Green Bay Google Transit

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Information about Green Bay Google Transit

Published on November 14, 2008

Author: ewug



In a joint effort, the Brown County Planning Commission/MPO and Green Bay Metro created an online transit routing application that is powered by Google Maps. This application gives users the ability to search Green Bay Metro's existing transit routes, bus stops, and pick-up times to help plan bus trips from beginning to end using the internet or mobile technologies. The Brown County Planning Commission developed the Google
Transit Feeds (GTF) based on Google’s specifications by
incorporating tables and geospatial data within its existing
transportation geodatabase schema. The GTF was developed using GPS, ArcMap, ArcSDE, SQL Server, DTS, and Google Transit open source software. The Brown County Planning Commission/MPO GTF presentation will provide information on
how to get started in developing the GTF, advantages,
disadvantages, future obstacles, and lessons learned throughout the Google Transit development experience. A live demo of the application will be shown following the presentation.

Green Bay Google Transit October 29, 2008 Brown County Planning Commission/Green Bay MPO Cole Runge, Principal Planner/MPO Director Lisa Conard, Planner (Transportation) Tim Hennig, Planner (Transportation/GIS) Brown County Information Technology Department Carrie Borofka, Programmer Analyst Green Bay Metro Chris Phelps, Green Bay Metro Director Google Google Transit Team

Brief History • In 2005, all of Green Bay Metro’s bus stops were mapped via GPS coordinates. This information was used as part of the Google Transit development (Thanks Eric Heidenreiter and the help from other interns).

The Creation of Green Bay’s Google Transit Brown County Planning Commission/Green Bay MPO developed the Google Transit feeds using its geographic information system (GIS). • Additional GIS and tabular data was developed within a MS SQL Server/ArcSDE enterprise geodatabase environment. Implemented Google Transit feed specifications as part of Brown County’s transportation geodatabase model schema. Scripting data transformation services (DTS) of GIS and table data and data compiling the data into a CSV file format. Basically the data transfer is transfer automated based on Google’s specifications. Google provides open source development tools. • There are tools you can use to validate your feeds. • Schedule viewer program. • KML (Keyhole Markup Language) writer program that integrates with Google Earth that validates bus stop location and information. Networking is a must! • The Google team will work with you. • You can post questions or comments in the Google Transit Groups. • Networking amongst other Google Transit developers (e.g. Cities of Appleton, Fond du Lac, and Duluth, ECRPC, and BLRPC).

GTF File Requirements All files in a Google Transit Feed Spec (GTFS) feed must be saved as comma-delimited saved comma- text. • The first line of your feeds must contain field names. Each subsection of the Field Definitions section subsection corresponds to one of the files in a transit feed and lists the field names you may use in that file. • All field names are case-sensitive. case- • Field values may not contain tabs, carriage returns or new lines. lines. • Field value in CSV file: quot;Contains quot;quot;quotesquot;quot;, commas and textquot; Field values should not contain HTML tags, comments or escape sequences. sequences. Name your feed files using the following naming conventions: • agency.txt • stops.txt • routes.txt • trips.txt • stop_times.txt • calendar.txt • calendar_dates.txt • fare_rules.txt • fare_attributes.txt • shapes.txt • frequencies.txt • transfers.txt Zip the files in your feed. Name the zip file Post the zip file in a directory named YYYYMMDD, where YYYYMMDD is the earliest date of valid service included in any of the files. YYYYMMDD, Source:,, September 2008.,,

IsoCountry Google Transit Feed -country_id : nmtoken Specification (2007/06/20) TM: AUTHORITY or © 2007 OPERATOR calendar service validity condition service_id -service_Id 1 Monday() : boolean * Tuesday() : boolean 1 Wednesday() : boolean agency Thursday() : boolean 1 agency_id : string TM VALIDITY Friday() : boolean CONDITION Saturday() : boolean agency_name() : string Sunday() : boolean agency_url() : url start_date() : date agency_timezone() : timezone exceptions end_date() : date angency_lang() : isoLang calendar_dates 1 «uses» service_id * «enumeration» date() : date availabilityEnum routes TM: VEHICLE exception_type() : availabilityEnum vehicle journeys JOURNEY 1 = available TM: ROUTE 2 = notAvailable + LINE TM: BLOCK trips * tripId : nmtoken block * route_id() : nmtoken service_id() : nmtoken 1 route_id block * trip_headsign() : string * route/line route_id : nmtoken «uses» * direction_id() : boolean TM: LINK -block_id route_short_name() : string 1 block_id() : nmtoken PROJECTION route_long_name() : string shape_id() route_desc() : string «enumeration» 1 route_type() : modeEnum modeEnum calls 1 route_url() : url link projection 0 = Bus 0..1 TM: STOP IN route_color() : hexColourValue 1 = Ferry SEQUENCE route_text_color() : hexColourValue 2 = Rail + PASSING 3 = Subway shape TIMES 4 = Tram shape_id : nmtoken * 5 = Cablecar shape_pt_lat() : lat TM: FARE 6 = Funicular shape_pt_lon() : lon PRODUCT stop_times shape_pt_sequence() : integer shape_dist_travel() : distance trip_id : nmtoken stop_id : nmtoken «enumeration» stop_sequence : stop_times distance matrix fare paymentMethodEnum 1 0 = onBoard arrival_time() : time fare_id : nmtoken TM: SCHEDULED * 1 = beforeBoarding stop departure_time() : time STOP POINT pickup_type() : activityEnum 1 drop_off_type() : activityEnum «uses» fare price «uses» 1 stops TM: DISTANCE rules stop_id : nmtoken «enumeration» MATRIX fares_attributes activityEnum stop_name() : string 1 fare_id : nmtoken stop_desc() : string 0 = Regular 1 = NoPickup * price() : amount stop_lat() : lat stop_lon() : lon 2 = DrtPhone currency_type() : isoCurrency zone_id() : nmtoken 3 = DrtDriver * payment_method() : paymentMethodEnum fares_rules transfers() : transfersPermittedEnum stop_url() : url tarrif zone origin zone fare_id : nmtoken transfer_duration() : seconds «uses» route_id : nmtoken * destination zone origin_id() : nmtoken currency * 0..1 * destination_id() : nmtoken * contains_id() : nmtoken zone 0..1 «enumeration» zone_id : nmtoken 0..1 transfersPermittedEnum * IsoCurrency 0 = none TM: TARIFF 0..1 contains tarrif zone zone 1 = one currency_type : isoCurrency ZONE 2 = two 0..1 3 = unlimited Source: The Google Transit Feed Specification – Capabilities and Limitations, Kizoom Limited; London, 2007.

Option A Option B

Issues - In some cases, Google Transit may suggest walking a little further if the overall trip time is reduced. Google Transit’s default routing time is set to real-time. Transfer points were not specified (this was later corrected). Route deviations are not included. Updating and testing route changes may take one to two weeks. Google Transit is not customizable. Communications with Google Transit team are through email. Google gets name recognition, where Brown County and Green Bay Metro do not.

Advantages of Google Transit You can search based on street address, street name, generalized area, or business name. Google provides web routing technology for free as opposed to paying thousands of dollars to maintain a network server. • Great for smaller transit systems. • Great for Metro call takers regarding transit routing. Google can provide web routing for commerce. • Example: A business may want to show how to get from Green Bay Metro to their business facility. Another transit guide option for existing and future riders. Green Bay will be known for its partnership with Google and for providing a service that can be accessed through the world wide web. We now have extensive GIS transit data (e.g. bus stops, time points, time frequencies, and fare information) for GIS and planning purposes.

Lessons Learned The complexity of developing and planning the Google Transit using GIS and implementing it as part of the Brown County’s transportation geodatabase model. The complexity of inputting, testing, and correcting the Google Transit feeds. You may have to wait a couple of weeks to make corrections and retest your feeds. There are other ways to develop the Google Transit feeds. • Excel download from Google Groups. • Data table approach. • Transit scheduling and operations software (e.g. GIRO’s Hastus Software).

Future Obstacles Incorporating a workflow process that includes GIS and tabular editing. Updating time points and sequences within GIS and tabular. Adding limited-service routes, deviations, and detours.

How to Get Started Create a Google user account. • Contact Google Transit. • Print Google Transit specifications. • Download open source GTFS software. • Get involved with Google Groups. • Search for Google Transit Brown County Planning Commission/MPO FTP • (Type this in your Windows Explore) User Name: MPO Password: BrownCounty

Google Transit Demo October 29, 2008 Brown County Planning Commission/Green Bay MPO Cole Runge, Principal Planner/MPO Director Lisa Conard, Planner (Transportation) Tim Hennig, Planner (Transportation/GIS) 305 E. Walnut Street, Room 320 Green Bay, Wisconsin 54301 Phone: (920) 448-6480 Web:

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