Measuring and estimating suppressed travel using enhanced activity-travel diaries

Abstract

Suppressed travel and the related phenomenon of latent transportation demand are important from the point of view of the implementation of traffic demand management strategies. However, the measurement and estimation of suppressed travel is a non-trivial task that cannot be achieved by using the commonly used activity-travel diaries of executed activity and travel episodes. In this paper, an empirical approach to investigating suppressed travel is developed that uses enhanced activity-travel diaries which consist of both a planning and an execution phase. This methodology is applied to data from a 7-day survey in Flanders. Suppressed travel is investigated by observing trip episodes that were planned but not executed. Next, a mixed logit model is built that estimates the probablility that a trip that was previously planned is discarded (i.e. not executed). Using this model, the household, individual, schedule, activity and trip attributes that significantly contribute to travel suppression (i.e. the non-execution of previously planned travel episodes) are identified. The presence of suppressed trips is an indication of the presence of latent transportation demand. Hence, the previously identified attributes can also be interpreted as attributes contributing to latent transportation demand. In addition, it is illustrated that by considering the special case of suppressed travel corresponding to non-suppressed activities, the clustering of activities at geographic locations can be investigated. This phenomenon is identified as a special case of trip chaining and as such, the attributes that significantly influence this form of trip chaining can be identified as well using the proposed approach.