KY Module 3: Geocoding and GPS

1. KY Module 3: Geocoding and GPS

2. What is the single hardest information to get from a travel survey? • Location, location, location • What is the address of YOUR grocery store? • Easiest to report are home and work location. Even school addresses are often difficult for respondents to report.

3. Respondent difficulties Street suffix (St, Ave, Blvd) Directionals (N, S, E, W, NE, SW, etc) Difficult street names CATI interviewers not familiar with local landmarks Interviewer and processing difficulties CATI interviewers not familiar with local landmarks Multiple matches to GIS basefile (Main Street, Washington Street). Difficulties in location reporting

4. Why do we need this geographic detail? • Attempt to code origins and destinations to latitude & longitude. • Previously code to TAZs, but TAZs keep getting smaller, as computer technology allows for larger O/D matrices. • By coding to lat/long, TAZs can be modified in the future and the data can be summarized for new TAZ definition. • Want to link detailed geographic info to model, e.g. slope, sidewalks, distance to bus stop.

5. Better location information • How to make it easier on respondents to provide location information?

6. Can web-response play a role? • Complete it on “their” time, not when the phone rings. • Sample bias, but high income hhlds and young males are also part of non-respondents, and this method is useful for reaching these hhlds.

7. Geocoding on Internet • Interactive Yellow Pages look-up • Who knows the address of their grocery store or barber shop/beauty salon? • Point and click on a map to identify a location • Type in an address or intersection and have the GIS interface locate it on the map

8. GPS may be more accurate and complete, by relying of passive data collection. GPS equipment is small and getting less expensive everyday. • A new Trimble GPS receiver is the size of a pencil eraser! But, you still need an antenna.

9. GPS in Household Travel SurveysStudies in the U.S. • 1995 Lexington, KY “proof of concept” (100 vehicles) • 2001 CalTrans: 3 counties in CA • 2001 SCAG (Ben Pierce) • 2001 Ohio DOT (Ben Pierce) • 2002 Smartraq; Atlanta TYPICALLY 200-500 HOUSEHOLDS, with up to 3 vehicles equipped per hhld.

11. Example from Geostats • Comparison of self-reported trips (phone retrieval) to GPS recorded data • Estimated 25-30% of trips are unreported, but still working to determine impact on VMT, cold starts, trips by purpose

12. Example from Geostats • GPS generated maps as a “recall”mechanism. People may be able to recall what they did a week ago if provide a map with numbering sequence and time-stamp. Use of internet to pass Map to the respondent. • Test in Louisiana, continued work in Australia (Peter Stopher)

13. Other approaches • Equipping sample of taxis with vehicle navigation service in Japan • Tracking cell phone users in Germany and in Japan (Dokomo) • Activity Motivation and re-scheduling: Sean Doherty

14. GPS in truck surveys • Very difficult to get good response rates from commercial vehicle surveys • One GPS survey in California (CARB and FHWA), conducted by Battelle • Only fleets were included, not “independent truckers” who make up 50% of the CA fleet.

15. GPS in truck surveys • Large fleets may already have GPS for fleet management, but not likely to share data with public sector, cuz it is considered proprietary information.

16. GPS for travel speed studies • Ability to cover large number of miles • Only need one person per vehicle (“old fashion” method with stop watches needed 2 people) • College students, working part-time, very comfortable with using palm-tops and laptops for data entry and data uploading.

17. Sample of digital video image, georeferenced to GPS data

19. GPS for travel speed studies • Travel Speed along links • Travel speed compared to posted speed • Travel speed by functional class • Examine recurring congestion • Examine queuing length (defined when speed falls below 5 mph or less for 5 seconds)

20. Show 2 .jpg from Steve’s CD