Monitoring And Modeling Bicycle And Pedestrian Mode Share: Analysis Of .
Monitoring and ModelingBicycle and PedestrianMode Share:Analysis of Current TrendsDecember 11, 2014Anne WelchChandra KhatriJinwoo SeoRuben Hovanesian
Overview Current Trends and Needs What is being done currently Literature Review Case Studies Recommendations
Current Trends inBicyclist and PedestrianMode Share
Rates of Walking and Bicycling toWorkSource: Modes Less Traveled - Bicycling and Walking to Work in the United States: 2008-2012, ACS Report Issued May 2014
“National bicycle mode share increased from488,000 to 768,000 from 2000 to 2008-2012, a60.8% increase. This increase in the number ofbicycle commuters exceeded the percentageincrease of all over travel modes during thatperiod.” “The combined rate of bicycle commuting for the50 largest US cities increased from 0.6% in 2000 to1.0% in 2008-2012.”Source: Modes Less Traveled - Bicycling and Walking to Work in the United States: 2008-2012, ACS Report Issued May 2014 [Emphasis added]
Bicycle Safety Decreasing2012 Bicycle Fatalities in Motor Vehicle Crashes Nationally: Increased 6% from 2011 762 deaths or 2% of all mode share fatalities Georgia: 17 deaths or 1.4% of all mode share fatalities2012 Bicycle Injuries Nationally: Estimated 49,000 injuries 2% of all traffic crash injuriesSource: Traffic Safety Facts, National Highway and Traffic Safety AdministrationPhoto Source: Fred Askew
Pedestrian Safety Decreasing2012 Pedestrian Fatalities in Motor Vehicle Crashes Nationally: Increased 6% from 2011 4,743 deaths or 14% of all mode share fatalities Georgia: 167 deaths or 14% of all mode share fatalities2012 Pedestrian Injuries Nationally: Estimated 76,000 injuries 3% of all traffic crash injuries Average 1 pedestrian injured every 7 minutesSource: Traffic Safety Facts, National Highway and Traffic Safety AdministrationPhoto Source: Right of Way
Fatalities in Traffic CrashesSource: USDOT, National Highway Traffic Safety Administration, Traffic Safety Facts: 2012 Data
Sources of Injury while BicyclingSource: 2012 National Survey of Bicyclists and Pedestrian Attitudes and Behavior, US DOT NHTSA
Sources of Injury while WalkingSource: 2012 National Survey of Bicyclists and Pedestrian Attitudes and Behavior, US DOT NHTSA
Atlanta Regional CommissionBicycle Network Level of ServiceSource: Atlanta Region Bicycle Transportation and Pedestrian Walkways Plan
Level of Service considerations:Width of outside travel laneWidth of any paved shoulder orbike laneVolume, mix, and speed ofvehicular traffic on the roadwaySources: ARC Bike/Ped Plan and https://www.facebook.com/groups/bikecommutersatl/
Level of Service considerations:Pavement ConditionPresence of on-street parkingSources: ARC Bike/Ped Plan and https://www.facebook.com/groups/bikecommutersatl/
ARC Pedestrian Network LOS“Walking along the Region's roadways, especially theregionally significant roadways that are the focus ofthis Plan (Atlanta Regional Bicycle Transportation &Pedestrian Walkways Plan), is seldom comfortableand is quite often very challenging.”Source: Atlanta Region Bicycle Transportation and Pedestrian Walkways Plan [Emphasis added]
LOS IssuesLack of separations between thesidewalks that do exist and thetraffic on the roads they parallelHigher speeds and volumes ofmotor trafficInconsistent presence of sidewalksSources: ARC Bike/Ped Plan and https://www.facebook.com/groups/bikecommutersatl/
Increased DemandSource: 2012 National Survey of Bicyclists and Pedestrian Attitudes and Behavior, US DOT NHTSA
Currently
Nationally MAP-21 Transportation Alternatives Funding 50% to MPO/TMA 50% to State“The DOT policy is to incorporate safe andconvenient walking and bicycling facilities intotransportation projects” – USDOT Policy Statement,2010But wait! There’s more!
Safer People, Safer StreetsInitiative 2014 Increase Walking and Biking and ReducePedestrian and Bicyclist Fatalities Walk and Bike AssessmentsThe Road Diet GuideHow to Design Safe Bicycling Facilities (Bikesafe)Separated Bike Lane Planning and DesignUpdate to “Resident's Guide for Creating Safe andWalkable Communities” And a lot more
Coming soon: NCHRP 07-19 Methods and Technologies for CollectingPedestrian and Bicycle Volume Data Passive infraredActive infraredPneumatic tubesInductive loopsPiezoelectricRadio beamSource: NCHRP 07-19 UC Berkeley SafeTrec Webinar 2014
GA State Pedestrian & StreetscapeGuidelines State Bike Plan State Ped/Bike Coordinator State HSIP Pedestrian SafetyConsideration Ped/Bike Safety RSA
Atlanta Regional Commission Three Goals1. Illuminate travel patterns in the region2. Determine effective return on investments for facilitytypes3. Create excitements for ped/bike planning! 5-year data collection program to establish baseline By land use and trip type Make funding decisions Website for collected ped/bike count data (2015) Modeling implementation in 15-20 years
Monitoring: Atlanta’s CurrentStateIssues Lack of data on state of bicycle infrastructure in Atlanta Atlanta lacks a standard infrastructure to monitor nonmotorized transportation. Travel demand models does not work without data
Monitoring: Atlanta’s CurrentStateInitiatives from ARC Regional bicycle network that includes on‐road facilities,shared use pathways Pedestrian network focused around major activitycenters Level of service: Mobility for citizens, ancillary benefits Level of pedestrian accommodation Policy and program recommendations that encouragenon-motorized transportation
Modeling: Atlanta’s Current StateIssues No good data, not enough dataInitiatives from ARC Activity Based Model with modules for Pedestrian andBicycle trip modeling Project assessment and project prioritization mechanism Propensity scores obtained for street segments on thenetwork developed New visioning to allow for broader influence
Current Needs Up to date mode-share countsNeed to know location and quality of currentinfrastructureStandardized methodology of data collectionKnow where safety issues existKnow where current and future demand existsDetermine best return on investment
Accounting for Walk andBicycle Trips in PlanDevelopment
Accounting Non-motorized Traffic3. Predictions, planning, recommendations2. Incorporating data in models1. Data collection
Data Needs Weekly, monthly, yearly monitoring Quality of infrastructure and counts Used to generate travel demand models Travel Monitoring Analysis System (TMAS) User characteristics Planned development Asset management System GIS database
Data Collection Methods Survey Obtain user characteristics, behavior Getting baseline information (origin-destination pairs) Manual For short-term counts Validation for automated technologies Automated Required because of unpredictable movements andcontinuous monitoring
Monitoring Methods andTechnologiesSurvey methods: Multimodal surveyOne day surveyPedestrian and bicycle surveyStated preference surveyIntercept surveyBike share surveyingInformation and communication technologies: Inductance loopMagnetometerPressure sensor / pressure mats and pneumatic tubesSeismic sensorsRadar sensorsVideo imaging automated and video imaging- manual reductionInfrared active & passiveManual counts: Only pedestrians, only bicyclists, or combination Integrated with motorized vehicle counts
Monitoring Technology Selection*Source: TMG, 2013
Monitoring Technology Selection Zelt Inductive Counting System Used for multi-modal highways with bike lanes, bikeboulevards, bike/bus lanes, bike paths, and bike trails
Monitoring Technology Selection Pyro Counting System Passive infrared pyro-electric technology and highprecision lens technology Detects change in temperature
Monitoring Technology Selection Multi-Integrated Counting System
Alternative Methods: GPS andBluetooth Mobile Applications: Commute Warrior: Second by second travel activity. Robust , can track multi-modaltrips Cycle Tracks: Monitors bicycling trips for travel demand model. SFO, Portland,Austin Cycle Atlanta: Monitoring for planners, ARC to provide better services andinfrastructure for commuters in Atlanta. Cost effectiveHelpful for obtaining origin-destination pairsUser characteristics and behaviorBias due to small sample
Monitoring Methods ComparisonAutomatic CountsBenefitsDrawbacks- Reduced Labor Cost- DurableManual Counts- User-characteristics- Higher accuracy onshort-term counts- Setting needs care- Labor intensive- Hard to extract behavior - Limits number of- Not all counts bothcount locationsSuggestions - Should not interferewith pedestrians andbicyclists- Integrating withexisting motor vehiclecountsSurveys- Detailed user-characteristics- Baseline information (origins- destinations)- Pre-planning surveydistribution- High labor costs- Smaller sample size- Simple design- Should be completed quickly
Data Collection Issues andFindings Poor quality of data for user characteristics,safety/crash Lack of data sources/inventories Analysis on 29 cities by FHWA Automated methods cheaper Manual counts, surveys invoke hidden costs: expensive TMG, 2013 Very little known about best and cheapest methods
Data Collection: Suggestions fromTMG, 2013 Guidelines: Improving the state-of-the-practice formonitoring Data format to store the counts effectively Framework : Travel Monitoring Analysis System (TMAS)for national level analysis Strategic areas for monitoring Sample bias should be considered before concludingresults Monitoring on lower-functional class roads Error rates of automated technologies are not fullyknown
Modeling
Modeling: Generic ModelingApproach Suggestions for modeling bicycling trips:1. Development of base-year and future-year bicyclingnetworks2. Base-year bicycle trip tables.3. Assignment of base-year bicycle trips to the bicycle network.4. Re-estimation based on actual roadway counts.5. Factoring of base-year to develop future-year trip tables.6. Assignment of future-year trips to the future-year bicyclenetwork. Suggestions for modeling pedestrian trips:1. Trip generation characteristics, as a function of land use type.2. Propensity between land use activities: function ofconnecting pathway attributes.3. The trip exchange patterns resulting from the above.4. Assignment of these trips to alternative network pathways.
Modeling: Issues Sparsity: Limited data Quality of predictionsPedestrian Mobility Mining with MovementPatterns, Liebig et al. (2012) Sensitivity to sensors Status of bikes and pedestriansat a given time and day System level constrains:Parameter tuning fromplanners, investors etc. Number of bike stations,locationsSensing and Predicting the Pulse of the Citythrough Shared Bicycling, Froehlich et al. (2009)Strategic design of public bicycle sharing systemswith service level constraints, Lin et al. (2011)
Modeling: Techniques, Use Cases(NCHRP)Modeling ApproachTour Generation/ Mode SplitGIS-Accessibility ModelTrip-Based ModelEnhancementCharacteristics- Simple/complex tour generation for trip purposes: socio-demographic,land use, local & regional accessibility- Mode choice (walk, bike, transit, auto): socio-demographics, land use,local & regional accessibility- Fully detailed walk and bicycle networks: physical attributes affectimpedance- Uses GIS layering to create accessibility scores for walk, bike, transit,and auto.- Links mode choice with accessibility scores at trip origin anddestination- Estimates mode share at block level- Builds walk trip table (but does not assign)- Highly visual presentation- Strategic changes to traditional four step TAZ model to improvesensitivity to land use and non-motorized travel- Sensitizes auto ownership and trip generation to land usecharacteristics- Performs pre mode choice to distinguish inter versus intra-zonal trips- Performs mode choice separately for intra zone(drive alone, sharedride, walk) and inter zone (drive, shared ride, transit, walk, bike) travelSourceSeattleArlington,VASeattle
Modeling: Techniques, Use Cases(NCHRP)Modeling ApproachPedestrian Demand ModelsBicycle Route Choice ModelsFacility-Demand ModelsCharacteristics- Modified four step approach focused on estimating walk trips- Walk trip generation for several purposes at PAZ level- Creates walk trip tables, assigns trips to walk NetworkSourcePortlandPedestrianModel (PSU)- Models built from GPS recorded trip data to predict choice of routefor bicycle riders- Quantifies importance of route characteristics (type facility, gradient,directness, traffic exposure)San FranciscoCounty, PortlandState University- Separate bicycle and pedestrian direct demand models- Predict PM peak hour bicycle demand based on employment density,proximity to bike facilities, land use mix, and intersections- Predict PM peak hour walk demand based on employment density,proximity to shopping, PM bus frequency, and traffic speedsSanta MonicaBicycleand PedestrianModels
Data Requirement for Different Models
Modeling: Recommendations Relationship betweennetwork quality & commuting Real-time: Minutesbefore predictions for bicyclistsand pedestriansThe Missing Link: Bicycle Infrastructure Networksand Ridership in 74 US Cities, Schoner et al. (2014)Urban Cycles and Mobility Patterns: Exploring andPredicting Trends in a Bicycle-based PublicTransport System, Kaltenbrunner et al. (2009)
Case Studies
Case Studies: Methods ofMonitoring and Modeling San Diego Chicago MinneapolisSource: Google Maps
San Diego Bike Counts Project Active Transportation Research Manual and Automated Counts Automated Counting Systems: Zelt Inductive Loop Counting System Pyro Counting System Multi-Integrated Counting SystemSource: City of San Diego Bicycle Master Plan
San Diego Using the Data Understand active travel behavior Help with planning process for bicycle and pedestriantrips Support the research in Active Transportation Research
San Diego Modeling Method Two types of travel Intra-community: Trip attractor and trip generator models Inter-community: Gravity model Intra-community Sum of trip attractor and trip generator scores Inter-community Assumes activity centers close to each other willgenerate higher demand for travel
San Diego Trip AttractorSource: City of San Diego Bicycle Master Plan
San Diego Trip GeneratorSource: City of San Diego Bicycle Master Plan
San Diego asdfSource: City of San Diego Bicycle Master PlanSource: City of San Diego Bicycle Master Plan
San Diego Trip Generator ModelSource: City of San Diego Bicycle Master PlanSource: City of San Diego Bicycle Master Plan
Chicago Chicago Department of Transportation Created Chicago Complete Streets Program Manual Counts Monthly Quarterly
Chicago Monthly 6 locations each month (depending on planned bicycleprojects, existing bicycle facilities, and ridership) Weekday morning (7am to 9am) and evening (4pm to 6pm)peaks Quarterly Spring, Summer, and Fall Weekday morning and evening peaks 20 locations Saturday (12pm to 2pm) 25 locations
ChicagoSource: Chicago Bike Monitoring Report
Chicago Using the Data Measure seasonal changes in ridershipUnderstand the impacts of bicycle facilitiesLocate frequently used routesCalculate mode sharePerform crash analysisEvaluate performance of new bicycle facilities
Chicago Modeling Method Model existing bicycle demand Local and National studies used 2009 Chicago Regional Household Travel Inventory 2009 National Household Travel Survey
Chicago Modeling MethodSource: Chicago Bike Monitoring Report
Chicago Modeling Method Chicago Regional Household Travel Inventory US Census National Travel SurveySource: Chicago Bike Monitoring Report
Minneapolis Minneapolis Public Works Department Partnered with Transit for Livable Communities Manual and automated counts Bicycle Counts: 30 locationsPedestrian Counts: 23 locationsSecond week of September (Tuesday, Wednesday, or Thursday)3 different counts: 2 hour counts 12 hour counts 24 hour counts Over 300 sites counted once every three years
Minneapolis Manual Counts 2 hour counts 4pm to 6pm 12 hour countsSource: Minneapolis Non-Motorized Traffic Counts: Operations and Methodology 6:30am to 6:30pm Modeling method used to estimate traffic for 24 hourperiod Automated Counting System 24 hour counts 3 locations with inductive loops Only detects bicycles
Minneapolis Using the Data Measure annual changes Understand significance of streets and trails for nonmotorized travel Develop crash rates Determine whether goals are being met
Minneapolis Modeling Method Two assumptions: 75% of bicycle and pedestrian traffic between 6:30am and6:30pm 20% of bicycle and 18% pedestrian traffic between 4pm and6pm Still not a good model Proposals for improvements Add more 12 hour count locations Video data collection for 24 hour counts
Minneapolis Modeling MethodSource: Minneapolis Non-Motorized Traffic Counts: Operations and Methodology
Final RecommendationsHow to become a World Class City for Pedestrians and Cyclists
Is this necessary? Is it worthwhile? National trend towards improving pedestrian andbicycle safety and mobility Federal requirements for funding Advocacy and community demand Lack of sufficient existing infrastructure
How do we get there?PolicyDataMethodology
PolicyShows political emphasis andguidanceState/MPOrequirement forcities to have aMaster Ped/BikePlanState requirementfor more robustconsideration ofped/bikeaccommodationon all stateprojectsChangingfrom an “FYI”approach to“shall”approachState Guidelinesbe referenced inHDM asrequirementProvide design standards andsafety analysis guidelinesState/MPO shouldadopt NACTOguidelinesState/MPOrequirement forped/bike RSA forprojects meetingpre-determinedthreshold crashlevels
DataInfrastructure inventoryAssetManagementSystemGIS databaseTravel BehaviorMPO shoulddevelop officialdata collectionpolicy and formatMPO requirementfor local agenciesto collect ped/bikecounts for anyproject wherevehicle counts arebeing collectedSafetyMonitoringRevised State andPolice Reportingmethods toinclude ped/bikecrash information
MethodologyModelingUse ActivityBased Modelwith �� forprioritizationConsiderpermanentcountingdevices ationandprioritizationmethods forfunding
Thank you!Questions?
References Traffic Monitoring Guide, FHWA, 2013 National Cooperative Highway Research Program,Transportation Research Board, 2014
1. Development of base-year and future-year bicycling networks 2. Base-year bicycle trip tables. 3. Assignment of base-year bicycle trips to the bicycle network. 4. Re-estimation based on actual roadway counts. 5. Factoring of base-year to develop future-year trip tables. 6. Assignment of future-year trips to the future-year bicycle network.
accomplishes this through planning, engineering and implementing bicycle facilities, including bicycle parking, and educating the community and agencies about bicycle transportation. Livable Streets is responsible for reviewing and fulfilling short-term bicycle parking requests and coordinating and assessing bicycle parking with other City .
Bicycle Program office, striped 28 miles of bicycle lanes, updated the City s Bicycle Master Plan, installed over 650 bicycle parking racks and 250 bicycle route signs, and i
3. Cycleway facility design 18 3.1 Bicycle path (one-way) 20 3.2 Bicycle path (two-way) 30 3.3 Quietway 40 3.4 Shared path 48 3.5 Shared zone 52 4. Public bicycle parking 56 4.1 Integrated bicycle parking 56 4.2 Types of public bicycle parking 56 4.3 Key locations for public bicycle
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