Design of stated adaptation experiments: discussion of some issues and experiences

Rescheduling of daily activities and associated travel in response to unforeseen events such as travel delays is receiving increased attention in the context of traffic management. In this paper, we describe the results of a stated adaptation experiment held among a large sample of individuals through a web-based questionnaire, to estimate parameters of such dynamic behaviour. In the experiment, subjects indicated their response to a reduction in available time for a planned activity in a number of hypothetical situations. A mixed logit model was used to estimate subjective preferences for adapting in certain ways conditional upon activity attributes and socio-economic variables. The results indicate that location and transport-mode adaptations are rare compared to duration adjustment or postponing/cancelling the activity, dependent on the relative size of reduced time. Socio-economic variables and activity attributes play a significant role too

Assessing planning decisions by activity type during the scheduling process

Existing activity-based models still make assumptions about scheduling decision processes that are not well-informed by empirical evidence. In this article, a step forward is taken to better understand the activity-scheduling process and to improve activity-based models. In particular, different planning decision mechanisms depending on several activity type classifications are explored. First, models describing the planning of several aggregate activity types are considered. For these activities, three planning decisions are studied: location, planning time horizon and rescheduling. The 'with whom' planning decision is also studied when subtypes of recreational/entertainment activities are investigated in depth. Significant differences are found in modelling results for each activity type and subtype and each planning decision. These results confirm the existence of different mechanisms underlying the activity-travel decision process when activity types and subtypes are considered. Important conclusions related to the improvement of microsimulation models are highlighted.Ruiz Sánchez, T.; Roorda, MJ. (2011). Assessing planning decisions by activity type during the scheduling process. Transportmetrica. 7(6):417-442. doi:10.1080/18128602.2010.520276S4174427

Interplay between telecommunications and face-to-face interactions - a study using mobile phone data

In this study we analyze one year of anonymized telecommunications data for over one million customers from a large European cellphone operator, and we investigate the relationship between people's calls and their physical location. We discover that more than 90% of users who have called each other have also shared the same space (cell tower), even if they live far apart. Moreover, we find that close to 70% of users who call each other frequently (at least once per month on average) have shared the same space at the same time - an instance that we call co-location. Co-locations appear indicative of coordination calls, which occur just before face-to-face meetings. Their number is highly predictable based on the amount of calls between two users and the distance between their home locations - suggesting a new way to quantify the interplay between telecommunications and face-to-face interactions

Integrated Land Use-Transport Model System with Dynamic Time-Dependent Activity-Travel Microsimulation

The development of integrated land use-transport model systems has long been of interest because of the complex interrelationships between land use, transport demand, and network supply. This paper describes the design and prototype implementation of an integrated model system that involves the microsimulation of location choices in the land use domain, activity-travel choices in the travel demand domain, and individual vehicles on networks in the network supply modeling domain. Although many previous applications of integrated transport demand-supply models have relied on a sequential coupling of the models, the system presented in this paper involves a dynamic integration of the activity-travel demand model and the dynamic traffic assignment and simulation model with appropriate feedback to the land use model system. The system has been fully implemented, and initial results of model system runs in a case study test application suggest that the proposed model design provides a robust behavioral framework for simulation of human activity-travel behavior in space, time, and networks. The paper provides a detailed description of the design, together with results from initial test runs