An examination of the accuracy of an activity-based travel simulation against smartcard and navigation device data. (April 2017) - Hwang, Jeong Hwan; Kim, Hyunmyung; Cho, Sungjin; Bellemans, Tom; Lee, Won Do; Choi, Keechoo; Cheon, Seung Hoon; Joh, Chang-Hyeon
Highlights: The accuracy of an activity-based travel simulator needs to be examined before applying the simulator to the analysis of behavioral sensitivity to policy scenarios. The accuracy of travels simulated by a travel simulator was examined against big data of smartcard and car navigation. The global and local indices of the matching between the destinations of simulated travels and observed ones suggest the need for further improvements of the simulator to enhance the accuracy of the travel simulation, in particular for the public mode use in the peripheral Seoul. Abstract: Activity-based travel simulators have been experiencing difficulty obtaining high quality activity-travel data and network information, which limits the applicability of the simulator to real world problems. For example, accurate information regarding travel time, link traffic volume and trip distribution is essential for sensitivity analysis using an activity-based travel simulator. Survey data, which relies on respondents' memories, is typically inaccurate. The recent development of big data engineering has enabled us to use passively collected big data such as from smartcards and navigation devices; their travel time and spatial information is highly accurate. Activity-based travel simulation based on the household travel survey (HTS) can therefore identify inaccuracies in simulated travels by comparing smartcard and navigation device data. This paper aims to examine the accuracy of journeys simulated by an activity-based travel simulator, FEATHERS Seoul (FS), against smartcard and car navigation device data collected in Seoul. The analysis found that the activity-based simulator performs well and reproduces individual travel decisions, as reflected by the overall trip frequency and distance, but it partly fails to correctly reproduce geographical distributions in flexible, non-work trip destinations. The results imply that an activity-based travel simulator needs to improve its incorporation of geographical characteristics using big data engineering to enhance the simulated travel accuracy.