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Final PresentationDec. 12, 2008

Craig Emmerton

Earl Morton

Shaun McDonald

David Richards

Nikki Torres-Avila

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PARKme System

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Problem Statement

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“Finding a parking space at GMU is a common frustration for commuters. Campus parking lots are often overcrowded during certain times of the day and week making parking a guessing game. This leads to students, faculty, & visitors being late for classes and appointments.”

Utilized Six Sigma Methods in Developing the Problem Statement

• Define the Problem• Identify Where the Problem is Appearing• Describe the Size of the Problem• Describe the Impact the Problem is Having on the Organization

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GMU Survey

*Worst case assumed is 40 minutes

Time

(minutes)

Number of Individuals

Percent(%)

5 1399 32

10 1063 24

20 847 19

30 450 10

40* 589 13

Average time spent to find a space at GMU

Average Time (Mean) = 16.5 minutesStandard deviation (σ) = 12.20409

Data is widely spread around the calculated mean of the data

0

200

400

600

800

1000

1200

1400

Ind

ivid

ual

s P

olle

d5 10 20 30 40

Time (minutes)

Average Time to Find a Parking Space - GMU Campus

Data Provided by Josh Cantor, Director of Parking for GMU

PARKme Goal: Average Time Under 8 Minutes!3

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System Concept of Operations (OV-1)

4High-Level Operational Concept Graphic (OV-1), DoDAF Version 1.5, 23 April 2007 4

Project Role & Deliverables

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PARKme System Deliverables

Business CaseNet Cash Flow

10 Year Plan

Prototype / SimulationColored Petri Net of SystemMonte Carlo Analysis

Statement of Work (SOW)Stakeholder Analysis Report

Concept of Operations (CONOPS)System Engineering Management Plan

(SEMP)Analysis of Alternatives (AOA)

PARKme Team Role

System Developer / Integrator•Collect stakeholder’s needs•Develop requirements•Analyze different architectures•Functionally decompose the system

Technical PlanRisk Management Plan (RMP)System Requirements Specification (SRS)System Design Document (SDD)CPN Description DocumentMonte Carlo AnalysisTechnology Strategy

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Work Breakdown Structure

WBS SCHEDULE

GANTT ChartPERT Chart 6

PARKme Risk Management

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Stakeholder Analysis

• Stakeholder Identification– End User – GMU Administration

• GMU Police/Security – Project Manager – GMU Maintainer – Engineers – Project Sponsors

• Key Stakeholders– End User– GMU Administration– Project Sponsors– Project Manager

Methodology developed by the Imperial College of London,Used in the government and private industry

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Stakeholder Needs Analysis

 Find Parking

 Update parking availability

<<include>>Driver

<<include>>

 Determine User

Preferences

PARKme System

Formalized scenarios and translated them to use cases

Quality Function Deployment

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Functional Architecture

Analysis of Alternatives

• Research• Researched parking alternatives on the Internet. • Study previous academic research. • Alternatives include:

• Utilizing existing parking system with minor updates. – Minor Updates include Parking Gate

• Valet Parking• Automated parking systems• Electronic devices (Sensors)

• Identified requirements to implement these alternatives. • Analyze the benefits and constraints of each of the systems.

• Conclusion• Utilizing existing parking system with entry gates would not improve the

time required to find empty parking spaces. • Valet parking would not be appropriate solution for a campus parking

environment.• Automated parking would be very expensive investment and require

complete redesign of the current parking at GMU• Sensors would be minimum impact on existing parking structure, and

provide maximum return on investment.

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• AoA Methodology• Use commercial-off-the-shelf (COTS) architectures.• Components are interchangeable, new technology easily incorporated.• Logical Decisions for Windows (LDW)

• General Definition• Project survey submitted to Sponsor and fellow classmates• Each alternative had a list of criteria used as weights • Six criteria that are being used in each of our subcomponents.

• ‘Start Up Cost’• ‘Maintenance Cost’• ‘Construction’• ‘Maturity’• ‘Reliability’• ‘Time Between Failures’.

AoA Methodology

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LDW & Rankings of Alternatives

Ranking of Sensors

Ranking of Human Interfaces

Ranking of Connectivity LDW Output Used for Architecture Comparison

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Evaluation of Alternatives

Weighing Factors (1-5: Lower is better)Start Up Cost: 3 (Medium importance)Monthly Cost: 1 (High importance)Time between Failures: 3 (Medium

importance)Reliability: 1 (High importance)Maturity: 3 (Medium

importance)Feasibility: 1 (High importance)

Creativity Techniques, The Engineering Design of System, 2000

• Sensors (Transceiver)• Wireless networking components• Housed in a plastic covering similar in size to a street reflector• One per parking space• Transmits parking data via the communications network

• Communications Network• The parking space information to the our main system.• Mesh Network

• Main System• The main system will be the interface between the parking space information and the end user.• Network server (Software)

• Human Interfacing• Transfers parking space availability information from the main system to the user. • In our case, electronic signs are used to relay parking space information

Morphological Box for PARKme System

Control System Space Sensors Human Interface Connectivity

Server Network Weight Plates Kiosk Units WiFi Network

Camera Electronic Signs T/R Antenna

RFID GPA Device (PED) Hard Cabled

Infrared Internet (PED) Cell Towers

Ultra-Sound PDA (PED)

Motion Detector Cell Phone (PED)

Light Sensor Patriot Web

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• Sensors• RFID sensor chosen; weight sensor eliminated

• Weight Sensor eliminated because of surveyed construction impact• Our student survey weighted the construction criteria as very high.• The second highest ranking is the light sensor.

• Light sensor eliminated because of reliability!

• Human Interface (PED ranked highest)• Initial implementation of the system will be electronic signs• Incorporation of PEDs

• Most of the remaining options were very closely ranked except for Kiosk. • Includes portable devices: cell phones, or laptops with Internet connectivity.

• Connectivity• Wi-Fi chosen; Cell towers ranked highest

• Campus control over Wi-Fi verses Cell towers• LDW ranked the Wi-Fi network as the second preferred selection.

Results

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System Design

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Top Level Software Functions Hardware Interface Diagram

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Technology Strategy

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• Technology Readiness Levels• PARKme System Requires a TRL of at least 7

• Proprietary Software• PARKme Software licensed for use only on PARKme Computer Systems• Underlying software used by the PARKme System will be licensed for use from corresponding software companies

• Intellectual Property Rights• Patent search reveals 1 patent and 3 patent applications of similar systems• Application for patent for concept of the PARKme System

• PARKme System designed with modular components in an “open architecture”

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Business Case

• Provide reasoning and justification for entering the market– Stakeholder Benefits

– PARKme Benefits

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GMU Purchase (no partnership)

GMU Purchase (with partnership)

Development funds provided by GMU $0 $14,000

Development funds from PARKme $68,950 $13,000

Total Development Cost $68,950 $27,000

Cost to GMU $1,060,737 $1,014,066

Expected Profit to PARKme (GMU purchase only)

$162,914 $135,279

Net Present Value (based on sale of 19 systems over 10 years)

$1,932,235 $1,906,495

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(500,000.00)

0.00

500,000.00

1,000,000.00

1,500,000.00

2,000,000.00

2,500,000.00

3,000,000.00

3,500,000.00

Net Cash flow

Cumulative Cash flow

Cash Flow

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Sensitivity/Decision AnalysisPARKme Analysis

4,438,670{28}

3,543,050{192,000}

3,046,385{13,000}

3,017,435{500}

1,542,200{10}

1,985,050{110,000}

2,959,385{100,000}

2,954,435{4,000}

0 500,000 1,000,000 1,500,000 2,000,000 2,500,000 3,000,000 3,500,000 4,000,000 4,500,000 5,000,000

Fixed cost per system

Development Cost

Profit Expectation

Systems Sold

Tornado Diagram

Decision Tree Branch

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PARKme Modeling Efforts

Small Fully Scalable Models

Proof of Concept

Top Level CPN ModelMonte-Carlo Timing Analysis

MathWorks MatLab

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Timing Model statistics

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GMU: Main campus parking conditions• Inner campus lots full during peak times• Outer overflow lots at 85.5% full• 16.5 minutes on average spent looking for a

parking space• Over 25% of students spend an average of

over 30 minutes

Parameters Modeled• 90 % probability a parking lot is full• 100,000 Monte-Carlo runs

Model Differences• First students on campus always get preferred

lots• Late students may go directly to overflow lots• Other students have insight into best lot from

past experience• Students may choose to park nearest to

building not hosting first classView Actual Model Output

Timing Model Results

• To compare our data with the data provided from GMU it can be noted that the worst case of 90% is an acceptable model.

• Our worst case model reflects an average of over 30 minutes spent looking for a free parking space.

• Our modeled worst case reflects an average of over seven lots searched before a parking lot with available spaces is found.

•• Using the PARKme system a parking lot with available spaces could have

been found in 5 minutes.

• Compared to the current GMU times this is a saving of over 10 minutes for the average case and 30 minutes for the GMU worst case.

PARKme Goal: Average Time Under 8 Minutes!

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Summary

University Image

• Technology Oriented Campus

• Embracing Green Movement

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End of Brief

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Comments & Questions?

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Backup Slides

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Functional Decomposition

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Activity Diagram – IDEF0

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Activity Model – Data Flow Diagram

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State Transition Diagram

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CPN Tools Top Level Architecture

RETURN

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Digital Signs - Colored Petri Net

RETURN

Driver Parking Lot

User Interface

Space Locator

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PED - Colored Petri Net

RETURN

User Interface

Parking Lot

Driver

Space Locator

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Monte-Carlo Model

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Parking Lot (1)

Preferred

Parking Lot (1)

Preferred

Parking Lot (5)

Parking Lot (5)

Parking Lot (4)

Parking Lot (4)

Parking Lot (3)

Parking Lot (3)

Parking Lot (2)

Parking Lot (2)

Facility PerimeterFacility Perimeter

Parking Lot (10)Overflow

Parking Lot (10)Overflow

Parking Lot (6)

Parking Lot (6)

Parking Lot (7)

Parking Lot (7)

Parking Lot (8)

Parking Lot (8)

Parking Lot (9)

Parking Lot (9)

PreferredBuilding

PreferredBuilding Average human walks at

60 ft/minute (WikiAnswers.com)Average human walks at

60 ft/minute (WikiAnswers.com)

RETURN

1 minute1 minute

Until a Parking Space is Found 4 minutes spent driving to each parking lot 1 minute spent searching each parking lot

Until a Parking Space is Found 4 minutes spent driving to each parking lot 1 minute spent searching each parking lot

PARKme System

RETURN 36

Parking Statistics

RETURN 37

Timing Model Statistics

• =====================================================• Number of Monte Carlo Runs: 100000• --------------------------------------------------------------------------------• This is pure time to find the parking space• Minimum Time: 5.00 minutes• Maximum Time: 50.00 minutes• Mean Time: 32.63 minutes• Mode Time: 50.00 minutes• Mode Occurrences: 39072.00• Median Time: 35.00 minutes• Time Variance: 290.44• Time Standard Deviation: 17.04• --------------------------------------------------------------------------------• This is the time to find the parking space and walk to the preferred building• Minimum Time: 10.00 minutes• Maximum Time: 100.00 minutes• Mean Time: 65.26 minutes• Mode Time: 100.00 minutes• Mode Occurrences: 39072.00• Median Time: 70.00 minutes• Time Variance: 1161.77• Time Standard Deviation: 34.08• --------------------------------------------------------------------------------• Minimum Number of Lots Searched: 1.000• Maximum Number of Lots Searched: 10.00• Mean Number of Lots Searched: 6.53• Mode Number of Lots Searched: 10.00• Mode Occurrences: 39072.000• Median Number of Lots Searched: 7.00• Number of Lots Searched Variance: 11.62• Number of Lots Searched Standard Deviation: 3.41• =====================================================

Parameters Modeled

• Distance from preferred lot to preferred building is 300 ft.• 90 % chance a parking lot is full• 10% chance a available lots fills up before the user arrive.• 10 parking lots were modeled.• 4 minutes t drive to a parking lot• 1 minute to search a parking lot

GMU: Main campus parking conditions

• Inner campus lots full during peak times• Outer overflow lots at 85.5% full• 16.5 minutes on average spent looking for a parking space• Over 25% of students spend an average of over 30 minutes

Timing Model Output: 90% Lots Full Case

RETURN 38