Utilizing automatically collected smart card data to enhance travel demand surveys

Public transport agencies have used manual surveys to collect demographic and travel diary information in order to understand their customers' travel behavior for many years. Recently many agencies have also begun to use automated sources of data from fare collection, vehicle location, and passenger counting systems to improve the understanding of their customers' detailed geographic and temporal travel behavior as well as frequency of usage, and travel pattern variation at a much larger scale than is possible with manually collected survey data. Transport for London (TfL), the public body responsible for all transportation services in London, was chosen as a case study to determine how and to what extent automatic fare card (Oyster) data can be used to enhance and validate the London Travel Demand Survey (LTDS) single day travel diary responses. This thesis found that combining survey responses with linked Oyster data for specific households could greatly enhance the validity of the single travel day and improve the understanding of the variability of weekly public transport (PT) use. However, it was difficult to match the survey diary responses and Oyster card records after the interview had taken place. This was evidenced by the fact that only 51.1% of Oyster journey stages had matching survey journey stages, only 45.6% of survey stages had matching Oyster stages, and only 44% of the sample had perfectly matching survey and Oyster stages. Even when there were matches, there were large differences in many journey start times and durations with an average start time difference of 61.2 minutes. This suggests that it would be advantageous to integrate the Oyster records earlier in the survey process, using some type of prompted recall methods with Oyster records in the near term, and new location tracking smart phone applications in the future. Analysis of the weekly variation in PT travel found that the single day survey overestimates typical PT use overall, but it underestimates the intensity of PT use on days when the survey sample chose to use the PT mode. Additionally, the reported frequency of PT use in the LTDS was significantly higher than the actual use as captured by the Oyster system, and therefore the LTDS is generally overestimating the PT use overall for London residents.