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Smarter Travel Update Presentation_ECIA, Jule Transit Copyright 2014 City of Dubuque Action Items # 1. ITEM TITLE: Smarter Travel Update Presentation SUMMARY: East Central Intergovernmental Association (ECIA) and City staff will be making a presentation on the IBM Smarter Travel Project. SUGGESTED DISPOSITION: Suggested Disposition: Receive and File; Presentation ATTACHMENTS: Description Type Smarter Travel Update Presentation-MVm Memo City Manager Memo Staff Memo Staff Memo Presentation Supporting Documentation THE CITY OF Dubuque UBE I erica .i Masterpiece on the Mississippi 2007-2012-2013 TO: The Honorable Mayor and City Council Members FROM: Michael C. Van Milligen, City Manager SUBJECT: ECIA and City Staff Presentation on IBM Smarter Travel Project DATE: July 25, 2016 East Central Intergovernmental Association and City staff will be making a presentation on the IBM Smarter Travel Project. // S4-Z�2=" Micliael C. Van Milligen MCVM:jh Attachment cc: Kelley Deutmeyer, Executive Director, ECIA Chandra Ravada, Director of Transportation, ECIA Barry Lindahl, City Attorney Cindy Steinhauser, Assistant City Manager Teri Goodmann, Assistant City Manager Candace Eudaley, Transit Manager Maurice Jones, Economic Development Director THE CITY OF Dubuque AII-Americ11 a City DUB E i r Masterpiece on the Mississippi 2007.2012.2013 TO: Mike Van Milligen, City Manager FROM: Candace Eudaley, Transit Manager CC: Maurice Jones, Economic Development Director RE: ECIA and City Staff Presentation on IBM Smarter Travel Project DATE: July 22, 2016 PURPOSE To provide an update on the IBM Smarter Travel Research Project including optimization methodology, volunteer recruitment strategy and coordination with Transit Division staff. BACKGROUND In 2010, IBM partnered with the City of Dubuque, East Central Intergovernmental Association (ECIA) and Dubuque Metropolitan Area Transportation Study (DMATS) to create the Smarter Travel Project Team. In 2011, Iowa DOT awarded funding from the Iowa Clean Air Attainment Program (ICAAP) to DMATS to fund 80% of the Smarter Travel Project. The goal of the projects is to study people's movements, analyze transit and transportation systems challenges in Dubuque, and improve and optimize their routes. The original Smarter Travel Project included three components, 1.) Data Collection, 2.) Data Analysis & Route Optimization, and 3.) Implementation of the "Midtown Loop" and "Nightrider" pilot routes. ECIA staff worked for three years with FHWA and Iowa DOT to develop a project scope for the research components that would meet both Federal and State requirements. During this time, all parties involved determined that it would be best to split component three into a separate contract and begin implementing the pilot routes using data from the Jule's intelligent transportation system (ITS) equipment. Iowa DOT approved the contract for the new pilot routes, Midtown Loop and Feeder, in November 2013, with the understanding that as the Data Collection and Route Optimization components of the project move forward, Jule routes would be evaluated and potentially modified based on analysis of the results. Jule staff redesigned routes based on data available from the new Jule ITS system and ridership patterns. The Jule implemented the Midtown Loop and Feeder routes in January of 2104 with dramatic increases to ridership seen over the next two years. The Data Analysis and Route Optimization components of the Smarter Travel project is underway and divided into five phases: Phase 1 o Data analysis for sample size, online survey for recruitment, travel diary to collect origin/destination information, determining recruitment sample size, and developing the public engagement and recruitment plan. o Developing and testing IPhone and android applications to collect origin/destination information and development of transit route optimization process. Phase 2 o Volunteer recruitment based on demographic data. Phase 3 o Create O/D from traditional survey methods, smart phone data and Airsage data. Phase 4 o Screenline testing of O/D using DMATS travel demand forecast model. Phase 5 o Transit route optimization using Origin / Destination (O/D) from traditional methods, smart phone and Airsage data. RECOMMENDATION/ACTION This memo and presentation are for information purposes. Additional information and recommendations will be made during the FY18 budget process. Smarter Travel • Dubuoue Smarter Travef Year I Update THE QN OF S M A R T E R DuB E C� DUBUQUE ) L Masterpiece on the Mississippi Smarter Travel . : , . t jBhv XPi c I Ep w i 7 A � � n z. City of Dubuque Transit in 2 lee, Nz i • tr !x k }{yp A Y�,H � L,�#�i� �13•.y i i,.. .'n fE f`_w ' qCP s q g�`�`� �` ,�' q �: AU1 "a.=(. t • r �.. }aln �j�s\ i�k y� ?o �rtB,F $ii � ✓'' e�� se 33' . . ', ' °r � - a � A z I-"aq � k f APF Smarter Travel • Impact of Route changes on Jule Transit _ _ _ _ _ _ _ -> Increase in Length of the trip & t inot designed to action areas Incre se i Bigger operating head ways Less co is Reliabilit I I I I I I Less Frequency Negative Few funds to Perception improve system I I I I II I I I I Decrease in Reduction in Less Fare Box Ridership Federal Funds a Smarter Travel • Process to Improve Jule Transit Plan What to do How to do Implement Contrast Supply vs Demand Time of Day Census Data Redesign Optimize services by Transit Routes time of day and Traditional activity Optimize Stop Surveys Placement Activity Based O ertrations Online surveys Design new P routes Measure unmet Data gathering demand New Service Create new using marketing plan Suggest new area & Demand technology bus routes --------- -------- --------- ----------- ----- ----- Smarter Travel • Project Description • Project Goal • Develop, test, and validate an integrated platform to leverage data captured from mobile devices complemented with travel diary surveys to generate information about travel patterns of commuters in the City of Dubuque, Iowa. • Data Generated Emergency Management • O/D Matrices • Corridor Speed Department of Transportation • Meaningful Locations • Travel Modalities • Trip Purpose, etc. • Project Outcome • Primary - Public Transit Route Optimization • Secondary — Adjust Signal Timing, Reduce Accidents, Resource Planning, etc. 6 Smarter Travel • Proposed Analytics/Optimization Process Phase 1 Recruitment Phase 2 Trip mode Travel Diary estimation Household Income Small Phone Household Duration of Stay Estimation A s size Smartphone • Number of Data Workers Trip Sampling • Location Segmentation Size Meaningful Compare Points of Trip Purpose With Travel Phase 2 Interest Estimation Location Diary info Classification has e Household Cell phone Travel Diary Travel O/D O/D from O/D Data Travel Survey Smart phone Airsage Data data Survey DMATS Phase 4 Four step Screen line test model Clean Sheet Optimal Phase 5 route Routes 0 timization Smarter Travel • Project Sample Size The project will have approximately 750 households recruited. Time Period i of i i (approx.) May, 2015 to August, 2015 250 February, 2016 to April, 2016 250 November, 2016 to January, 2017 250 Total Study Area Households : 39,046 Volunteer Requirements • Transmit data from smart phone for 14 days. • Complete travel diary for three consecutive weekdays. 8 Smarter Travel • Sampling Plan and Travel Diary Sampling Plan How do we pick people to participate in the study? • Household Demographics • Household income • Number of people in the household • Number of Workers in the household • Transit rider TOTAL Household Number of Workers Household Size No Worker 67 Household Income Total Households Households 4-or-more 1-person 2-person 3-person persons households 1 or more 183 worker Households Less than $25,000 35 14 5 2 56 Households $25,000 - $49,999 22 32 9 10 73 $50,000 - $74,999 7 22 8 15 52 Transit Riders $75,000 or more 3 26 1 14 1 26 69 10-20 households making at Total 67 94 36 53 250 least one trip today 9 Smarter Travel • Mobile Application Infrastructure Supported Platforms User Experience • Private IBM cloud • iOS 7.1 .1+ • Periodic uploads • Secure and anonymized • Android 4.3+ • Battery-optimized sampling transmission of samples • Accuracy enhance sampling • Integration with other datasets • Client notifications .apo.( Tea Pea 1ETa%tea IDS 51mulamr-(Phare 55-(phone 55/los 8.. Lamer? s'.09PM 1m QinalgMaln motion 1Rcou0 � AbOUI Insights in Motion 1aM C1J Userid1953983780864 Rules of Participation: In order to receive your"0 HyVee pull of on gift card: arlor b receive WD,5501fyVee gift curd '"""'•""""` '°••�'^^•"^� App must run for 14 consecutive days A App must run for 14 consecutive iA Insights in Motion add three days must be recorded on the . Inua imel oualneu Ma nms corp days and three days must be prpyjtletl travel diary After the 14 days,arca participant has recorded on the provided trawl FULLY COMPLETED and®tumed the travel diary amd diary matches app data,participant - After the 14 days,once © ® well De Morocco on where m pick up gill cardiCOMPLETED ary and returned the travel d and diary matches app data,participant lnw.� saw will be riftructed on here to pick up gift card. The application aims to support a study for the City of Dubuque. READ MORE 10 Smarter Travel • Data Analytics • Remove erroneous data points • Identify stops and trips • Rule-based approach • Compute average corridor speed • PWL extrapolation and integration • Find meaningful locations • Clustering stops • Generate O/D matrix • Map to TAZ • Normalized via scaling factors derived from volunteer's socioeconomic data and census data. Smarter Travel • Trip Purpose Classification and O/D from Travel Diary Trip Where Did Your Route? The Time? Tunneled? #1 On your way to What did you do at this location? What time did What was the primary type of Indudipgyog, this location did (check all that apply) you ARRIVE at transportation you used, how many Hy-Vee you cross the this location? �� Walk people Diode The Mississippi River, 01 workng at Home o School Bus thistrip? Name or Description of Place 02 O[her Home aRi•nties Place YES NO 03 iVork/]ob(at work lotion) Circle one: o Bike 1 1 04 Wurk/Busiv,ss relateJl AM PM o Auto,Van,buck Went taas[Sareet 055chool o Transit Bus(Route: ) Including you, O6 Change Mode(a g.,car to bus) What time did Other how many Address ion(or nearest dude you DEPART people tersectien include suffer St,Ave., O) Dropped off passenger from car fmni YOUR ( If YES:Which this IOatignT If you used car,van,or track lane,Cc.) hi hwa i mad 09 Pilled up passengerfrom wr (enter NA hyou Y HOUSEHOLD-o"'pi g V yon for th/s trip,were you the: were nn rhi. brill did 09 Personal resines to th hareh bridge you use 10 Health rare(doctor,dentist) krthe Jay here; trio' to voss the river, � glousz Driver OR Passen Dubuque ]A 11 Gvi Rell ctivires ger 12 Eat meal outride of home erre. _q:45_ —1— ❑ty B�� Cirde one: Pleaseheve illi Following 52001 13 Recreationej Relative, t AM PM about the vehicle: Wbatwere the 19 Visit friends]Relatives Year: 2004_Make/Model_Toyotaother f the Zip(if known) 15 Other,Specify -Groceries PH us household peolmrs Was this your household's traveling with vehicle? YES NO youv 12 • L p Segmentation Analysis Map Naw of 1261720961024 activlty on 2015(-06.20 ! i .moo„. ,,,�"'` ✓ w'..m..` S vi y,..,. sw s Y u. ✓ "1no,��yr -� f Display daily trajectories. Kati- 11"I,= �; o StapMae a4 kDisplay stops and trips. Clicking on each Start 2015-06-2013:26:3d.0 a� stop or trip will display its properties, such EntlDura :2015-06-2fi1fi96:52.6 as starting/stopping time, duration, land Land lana use:COM � w.00�onm, wo= revmn use, trip purpose and trip mode. �p �1 Ability to pin custom locations on the map. � .i., �� 13 Smarter Travel • Trip Purpose Classification and O/D Matrix n-. N P, . �� ® ,.,00, ,aIZ, • Three categories of POIs (schools, shopping/restaurants, other) • Classify work and home locations based on duration of stay and time of day • Trip purpose: home-based work, non-home-based work, home-based school, non-home- based school, home-based shopping, non-home-based shopping, home-based other, and non-home-based other. These categories will be used to partition the O/D matrix • The O/D matrix is aggregated between all the users and for different time intervals 14 Smarter Travel • Validation of Smartphone and Travel diary data The Smarter phone data and Travel Diary data are compared at different levels. Level l: Data collection The Smartphone data and Travel Diary data are compared to check accuracy of • Location • Missing trips • Mode choice Level 2: Trip purpose The Smart phone data is compared to Travel Diary data to check purpose of the trip Level 3: Origin/Destination matrix The origin/Destination matrix from both sources are compared to each � other once the survey sample is extrapolated to MPO Smartphone peak O/D Travel Diary peak O/D 15 Smarter Travel • Screenline Test of O/D Data. tLAADT207D 0-1.000 —5,0D1-e,9DD0/1) data liV o2TY�J17JUoRfi for the 1,007-3,000-8,001-12,000 region 3001-5000- 1 MR- 400 1 2 3M e u nniE e1 a� 5 \ I �, 151 Travel Diary 3 I11 BURY 32 ueu4 Smartphone _ _ _ 35, EAS, DUAUOOEl ' ` C� t 1 I1L DU [n'uw 30l Airsage PERSIA �► 20 I I isr I _ \ N I a1_ ' "' Screenlines Smarter Travel • Meaningful Location i S i - ♦ f. . •.S J Y. y. • , f . LN+ .ASL•. `� / f' yds .v t xM,� P Time options: days of week, all weekends, all weekdays and all days of week. View data in time periods. Overlay location clusters. 17 Smarter Travel • Corridor Speed and Travel Time � _« . Ills 1 ®® 1 ,g . Corridor speed or travel time . Time options: Time of Day . Direction of Travel 18 Smarter Travel • Bus Route Optimization approach • Input data: rGenerate • Street intersections and street links candidate • Travel time of various travel modes on each link routes • Maximum number of buses and bus capacities • O/D matrix _ _ ct • Additional constraints/requirements optima[ set • Generate a set of candidate routes of • • Can include constraints such as hubs, limited change from current routes, etc. • Choose an optimal set of routes minimizing average travel time by formulating objective function and optimization problem as an mixed integer program (MIP) • Solve MIP using 2 types of algorithms: CPLEX and Volume algorithm • Routes are adjusted based on feedback and expert guidance from Jule 19 Smarter Travel • Optimized Bus routes � t � i . 4r 0 •• t 1 t Bus routes based on peak period O/D 20 Smarter Travel • Jule Staff Role • Provide feedback on IBM proposed routes based on topography, high demand stops, local knowledge, impacts to low income, minority, disabled and elderly populations • Review existing ridership patterns for • Comparison with proposed IBM routes • Opportunities for route combination during off peak on weekdays • Opportunities for route combination on Saturdays • Construct schedules, placement and review of new bus stop locations • Propose route/service changes to Transit Advisory Board for inclusion in budget recommendations • Find cost savings in existing service to fund any proposed increases in service 21 Smarter Travel • Questions Contacts Chandra Ravada Chai Wah Wu Director of Transportation Department IBM T. J. Watson Research Center East Central Intergovernmental Association P. O. Box 218 ph.: 563-556-4166 Yorktown Heights, NY 10598, U. S. A. e-mail: cravada(c_r�eci, a.org ph. : 914-945-1567 e-mail: cwwu us.ibm.com Web Sources http://www.Citvofdubuque.org/1496/Smarter-Travel http://www.eciatrans.org/DMATS/SmarterTravel.cfm 22