Milad Ghasri

How Should Travel Demand and Supply Models Be Jointly Calibrated

Calibration is a critical aspect of model development that has long been recognized by researchers as a challenging issue. In particular, difficulties arise when the observed data used for calibration do not match the model output, which is the case in the majority of transport planning models. In the traditional calibration process, the origin–destination (OD) matrices are the key interface between demand and supply models, which could lead to issues when observed traffic link counts are used to update the OD matrix, causing a loss of key demand characteristics in the process. Developing a unified structure for modeling both demand and supply requires a calibration process that meets the requirements of both types of models, a serious issue which has received less attention in the literature. In this paper, the existing processes of developing and integrating demand and supply models are discussed and then examined using a case study in the Melbourne area. The numerical results show that the standard OD calibration procedure causes unrealistic changes in the OD matrix. Finally, some possible solutions to address the current limitations in development of a unified structure are discussed.

Investigating the Internal Compromise Between Wife and Husband’s Commute Time Changes in Residential Relocation

This study investigates how employed members in a household compromise their commute times when deciding about the location of household’s living place. The hypothesis of an internal negotiation between household breadwinners is statistically tested using a longitudinal survey of “Household Income and Labour Dynamics in Australia” (HILDA). The residential relocation history of dual-worker households is extracted from HILDA and according to the variations in commute time before and after relocation a reciprocal model specification is proposed. The reciprocal model is then transformed to a linear model, and the test of overall significance is conducted to validate the hypothesis. It is found that the household structure and wife’s job type have significant impacts on how breadwinners adjust their commute times in response to their partner’s conditions.

Comparing Survival Analysis and Discrete Choice Specifications Simulating Dynamics of Vehicle Ownership

Modeling travel-related decisions of transport system users is the core of many behavioral travel demand models. It is of great significance to use these models for planning purposes in which decisions of individuals are simulated for specific time intervals or on a continuous dimension until the target year. Discrete choice and survival analysis methods are two popular econometric structures to model and forecast time-dependent outcomes. This paper elaborates the conceptual and practical differences between these two methods in the context of vehicle ownership modeling. There are meaningful differences between these two methods including data preparation approaches, interpretations of the variable of interest in the model, and the simulation procedures. Further, this paper shows how negligent application of discrete choice methods for modeling time-to-event variables results in specification bias. This discussion paves the path for using hazard-based models in travel demand modeling, as the application of these models have been quite limited compared with their capacity.

A competing survival analysis for housing relocation behaviour and risk aversion in a resilient housing market

Residential relocation decision making is a complicated process, and modelling this complex course of actions requires careful scrutinisation of different aspects. The relocation decision comprises several different decisions, including the reason for the relocation, relocation timing, and attributes of the desired residence. Among these decisions needing to be taken, the reason for relocation and its timing are decided earlier than others. Depending on the variant reasons and motivations for relocating, its timing may be accelerated or decelerated. Relocation usually occurs because of a multiplicity of reasons, which necessitates using a multivariate model for relocation decision making that is jointly modelled with the timing decision. A competing accelerated failure model to jointly formulate these decisions. The housing search literature emphasizes on the importance of considering financial risk acceptance level of decision makers in residential relocation decision models. Therefore, a binary logit model is used to model whether the decision maker is financially risk averse or not. This paper used longitudinal data collected in Australia from the Household, Income, and Labour Dynamics in Australia Survey. Further, the impact of group decision making on residential relocation is captured in this paper through the information provided in Household, Income, and Labour Dynamics in Australia Survey regarding the manner in which decisions are made within households.