Taka Morikawa

Extended Framework for Modeling Choice Behavior

We review the case against the standard model of rational behavior and discuss the consequences of various ‘anomalies’ of preference elicitation. A general theoretical framework that attempts to disentangle the various psychological elements in the decision-making process is presented. We then present a rigorous and general methodology to model the theoretical framework, explicitly incorporating psychological factors and their influences on choices. This theme has long been deemed necessary by behavioral researchers, but is often ignored in demand models. The methodology requires the estimation of an integrated multi-equation model consisting of a discrete choice model and the latent variable model system. We conclude with a research agenda to bring the theoretical framework into fruition.

Discrete choice models incorporating revealed preferences and psychometric data

This paper proposes a methodology for incorporating psychometric data such as stated preferences and subjective ratings of service attributes in econometric consumers discrete choice models. Econometric formulation of the general framework of the methodology is presented, followed by two practical submodels. The first submodel combines revealed preference (RP) and stated preference (SP) data to estimate discrete choice models. The second submodel combines a linear structural equation model with a discrete choice model to incorporate latent attributes into the choice model using attitudinal data as their indicators. Empirical case studies on travel mode choice analysis demonstrate the effectiveness and practicality of the methodology.

Feasibility of Using Taxi Dispatch System as Probes for Collecting Traffic Information

Using commercial vehicle fleets as probes may be a cost-effective method for obtaining real-time traffic information. Because the taxi dispatch system automatically records the location of a taxi traveling in an urban network, large quantities of real-time travel data can be obtained at low cost. The reliability of this information about real-time traffic conditions, however, has not been investigated. This study examines the feasibility of using taxi dispatch systems as probes for real-time traffic surveillance. The examination focuses on the uncertainties in the data provided by the two types of wireless communications systems—analog and digital Multi Channel Access (MCA)—that are used for dispatching taxis. The study reveals that the digital MCA wireless system is much better than the analog wireless system for data transmission. This article exemplified that selection of longer road segments helps to greatly reduce traffic surveillance errors. Finally, this article discusses the lessons learned from this study and the limitations that must be overcome before the system can be widely deployed.

Feasibilities and Challenges of Probe Technologies for Real-Time Traffic Data Collection

Probe vehicles are playing an increasingly important role in the field of intelligent transportation systems (ITS), and showing high value for various applications over the last decade. Recent advances of probe vehicle technologies in Japan are explored by reviewing the existing studies in both academic fields and ITS practice projects. The methods of data collection and data processing are summarized, which is followed by a brief review of recent attentions and the possible solutions. In order to enhance the feasibility of probe vehicles for real-time traffic surveillance through the entire road network, this paper tries to identify some unresolved issues that may have impacts on the reliability of obtained real-time traffic data and the efficiency of data collection. Four addressed issues include: error propagation of map matching, the bias in link travel time estimation, lower accuracy of link travel time measurement through infrequent observations, and the efficiency in area coverage.

EFFICIENT LINK TRAVEL TIME ESTIMATION FOR SIGNALIZED LINK BY SMALL SIZE PROBE REPORTS

For probe vehicle system, there are only few travel time data (sample) available for real-time link travel time estimation due to limited number of probe vehicles. However, the population of link travel time (travel times of all vehicles) has large variance. In this circumstance, it is difficult to reliably estimate the population mean by the sample mean directly. In this paper, the population is redefined by the link travel times of such vehicles which have through movements at upstream and downstream intersections. However, there are still two groups of vehicles (without delay and with delay) with significantly different travel time. The relationship between the three variables (two means of the groups and the portion of the first group) is analyzed and an estimation method based on the relationship is proposed. The comparison between the new and the conventional method shows that the proposed method can provide more precise estimation result.