Activity-travel scheduling is at the core of many activity-based models that predict short-term effects of travel information systems and travel demand management. Multi-state supernetworks have been advanced to represent in an integral fashion the multi-dimensional nature of activity-travel scheduling processes. To date, however, the treatment of time in the supernetworks has been rather limited. This paper attempts to (i) dramatically improve the temporal dimension in multi-state supernetworks by embedding space–time constraints into location selection models, not only operating between consecutive pairs of locations, but also at the overall schedule at large, and (ii) systematically incorporate time in the disutility profiles of activity participation and parking. These two improvements make the multi-state supernetworks fully time-dependent, allowing modeling choice of mode, route, parking and activity locations in a unified and time-dependent manner and more accurately capturing interdependences of the activity-travel trip chaining. To account for this generalized representation, refined behavioral assumptions and dominance relationships are proposed based on an earlier proposed bicriteria label-correcting algorithm to find the optimal activity-travel pattern. Examples are shown to demonstrate the feasibility of this new approach and its potential applicability to large scale agent-based simulation systems.

/pdf/incorporating-space-time-constraints-and-activity-travel-578b10hq82.pdf

Incorporating space-time constraints and activity-travel time profiles in a multi-state supernetwork approach to individual activity-travel scheduling

In this paper, the authors develop and apply a series of stated preference (SP) experiments to estimate a comprehensive multimodal, multi-stage travel choice model In total, four experiments are designed focusing on particular multimodal (including P+R) and public-transport choices for trips of varying distance A representative national sample (N = 2746) of individuals from the Netherlands participated in the experiments through an online questionnaire The data pooled across experiments are used to estimate the model in a scaled mixed multinomial logit framework In this way, valuations of time, costs and service-quality attributes could be estimated on a relatively high level of detail concerning modes and trip stages The estimation results can be used to specify link costs functions in multimodal network models for network analysis and route planning

Travelers’ Preferences in Multimodal Networks: Design and Results of a Comprehensive Series of Choice Experiments

Multimodal and multiactivity travel planning is a practical but thorny problem in transportation research. This paper develops an improved supernetwork model to address this problem. The supernetwork is constructed mainly in three steps: a personalized network is first split into two types of networks with all links mode-specified; these are then assigned to all possible activity-vehicle states by means of state spreading from the beginning activity state. Finally, these discrete networks are connected into a supernetwork by state-labeled transition links. The proposed supernetwork is easier to construct than previous proposals and reduces the size needed to embody all combinations of choice facets explicitly. It can be proved for any activity program that any tour is a feasible solution in this representation. Consequently, every transport and transition link can be defined mode and activity-state dependent; thus standard shortest path algorithms can be used to find the most desirable tour. A case study is presented to show that the supernetwork model can be applied in a real-time manner for practical travel planning.

/pdf/supernetwork-approach-for-multimodal-and-multiactivity-2ukguhhgtt.pdf

Supernetwork Approach for Multimodal and Multiactivity Travel Planning

Least-costs path finding methods belong to the standard toolkit of geographical information science and allow one to assign trips with known origin and destination to a transport network. An extension of the network representation is proposed that allows one to model complete trip chains (tours) that may involve multiple transport modes and multiple activities, as a least-cost path through the network. The extension is based on the notion that link costs may change as a consequence of activity and vehicle choices during the tour. The extended network or supernetwork contains as many copies of the network as there are possible activity–vehicle states and additional state transition links to interconnect them. In this way, not only the generalized link cost function, but also the start and end points of a path can be defined state dependently. A least-cost path through a multistate network defines an optimal sequence of travelling, transferring, parking, conducting activities and dropping off products of ac...

Multistate supernetwork approach to modelling multi-activity, multimodal trip chains

A unified framework coupling activity-based modelling and dynamic traffic assignment has recently been proposed. It formulates dynamic activity-travel assignment (DATA) in multi-state supernetworks as a dynamic user equilibrium. Choices of departure time, route, mode, activity sequence, and activity/parking location are determined endogenously, reflected in time-dependent activity-travel patterns (ATPs). However, capacity constraints associated with activities, parking, and public transit vehicles have not taken into account. This paper extends this approach by formulating these constraints and incorporating them into the DATA framework. Three numerical examples are presented to illustrate the effectiveness of the approach. It is shown that capacity constraints have significant effects on the choice facets.

/pdf/dynamic-activity-travel-assignment-in-multi-state-2iq5rwjdtg.pdf

Dynamic activity-travel assignment in multi-state supernetworks with road and location capacity constraints

A supernetwork approach towards multimodal travel modeling

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A supernetwork approach towards multimodal travel modeling