Budgetary constraints coupled with the rapidly evolving urban infrastructure of southern california have created major problems for local transportation agencies in maintaining up-to-date travel data bases. In an effort to rectify data base deficiencies, local agencies have sought more innovative and cost-effective approaches to collect needed data. The orange county transit district and the california department of transportation have applied a survey methodology of corridor travel levels in orange county that uses video cameras to photograph license plate numbers of travellers. The owners of the vehicles are then sent mailback postcard surveys to obtain information on their trip making. Responses are analysed anonymously for use in commuter market studies, transit service plans, and travel demand models. Three corridors in orange county have been surveyed to date using this technique. A follow-up survey was performed in one of the travel corridors 2 years later at the same location to allow for a detailed time series study of changes in travel behaviour before and after the opening of carpool lanes in that corridor. The 1987 follow-up survey recorded some significant changes in corridor travel characteristics from the 1985 statistics for the morning peak period. The analysis of the results of the before and after surveys indicated that the facility with the median carpool lanes in operation had become more heavily used by home-to-work commuters during the morning peak period and more efficient at moving people rather than just vehicles. The data bases collected using this approach have been sizeable (6,200 or more records), ensuring high statistical reliability in comparing the characteristics of small subsets of respondents, such as carpoolers commuting to work during the morning peak. The technique affords a high degree of control by location and time thereby allowing for detailed analyses of travel patterns. The four video postcard surveys conducted to date have not been disruptive to traffic, have experienced a high return rate, and have proved to be cost-effective at obtaining large-scale and accurate travel data.
Abstract