Post on 24-Jul-2020
Managing Effective Transportation Safety Systems:
Research Update
Tuesday, September 24, 20192:00-3:30 PM ET
TRANSPORTATION RESEARCH BOARD
The Transportation Research Board has met the standards and
requirements of the Registered Continuing Education Providers Program.
Credit earned on completion of this program will be reported to RCEP. A
certificate of completion will be issued to participants that have registered
and attended the entire session. As such, it does not include content that
may be deemed or construed to be an approval or endorsement by RCEP.
Purpose
To summarize safety management research presented during the TRB Annual Meeting in January 2019.
Learning ObjectivesAt the end of this webinar, you will be able to:
• Discuss new methods for better defining system safety issues
• Describe organizational structures and resource allocation in safety planning
• Identify techniques for building coalitions and improving media relations to generate support for road safety planning and projects
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Data Analytics Infrastructure for Vehicle Safety and Emissions Inspection Analysis
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• Our initial explorations were state-specific analyses, including of manufacturer, model year, and test result trends
• As our data have grown, we can do higher level analyses of performance across states, and still at the vehicle, model year, and test result levels.
• We believe analytics is critical in determining what states (and agencies like NHTSA, EPA) need to know about how IM programs are performing and how they can be improved
PA Inspection & Registration Data
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e-SAFETY CompuSpections Registration
Record Count 980k (total) 3.3 million (total) 10 million (each)
Frequency 7 years(2008-2014)
5 years(2008-2014)
4 snapshots(March ‘12 & November ‘13
November ’14, May ‘17)Percent of Registered Vehicles per Year ~3% ~10% ~100%
VIN X X X
Odometer X X X*
Date X X X*
Location (zip code/county) X X X*
Vehicle make and/or model X X
Inspection Type (e.g., annual) X X
Inspection Action (e.g., pass, new) X X
Insurance Policy X X
*At time of registration for current owner in PA
Leveraging Detailed Safety Inspection Records
• Past failure rate analysis just looked at overall pass/fail data in safety inspection categories (12-18% rate)
• We wanted to leverage our analytics engine for each vehicle inspection to demonstrate data-driven analyses possible. Chose a hot topic..
• Should we look harder at the safety thresholds used for tire tread?• What is the deterioration rate of tire tread in passenger vehicles? • Given inspection thresholds, how many cars would be expected to
be “below threshold” before their next annual inspection? • How many are potentially driving around ‘unsafe’ on bald tires?
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Data-Driven Tire Tread Deterioration Motivating Example
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Year
Tread(32nds Inch)
InspectedJan 1, 20125/32” Inspected
Jan 1, 20133/32”
Tread deterioratingfor this vehicle at 2/32” over 12 months
NHTSA Inspection Threshold
2
At that rate, it will fall below3/32” at 6 months after inspection(July 1, 2013)
Part 1: Deterioration Model Results• Analyzed records in both safety datasets (2008-2016)
• About 10 million inspection records / 1 million unique vehicles• Historical vehicle level analysis of tire tread deterioration rates
• Summary Results:• In 90%+ of inspections, all 4 tires are recorded as within 1/32”• We find difference in tire tread for year vs. miles driven
• Overall average is about -0.3 per 1,000 mi. • Given 10,000 VMT .. avg tread loss is 3/32” per year
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Part 2: Projections and Policy Analysis
• We’d expect an average car at 4/32” (i.e., within 2/32” of the limit) at time of an inspection to need new tires before next inspection.• Drivers who don’t take routine maintenance seriously may be
driving on unsafe tires soon after the inspection.
• A static inspection threshold (e.g., 2/32”) might not be anticipating problems for cars that will fall below the threshold soon after their inspection (and maybe drive around for nearly a whole year)
• Overall, we estimate about 30% of cars will “need new tires” before next inspection, i.e., cars would be at risk of having unsafe tires
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Implications of Data-Driven Analysis• Implications for a state..
• What about changing the thresholds (e.g., 4/32”)? • What about considering average annual VMT when inspected?• What about having different thresholds for different types of
passenger vehicles (cars vs. SUVs)?
• We estimate a sweet spot for threshold of ~5/32 – 6/32” where risk gets significantly lower (but still not zero)
• Overall, lots of potential ways in which analyzing your own data can lead to potential program improvements and safer transportation
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Thank You!
Allocating Spending between Hotspot and Systemic Approaches to Safety ManagementPresented by:Tim Harmon, PEVHB
September 24, 2019
© In
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Roadway Safety Management Process
§ Determine opportunities for improvement– Locations with highest expected crash frequency or PSI– Highly prevalent crash types or contributing factors
§ Identify appropriate countermeasures
§ Implement most effective projects
§ Evaluate effectiveness
Source: FHWA 2
Objectives
1. Demonstrate the reliability and value of the systemic approach in practice.
2. Estimate the relative effectiveness of hotspot and systemic.
3. Determine how much hotspot and systemic agencies should implement.
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Applying Network Screening Results
§ Hotspot Approach– Highest PSI locations– Address unique problems– Higher cost projects
§ Systemic Approach– Moderate PSI locations– Address common problems (SHSP)– Lower cost projects
§ Systematic Approach– Address everywhere, not crash-based– Often to upgrade hardware– Variable costs
§ Planning and Data Improvements4
Hypothetical Network Screening Results
Ranking by expected fatal and injury crash frequency
Rank Site ID Facility Type MajorRoad MinorRoad PredKABC ExpKABC ExcKABC Total Crashes AADT1 1234 Urban; 4-leg signalized Main St North St 0.56 1.71 1.15 80 170002 2345 Urban; 4-leg signalized West Rd Union St 0.50 1.49 0.99 77 141053 3456 Urban; 4-leg signalized Church St Beech St 0.43 1.39 0.97 60 120004 5678 Urban; 4-leg signalized Valley St Union St 0.42 1.32 0.90 49 110835 4567 Urban; 4-leg signalized Acorn Rd Oak Ln 0.35 1.29 0.94 62 80006 35456 Urban; 4-leg signalized Broadway Main St 0.65 1.19 0.55 75 220007 6789 Urban; 4-leg signalized Maple St Spruce St 0.25 1.12 0.87 56 64008 37297 Urban; 4-leg signalized Willow St Main St 0.59 1.10 0.51 56 207909 23456 Urban; 4-leg signalized Elm St West Ave 0.49 1.09 0.60 57 15000
10 65630 Urban; 4-leg signalized Main St Spring St 0.53 1.07 0.54 70 1782011 27633 Urban; 4-leg signalized Second St Elm St 0.62 1.07 0.45 50 2300012 20710 Urban; 4-leg signalized Park St Sixth St 0.57 0.98 0.41 68 2475013 2965 Urban; 4-leg signalized Washington St Chestnut St 0.69 0.98 0.29 46 2475014 23385 Urban; 4-leg signalized Third St Maple St 0.45 0.96 0.51 51 1400015 28289 Urban; 4-leg signalized Magnolia St Dogwood St 0.43 0.95 0.52 60 1700016 16729 Urban; 4-leg minor-rd STOP Cedar St Aspen St 0.50 0.95 0.45 73 1504817 12345 Urban; 4-leg signalized First St Holly St 0.33 0.94 0.61 53 775818 35544 Urban; 4-leg signalized Park Ave Main St 0.69 0.94 0.25 31 2900019 7890 Urban; 4-leg minor-rd STOP Walnut St Fourth St 0.10 0.90 0.80 43 1309820 30146 Urban; 4-leg signalized Fifth St Central St 0.39 0.89 0.50 44 21780
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Example Network Screening
Highway Safety Project Benefits
NPV = Ncrash Crash Cost ) Project Costs
NPV = net present value = net benefits
Ncrash = crash frequency before project implementation
CMF = crash modification factor
§ Higher PSI sites can justify more expensive and effective projects.
§ Low PSI sites will only allow low project costs, regardless of effectiveness.
Potential Monetary Benefits/PSI
Monetary Benefits from Crash Reduction
Countermeasure Data
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Selecting Effective Countermeasures§ Most alternatives have increasing costs and effectiveness
§ Simple choice if one countermeasure is cheaper and better
*95% confidence interval—source: HSM 1st Edition
§ Otherwise, when is the additional investment worth it?
§ Net benefits of two alternatives are equal at some crash frequency:
NPVhigher cost, higher CRF = NPVlower cost, lower CRF
Countermeasure Cost CMFKABC* (CRF)
Various Low-Cost Systemic Improvements $5,000 0.90 ± 0.06 (10%)
Minor STOP to All-way STOP $50,000 0.30 ± 0.12 (70%)
Minor STOP to Traffic Signal $500,000 0.62 ± 0.10 (40%)
Minor STOP to Roundabout $1,000,000 0.18 ± 0.08 (78%)
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Project Breakeven Equation
Nbreakeven = breakeven crash frequency where the benefits of two alternative projects or countermeasures are equal
AVC = annualized value of project costs
CMF = project effectiveness
CC = average crash cost
Nbreakeven=AVChigh AVClow
CC CMFlow CMFhigh
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Example Application:RAB vs. Low-Cost Signing & Marking Package
NKABC,breakeven=CostRAB Costlow cost
CCKABC CMFKABC,low cost CMFKABC,RAB
NKABC,breakeven = $750,000 $6,000$160,000 0.90 0.15 = 6.2 crashes
>6.2 KABC, consider roundabout or low-cost
-cost package only10
Applying Network Screening Results
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HOTSPOT SYSTEMIC
Roundabouts
Traffic signals
Curve realignment
Road diets
Reduce approach skew
PHB/HAWK
Rumble strips
Median barrier
Shoulder widening
Clear vegetation
Increase friction
FYA
Paint edgelines
Sign retroreflectivity
Safety Edge
Low-cost intersection improvements
Signal backplates
HIGHER COST
HIGHER CRASH REDUCTION
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Cost-Effectiveness Evaluation
§ Gathered data from implemented project evaluations of typical hotspot and systemic countermeasures
§ Assessed cost-effectiveness of each with $10M budget
Hotspot– Add left turn lanes (LTL)– High friction surface treatment– Reconfigure Intersection– Reduce skew and add LTLs– Road diet without resurfacing– Road diet with resurfacing– Roundabout
Systemic– Cable median barrier– Centerline and shoulder rumble strips– Ramp curve signage– Curve warning signage (chevrons)– Low-cost STOP-control treatments– Low-cost signal treatments
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Research Findings
Countermeasure Data Hotspot Systemic
Average Cost (scale to budget) $9,901,286 $9,998,000
Average Project Benefits $226,519,265 $700,219,396
Average Benefit-Cost Ratio (BCR) 23.0 70.0
Average Cost per Mile/Site $20,000 $750
Weighted Average CMF 0.73 0.90
1. Systemic uses lower unit-cost treatments, scales more efficiently
2. Systemic more cost-effective on average
3. Hotspot countermeasures were more effective at each site
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Hypothetical Example: Hotspot vs. Systemic
Nbreakeven=Costhotspot Costsystemic
CCKABCO CMFsystemic CMFhotspot
Nbreakeven =$20,000 $750
$56,000 0.90 0.73 = 2.0 crashes
§ At locations above breakpoint, consider seeking higher crash reductions at a higher cost as well as low-cost, efficient countermeasures.
§ Below breakpoint, consider only low-cost systemic or systematic treatments.
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Hypothetical Implementation Scenarios
§ Track and evaluate implemented projects more completely
§ Develop more CMFs for systemic and systematic treatments
§ Apply decision making beyond only two countermeasures
§ Expand research to include more types of treatments and confidence intervals
§ Contrast results with other allocation methods
§ Assess approach time savings or improved project effectiveness
§ Develop more DDSA tools for program investment
§ Explore hotspot/systemic hybrid project implementation
Future Research Needs
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Tim Harmon, P.E. | tharmon@vhb.com | 919.741.5542www.vhb.com
Thanks to:FHWA Office of SafetyNew Hampshire DOT
EDITORIAL PATTERNS IN BICYCLIST AND PEDESTRIAN CRASH REPORTINGEVAN IACOBUCCI | RUTGERS KELCIE RALPH | RUTGERS CALVIN THIGPEN | ARIZONA STATE TARA GODDARD | TEXAS A&M
SEPTEMBER 24, 2019
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Media Influence
Agenda Setting Framing
Research Questions
Who gets blamed for bicycle and pedestrian crashes?
To what extent do articles frame crashes as a public health issue?
Data and Methods
Local U.S. news articles
Automated search by keyword
200 articles:
100 bicycle
100 pedestrian
Data and Methods
Data and Methods
Content analysis
Developed coding guide
Coded articles according to guide
Data and Methods
Tabulated results of coding
Attributing Blame
Agency
Focus
Car or Driver
Counterfactuals
Is there an agent acting in the crash?
Yes:
“… a vehicle that was turning left from Palm hit one of the riders.”
No:
“…a man on a bicycle was hit.”
Agency
Focus
Counterfactuals
Car or Driver
Agency
Focus
Counterfactuals
65% Agentive 35% Non agentive
Car or Driver
Counterfactuals
Focus
Agency Upon which actor does the sentence focus?
“… a bicyclist suffered major injuries when she was hit by a car…”
“… an SUV driver fell asleep and fatally struck a pedestrian…”
“… a vehicle that was turning left from Palm hit one of the riders.”
Car or Driver
Agency
Focus
Counterfactuals
73% VRU 11% Driver 13% Vehicle
65% Agentive 35% Non agentive
Car or Driver
Focus
Counterfactuals
Agency If mentioned, does the sentence refer to a driver or a vehicle?
“… a vehicle that was turning left from Palm hit one of the riders.”
“… an SUV driver fell asleep and fatally struck a pedestrian…”
Car or Driver
Agency
Focus
Counterfactuals
73% VRU 11% Driver 13% Vehicle
19% Driver 81% Vehicle
65% Agentive 35% Non agentive
Car or Driver
Agency
Focus
Counterfactuals
Were there counterfactuals in the article?
“The pedestrian was not in a crosswalk, he was wearing dark clothing and it was raining…”
“… the victim was struck after he darted into the path of a GMC Yukon.”
Car or Driver
Agency
Focus
Counterfactuals 48% of articles include at least one counterfactual
73% VRU 11% Driver 13% Vehicle
19% Driver 81% Vehicle
65% Agentive 35% Non agentive
Car or Driver
Agency
Focus
Counterfactuals
>1/3 of the time, no one is portrayed as responsible
The focus is overwhelmingly on the VRU
The VRU is injured by an inanimate object, not a person
The VRU could have avoided injury if they acted differently
Car or Driver
Negligent Complicit
Responsible
Neutral Blameless
(If even mentioned)
Negligent Complicit
Responsible
Neutral Blameless
(If even mentioned)
Blaming the Victim
Overall Framing
Thematic Elements
Incident Term
Public Health Framing
Overall Framing
Thematic Elements
Incident Term
Thematic:
“Boy struck in hit-hit-and-run uninjured, but road’s safety called into question”
Factual:
“14 year old boy riding bicycle hit, killed”
6% Thematic 97% FactualOverall Framing
Thematic Elements
Incident Term
Overall Framing
Thematic Elements
Incident Term
Does any of the article acknowledge a broader theme or link?
“The accident happened … along a long stretch of residential road that’s marked with a 25 mile-per-hour speed limit. According to neighbors, that limit is often overlooked.” (296)
“A national report released earlier this month found Arizona has the highest rate of pedestrian deaths in traffic accidents in the country, based on data from 2017.”(74)
Overall Framing
Incident Term
6% Thematic 97% Factual
8% Number of Crashes
7% Road Design
2% Transportation
Context0% ExpertsThematic
Elements
Overall Framing
Incident Term
6% Thematic 97% Factual
8% Number of Crashes
7% Road Design
2% Transportation
Context0% ExpertsThematic
Elements
Overall Framing
Thematic Elements
Incident TermIncident Term
What word(s) did the article use to refer to the crash?
Overall Framing
Incident Term
6% Thematic 97% Factual
8% Number of Crashes
7% Road Design
2% Transportation
Context0% Experts
47% “Accident”
21% “Incident”
11% “Collision”
Thematic Elements
45% “Crash”
Overall Framing
Incident Term
6% Thematic 97% Factual
8% Number of Crashes
7% Road Design
2% Transportation
Context0% Experts
45% “Crash”
47% “Accident”
21% “Incident”
11% “Collision”
Thematic Elements
Overall Framing
Thematic Elements
Incident Term
Facts are presented about individual incidents; rarely linked
Thematic elements are rarely included, particularly expert voices
Use of “crash” and “accident” are about equal
Egregious InstancesReferring to crash as an “accident”, even when the driver has been arrested and charged with crimes for causing it
Explicit denial of connection between strings of crashes
Describing the cyclist/pedestrian as crashing into the car, with no explicit evidence of that sequence
Describing pedestrians as not using crosswalks, but failing to mention the absence of such features where the crash took place
Isolated incidents Systematic problem
Connect the dots?
“POLICE SAY A 46 YEAR OLD MALE WAS WALKING IN THE SLOW LANE OF SHADELAND WHEN HE WAS STRUCK BY A CAR.”
“POLICE SAY A 46 YEAR OLD MALE WAS WALKING IN THE SLOW LANE OF SHADELAND WHEN HE WAS STRUCK BY A CAR.”
Followup: An Experiment
Pedestrian-focused language incurs more blame, less support for systemic solutions
Thematic framing decreases blame on both pedestrians AND drivers
Thematic framing increases support for systemic solutions (e.g. infrastructural improvements)
Recommendations
Include humanizing elements when possible
Be aware of the relationship between grammatical choices and perceived blame (hammer)
Frame crashes with a public health focus!
Planners and practitioners: Prepare a statement
While I am unfamiliar with the details of this specific crash, I can say that this is not an isolated incident. Today’s crash is just the most recent in an epidemic of crashes that claim the lives of thousands of Americans each year. To meaningfully reduce traffic fatalities, we need to address the common denominator: road design.
Our current road network prioritizes vehicle speed and flow at the expense of all other road users. We can save lives, like the life of [victim’s name], by making common-sense changes to our road network.
(Ralph, Iacobucci, Thigpen, Goddard 2018)
An Experiment
Questions:
Do editorial patterns affect how readers apportion blame for a crash?
Do editorial patterns influence readers’ support for various solutions for improving road safety?
Hypotheses:Driver-focused text will cause less pedestrian and more driver blame
Thematic frame will:
Cause more support for pedestrian infrastructure
Decrease support for educational campaigns that focus on the actions of the pedestrian
Constructed a survey instrument
Sampled participants via Prolific.ac
Data and Methods
Data and Methods
Three versions of hypothetical coverage:
Pedestrian-focused
Driver-focused
Thematically framed
Data and Methods
Measured differences between groups
Increase, then decrease in blame on driver
Consistent decrease in pedestrian blame
Public health frame causes jump in “Other” as cause
0%
10%
20%
30%
40%
50%
60%
70%
The driver The person walking Other
Share of blame attributed to driver, pedestrian, or "other" based on article version seen by respondent
Ped-focused Driver-focused Thematic frame
Ped-focused and driver-focused nearly equal in terms of support
Thematic framing causes huge increase 50%
55%
60%
65%
70%
75%
80%
85%
90%
95%
100%
Ped-focused Driver-focused Thematic frame
Support for infrastructure changes
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Editorial Patterns Affect Perception
A conceptual framework and building blocks for regional transportation collaboration: a regional safety coalition case
J A N I L L E S M I T H - C O L I N , P H D, P EC I V I L A N D E N V I R O N M E N TA L E N G I N E E R I N G
S O U T H E R N M E T H O D I S T U N I V E R S I T YS E P T E M B E R 2 4 , 2 0 1 9
Agenda1. Motivation and context2. Goals and objectives3. Literature review and conceptual framework4. Case study: regional safety coalitions5. Survey instrument and results6. Performance typologies and building blocks7. Closing remarks
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2
MAP-21/FAST ACT emphasized increased coordination and collaboration
Efforts by the FHWA and AASHTO to deploy innovations that promote collaboration
Inclusion of ‘external collaboration’ in the transportation performance management framework (TPMF)
Ongoing efforts by states and MPOs to develop and implement strategic highway safety plans and local road safety plans requiring collaboration with the 4Es*
Performance Contextsafety planning
Motivation and Context
*4Es = education, enforcement, emergency services, and engineering
Key DefinitionThe Federal Highway Administration (2004) characterized regional
transportation collaboration (RTC) as….....
“the deliberate, continuous, and sustained activity that takes place when transportation agency managers and officials responsible for daily operations
work together at a regional level to solve operational problems, improve system performance, and communicate better with one another.”
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Goal and Objectives
Objective 1: Integrate hitherto disparate bodies of knowledge about collaboration in the literature, to support ongoing efforts to systematically improve regional collaboration within a performance-based context.
Objective 2: Develop a conceptual framework linking regional transportation collaboration and performance outcomes.
Objective 3: Identify building blocks for high-order performing regional transportation collaboration relationships.
Objective 4: Offer implementation guidance to practitioners working to improve performance outcomes through collaborative partnerships.
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Goal: To provide a conceptual framework and analytical tools to support RTC implementation in a performance-based context
Literature Review
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§ Collaboration and performance should be viewed as interlinked constructs
§ Successful collaboration is the result of internal and external enablers
§ Collaboration measures can be result focused, process focused, or relationship focused
Research Gaps and Opportunities
§ Investigate collaboration in the safety planning context § Identify strategies to improve
performance through an explicit focus on collaboration§ Identify building blocks and
dimensions of collaboration that support performance goals
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Research Opportunities
Transportation practice has not made the leap from identifying dimensions of collaboration to establishing linkages between collaboration and performance
Little effort to identify building blocks for collaboration that support higher-order levels of performance
Research Gaps
High
Low
Internal EnablersDynamics Structure
Governance
External EnablersResourcesTools/Data
Collaborative strategies
System Context
Inter-organizationalEffectiveness
EfficiencyReputation
System - Safety Change in
fatalities/serious injuryper vehicle miles
travelled
How are collaboration and performance linked?
PerformanceCollaboration
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High
Medium
Low
Collaboration-Performance Framework
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System Context and Drivers
Structure Governance Resources
General environment in
which collaborations are
embedded
Vertical components, structural
arrangements, and coordinating and
monitoring activities that must occur for
collaboration to survive
Coordinating and monitoring
activities used by the collaboration
and horizontal components of
the group
Conditions available for
sustaining and implementing collaboration
Impact pathwayGeneral
environment of support and
reduced constraints
Impact pathwayFormalized rules and procedures within a
flexible structure
Impact pathwayStrong or inclusive
governance centralized vs. decentralized governance
Impact pathwayJoint or shared
resources; diverse resource
opportunities
Collaboration Dimensions
Vision: To reach destination zero deaths on Louisiana roadways
Mission: To reduce traffic crashes and fatalities through widespread collaboration and an integrated approach
Award-winning: Award for “advanced partnerships and the use of data-driven solutions” to achieve performance-driven goals
Collected ‘perceptions’ about coalition collaboration and performance - 5-point Likert (SA to SD)
Collaboration and performance questions developed based on broad review of literatureSurvey administered to approximately 450 coalition members107 responses received (state, local, and citizen respondents; all 4Es represented)Interviews held: 8 regional safety coalition coordinators, 2 statewide leaders, and 1 former regional safety coalition coordinator
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Regional Transportation Collaboration Survey
RTC Survey Results
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Survey response distributions calculated and weighted
Collaboration scores calculated for each coalition
Performance scores calculated coalition
For each coalition: scores benchmarked and categorized (high, medium, low )
Performance-Collaboration Typology
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4 performance-collaboration typologies revealed
Building Blocks1. A set of Foundational, Tier 1, and Tier 2, building blocks was defined2. Building blocks were revealed through a rank ordering of survey responses3. Represent the set of characteristics needed to achieve high-order levels of
collaboration and performance
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High performer building blocksAbove average building blocks
Highperformers
Average performers
Emerging performers
Focus on relationship buildingImprove meeting productivityMeet consistentlyPrioritize data access and useCoordinate communicationDeliver a consistent message
Operate formally Meet consistentlyBroaden decision-making coreShare learning and expertiseRely less on coordinator
Above averageperformers
Improve working relationshipsAccess tools and strategiesShare transportation information and data Increase reliance on coordinator
HHH
LLL
Performance Typology Building Blocks
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HHH
Performance-Collaboration Ladder
Building Blocks – Coordinator FeedbackHHH Building Blocks Ranking Coordinator Interview Comments
Place an emphasis on building relationships (governance)
1 Have the right relationships and the right partners at the table; weed out the ones that you don’t need; develop long-lasting relationships with law enforcement education, EMS, etc...so that they continue on
Coordinate communication (strategy)
2 Have open lines of communication in order to share information and support relationships
Deliver a consistent message (strategy)
3 Say things with clarity and simplicity; have a consistent message
Accomplish what is necessary during meetings (structure)
4 Stay on track and accomplish what is needed to move forward
Use common procedures and plans (strategy)
5 From state level – use standards that come downFrom local level - grass roots communication and relationship building
Meet on a consistent basis (structure)
6 Meet when you need to meet, and not just for the sake of meeting
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System Context Findings
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AgeHigh performer
coalitions were of different ages
Coordinator Stability
High performer coalitions had
coordinator stability
Coalition MeetingsAverage performer
coalitions do not meet as regularly as a full coalition and in their sub-committee
groups
MOU/By-lawsHigh performer
coalition with highest effectiveness score
had an MOU/By-laws
Meeting Rotation
Emerging coalitions did not rotate
meeting locations
Virtual MeetingsAbove average performer
coalitions allowed for virtual participation
Private FundingHigh performer and above
average performer coalitions actively pursued
private funding
Contributions
1. Develops a performance-based conceptual framework for regional transportation collaboration
2. Identifies building blocks available for strengthening regional transportation collaboration
3. Outlines an approach to link coalition performance (short-term output) to system performance (long-term outcome)
4. Investigates collaboration practices that can support local road safety plan and SHSP development
1. Integrates disparate bodies of literature to support the implementation of regional transportation collaboration
2. Links performance and collaboration and offers guidance for progressively improving performance
3. Creates the performance-collaboration ladder4. Reinforces “central tenants” for collaboration
identified in previous research
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Body of Knowledge Practice
Limitations1. Small-N comparative case analysis
a. Generalizability of results less a priority than developing an understanding of phenomena in given context.
2. Reliance on stakeholder perceptions for coalition performance and collaboration data
3. Benchmarking of coalitions against one anothera. Highest performing coalition could likely be the lowest performing coalition in another
sample
4. Researcher bias in coding decisions 5. Key in such research is transparency, verification, cross-validation of results
a. Cross-validation steps incorporated into research design – multiple data collection instruments
b. Feedback loops - consultation with regional coordinators, statewide staff, and research center staff
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ReferencesCurrent Work
Smith-Colin, J., Amekudzi-Kennedy, K., and Kinsley G. Development of Building Blocks for a Collaboration-Performance Conceptual Framework: Application in an Embedded Case Analysis of Regional Safety Coalitions, Transportation Research Part A: Practice and Policy (Under Review).
Other Sources
RTOCC (n.d.). FHWA-HOP-08-001: The Collaborative Advantage: Realizing the Tangible Benefits of Regional Transportation Operations Collaboration (A Reference Manual) Federal Highway Administration – Office of Operations, Washington D.C., 2007. https://ops.fhwa.dot.gov/publications/benefits_guide/index.htm
Emerson, K, T. Nabatchi, and S. Balogh. “An Integrative Framework for Collaborative Governance.” Journal of Public Administration and Research Theory, Vol. 22, Issue 1, 2012.FHWA 2012.
Meyer, M.D., Campbell, S., Leach, D., and Coogan, M. (2005). Collaboration: The Key to Success in Transportation. Transportation Research Record: Journal of the Transportation Research Board, Volume 1924, pp 153 – 162.
Smith-Colin, J., and Fischer, J., (2016). “Promoting and Measuring Collaborative Effectiveness to Achieve Performance-Based Goals: Conceptual and Operational Frameworks to Support MAP-21 Implementation.” TRB Session 583, paper: 16-3818.
Smith-Colin, J., Fischer, J., Akofio-Sowah, M., and Amekudzi-Kennedy, A., (2014). “Evidence-Based Decision Making for Transportation Asset Management: Enhancing the Practice with Quality Evidence and Systematic Documentation,” Journal of the Transportation Research Record, No. 2460, pp 146-153.
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THANK YOU!
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Today’s Participants• Jaeyoung Lee, Central South University,
jaeyoung@knights.ucf.edu
• Scott Matthews, Carnegie Melon University, hsm@cmu.edu
• Tim Harmon, VHB, tharmon@vhb.com
• Evan Iacobucci, Rutgers, evan.iacobucci@rutgers.edu
• Janille Smith-Colin, Southern Methodist University, jsmithcolin@smu.edu
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