tamu.edu/files/2011/09/congestion-cost.pdf
UK Department for Transport. (January 12, 2010). Passenger Information Systems. Retrieved
from http://www.dft.gov.uk/itstoolkit/Tools/T20.php#Benefits