Towards disaggregate dynamic travel forecasting models

Mobility as a Service: A Critical Review of Definitions, Assessments of Schemes, and Key Challenges

“…Dissatisfaction with trip-based models, policy needs for detailed sociodemographic information for the trip at individual/household level but mostly the behavioural inadequacy of this approach has led to the emergence of disaggregate forecasting models (Bhat & Koppelman, 1999). Both supply and demand models have evolved from static to dynamic capturing travel behaviour in terms of time-dependent conditions and information, and from an aggregate to a disaggregate representation of travel, focusing on the heterogeneity of individual traveling (Ben-Akiva, Bottom, Gao, Koutsopoulos, & Wen, 2007).…”

Transport Modeling With a Purpose: How Urban Systems Design Can Bridge the Gaps Between Modeling, Planning, and Design

“…STATIC, AGGREGATE, AND DETERMINISTIC MODELS Travel forecasting models can take on many different forms, depending on the intended use, the available and useable data for inputs and assumptions, and the tools, whether open-source or not. Conventional travel forecasting models date back to the late 1960s and are characterized by static, aggregate, and deterministic supply and demand modules and relationships [5]. The four-step model is the standard, and most simplified, version of a travel forecasting model with the steps of Trip Generation, Trip Distribution, Mode Choice, and Route Choice (or Trip Assignment) which provide the mechanism to determine equilibrium flows in a particular network [7].…”

“…The four-step model is the standard, and most simplified, version of a travel forecasting model with the steps of Trip Generation, Trip Distribution, Mode Choice, and Route Choice (or Trip Assignment) which provide the mechanism to determine equilibrium flows in a particular network [7]. Over time, there have been modeling advancements on both the supply-side and the demand-side, moving from static to dynamic considering the traveler choices of time, mode, and chosen route, from aggregate to disaggregate considering the individual traveler or household as an agent instead of a part of a more generalized population, and from deterministic to stochastic considering the minor to major changes that can happen to both demand and available supply as travelers make different choices [5]. However, these advancements in travel forecasting and modeling have not been represented in practice, aside from many regions moving to activity-based travel demand models [8].…”

“…As travel forecasting models are commonly used to predict the flows and conditions that result from the interaction between demand for travel by transportation system users and the travel operations that the system supplies to the users [3]- [5], there have become "standard" practices that lack critical thinking of the process that produces the final results of said analyses. Transportation modeling is meant to impact planning and design, and therefore the public interest, in a positive manner -using the travel forecasting models to be purposeful, instead of reactive, in design -but over time have become less standardized as assumptions within the models have become more flexible.…”

An enhanced SPSA algorithm for the calibration of Dynamic Traffic Assignment models

“…Simulation-based DTA has more detailed modeling abilities by capturing individual drivers' behaviors and the sophisticated interactions between the demand and supply, and therefore has been applied more frequently in real-world traffic systems to evaluate network performance, including flow, density, speed, travel time, and queues. There are numerous examples of successful adoption of simulation-based DTA for traffic planning (see, e.g., Ben-Akiva et al, 2007;Rathi et al, 2008;Balakrishna et al, , 2009Sundaram et al, 2011;Florian et al, 2001;Barcelo and Casas, 2006;Ziliaskopoulos et al, http://dx.doi.org/10.1016Ziliaskopoulos et al, http://dx.doi.org/10. /j.trc.2014.006 0968-090X/Ó 2014 Elsevier Ltd. All rights reserved.…”