Implicit choice set generation in discrete choice models: Application to household auto ownership decisions

Latent choice set models that account for probabilistic consideration of choice alternatives during decision making have long existed. The Manski model that assumes a two-stage representation of decision making has served as the standard workhorse model for discrete choice modeling with latent choice sets. However, estimation of the Manski model is not always feasible because evaluation of the likelihood function in the Manski model requires enumeration of all possible choice sets leading to explosion for moderate and large choice sets. In this study, we propose a new group of implicit choice set generation models that can approximate the Manski model while retaining linear complexity with respect to the choice set size. We examined the performance of the models proposed in this study using synthetic data. The simulation results indicate that the approximations proposed in this study perform considerably well in terms of replicating the Manski model parameters. We subsequently used these implicit choice set models to understand latent choice set considerations in household auto ownership decisions of resident population in the Southern California region. The empirical results confirm our hypothesis that certain segments of households may only consider a subset of auto ownership levels while making decisions regarding the number of cars to own. The results not only underscore the importance of using latent choice models for modeling household auto ownership decisions but also demonstrate the applicability of the approximations proposed in this study to estimate these latent choice set models.     

Inference on mode preferences,vehicle purchases,and the energy paradox using a Bayesian structural choice model

Discrete choice modeling is experiencing a reemergence of research interest in the inclusion of latent variables as explanatory variables of consumer behavior. There are several reasons that motivate the integration of latent attributes, including better-informed modeling of random consumer heterogeneity and treatment of endogeneity. However, current work still is at an early stage and multiple simplifying assumptions are usually imposed. For instance, most previous applications assume all of the following: independence of taste shocks and of latent attributes, exclusion restrictions, linearity of the effect of the latent attributes on the utility function, continuous manifest variables, and an a priori bound for the number of latent constructs. We derive and apply a structural choice model with a multinomial probit kernel and discrete effect indicators to analyze continuous latent segments of travel behavior, including inference on the energy paradox. Our estimator allows for interaction and simultaneity among the latent attributes, residual correlation, nonlinear effects on the utility function, flexible substitution patterns, and temporal correlation within responses of the same individual. Statistical properties of the Bayes estimator that we propose are exact and are not affected by the number of latent attributes.     

Tour-based mode choice modelling as the core of an activity-based travel demand modelling framework: a review of state-of-the-art

ABSTRACT

The paper presents a critical review of the methodological approaches used in tour-based mode choice models within the activity-based modelling frameworks. Various components of the activity-based models, such as activity type choice, activity location choice, and activity duration have already matured significantly. However, the mode choice component is often simplified in many ways. Both trip-based and tour-based approaches are used in many cases. However, the tour-based approach is considered to be the most relevant to the activity-based modelling framework. This paper presents a synthesis of the strengths and weaknesses of existing tour-based mode choice models. The previous studies on tour-based mode choice models are grouped into seven categories, ranging from simplified main tour mode to complex dynamic discrete choice models. Besides, challenges with data-hungry models, simulation-based models and static models are discussed elaborately. In conclusion, it proposes a few methodological suggestions for researchers and practitioners for finding an appropriate mode choice modelling framework for activity-based models. In addition, the paper also provides a guideline on how to incorporate automated vehicles and Mobility-as-a-Service within the framework of tour-based mode choice models.     

Empirical flow-density and speed-spacing relationships: Evidence of vehicle length dependency

Traffic flow theory has come to a point where conventional, fixed time averaged data are limiting our insight into critical behavior both at the macroscopic and microscopic scales. This paper develops a methodology to measure relationships of density and vehicle spacing on freeways. These relationships are central to most traffic flow theories but have historically been difficult to measure empirically. The work leads to macroscopic flow-density and microscopic speed-spacing relationships in the congested regime derived entirely from dual loop detector data and then verified against the NGSIM data set. The methodology eliminates the need to seek out stationary conditions and yields clean relationships that do not depend on prior assumptions of the curve shape before fitting the data. Upon review of the clean empirical relationships a key finding of this work is the fact that many of the critical parameters of the macroscopic flow-density and microscopic speed-spacing relationships depend on vehicle length, e.g., upstream moving waves should travel through long vehicles faster than through short vehicles. Thus, the commonly used assumption of a homogeneous vehicle fleet likely obscures these important phenomena. More broadly, if waves travel faster or slower depending on the length of the vehicles through which the waves pass, then the way traffic is modeled should be updated to explicitly account for inhomogeneous vehicle lengths.     

组合式堵漏箱堵漏过程中的水压作用机理

利用动量定理推导了组合式堵漏箱不同结构形式处于不同工况时的动量方程，探讨了堵漏板垂直堵漏、堵漏板斜置堵漏、堵漏箱垂直堵漏、堵漏箱斜置堵漏等四种工况下堵漏作业过程中的水压作用机理，最后通过堵漏试验对理论分析结果进行了验证。结果表明，理论分析结果与试验现象基本吻合，可以用于组合式堵漏箱的水压计算和测试依据。     

大数据背景下重庆市综合交通模型维护升级

利用传统交通调查数据开展交通模型维护升级工作存在抽样率低、样本量小、人工成本高、精度低、实施难度大等多种现实问题.在大数据技术不断更新完善的背景下,有必要探索新的模型维护升级技术和方法.首先,阐述重庆市交通大数据的发展历程、数据类型、数据采集与数据格式.其次,在重庆市综合交通模型的框架结构中,分别利用大数据资源探索公共汽车线网的构建、各等级道路流量延误函数标定、常住人口和就业岗位分析、出行分布特征分析和公共交通出行需求分析等相关技术方法.最后,以重庆市综合交通模型的应用实践成果验证模型的可靠性和准确性.     

Is car drivers’ response to congestion charging schemes based on the correct perception of price signals?

This paper deals with the question of whether the capability of car drivers to estimate the cost of a new hypothetical, highly differentiated congestion charge influences their decision to change travel behaviour. The analysis makes use of an integrated choice and latent variable model (ICLV) which merges classic choice models with the structural equation approach (SEM) for latent variables. This hybrid model improves the explanatory power considerably compared with a conventional discrete choice model. The results suggest that charge complexity decreases the resistance in considering behavioural changes. Car drivers tend to avoid a travel option where the price is not known beforehand, a phenomenon known as ambiguity avoidance.     

Adaptive traffic parameter prediction: Effect of number of states and transferability of models

Traffic parameters can show shifts due to factors such as weather, accidents, and driving characteristics. This study develops a model for predicting traffic speeds under these abrupt changes within regime switching framework. The proposed approach utilizes Hidden Markov, Expectation Maximization, Recursive Least Squares Filtering, and ARIMA methods for an adaptive forecasting method. The method is compared with naive and mean updating linear and nonlinear time series models. The model is fitted and tested extensively using 1993 I-880 loop data from California and January 2014 INRIX data from Virginia. Analysis for number of states, impact of number of states on forecasting, prediction scope, and transferability of the model to different locations are investigated. A 5-state model is found to be providing best results. Developed model is tested for 1-step to 45-step forecasts. The accuracy of predictions are improved until 15-step over nonadaptive and mean adaptive models. Except 1-step predictions, the model is found to be transferable to different locations. Even if the developed model is not retrained on different datasets, it is able to provide better or close results with nonadaptive and adaptive models that are retrained on the corresponding dataset.     

A study of economic efficiency in port security inspection

The purpose of this paper is to study an economic efficiency for the prediction of additional truck turnaround time and for determining the number of the port security inspection equipment required at a terminal inspection station. The economic efficiency with six base models was developed to assist terminal operators' decision‐making. In addition, this study developed an optimal procedure that terminal operators could use to optimally run in terms of various statistics processes including exponential, deterministic, and others, seeking a solution that was beneficial for both terminal operators and truckers. As a result of this research of the additional cargo turnaround time for port security delay, the following conclusion can be drawn and made. The average additional delay time in the inspection station is very dependent on the inspection rate of the lower stage. The higher weighted inspection time based on raising security level allows less number of trucks to be inspected, which will derive high delay in the inspection station. Increase of rate of Green Lane usage will allow a decrease in the arrival rate, which may derive improvement of inspection equipment efficiency and average delay time at the inspection station. In multiple stage model, total number of trucks and delay time very closely follow those of low inspection stage rate and number of inspection units. Free Lane is to be followed by Customs‐Trade Partnership Against Terrorism and standardization of customs, packing, loading and unloading, documents, procedure, and exchange working in each country. Copyright © 2012 John Wiley & Sons, Ltd.