Utilize and Abuse of Crash Data in Roadway Access Management

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Utilize and Mishandle of Accident Information in Roadway Access Administration. A Workshop at the National Access Administration Gathering Baltimore, Maryland July 13, 2008. Teacher Group. Educator group presentations David Plazak Zach Hans James Sun Eric Fitzsimmons. Workshop Review.

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Utilize and Abuse of Crash Data in Roadway Access Management A Workshop at the National Access Management Conference Baltimore, Maryland July 13, 2008

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Instructor Team Instructor group presentations David Plazak Zach Hans James Sun Eric Fitzsimmons

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Workshop Overview The theme of this workshop was proposed by participants at the Park City, Utah National Access Management Conference in 2006 Persons who recommended the subject showed that they might want to have the capacity to utilize accessible crash information to assess get to administration arranges and to market get to administration as an approach to enhance security This workshop has been intended to be extremely "hands-on"— members ought to have the capacity to promptly apply a hefty portion of the ideas they learn

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Participant Introductions Brief member presentations Your name Your contribution with get to administration We'd get a kick out of the chance to attempt to get a decent blend of level of involvement with the tables for the intelligent activities

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Parts of Today's Workshop plan: Part one: Time: 1:00 PM to 2:20 PM Workshop presentation and destinations Key get to administration wellbeing ideas, including crash decrease calculates A hands-on issue: settle a "get to administration mess" where all tables have finish information to work with Part two: Time: 2:35 PM to 4:30 PM Data quality contemplations Some information issues that may be experienced Hands-on issue #2: Fix a "get to administration mess" where tables have distinctive levels of information culmination and quality to work with Workshop wrap-up

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Workshop Objectives Provide the members with a decent working information of: Crash sorts related with absence of sound get to administration Typical crash diminishment variables related with get to administration medications Crash information and potential shortcomings of crash information

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Your Interest in Attending this Workshop? How about we circumvent the room rapidly and order a rundown of things you'd most get a kick out of the chance to learn amid this workshop Each table will give one new thought, then we'll proceed onward to the following table until we come up short on thoughts

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Data-Driven Access Management Access administration medications and arrangements ought to be specifically fixing to quantifiable destinations, for example, crash rate or crash cost diminishment Access administration medicines proposed ought to be fitting given the sorts of accidents and example of accidents being knowledgeable about a hall Access administration treatment costs should be reasonable based upon the normal advantages of crash decreases and different targets Stakeholders and leaders must be persuaded that the "pick up" of get to administration is justified regardless of the "agony" Confidence in both past ("before treatment") and expected future crash rates ("after treatment") ought to be high You need to be certain that any medications will create a discernible and positive outcome

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Access Management and Safety Most get to administration related accidents happen on urban and rural blood vessel roadways at rates of 35 to 55 miles for every hour Up to half of all accidents in urban territories are identified with issues of get to (minor open street convergences, activity flag dispersing, garages) Although most get to related accidents happen in urban or rural ranges, get to related crashes in rustic zones have a tendency to be serious crashes because of higher travel speeds Access-related accidents happen at struggle focuses The outline speaks to one crash information point

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Conflict Points Diverging Merging Crossing

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Examples of Conflict Point Reduction Treatments

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Driveway Crash Pattern Left turn developments produce ¾ of all accidents at carports Left turn entering developments create nearly ½ of all accidents at garages Source: Federal Highway Administration

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Common Types of Access Management Traffic flag dividing Marginal get to administration Management of get to highlights at (and past) the roadway right of way line Examples: controlling garage area and least dispersing between garages Medial get to administration Management of get to highlights in the focal point of the roadway Examples: middle sorts and middle openings Separation of turning movement from through movement streams Example: devoted left-turn paths or bays

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Effectiveness of Traffic Signal Spacing Reducing signals from 4 for each mile (1/4 mile dividing) to 2 for every mile (1/2 mile separating) will lessen the aggregate crash rate by up to 50%* (This will likewise significantly affect nature of movement stream amid pinnacle hours) Uniform movement flag dispersing is more secure and more proficient than non-uniform dividing *The hotspot for all crash lessening variables is the National Highway Institute course "Get to Management: Location And Design"

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Effectiveness of Marginal Access Management Treatments Applying complete get to control (e.g. permitting no immediate carport gets to) Reduces crash rates by 40-45% on middle partitioned roadways Managing access thickness (garages per mile) Reducing access thickness by 20-25% can diminish add up to crash rates by 25-40%

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Effectiveness of Medial Access Control Treatments Adding a two-way left swing path to a unified 4 path roadway will lessen crash rates by 20-25% Pedestrian crash rates won't change Adding a non-safe (raised) middle to a unified 4 path roadway will diminish crash rates by 40-45% Pedestrian crash rates will diminish by half

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Effectiveness of Left Turn Lanes or Bays Adding a left-turn sound at a bustling un-signalized urban or rural crossing point may decrease crash rates by up to 70% Adding a left turn narrows at a bustling signalized urban or rural convergence or at a bustling rustic un-signalized crossing point may diminish crash rates by 40-half

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Problem 1: Fix This Mess South Ankeny Blvd., Ankeny, Iowa

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What Do Crash Data Really Look Like?

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Crash Rate Calculation C = Number of accidents over Y years Y = Number of years being assessed Links Nodes (Intersections) M = Hundred million vehicle miles/year (MHVM) for connections M = Million entering vehicles/year (MEV) AADT = Average yearly every day activity

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What's On Your Table … Traffic after some time Crash information tables and outlines Corridor photographs Land Use 22 Laminated base guide Crash information stack delineate An Example Plan …

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Brief Table Reports … What Treatments Do You Recommend?

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Part Two Data quality contemplations Some information issues that may be experienced Hands-on issue #2: Fix a "get to administration mess" where tables have diverse levels of information fulfillment and quality to work with Workshop wrap-up

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Think About It … (to talk about later, on the off chance that we have time) How would you utilize crash information? What is critical to you about crash information? What are a portion of the worries/issues you involvement in utilizing crash information?

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Crash Data Allow Better … Problem Identification Understanding of the issue before bouncing into investigating and planning arrangements Focus on serious crashes as opposed to every single (minor) crash However …

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You Need Good Quality Data The Ingredients Matter: Quality Control

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The Characteristics of Data Quality (The "Six-Pack")

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Crash Data Quality: Timeliness Sometimes crash information are not accessible for quite a long time or even years Varying auspiciousness of various wards can bring about issues for similar examination Time itself is critical – accomplished something change amid the examination time frame? Additionally – the day and age is critical … one year of information are most likely insufficient!

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Crash Data Quality: Accuracy Considering practical range Original Spatial Location Attributes, e.g., seriousness, crash sort, roadway data 1 ST Road SOUTH ANKENY BOULEVARD v

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Crash Data Quality: Completeness Missing information can prompt to a deceptive picture and mistaken conclusions Some crash records have "obscure" or "other" fields Some crash records are missing by and large Variations between purviews (district level, state level) can prompt to errors in relative investigation

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Crash Data Quality: Consistency/Uniformity Across locales Across time Consistent severities

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Crash Data Quality: Integration gives a 'wealthier', more total wellspring of data (e.g., mix with roadway highlights) Double keep an eye on exactness (counting seriousness)

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Crash Data Quality: Accessibility How would you be able to get crash information? How simple is it to get? What shape do you need it in? Continuum: not accessible … exceptional demand w/delay … customary updates … benefit … moment web get to

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Typical Crash Data Issues These may not be obvious to the information client

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Changes in Crash Forms Collision Type Before After Content Addition/disposal of properties gathered Change in definitions (values)

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Changes in Crash Forms, cont. Change in crash frame Crash Rate Crash Rate Year Statewide Site #1 Impacts : Difficult to perform coordinate examinations over investigation period. May bring about precise change in obvious crash execution, e.g. crash diminishment.

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Cartographic (Base Map) Changes Shift, refresh to reference street organize Impact : Challenging to efficiently allocate crash area.

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Location Accuracy How are the accidents found? GPS (where?) Manually determined, in light of strict portrayal LRS, Link-hub, other? What reference systems are utilized? GIS LRS Link-hub

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X Location Accuracy, cont. How do correctnesses differ among area techniques and reference systems? Ex. GPS ±5m v. GIS-based street organize ±10m Crash might be found anyplace inside this region. X Roadway might be exhibited anyplace inside this region. GIS street organize Actual crash area Geocoded crash locatio