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Measuring and Estimating Suppressed Travel with Enhanced Activity–Travel Diaries

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 nontrivial task that cannot be achieved with the commonly used activity–travel diaries of executed activity and travel episodes. This paper develops an empirical approach for investigating suppressed travel that uses enhanced activity–travel diaries consisting of both a planning and an execution phase. This methodology is applied to data from a 7-day survey in Flanders, Belgium. First, suppressed travel is investigated by observing trip episodes that were planned but not executed. Next, a mixed logit model is built to estimate the probability that a previously planned trip is discarded (i.e., not executed). By means of this model, the household, individual, schedule, activity, and trip attributes that significantly contribute to travel suppression (i.e., the nonexecution 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 contributing to latent transportation demand. In addition, the study illustrates that, by considering the special case of suppressed travel corresponding to nonsuppressed 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 also be identified by means of the proposed approach.