April 23, 2014 – Bi-State Regional Commission contracted with a consultant team, URS Corporation, ETC and Texas Transportation Institute, to conduct a household travel survey and enhance the current metro area travel demand model for predicting future traffic. Not since the late 1960s has a study of this type been done for the Quad Cities.
The survey was conducted between July 2013 and January 2014 with the majority of them being completed between October and January. A sample size of 1,500 households was targeted with nearly 1,800 household surveys being completed.
For households filling out travel diaries and those with GPS tracking, their efforts represented 2,800 hours of volunteered time towards the survey. The survey results included 4,100 persons, 3,523 vehicles and 13,803 trips. A trip is defined as travel between a origin and a destination, so one trip might be from home to school to drop off kids and another trip would be from school to work.
To help predict Mississippi River travel in the Quad Cities, participants were asked about their bridge crossing travel. Of the household surveyed, 58% reported bridge crossing travel at least once per week and 28% reported at least one bridge crossing daily. Nationally, the average household person trip is from 8-10 trips per person per household per day. The average trip rate for the Quad Cities on the entire data set was 7.8 trips. The survey data was stratified by household size, income and presence of workers in the household. Consistently with other national trends, larger households make more trips in the Quad Cities. Households with more vehicles make more trips and those households with greater income also make more trips. The data was also shown by trip purpose, such as work trips or shopping trips and vehicle occupancy by trip purpose.
The full report is expected in early May. The data will be used to develop special trip rate formulas by trip purpose for the travel demand model. The model is a software program that uses the household data and socio-economic data to predict traffic. The traffic forecasts are used to help local officials set policies on congestion management, transportation alternatives and set priorities for roadway improvements.