STRATEGIES FOR ORGANIZATION, VALIDATION AND DISTRIBUTION OF TRANSIT GEOGRAPHIC INFORMATION SYSTEMS DATA Jonathan Wade Manager, Service Development Support Regional Transpiration District, Denver, CO GIS in Transit Conference, October 16-17, 2013, Washington, D.C.

QUALITY STRATEGIES IN SYSTEMS DESIGN Base routes and schedules on real, quantitative data to constantly monitor to improve the customer experience One database of record for each data element Use best available database and consolidate data wherever logical Fix errors at their source Immediate feedback loops to fix errors Frequent, automated processes to incorporate revisions and fixes in downstream systems Constant and continuous incremental upgrades to data and systems

BASE ROUTES AND SCHEDULES ON REAL, QUANTITATIVE DATA Requirements for persuasive presentations of data: The data is complete Stop data Ridership data The data is accurate Passes all validation processes Updated frequently The data is readily available Uses know where and how to access the data quickly

CONSTANTLY MONITOR TO IMPROVE THE CUSTOMER EXPERIENCE Routing defined Time points Trapeze scheduling Bus stops defined TIES DB for error checking, production and data collection Ridecheck Plus ridership analysis and reporting INIT CAD/AVL /APC data collection Other schedule data TriTapt on- time performance analysis Can we improve the customer experience ?

IMPROVING THE CUSTOMER EXPERIENCE Scope of GIS and Schedule Data Changes 3 Major run boards year (usually in August, January and May) 30 to 50 revisions to each run board after voting Minor changes: footnotes, running time changes Major changes: rerouting, modifying operator run Special Services each year (scheduled in Trapeze) Examples: Broncos Ride (football), Rockies Ride (baseball), etc. About 1100 Special Service orders per year (scheduled in TIES)

PointsSchedulesLinesPolygons Schedule Development Database (Trapeze) Production Database (TIES – developed at RTD) Customer Interfaces Operations Interfaces HIGH-LEVEL DATA FLOW Data entered by Service Planner/Schedules Customer interfaces Trip planners Web schedules Paper schedules Operations Interfaces CAD-AVL Systems Operator pay Ridership and schedule adherence systems

GPS BUS STOP DATA FLOW DATABASES OF RECORD FOR STOP DATA Method 2: GPS Field Data Collection Method 1: Stop Tool Data Entry Method 3: Edits Upload GPS Arc Catalog Visual GPS Verification Append New GPS Data - Shape file Merge Shape file to Staging Table (Model Builder, Arc Toolbox, Arc Catalog) Update SDE Bus Stops in Oracle Trapeze, database of record for geographic coordinates and relationships of stops to routes TIES Maximus (Asset Works) database of record for stop names and stop amenities Trapeze FX Processing 1. Sequence on route 2. Extract stops on patterns 3. Calculate distance 4. Calculate estimated stop times for each trip Coordinates only No Coordinates Convert stop names to all upper case Convert stop names from upper case

RTD Collection Staff 43 Street & LRT Supervisors Laptops (pointchecks) 6 Service Monitors Laptops ( ridechecks/pointchecks) 2 Station Starters Desktop (pointchecks) Bus and LRT Schedule Data & Bus Vehicle Assignments (Trapeze & TIES) CAD/AVL System Schedule Adherence Data (INIT data 2013, ACS data pre-2013) Schedule Adherence Reports Ridership Analysis Reports Ridership Analysis Maps Init Automated Passenger Counting System 302 Buses (of ~ 1000) APCs (ridechecks) 42 LRT Cars (of ~ 178) APCs (ridechecks) LRT Factoring APC Validation Automated Survey Validation Technician Analysis and Reporting INFORMATION FLOW CONSOLIDATING RIDERSHIP DATA Google Earth Ridership Maps TriTapt and On-Time Performance Toad for Ad Hoc Reporting 56 Commuter Rail (Future 2016) All with APCs (ridechecks) Commuter Rail Schedules & Vehicle Assignments (Hastus and TIES) Ridecheck Plus

Points Schedules Lines Polygons Schedule Development Database (Trapeze) Production Database (TIES – developed at RTD) Customer Interfaces Operations Interfaces New Validation Needed? Errors? FIX ERRORS AT THEIR SOURCE Validations conducted as data is created On demand by scheduling staff Currently 65 custom validations for route, pattern, trip, block, time point and run cut data Adding a new validation rule at the rate of about one a month Data Valid?

IMMEDIATE FEEDBACK LOOPS TO FIND AND FIX ERRORS Automated queries check schedule data via a web-based interface Suite of validations complete in about a minute On demand by Schedulers/Planners Summarizes errors and provides drill- down for details

FREQUENT, AUTOMATED PROCESSES TO INCORPORATE REVISIONS AND FIXES Daily or more frequent update Stop data Every 3 hours Customer schedules on website Customer schedules on mobile website Electronic passenger information displays Every few days to weekly update 2-3 times a week Dispatch electronic schedules Operator web site Weekly CAD-AVL data for operations External GIS System Map Less frequently, less automated Internal Trip Planner Every other month Goal is weekly in 2014 External Trip Planner About Monthly Goal is weekly in 2014 GTFS About Monthly 3 week lag time a major hindrance

BENEFITS OF APPROACH Credibility, better decision making All stakeholders within RTD are working with the same data Reporting can consider a variety of data sources at one time Minimizes frustration by eliminating errors before they get to downstream systems The persons most likely to have created the error gets information needed to fix it quickly Customers and operations benefit from accurate, timely schedule and GIS data