NATMEC: Improving Traffic Data Collection, Analysis, and Use
June 29– July 2, 2014, Chicago, Illinois
Business Intelligence System for Traffic Data Integration: Linking Roadway, Collision and Traffic Flow Data
to Improve Traffic Safety
Stevanus A. Tjandra, Ph.D. City of Edmonton Office of Traffic Safety
NATMEC: Improving Traffic Data Collection, Analysis, and Use
June 29– July 2, 2014, Chicago, Illinois
Outline
City of Edmonton Office of
Traffic Safety
Performance Measurement
and Traffic Safety
Problem
Business Intelligence (BI) System for Traffic
Data Integration
Integrated Data
Analysis
BI, KPI and Predictive Analytics
NATMEC: Improving Traffic Data Collection, Analysis, and Use
June 29– July 2, 2014, Chicago, Illinois
City of Edmonton Office of Traffic Safety (OTS)
Established in 2006 as a result of Mayor Traffic Safety Task Force
World urbanization - UN report 2009:1
Year Urban Population Rural Population
2009 3.4 billion 3.4 billion
2050 6.3 billion 2.9 billion
The OTS will reduce the prevalence of fatal, injury, and property damage
collisions through the 4 E’s of traffic safety (Engineering, Education,
Enforcement, and Evaluation) by improving
urban traffic safety engineering
road user behaviour
speed management and
data, business intelligence and analytics
http://www.edmonton.ca/transportation/traffic-safety.aspx
1World Urbanization Prospects The 2009 Revision http://esa.un.org/unpd/wup/Documents/WUP2009_Highlights_Final.pdf
NATMEC: Improving Traffic Data Collection, Analysis, and Use
June 29– July 2, 2014, Chicago, Illinois
Measuring Performances
Key Result and Performance Indicators (KRIs and KPIs) Strategic Statement
+
Data
Analytics
“You Can’t Manage What You Don’t Measure” “What Gets Measured Gets Done” (Peter Drucker)
KPI Level I and II
Level I
Level II
Traffic Safety: A Multidimensional Problem
Traffic
safety
Road User
Behaviour Regulation
Roadway
Engineering
Nature Vehicle Enforcement
Driving
decision
Speeding
Seat belt
Driving skill/training
Alertness:
alcohol/drug,
fatigue, health
Attention: cell phone, music
Age
Speed limit Geometric
design:
curves,
slope, lane
width, etc.
Lighting
Traffic signs
Non-reflective
paint
Sun glare
Ice,
Rain,
Fog
Animal
crossing
Enforcement
camera:
intersection,
road segment
Community
Program to
promote traffic
safety
Visibility
of
windows
Brake
malfunction
Side-view
mirrors
Road connection that
creates high traffic
variability
Speed bump Gender
Presence of
enforcement
officers
Vehicle safety
performance:
crashworthiness,
aggressivity.
Presence of
passengers
Road physical conditions
Demand vs. capacity: road
congestion, required # road
connections to meet the traffic
growth
Socio-
economic level
Visibility
Index
Distracted
Driving
Law
Seat belt
Education
Speed
display
Check Stop
Dynamic
Message Sign
(DMS)
Weather Impacts on
Traffic Safety:
Trends and Patterns
NATMEC: Improving Traffic Data Collection, Analysis, and Use
June 29– July 2, 2014, Chicago, Illinois
Repeat Violators
NATMEC: Improving Traffic Data Collection, Analysis, and Use
June 29– July 2, 2014, Chicago, Illinois
Violations and Collisions
0%
5%
10%
15%
20%
25%
30%
1 2 3 4 5 6 7 8 9 10 11 12+
Number of AE violations % V
eh
icle
s I
nvo
lve
d i
n a
t L
east
1 C
ollis
ion
Edmonton Automated Enforcement and Collision Data: January 1, 2010- December 31, 2011
Topinka, Neil. Project Mercury: Automated Enforcement Data and Driver Behaviour in the Edmonton Capital Region. International
Forum on Traffic Records And Highway Safety Information Systems - Special Session, May 2, 2013. Edmonton, Canada.
NATMEC: Improving Traffic Data Collection, Analysis, and Use
June 29– July 2, 2014, Chicago, Illinois
Urban Traffic Safety Engineering Road Design Improvement
Yellowhead Trail WB RAMP – Victoria Trail NB
NATMEC: Improving Traffic Data Collection, Analysis, and Use
June 29– July 2, 2014, Chicago, Illinois
Urban Traffic Safety Engineering Video Analytics
Before After Yellowhead Trail WB RAMP – Victoria Trail NB
The project cost: $437,240
The collision reduction resulted in an annual cost saving of $887,685
NATMEC: Improving Traffic Data Collection, Analysis, and Use
June 29– July 2, 2014, Chicago, Illinois
Data, Information, and Knowledge Silos
Inadequate knowledge about the existence of various data and their availability,
Lack of linkages with other databases resulting in duplicate data collection, processing and management,
No standardized method for the specific identification of attributes across data sources,
Lack of communication among stakeholders of important changes to the data, and
Lack of access to other data systems
Crime
Modified from the original picture published in
http://blogs.sun.com/bblfish/entry/business_model_for_open_distributed
NATMEC: Improving Traffic Data Collection, Analysis, and Use
June 29– July 2, 2014, Chicago, Illinois
NATMEC: Improving Traffic Data Collection, Analysis, and Use
June 29– July 2, 2014, Chicago, Illinois
Traffic Data Coordination Committee (TDCC)
Task Force
Traffic Data
Oversight Committee
Task Force Task Force Task Force
Policy
direction,
strategic
needs
Program
oversight
Recommended operational
needs and actions (e.g.,
standardized format, critical
data, data collection and
analysis procedures)
Recommended
Integrated System and
Five-Year Plan
Policy
direction,
strategic and
tactical needs
Program
oversight
Traffic Data Coordination Committee
University of Alberta
NATMEC: Improving Traffic Data Collection, Analysis, and Use
June 29– July 2, 2014, Chicago, Illinois
Data Analysis and Business Intelligence – Traffic Data Integration
• Enforcement durations
• Traffic counts • Offence statistics • Issued tickets
statistics • Locations
Spatial
Business
Intelligence
Framework
Environment Canada
Federal Census
Traffic Complaints
System
Edmonton Police
Service
Transit Safety & Security Transit Transportation
Operations
Speed & traffic complaints
• Manned enforcement
• Impaired driving • Crime statistics • Shift schedules
Accidents/incidents
• Bus Stops & routes • Passenger counts
• Road conditions • Roadway maintenance
Weather conditions
Demographic statistics
Spatial Land Inventory
Management (SLIM)
Roadway inventory
Traffic Count Management
(TCM)
• Traffic volume • Turning movement
counts • Speed surveys
Automated Enforcement (Intersection
Safety Cameras and Photo
Radar Cameras)
Motor Vehicle Collision
Information System (MVCIS)
Roadway collisions
Initial Release 2011 WINNER of IBM SMARTER CITY,
one of 24 cities worldwide
NATMEC: Improving Traffic Data Collection, Analysis, and Use
June 29– July 2, 2014, Chicago, Illinois
Spatial Business Intelligence
Spatial Business Intelligence (SBI) supports traditional and spatial data through merging Geographic Information Systems (GIS) and Business Intelligence (BI) technologies
Reporting
Mapping
Analytics
EFFICIENT
&
EFFECTIVE
DECISION
MAKING
Integration
&Collaboration
Business Intelligence of Traffic Data Integration
Use BI Launchpad in BusinessObjects 4.0 as an Enterprise Report Portal for sharing business intelligence reports
Business Intelligence of Traffic Data Integration
The last traffic
survey: 2011
NATMEC: Improving Traffic Data Collection, Analysis, and Use
June 29– July 2, 2014, Chicago, Illinois
Benefits of Business Intelligence
(Eckerson, The Data Warehousing Institute, 2003)
Integrated Data Analysis: Inner Ring Road
Empirical Bayes analysis led us to identify
170 St - North of 95 Ave as the worst section
for traffic collisions
From 2009 to 2011 there were:
55% more collisions than other similar
mid-block locations
23 more collisions than expected
West
Edmonton
Mall
*Brandt Denham, City of Edmonton Office of Traffic Safety, 2013
2nd from Curb50%
3rd from Curb8%
Right Curb25%
Unknown17%
Collisions by Driving Lane (2012)
2012 data has less unknown traffic lanes so it may be a more accurate breakdown of the collisions by lane
The 2nd from curb lane is lane #3
(The right curb lane is not a through lane)
Chng. Lanes Impr.18% Fld. Yield
R.O.W.6%
Flwd. Too Closely
72%
Ran Off Road2%Struck Parked
Veh2%
Collisions by Cause (09-11)
1 2 3
Study area
The top 5 violators are all rental and cab companies.
0
5
10
15
20
25
Mon Tue Wed Thur Fri Sat Sun
Collisions by Day of Week (09-11)
Peak collision periods: Nov-Dec Christmas shopping Fri-Sat weekend shopping Mid afternoon shopping
23%
57%
20%
Average Monthly Speed Tickets Issued
Lane 3 (67)Lane 1 (77)
Lane 2 (195)
24%
40%
36%
Average Monthly Red Light Tickets Issued
Lane 3 (10)
Lane 1 (6)
Lane 2 (11)
41.26%58.74%
Violator Registered Owner Postal Code
Within Edmonton
Outside of Edmonton
Implementation
Integrated Data Analysis: Inner Ring Road
NATMEC: Improving Traffic Data Collection, Analysis, and Use
June 29– July 2, 2014, Chicago, Illinois
BI, KPI and Predictive Analytics
Predictive Analytics
Short-Term Weather and Collision Prediction
NATMEC: Improving Traffic Data Collection, Analysis, and Use
June 29– July 2, 2014, Chicago, Illinois
City of Edmonton Weather, Collision and Traffic Flow Prediction
Calendar Data
Month, Day of Week, Holiday
Weather Data
Set-up for Edmonton
Traffic Flow Data
VDS Sites: Speed, Volume
0
2
4
6
8
10
12
14
16
12
-Feb
13
-Feb
14
-Feb
15
-Feb
16
-Feb
17
-Feb
18
-Feb
19
-Feb
20
-Feb
21
-Feb
22
-Feb
23
-Feb
24
-Feb
25
-Feb
26
-Feb
27
-Feb
28
-Feb
1-M
ar
2-M
ar
3-M
ar
4-M
ar
5-M
ar
6-M
ar
7-M
ar
8-M
ar
9-M
ar
10
-Mar
Sno
w F
all A
mo
un
t (cm
)
1-day-earlier Forecast Snow (cm)
Actual Amount Snow (cm)
7-day-earlier Forecast Snow (cm)
Past Future
Weather
Prediction 0
1
2
3
4
5
6
7
8
0
20
40
60
80
100
120
140
1-A
pr
2-A
pr
3-A
pr
4-A
pr
5-A
pr
6-A
pr
7-A
pr
8-A
pr
9-A
pr
Am
ou
nt o
f Pre
cip
itat
ion
(MM
)
Pre
dic
ted
To
tal &
FTC
Co
llisi
on
sPredictedTotal PredictedFTC AmountPrecipitation
60
65
70
75
80
85
90
11
/20
/20
12
11
/22
/20
12
11
/24
/20
12
11
/26
/20
12
11
/28
/20
12
11
/30
/20
12
12
/02
/20
12
12
/04
/20
12
12
/06
/20
12
12
/08
/20
12
12
/10
/20
12
12
/12
/20
12
12
/14
/20
12
12
/16
/20
12
12
/18
/20
12
12
/20
/20
12
12
/22
/20
12
12
/24
/20
12
12
/26
/20
12
12
/28
/20
12
12
/30
/20
12
01
/01
/20
13
01
/03
/20
13
01
/05
/20
13
01
/07
/20
13
01
/09
/20
13
Day
Traffic Speed (km/h, Location: SW VDS Site - WMD & 156 St)
High Speed Alert Warranted
Volume & Speed
Prediction
Collision
Prediction
Future Work
5,665 5,951 6,3276,817 7,151
7,658
6,3815,564 5,873 6,092
5,5134,758
3,991 3,792 3,504 3,389 3,246
17,648
19,128 19,082
20,992 21,000
23,542
22,137
20,606
22,784
26,066
28,52029,072 28,832 28,480
23,442 23,243
24,803
28.2
30.129.4
31.9 31.5
34.8
31.7
29.1
32.0
35.2
38.5 38.6
36.835.9
28.928.4
29.7
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Collisions in Edmonton 1997-2013
Total Collisions
Injury and Fatal Collisions
Collisions per 1,000 Population
The Growing Challenge
Decrease 14,451 injury & fatal collisions (20,795 injuries and fatalities) Save $ 999.8 M
NATMEC: Improving Traffic Data Collection, Analysis, and Use
June 29– July 2, 2014, Chicago, Illinois
Zero fatal and
serious injury collisions Our Vision:
Zero Fatal and Injury Collisions
NATMEC: Improving Traffic Data Collection, Analysis, and Use
June 29– July 2, 2014, Chicago, Illinois
Thank You Contact: [email protected]