Transportation System
May 1 2012
CS410 Red Team
Current – Intelligent
Where do you need to go?
1
•
•
•
•
•
•
•
•
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•
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22-27 Hardware Overview
28-31 Hardware Milestones
32-39 Software Overview
40-42 User Interface Overview
43-49 Software Milestones
50-52 Database Schemas
53-56 Gantt Charts
57-59 Project Budget & Cost
60-64 Project Risks
65 Conclusion
67 References
CS410 Red Team
•
3 Team Introduction
•
4 Problem Statement
• 5-10 Background Research
•
11 Process Flows (Pre Solution)
•
12 Solution
•
13 Process Flows (Post Solution)
•
14 Objectives
• 15-18 Market Analysis
•
19 What’s In The Box
•
20 What’s Not In The Box
•
21 Major Functional Component
May 1 2012
Outline
2
Introduction: Our Team
Akeem Edwards
- Financial Specialist
- Software Specialist
Brian Dunn
- Marketing Specialist
- Web Developer
Dean Maye
- Documentation
- Database Admin
Kevin Studevant
- Database Admin
- Software Specialist
CJ Deaver
- Risk Analyst
- Hardware Specialist
Domain Expert
Kamlesh Chowdary
ITS Engineer at HRT
Domain Expert
Dr. Tamer Nadeem
Mobile Apps at ODU
Mentor
Dave Farrell
Systems Engineer at
MITRE Corp.
CS410 Red Team
Chris Coykendall
- Web Developer
- Software Specialist
May 1 2012
Nathan Lutz
- Project Manager
- Hardware Specialist
3
Lack of complete information prevents transit organizations and
local businesses from maximizing the potential benefits of light
rail systems.
CS410 Red Team
May 1 2012
Introduction: The Problem
4
- Increased retail sales
- New jobs and development
- Higher property values
CS410 Red Team
- Studies show that light rail systems have a history of directly
boosting local economies in three key ways:
May 1 2012
Background: Economy
5
Background: Increased Sales
CS410 Red Team
• A study in Dallas showed a 33% increase in retail sales of businesses near the
DART starter line.1
• Near Norfolk’s Tide light rail station on Newtown Road, a 7-Eleven owner
reported a 13-14% increase in sales.2
• In Salt Lake City, a restaurant owner reported annual increases of 25-30% due
to their proximity to the TRAX light rail.3
• In Phoenix, one business owner reported a 30% increase in revenue since the
local light rails opening.4
May 1 2012
Due to increased accessibility and an influx of new customers, local
businesses in light rail service areas see increased sales:
However, these systems do not maximize this potential by working with
local businesses and providing information to riders.
1)
2)
3)
4)
http://www.detroittransit.org/cms.php?pageid=26
http://hamptonroads.com/2012/02/some-stores-near-norfolk-light-rail-stations-see-boost
http://www.gulfcoastinstitute.org/university/LightRail_BusinessImpact.pdf
http://www.friendsoftransit.org/The-Businesses-of-Light-Rail.pdf
6
Background: Jobs & Development
-
In Charlotte, over $291 million in new development was seen along their new
10-mile line with another $1.6 billion expected.1
The Maryland Transit Administration estimated 27,000 new jobs per year
over the next 30 years attributed to their new Purple Line.2
If light rail usage is maximized, then the potential for further
expansion can boost these numbers even further.
CS410 Red Team
-
May 1 2012
Over the past five years, studies have shown light rail systems as
an effective stimulant for new development and jobs:
Dallas LRT Projected Spending vs. Impact3
1)
2)
3)
Line
Spending
Impact
Jobs
Blue Line
$289 Million
$502 Million
3,969
Orange Line
$1.18 Billion
$2.05 Billion
16,205
Green Line
$868 Million
$1.5 Billion
11,921
Total
$3.14 Billion
$5.65 Billion
32,095
http://www.detroittransit.org/cms.php?pageid=26
http://washingtonexaminer.com/local/maryland/2011/11/purple-line-expected-be-major-economic-engine-md-officials-say
http://www.dart.org/about/WeinsteinClowerTODNov07.pdf
7
• About 70% of downtown workers did not know the stop locations.
• About 55% of other respondents did not know the stop locations.
• 69% of respondents ranked information about stops as an important
problem.
CS410 Red Team
A survey of over 1000 Norfolk residents was taken and although
90% were aware of new light rail, many lacked other information:
May 1 2012
Background: Tide Case Study
• 75% of respondents ranked schedule information as an important
problem.
8
http://www.gohrt.com/publications/reports/sir-light-rail-summary.pdf
15,000
5,000
4,500
10,000
4,000
CS410 Red Team
The Tide ridership started strong, breaking the first-year 2,900
daily rider estimate in its opening months, but has been in decline
since.1
May 1 2012
Background: Tide Ridership
3,500
5,000
3,000
0
August
September
October
9
1)
http://www.gohrt.com/public-records/Commission-Documents/Commission-Meetings/FY2012/January-2012.pdf
Need to evaluate &
expand Tide light rail
services
Need to go
somewhere
Receive user
feedback about
service through
traditional
means
-Visit website
-Get schedule
information
-Get fare info
-Get stop info
-Purchase eticket
Set schedule,
stops/stations and
fare for light rail,
and determine
new service areas
Go to
stop/station
Light rail
normal
operation
Ride to next
stop
Embark
CS410 Red Team
Static ridership
data
May 1 2012
Process Flow pre-Current ITS
Disembark
Tide Rider
Want to attract Light
Rail customers
Local Business Owners
Traditional
advertising
media (print,
radio, TV)
Inefficient
marketing
No big returns on tax
payer investment in
light rail
10
Intelligent Transportation System (ITS)
Current will provide accessible, real-time, and
accurate information to transit authorities for
maximizing adoption and expansion of emerging light
rail public transportation systems.
CS410 Red Team
Current
May 1 2012
The Solution
11
Process Flow with Current ITS
Real-time
ridership + GPS
data
Send alerts &
receive user
feedback about
service through
Current ITS
Need to go
somewhere
Tide Rider
Current ITS
provides all info
needed by rider
Quickly &
accurately set
schedule,
stops/stations and
fare for light rail
Go to
stop/station
Efficient light
rail operation
Ride to next
stop
CS410 Red Team
Need to evaluate &
expand Tide light rail
services
May 1 2012
Historical data &
event data
Embark
Disembark
Want to attract light
rail customers
Local Business Owners
Advertising with
Current ITS
Effectively
target market
Realize returns on tax
payer investment in
light rail
12
Objectives
• Provide transit authorities and local businesses with analysis and
reports showing detailed information about riders and their habits.
• Provide real-time updates on train locations, seat availability, service
interruptions, local events, and important announcements.
CS410 Red Team
• Direct, two-way communication with riders will allow operators to
deliver important information and collect feedback from riders.
May 1 2012
• Cooperation with local businesses through targeted advertising and
listing will directly contribute to local economic growth.
• Provide easily accessible static information to riders regarding
schedules, stop locations, and local businesses.
• Multiple mediums (mobile apps, station kiosks, and websites) will be
used for information and communication to ensure easy access.
13
• Current ITS will not provide automatic rerouting or boost capacity in
itself, but will provide operators the necessary information to make
these decisions.
• As an example, Norfolk’s Grand Illumination Parade generated 3x the
normal average daily ridership, but HRT provided no additional
capacity.1
CS410 Red Team
• Current ITS provides detailed information regarding light rail usage.
This data can be sorted to highlight different stops, special events,
and time of day trending.
May 1 2012
Current Trend Analysis
Average Daily Boarding 2
1200
1000
800
600
400
200
0
EVMS
1)
2)
York
Street
Monticello MacArthur Civic Plaza Harbor
Ave
Sq
Park
NSU
Ballentine Ingleside
Blvd
Military Newtown
Hwy
Rd
http://www.gohrt.com/public-records/Operations-Documents/Rail/Monthly-Ridership/Rail-Ridership-Current.pdf
Debbie Messina, “The Tide.” The Virginian-Pilot. February 18th, 2012.
14
• Through a GUI allowing users to easily find
local businesses and attractions, riders will be
more likely to explore and rely on the system
for recreational usage.
CS410 Red Team
• Previous research showed how much impact
light rail stops can have on local businesses,
but riders still lack information about them.
May 1 2012
Local Businesses
• In addition, the business owner backend will
allow local businesses to advertise companies
through Current ITS.
15
Target Market
• New light rail development and expansion costs millions to
taxpayers who demand quick results for their money.2
CS410 Red Team
• As the result of Obama investing $8 Billion in stimulus funding for
rail transit, even more projects are now under development and
expansion.1
May 1 2012
• As traffic, gas prices, and pollution rise, light rails are quickly
catching on as a more efficient means of transportation.1
Light Rail Project Costs
Baltimore
Buffalo
Camden
Charlotte
Cincinnati
Denver
Detroit
$400 Million
$636 Million
$604 Million
$350 Million
$750 Million
$118 Million
$494 Million
Miami
Indianapolis
Portland
Sacramento
Salt Lake City
Minneapolis
Oakland
$340 Million
$498 Million
$214 Million
$176 Million
$300 Million
$548 Million
$320 Million
1)
2)
http://www.cbsnews.com/8301-503544_162-4949672-503544.html
http://www.lightrail.com/projects.htm
16
Our Competition
Simran
Infodev
HRT Bus
Clever Devices NextBus
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✓
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✓
x
x
x
May 1 2012
NY MTA
CS410 Red Team
Information Provided
GPS Tracking
Occupancy Info
Local Businesses
Event Calendar
Service Alerts
Platforms
Station Signage
Mobile App
Website
Features
Real-Time
GTFS Adherence
Business Advertising
Rider Feedback
Current ITS
17
In The Box
Web Application Engine
Prediction Server/ Decision Engine
Embedded Linux Transmission Application
Android Application
Real-Time Train Tracking (GPS)
Real-Time Passenger Counting (APC)
CS410 Red Team
•
•
•
•
•
•
May 1 2012
A service to set up and maintain:
Algorithms
• To provide customized reports and forecast data
• Backend to provide location based business advertisements
18
CS410 Red Team
• Trains
• Tracking System for Buses
• Real-time Rerouting
May 1 2012
Not In The Box
•
•
•
•
Text message alerts (future feature)
QR Code Ticketing (future feature)
Social media integration (future feature)
Total transit management integration (future feature)
19
DB
Onboard Unit
Decision
GTFS
Engine
Web App
Server
CS410 Red Team
May 1 2012
Real World Product (RWP) Major
Functional Component Diagram
GPS Transponder
Infrared Counters
20
DB
Trending
GTFS
Algorithms
Web App
Server
CS410 Red Team
CS Dept Virtual Machine
May 1 2012
Prototype Major Functional
Component Diagram
Simulated GPS Data
Simulated APC Data
21
RWP
Prototype
Functionality
IRMA Matrix
Simulated
Partial
Garmin GPS 18x
Static Android GPS
Data
Partial
Habey BIS-6620-IV-Z530
Omitted
N/A
Novatel MC935D
Omitted
N/A
US Stamp & Sign Electronic LED
Omitted
N/A
Physical Server
Dell R710
CS Dept Virtual
Machine
Full
Virtualization Software
RHEL KVM
Omitted
Partial
Red Hat Enterprise server
CentOS server
Full
Automatic Passenger
Counter (APC)
GPS Antenna
Embedded Computer
System
3G Modem
Electronic Signage
Operating System
Software
CS410 Red Team
Hardware
May 1 2012
RWP vs. Prototype
22
RWP
Administrative Interface,
Schedule Delays, Rail Capacity,
Web GUI
Forecasts, Rider Feedback,
Module Ridership Counts, and
Local Event Calendar
Capacity Check, Accept
Feedback, Retrieve Schedule,
General Request Handler
Local Destinations, and Retrieve
Forecast
Database I/O
Rider Feedback
Google Places API Checker, and
Syndication Process
GTFS/AJAX/Etc. Publication
Test Harness
Omitted
Prototype
Functionality
Partial
Same
Full
Same
Full
Same
Full
Same
Full
Backend GUI to
simulate various
scenarios - i.e. sensors
failure, simulated train
problems, controllable
occupancy levels, etc
N/A
CS410 Red Team
Software
Web Application Engine
May 1 2012
RWP vs. Prototype
23
GUI
Processes
Decision Engine
Database I/O
Request Handler
Gradient Descent
Algorithm
Option Route Detection
Linux Reporting Agent
RWP
Prototype
Settings and Shared Preferences
Schedule Delays, Rail Capacity
& Delays, Rider Feedback
Module, Ridership Counts, Local
Places, Local Event Calendar
UI Event Handler,
GPS/Triangulation Checker,
WAE Request Interface, Rider
Feedback Submission, Ticket
Purchasing
Same
Functionality
Full
Full
Same
Full
Ticket Purchasing
Omitted
Full
Forecast Tables
Delay Forecast, Ridership
Forecast, Optional Routes
Rider Features, Historical
Features Location Features.
Shortest Path, Shortest Time,
GTFS Interface
GPS Interface, APC Interface,
Database I/O
Same
Delay Forecast,
Ridership Forecast
CS410 Red Team
Software
Mobile Application
Local Database
May 1 2012
RWP vs. Prototype
Partial
Full
Partial
Same
Full
Omitted
N/A
Omitted
N/A
24
In The Prototype
Web Application Engine
Decision Engine for Forecasting
Android Application
Test Driver
Algorithms
• To provide forecast data
• Backend to provide location based business advertisements
CS410 Red Team
•
•
•
•
May 1 2012
A service to set up and maintain:
25
Prototype Software Overview
LEVEL I
LEVEL II
LEVEL III
LEVEL IV (ASYNCHRONOUS)
Mobile
Application
Browser
Interface
Internet
Web
Application
Engine
Decision
Engine
DB
Simulated
GPS Data
CS410 Red Team
May 1 2012
Simulated
APC Data
26
CS410 Red Team
• In actual product deployment, vehicles will have
an embedded Linux-based PC module running a
transmission application to send GPS and
Automatic Passenger Counter (APC) information
back the database via GSM network.
May 1 2012
Level I – Embedded System
• For prototyping purposes a test driver will be
used to simulate modifiable static ridership and
train position data.
27
Level II - Prediction
May 1 2012
MySQL Database Server
CS410 Red Team
• Ridership counts and GPS
coordinates of the vehicles will be
retrieved from database, along
with historical ridership data.
• This data will be analyzed based
upon various features of time,
riders, waypoints and other trends.
• The Decision Engine will generate
and save a training data set for
forecasting.
Decision Engine
28
Decision Engine (DE) Request
Algorithms
Request new
historical data
Associate
ridership/time/locati
ons with actual
reported incidents
Generate new
training sets and
save to forecast
tables
SQL
Database
Prediction
type?
Capacity
Delay
Retrieve ridership
forecast table
Retrieve delay
forecast table
CS410 Red Team
Poll Interval Reached
May 1 2012
WAE Request
Received
Apply batch gradient
descent learning
algorithm w/ client
position vector
Reset poll clock
Return forecast result
to WAE
29
CS410 Red Team
• The Web Application Engine (WAE) publishes a public,
accessible feed compliant with General Transit Feed
Specification (GTFS).
• The WAE also checks with the Google API to update its
record of local destinations at the station waypoints from
Google Places.
May 1 2012
Level III - Reporting
Internet
Decision Engine
Web Application
Engine
30
Internet
CS410 Red Team
• With the WAE in place and an extensible interface to it, any webenabled device can retrieve the information using our API.
• Rider feedback from end-users (website , Android app, etc.) will
be collected to the database.
• Transit authorities and businesses can view the trend data via a
back-end monitoring interface.
May 1 2012
Level IV - Presentation
Web
Application
Engine
31
Mobile App GUI Sitemap
Splash Screen
Local Events
Starred Events
Upcoming
Event
Calendar
Main Menu
& Alerts
Browse
Attractions
Google Maps
Overlay
App Settings
(Menu)
CS410 Red Team
Feedback
Submission
Form
May 1 2012
User Login
Trip Planning
Rail Stop List
Map
Plan Trip w/
Destination
Rail Vehicle
Vacancy &
Delays
32
CS410 Red Team
May 1 2012
HRT GUI Mockup
33
CS410 Red Team
May 1 2012
Business GUI Mockups
34
Milestone Overview
Server Software
Mobile Application
CS410 Red Team
Test Driver
May 1 2012
Software
Simulated APC Data
Simulated GPS Data
35
Milestone Overview
Server Software
Mobile Application
CS410 Red Team
Test Driver
May 1 2012
Software
Database
Decision Engine
Web Application
Engine
36
Mobile App Milestone
Database
Setting Shared
Preferences
GUI
Processes
Schedule Delays
UI Event Handler
Rail Capacity &
Delay Forecast
GPS/Triangulation
Checker
Rider Feedback
Module
WAE Requester
(Interface)
Ridership Counts
Rider Feedback
Submission
Local Places
Local Event
Calendar
CS410 Red Team
GUILocal
May 1 2012
Mobile
Application
37
DB Server Milestone
Install OS
Disk
Layout
Networking
Configure DBMS
Access Control
Design
Schemas
Tables
Firewall
Fields
Backups
Keys
Install
DBMS
CS410 Red Team
Configure Server
May 1 2012
Database
Server
38
Constraints
Decision Engine Milestone
Forecast Tables
Request
Handler
Gradient Descent /
Supervised
Learning
Algorithm
Delay Forecast
Rider Features
Ridership Forecast
Historical Features
CS410 Red Team
Database I/O
May 1 2012
Decision
Engine
Location Features
39
WAE Milestone
Rider Feedback
Web GUI
Syndication
Process
Administrative
Interface
Capacity Check
Google Places API
Checker
Schedule Delays
Retrieve Schedule
GTFS/AJAX/Etc
Publication
Rail Capacity &
Delay Forecast
Accept Feedback
Rider Feedback
Module
Local Destinations
Ridership Counts
Retrieve Forecast
Local Event
Calendar
CS410 Red Team
Database I/O
General
Request
Handler
May 1 2012
Web
Application
Engine
40
User Database Schemas
Interface User Profile
View
Base Info
Edit Event
Business
Details
View
Detailed
System Info
1
Admin
✔
✔
✔
2
HRT
✔
✔
✔
3
Business
✔
4
Event
✔
5
End User
✔
CS410 Red Team
May 1 2012
user_id
user_name
user_password
user_permission
41
Other Database Schemas
Train Info
train_id
curr_train_loc
train_ontime
train_capacity
train_schedule
Events Info
event_id
event_lat
event_lon
event_start
event_stop
event_cost
event_artwork
stop_id
stop_name
stop_lat
stop_lon
Attractions Info
May 1 2012
Stops Info
CS410 Red Team
Events and Attractions will be
stored in reference to the stop
closest to them.
attraction_lat
attraction_lon
attraction_category
attraction_ desc
attraction_logo
42
Database Schema ERD
Relays
Stops
provides
Events Info
CS410 Red Team
May 1 2012
Interface User
Profile
alerts
Attractions
Info
Lists
within
radius
Trains
43
T1: Data latency/accuracy
T1,C1
T2: Realistic representation
T2
C2
CS410 Red Team
Technical
May 1 2012
Risk Matrix
Customer
C3
C1: Lack of transit authority
interest
C2: Low rider acceptance
C3: No local business buy-in
44
Technical Risks
CS410 Red Team
• Risk: Data provided to the end user has exceeded time of
use.
• Risk Strategy: Determine acceptable latency periods and
provide user warning if data is time deficient.
• Risk: Data is incorrect or not updating.
• Risk Strategy: Provide system diagnostic capability to run
during maintenance periods
May 1 2012
T1: Data latency/accuracy 2/4
T2: Realistic Representation of Sensor Data 1/3
• Risk: Sensor simulations are not accurate enough to predict
actual values.
• Prototype Risk Strategy: Conduct data collection to form an
accurate model for simulation.
45
Customer Risks
Risk: Transit authorities feel current systems are efficient
Risk Strategy: Spur interest by providing granular riding data to aid
in faster service changes to maximize efficiency and predict growth.
C2: Low rider acceptance 1/2
•
•
Risk: Riders and prospective are averse to utilizing products.
Risk Strategy: Develop application to operate on multiple platforms
to address customer preference range.
CS410 Red Team
•
•
May 1 2012
C1: Lack of interest by transit authorities 2/4
C3: No local business buy-in 3/2
•
•
Risk: Local businesses choose to not support with advertising
dollars.
Risk Strategy: Provide local businesses with adequate resources to
update and inform prospective customers to drive up business.
46
Prototype Risk Mitigations
C1: Lack of interest by transit authorities 2/4
•
•
Better decision making from real-time data
Improvement of customer satisfaction
C2: Low rider acceptance 1/2
•
•
CS410 Red Team
• Test and display actual latency times and accuracy factors
May 1 2012
T1: Data latency/accuracy 2/4
Ease of use for rider
Multiple access platforms
C3: No local business buy-in 3/2
•
Targeted advertising capability
•
Increase customer awareness
47
• Right Now: Inefficient or nonexistent communication,
resulting in non-optimal Tide utilization.
• Current ITS will solve these issues in a flexible manner.
• The prototype will be developed to show the
completeness of our design.
CS410 Red Team
May 1 2012
Conclusion
48
CS410 Red Team
May 1 2012
Questions?
49
http://www.gohrt.com/publications/reports/sir-light-rail-summary.pdf
http://www.gohrt.com/public-records/Commission-Documents/Commission-Meetings/FY2012/January-2012.pdf
http://hamptonroads.com/2011/11/poll-public-board-expanding-lightrail-route
http://www.metro-magazine.com/News/Story/2011/08/INIT-employees-to-serve-as-Tide-Guides-.aspx
http://hamptonroads.com/2011/07/control-room-nsu-serves-brains-light-rail
http://www.serpefirm.com/responsibilities-the-tide-light-rail-controller-operator.aspx
http://www.gohrt.com/public-records/Operations-Documents/Rail/Monthly-Ridership/Rail-Ridership-Current.pdf
http://www.metro-magazine.com/News/Story/2011/08/Va-s-The-Tide-opens-hits-30K-boardings.aspx
http://www.cbsnews.com/8301-503544_162-4949672-503544.html
http://www.lightrail.com/projects.htm
http://www.realtor.org/wps/wcm/connect/212699004205f031b404fcc7ba2f3d20/cpa_transport_090.pdf
http://hamptonroads.com/2012/02/some-stores-near-norfolk-light-rail-stations-see-boost
Debbie Messina, “The Tide.” The Virginian-Pilot. February 18th, 2012.
http://apta.com/resources/statistics/Documents/Ridership/2011-q3-ridership-APTA.pdf
http://www.lightrailnow.org/success2.htm
http://www.prweb.com/releases/light_rail/light_rail_transit/prweb4253534.htm
http://www.itscosts.its.dot.gov/its/benecost.nsf/images/Reports/$File/Ben_Cost_Less_Depl_2011%20Update.pdf
http://www.detroittransit.org/cms.php?pageid=26
http://www.dart.org/about/economicimpact.asp
http://reason.org/news/show/126773.html
http://mobility.tamu.edu/files/2011/09/congestion-cost.pdf
http://www.vtpi.org/railben.pdf
CS410 Red Team
•
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May 1 2012
References
50
Background: Property Values
Background: Traffic & Parking
End-User Problems
Operating Problems
Multiple Mediums
The problem: revisited
Real World Product Milestones
CS410 Red Team
•
•
•
•
•
•
•
May 1 2012
Appendix
51
• In Dallas, residential properties increased by an average of 39% while
commercial properties increased by 53% over similar properties not located
near the rail.1
• A study in Portland showed an increase of over 10% for homes within 500
meters of the MAX Eastside line.2
• In Denver, the poor economy led to an average market decline of 7.5%, but
homes near the light-rail stations still saw an increase of almost 4%.3
CS410 Red Team
• Both directly through increased accessibility and indirectly through
area development, property values increase from light rail systems:
May 1 2012
Background: Property Value
• This proves that even during tough economic times, maximizing the
value of light rail systems is important.
52
1)
2)
3)
http://www.dart.org/about/economicimpact.asp
http://www.rtd-fastracks.com/media/uploads/nm/impacts_of_rail_transif_on_property_values.pdf
http://www.denverpost.com/news/ci_10850014
• Local: By 2030, Virginia will need an estimated 989 new lane-miles to
accommodate growing traffic which will cost $3.1 Billion.2
• National: Congestion and traffic cause over $115 Billion in lost productivity
and wasted fuel in the US each year.3
• How? Even a reduction as small as 5% in traffic volume will reduce delays by
20% or more during peak hours.1
CS410 Red Team
• Studies estimate that a $12.5 Billion rail system subsidy returns
$19.4 Billion just through reduced congestion and another $12.1
Billion in parking.1
May 1 2012
Background: Traffic & Parking
• In order to maximize these benefits, end-users must trust the transit
systems’ reliability as an alternative to driving.
53
1)
2)
3)
http://www.vtpi.org/railben.pdf
http://reason.org/news/show/126773.html
http://mobility.tamu.edu/files/2011/09/congestion-cost.pdf
• No real-time or direct alerts and updates regarding service
status and service interruptions.2
• With no information regarding local businesses and attractions
at the stops, riders have no incentive to use the light rail to
new areas.
CS410 Red Team
• The Tide riders lack access to real-time information, which is a
cost-effective measure that can reduce perceived wait times
by an average of 10%.1
May 1 2012
End-User Problems
54
1) http://www.sciencedirect.com/science/article/pii/S0965856406001431
2) http://www.gohrt.com
CS410 Red Team
• The Tide tracks the number of riders entering the train, but no
detailed information.1
• Operators have no form of real-time alerts or status updates.2
• Dispatchers have no way of tracking train positions on the
downtown portion of the rail system, so must rely on radios.3
May 1 2012
Operating Problems
55
1) http://www.metro-magazine.com/News/Story/2011/08/INIT-employees-to-serve-as-Tide-Guides-.aspx
2) http://hamptonroads.com/2011/07/control-room-nsu-serves-brains-light-rail
3) http://www.serpefirm.com/responsibilities-the-tide-light-rail-controller-operator.aspx
• All three systems will use the same underlying system and
authentication process, providing appropriate tools based on the user
level (rider, business owner, operator).
• The key to the interfaces will be providing a way for HRT and local
businesses to provide riders with the necessary data to fully utilize the
light rail system.
• In addition to providing static information, use of these mediums will
provide riders with real-time tracking, allow operators to issue service
updates, and give business owners a new way of delivering targeted
advertising.
CS410 Red Team
• Current ITS will be fully accessible from three different mediums:
mobile applications, station kiosks, and a website. This will ensure that
users can access it easily from virtually any location.
May 1 2012
Multiple Mediums
56
• Information: Everything from details about local businesses to train
schedules during major events is vital.
• Communication: Two-way, real-time communication is essential in every
aspect of improving light rail systems towards further expansion.
CS410 Red Team
• These studies show the benefits, but return on investment can
be further boosted in 3 key areas:
May 1 2012
The Problem: Revisited
• Overall Satisfaction: Providing an easy to use system for local businesses,
riders, and operators will promote maximal adoption of the light rail
system.
57
Overall Milestones
Production
Servers
Workstations
Web App Server
Dev Servers
Database
Server
Dev Phone
Onboard Hardware
GPS Sensors
Embedded Apps
Linux Reporting
Agent
Automatic Passenger Counters
Master PC
Server
Software
Mobile/Kiosk
App
Database
CS410 Red Team
Software
Hardware
Development
May 1 2012
Current ITS
Decision
Engine
Web
Application
Engine
58
RWP Hardware Milestones
Development
Workstations
Production Servers
Onboard Hardware
CS410 Red Team
May 1 2012
Hardware
Dev Servers
Dev Phone
59
RWP Hardware Milestones
Development
Production Servers
WAE Server
Onboard Hardware
CS410 Red Team
May 1 2012
Hardware
DB Server
60
RWP Hardware Milestones
Development
Production Servers
Onboard Hardware
CS410 Red Team
May 1 2012
Hardware
People Counting Sensors
GPS Sensors
61
Embedded PC
Web App Engine Server
Install OS
Disk
Layout
Networking
Configure
Webserver
Access
Control
Interface to
DB
Interface to
Decision Engine
Decision
Engine
Interface
to DB
Interface to
Decision
Engine
CS410 Red Team
Configure Server
May 1 2012
WAE Server
Firewall
Install
Webserver
Develop Decision
Engine
62
Onboard Hardware
Quote from multiple
vendors
Interface to
Master PC
Automatic Passenger
Counters
Quote from multiple
vendors
Interface to
Master PC
Master PC
Quote from multiple
vendors
Configure
Device
OS Install
CS410 Red Team
GPS Sensors
May 1 2012
Onboard Hardware
Networking
Reporting Agent
Interface to GPS
Interface to APC
Interface to DB
63