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S U RV E Y M E T H O D S 35 the Kansas City area in 2004. Volume 2 includes a paper computer-assisted telephone interviewing (CATI) and on this topic.2 The following points were covered in her GPS data are available for 228 of the 294 households. presentation. The analysis focused on the 228 households and the cor- responding 377 drivers and 2,359 vehicles trips. The GPS has been used in at least 12 regional travel sur- GPS participants were more likely to own more vehicles, veys over the past 10 years. The primary use of GPS in to have higher incomes, and to live in single-family these surveys has been to audit trip reporting, to assess dwellings than non-GPS participants. the level of trip underreporting, and to develop correc- Of the 377 drivers participating in the GPS com- tion factors for the data. Most applications have used in- ponent, 71% accurately reported all travel in their CATI vehicle devices to obtain data on both the driver and survey, while 29% had at least one nonreported trip. Of passengers. A few surveys, such as the Portland, Oregon, those drivers who underreported trips, 49% missed one survey, focused only on the driver. Thus, GPS has been trip, 20% missed two trips, 10% missed three trips, and used mostly for passive data collection, although per- 20% missed more than four trips. sonal digital assistants (PDAs) were used with surveys in The hypothesis underlying the empirical analysis Los Angeles and Ohio. Different processes have been was that trip underreporting is influenced by three major used for detecting missed trips. Rates for missed trips factors: the demographic characteristics of the driver, the have ranged from 5% in Reno, Nevada, to 81% in characteristics of the trip, and the level of adherence to Laredo, Texas. Also, time thresholds and other consider- the survey protocol. Examples of driver demographics ations have varied. include age, type of household, employment status, and Key findings can be identified from the use of GPS the number of vehicles in the household. Trip character- in the 12 regional travel surveys. First, GPS participants istics included the total number of trips, the average trip are a select group of respondents. GPS participants tend distance, and the level of trip chaining. Elements associ- to have higher incomes and higher home ownership ated with following the survey protocol included use of rates. Second, different methods have been used to the travel survey to record all trips and talking directly process GPS data. These methods appear to influence the with the interviewer. rates of trip underreporting. The instructions provided A joint binary choice-ordered response discrete to participants also appear to influence underreporting. model of underreporting and an ordered-response model In most cases, participants are instructed not to report for level of underreporting among underreporting indi- trips out of a specifically defined area and trips for com- viduals were developed by adopting a systematic proce- mercial purposes. dure of eliminating statistically insignificant variables. A research project was conducted to examine the The exogenous inputs to the model are classified accord- use of GPS in the 2004 Kansas City regional household ing to the three areas of influence. The binary choice- survey. The project had four research objectives. The first ordered response discrete model includes two objective was to identify the likelihood and the magni- equations--one addressing likelihood and one addressing tude of trip underreporting at the person level. The sec- magnitude--and accounts for correlation in error terms. ond objective was to develop a joint model that The results of the modeling effort help identify recognizes the implicit relationship between the likeli- underreporting tendencies with household travel sur- hood and the level of underreporting. The third objective veys. The underlying mechanism that represents whether focused on examining a comprehensive set of variables an individual underreports is different from the mecha- related to driver demographics, driver travel characteris- nism that determines the level of underreporting. There tics, and driver adherence to survey protocol. The final are factors that influence both the underreporting objective was to identify methodological improvements propensity and the propensity associated with the level to reduce underreporting in future travel surveys based of underreporting. The effect of driver demographics on the research results. indicates that adults under the age of 30, men, individu- The Kansas City regional travel survey was con- als with less than a high school education, unemployed ducted in 2004 under the sponsorship of the Mid- individuals, individuals working in clerical and manu- America Regional Council and the Kansas and Missouri facturing positions, and individuals working at residen- Departments of Transportation. The survey included tial, industrial, and medical facilities are more likely to 3,049 randomly sampled households, 7,570 persons, underreport trips than other respondents. Driver travel and 32,011 trips. The GPS component involved equip- characteristics that influence underreporting include ping the vehicles of 294 households with GPS devices to higher trip rates on the survey day, traveling long dis- record all vehicle travel during the survey period. Both tances per trip, and high levels of trip chaining. Also, drivers who do not use their travel diary to record their 2 See Bricka, S., and C. Bhat. Using Global Positioning System Data travel are more likely to miss trips than those who use to Inform Travel Survey Methods. Volume 2, pp. 8993. the travel diary. Based on elasticities, the most important