Currently, modal split modeling is done mainly by means of disaggregated mode choice models. The almost absolute dominance of multinomial and nested logit models over other mode choice models among applied transportation modelers is attributable to their theoretical soundness, to their simple and understandable analytical structure, and to the calibration procedures that have been developed. Typical urban transport systems, however, are characterized by a variety of modes including private (automobile), public transit (bus, suburban rail, light rail, and subway), and various combinations of these. Analysis reveals that the nested logit model based on the assumption of groupwise similarities among modes is not a suitable modeling tool in such situations. A cross-nested model that is derived from the generalized extreme value class and that can be thought of as a generalization of the nested logit model is proposed. The model takes into account the cross similarities between different pure and combined modes. The cross-nested structure allows for the introduction of the differentiated measurement of pairwise similarities among modes as opposed to the inflexible groupwise similarities permitted by the nested logit model. The proposed model is described, and it is compared with alternative modeling constructs.
A new link-nested logit model of route choice is presented. The model is derived as a particular case of the generalized-extreme-value class of discrete choice models. The model has a flexible correlation structure that allows for overcoming the route overlapping problem. The corresponding stochastic user equilibrium is formulated in two equivalent mathematical programming forms: as a particular case of the general Sheffi formulation and as a generalization of the logit-based Fisk formulation. A stochastic network loading procedure is proposed that obviates route enumeration. The proposed model is then compared with alternative assignment models by using numerical examples.
Intra-household interactions constitute an important aspect in modeling activity and travel-related decisions. Recognition of this importance has recently produced a growing body of research on various aspects of modeling intra-household interactions and group decision-making mechanisms as well as first attempts to incorporate intra-household interactions in regional travel demand models. The previously published research works were mostly focused on time allocation aspect and less on generation of activity episodes, trips, and travel tours that are necessary units for compatibility with regional travel demand models. Also, most of the approaches were limited to household heads only and did not consider explicitly the other household members as acting agents in the intra-household decision making. A model is proposed for joint choice of daily activity pattern (DAP) types for all household members that explicitly takes into account added group-wise utilities of joint participation in the same activity. The model is based on the aggregate description of individual DAP types by three main categories -mandatory travel pattern, non-mandatory travel pattern, and at-home pattern. Important intra-household interactions can be captured already at this aggregate level. A choice structure considers all possible combinations of DAPs of all household members as alternatives. Utility function of each alternative includes components corresponding to each individual DAP type as well as group-wise interaction terms that correspond to joint choice of the same pattern by several household members. Statistical analysis of intra-household interactions and estimation results of the choice model are presented. The model estimation has confirmed a strong added utility of joint choice of the same pattern for such person types as non-worker or part time worker in combination with child, two retired persons, two children, and others. The proposed model represents a part of the advanced regional model system being developed for the Atlanta Regional Commission.
In current practice, regional models are limited in their capability to analyze policies involving changes and improvements to airports (and their services) and ground access transportation. Typically, airports are treated only as employment centers or as special generators. Important and distinct features of air passenger travel affecting trip distribution and mode choice are rarely modeled explicitly. This paper presents the development of a joint airport and ground access mode choice model for the New York City metropolitan region based on an extensive survey of airport users. Unlike travel to and from most U.S. cities, air passengers flying to and from the New York region face a nontrivial choice of airports and ground access modes (including premium transit options). A nested logit model was formulated with airport choice at the upper level and ground access mode choice at the second level; however, a multinomial logit model was found to be statistically preferable. Results indicate that air passenger travel behavior is significantly different for business and nonbusiness travelers. Overall, willingness to pay for trips to and from the airport is much higher than for regular intracity trips. Average yield, access time, and access cost are the most important determinants of air passenger's choice; demographics and trip characteristics are also significant. The developed tool was used for a comprehensive study of airport development alternatives in the New York region and is seen as the platform for additional data development and model extensions for future studies of air passenger service planning in the New York megaregion.
The paper describes recent experience with the application of an innovative Global Positioning System (GPS)–assisted prompted recall (PR) method for a large-scale household travel survey (HTS) in Jerusalem, Israel. The survey was designed to support development of an advanced activity-based model (ABM). The requirements for an HTS to support an advanced ABM are discussed, and the corresponding decisions for survey methods are substantiated. Development of an advanced ABM requires individual records for the entire daily pattern without gaps, missing trips, overlaps, or other data inconsistencies found in a conventional HTS. A consistent record of joint activities and trips of multiple household members is essential. In addition, high levels of spatial and temporal resolution are required. The GPS-assisted PR survey has been identified as the most promising methodology for meeting these requirements. The experience of the first phase of the Jerusalem HTS in 2010 proved the feasibility of the GPS-PR method for all population sectors including specific Orthodox Jewish and Arab populations, which typically featured large household sizes. Various structural comparisons of trip and tour rates obtained during the first phase of the Jerusalem GPS-assisted HTS (3,000 households) with the non-GPS surveys previously implemented in Jerusalem and several metropolitan regions in the United States as well as comparisons between the GPS and non-GPS subsamples within the Jerusalem HTS were made. The results confirmed the ability of the GPS-PR approach to create full and consistent daily records of individual activity travel patterns and practically eliminate the underreporting issues that have plagued HTS.
A substantial portion of regional travel is implemented by household members who travel together, primarily to participate in a shared household activity. Joint household travel is not explicitly accounted for in most regional travel models in which the unit of travel (either trip or tour) is considered for each person separately at each modeling stage—generation, mode, destination, and time-of-day choice. In addition, statistical evidence demonstrates that the vast majority of shared-ride travel consists of joint household travel. A modeling approach that distinguishes shared activity-based joint household travel from arranged interhouse-hold carpooling is clearly desirable to support accurate forecasts of shared-ride travel, critical in the evaluation of high-occupancy vehicle lanes or the adoption of toll strategies differentiated by occupancy levels. A range of aspects of joint travel both with empirical evidence and with discussion of modeling issues are addressed. A set of joint travel models is presented that has been estimated with the mid-Ohio regional travel household-interview survey. The model reported is one of the innovative components of the tour-based travel demand modeling system that has been developed for the Mid-Ohio Regional Planning Commission.
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