A composite attitude-behavior model of traveler decision making

A general model for the behavioral analysis of traveler decision making is described. The model is one which blends research in human information processing with probabilistic choice theory. The model is used as a basis for discussing two studies of grocery store choice behavior. In these studies, algebraic models of individuals' grocery store preferences which are derived using controlled hypothetical choice situations are related to real-world choice behavior. Results show a high monotonic correspondence between laboratory and real-world behavior. Implications of the research for existing approaches to behavioral modeling are described.     

Comparative analysis of traveler destination choice models by method of sampling alternatives

In a destination choice model, it is important to introduce alternatives that have been adequately aggregated into traffic analysis zone levels based on spatial similarities and feasibility of analysis, because considering every spatial location possible for the traveler as an elemental alternative is intractable in terms of data management and analysis. In this study, we derive strata for alternative sets through simple random sampling and stratified importance sampling based on the concept of Moran’s I. As a result of comparative analysis, we are able to reduce errors by drawing an adequate number of samples for the destination choice model’s choice alternative sets based on measures of spatial similarity.     

An integrated framework for embedding large-scale dynamic traffic assignment models in advanced traveler information systems

In recent years, increasing attention has been drawn to the development of various applications of intelligent transportation systems (ITS), which are credited with the amelioration of traffic conditions in urban and regional environments. Advanced traveler information systems (ATIS) constitute an important element of ITS by providing potential travelers with information on the network's current performance both en-route and pre-trip. In order to tackle the complexity of such systems, derived from the difficulty of providing real-time estimations of current as well as forecasts of future traffic conditions, a series of models and algorithms have been initiated. This paper proposes the development of an integrated framework for real-time ATIS and presents its application on a large-scale network, that of Thessaloniki, Greece, concluding with a discussion on development and implementation challenges as well as on the advantages and limitations of such an effort.     

Driver recruitability for advanced traveler information system experiments

A number of Advanced Traveler Information System (ATIS) field experiments are being undertaken to study the effectiveness of the ATIS concept in ameliorating traffic congestion and reducing delays. Many of these experiments require the participation of private drivers willing to allow in-vehicle navigation units to be installed in their vehicles over an extended period of time. A critical part of any ATIS field experiment is the selection or recruitment of private drivers to fulfill the multi-purpose participation needs of the ATIS experiment. To provide an informed basis for designing such a driver recruitment effort, it is important to understand the factors affecting driver recruitability or “willingness to participate.” This research presents the results of a quantitative analysis of driver recruitability conducted to aid in the design of recruitment procedures for ADVANCE (Advanced Driver and Vehicle Advisory Navigation Concept), the largest ATIS field experiment of its kind. The approach used a telephone survey to assess driver willingness to participate in the ADVANCE field experiment and to explore variations in that willingness among different drivers and across characteristics of the ADVANCE system and experimental design. The results indicate that the willingness to participate in the ADVANCE field test is greater for men, persons who hold executive or managerial occupations, individuals who drive extensively, persons who use electronic devices such as personal computers and car phones regularly, and persons who have positive beliefs regarding the usefulness of the ADVANCE concept. The result also suggest that drivers' willingness to participate is not strongly affected by monitoring/reporting requirements such as responding to surveys, mailing electronically stored records of system operation, and periodic service requirements. However, the willingness decreases considerably if drivers have to bear the financial responsibility for damage of the navigation equipment and any equipment-caused electrical failures to the car. Finally, the incentive of a lottery prize raises the level of participation willingness. These results have important implications for the recruitment effort, both in terms of recruiting drivers for participation in the demonstration and specifying the operational details of the field test.     

The value of advanced traveler information systems for route choice

Over the next few years, driver behavior should become more informed with the advent and deployment of in-vehicle navigation systems. This paper analyzes systems that provide the driver the fastest path between his or her current location and final destination, updated in real-time to consider recurring and non-recurring congestion. The traveler’s full cost per trip is a bundle comprised of both expected travel time and its reliability. This paper explores these topics from a theoretical economic perspective and then simulates stylized cases. Simulation results indicate that typical information benefits are at a maximum on the precipice of congestion, when vehicles are arriving at a rate of 95% of the capacity, while non-recurring congestion benefits are much greater.     

Structural equation modeling for national travel demand: an examination of the relationships between communication modes

This paper examines the relationships among different transportation modes, and between transportation and telecommunications, by applying the structural equation modeling (SEM) technique. For this purpose, we collected and compiled time series data on national travel demand, and socioeconomic and telecommunications conditions in Taiwan, and built national travel demand models using SEM. The estimation results show that the relationship between telecommunications and transportation demand (either car ownership or public transportation) is more complementary than substitutional. Moreover, car ownership is a type of inelastic necessity good, and its relationship with public transportation is more substitutional than complementary. Finally, among the three public transportation modes – rail, bus and domestic air – it is found that air is weakest in terms of competitive power. From the viewpoint of long-term forecasting trends, the bus holds its competitive power in comparison with other public transportation modes and would not be replaced in the future.     

An advanced traveler general information system for Fresno,California

This study estimates the effects of an advanced traveler general information system (ATGIS), which includes fuel consumption and health-related emissions cost information on transportation network users’ travel choice behavior for recurrent congestion conditions. The effects are estimated using four different formulations based on four different behavioral assumptions. Incorporating stochastic features in link cost estimation rather than in route choice, we provide a novel modeling approach that enables us to use transportation planning models of major metropolitan areas without a need for major computationally-expensive changes in the existing models. We examined the effects of an ATGIS on the Fresno, CA, road network and found several interesting results. First, the ATGIS impact is closely related to pre-system (prior to the implementation of an ATGIS) perceived fuel and emissions costs. Total travel time in the city can be reduced by 17% (no pre-system perceived costs) to 1% (accurate pre-system perceived costs), and even increased by 1% (higher-than-actual pre-system perceived costs). Second, the addition of emissions costs, although negligible relative to fuel and time costs, can effectively reduce total system-wide travel time by up to 1% and fuel consumption by up to 0.6% during peak hours. Third, the ATGIS can reduce annual social costs by as much as $1053 million (high gas price, no pre-system perception) to $48 million (medium gas price, accurate pre-system perception), which are comparable to social cost savings by a congestion pricing (CP) scheme in the study area.     

Empirical analysis of freeway flow-density relationships

Many researchers have reported on the occurence of gaps in freeway speed-density and flow-density data and have suggested that discontinuous functions are necessary to properly describe “observed” traffic behavior. This paper investigates the flow-occupancy (spot-density) relationship using an extensive data set collected on the Queen Elizabeth Way in Ontario. Daily time-traced plots of 5-minute average flow rates versus occupancy were analyzed. Results indicate that there is another interpretation of gaps in data, which does not imply a discontinuous function, but rather, an inverted V shape (continuous, but not continuously differentiable). Three conclusions were reached: (a) it is essential to provide details of data collection locations if one is to know whether a particular pattern in resulting data represents a “true” relationship, or just the specifics of a particular place; (b) there are clear advantages to examining daily time traces of traffic behavior, rather than relying on scatter diagrams of numerous days of accumulated data; and, (c) previously documented arguments for a discontinuous flow-occupancy relationship do not seem convincing, because knowledge of daily operations at a particular location could easily explain the occurence of gaps in the data.     

Seattle smart traveler: dynamic ridematching on the World Wide Web

Seattle Smart Traveler (SST) is an application of World Wide Web (WWW) technology to test the concept of automated dynamic rideshare matching. In SST, the rideshare clientele interact with the rideshare system using only WWW pages. SST collects spatial and temporal trip information using a series of WWW pages, performs a match using structured query language (SQL) specifications to a database engine, and supports both the standard phone-based contact methodology as well as two new, unique e-mail-based contact methodologies. SST was operated in parallel to a traditional, regional rideshare system for one year, and the two systems were marketed to the user community on a side-by-side basis. SST and the traditional system acquired approximately the same number of new users over a nine-month test period; however, there was little overlap in the population using the two parallel systems. SST demonstrates that there is a user population that can be reached using Internet technologies for immediate/dynamic ridematching that is not reached by traditional ridematch programs. This paper also reports a new statistical model for quantifying rideshare matching and carpooling. The model is validated using the SST experimental results, and the model demonstrates that the carpooling process is a quadratic function of the number of users participating.     

Exploring key determinants of travel satisfaction for multi-modal trips by different traveler groups

Using a primary dataset from an experimental survey in eight European cities, this study identified the key determinants of satisfaction with individual trip stages as well as overall journey experience for different travel modes and traveler groups. Multivariate statistical analyses were used to examine the relationships between overall satisfaction and travel experience variables, trip complexity, subjective well-being indices, travel-related attitudes as well as individual- and trip-specific attributes. The results indicate that for certain traveler groups, such as women, young and low-income or unemployed travelers, there are distinctive determinants of satisfaction with trip stages for various travel modes. The results also indicate that satisfaction with the primary trip stage is strongly linked to overall trip satisfaction, while satisfaction levels with access and egress trip stages are strongly related to satisfaction with the primary trip stage. Past experience, traveler expectations and attitudes, and the emotional state of travelers are also significant explanatory variables for travel satisfaction. The results indicate that when an individual consciously chooses a particular travel mode, they will report a higher level of satisfaction with that chosen mode. Notwithstanding, while past experience highly influences an individual’s current travel satisfaction, the more they travel with the current mode, the less satisfied they are with their choice. The results of this study highlight the importance of gaining a better understanding of the interaction between instrumental variables and non-instrumental variables at different trip stages and the influence on user preferences, satisfaction and decision-making processes.     

Real-time traveler information for urban arterials: a method for selecting metropolitan routes of significance

Although multi-criteria analysis (MCA) has been commonly used to guide transportation decisions related to traditional infrastructure, limited applications are reported for intelligent transportation systems. The objective of this study is to apply MCA for selecting arterial routes for real-time traveler information, to conform with recent US federal regulations. This study applies the method in two metropolitan areas and the paper describes which criteria were chosen and how important each were considered. In all, this study guided the selection of seven arterial routes for deployment of real-time traveler information collection and dissemination. This study demonstrates how a transportation agency can apply MCA for traveler information planning and the method provides value for other agencies seeking to come into compliance with traveler information regulations.     

单线铁路模板台车的结构分析

文章主要介绍了单线铁路模板台车的工作原理和结构,应用有限元软件对模板台车进行了整体的结构分析,并依据分析结果对模板台车的结构设计提出了改进建议,为其以后的优化设计和参数设计提供了理论依据.     

Additive models for network data envelopment analysis in the presence of shared resources

This paper studies the problem of evaluating the relative efficiency of a set of specialized and interdependent decision-making subunits that make up a large decision-making unit (DMU). The paper develops a data envelopment analysis (DEA) approach for measuring the efficiency of decision processes which can be divided into two stages. In these processes the first stage uses its own inputs to generate outputs which a part of these outputs become the inputs to the second stage. Moreover, DMUs use shared input sources in both operation stages. This paper provides a set of additive models which measure the performance of two-stage network DEA processes with shared inputs. Numerical examples show the applicability of the approach.     

A study of traveler behavior under traffic information-provided conditions in the Beijing area

ABSTRACT

The quality of traffic information has become one of the most important factors that can affect the distribution of urban and highway traffic flow by changing the travel route, transportation mode, and travel time of travelers and trips. Past research has revealed traveler behavior when traffic information is provided. This paper summarizes the related study achievements from a survey conducted in the Beijing area with a specially designed questionnaire considering traffic conditions and the provision of traffic information services. With the survey data, a Logit model is estimated, and the results indicate that travel time can be considered the most significant factor that affects highway travel mode choice between private vehicles and public transit, whereas trip purpose is the least significant factor for private vehicle usage for both urban and highway travel.     

Structural equation approach to investigate trip-chaining and mode choice relationships in the context of developing countries

This paper investigates empirical relationships between trip chain type and mode class choice for developing countries. To formulate these two sets of decisions, four empirical models are developed using structural equation modeling (SEM). Those models are calibrated using one-month travel diary data collected in Dhaka city. SEM correlates the observed variables and identifies their relationship with trip-chaining type utility and mode class choice utility. The fitted models are selected based on statistical results and similarity with the real-life situation. Direct relationships between trip-chaining and mode choice utilities are found insignificant. However, several socio-demographic factors influence both simultaneously. Consequently, it is essential to consider mode class choice concurrently for modeling trip chains. This study also investigates the influencing factors for work-based and non-work-based trip chains separately and effects of road users’ heterogeneity. The research results can be utilized to perceive trip chain-mode choice patterns for developing countries.     

Measuring and enhancing the transferability of hidden Markov models for dynamic travel behavioral analysis

As an emerging dynamic modeling method that incorporates time-dependent heterogeneity, hidden Markov models (HMM) are receiving increased research attention with regards to travel behavior modeling and travel demand forecasting. This paper focuses on the model transferability of HMM. Based on a series of transferability and goodness-of-fit measures, it finds that HMMs have a superior performance in predicting future transportation mode choice, compared to conventional choice models. Aimed at further enhancing its transferability, this paper proposes a Bayesian conditional recalibration approach that maps the model prediction directly to the context data. Compared to traditional model transferring methods, the proposed approach does not assume fixed parameterization and recalibrates the utilities and the prediction directly. A comparison between the proposed approach and the traditional transfer-scaling favors our approach, with higher goodness-of-fit. This paper fills the gap in understanding the transferability of HMM and proposes a practical method that enables potential applications of HMM.

     

Measuring user benefits of changes in the transport system when traveler awareness is limited

This paper derives and illustrates measures for the ex ante evaluation of user benefits associated with improvements in the transport system. In contrast with conventional analyses, we assume that awareness among travelers of changes in the transport system is limited and grows over time. Specifically, we postulate that each day (trip) provides travelers with an opportunity to learn about changes that occurred recently in the transport system. This learning process may involve learning through direct experience and indirect learning through for example social networks or information provision. Our measure of user benefits incorporates the conventional logsum-measure as a special case (when full awareness is assumed) and has a closed form solution under reasonable error term assumptions. A numerical illustration provides a first sign of face validity. We derive and discuss a number of practical implications, and discuss possible model extensions.     

Modeling the effects of traveler information on freeway origin–destination demand prediction

The primary focus of this research is to develop an approach to capture the effect of travel time information on travelers’ route switching behavior in real-time, based on on-line traffic surveillance data. It also presents a freeway Origin–Destination demand prediction algorithm using an adaptive Kalman Filtering technique, where the effect of travel time information on users’ route diversion behavior has been explicitly modeled using a dynamic, aggregate, route diversion model. The inherent dynamic nature of the traffic flow characteristics is captured using a Kalman Filter modeling framework. Changes in drivers’ perceptions, as well as other randomness in the route diversion behavior, have been modeled using an adaptive, aggregate, dynamic linear model where the model parameters are updated on-line using a Bayesian updating approach. The impact of route diversion on freeway Origin–Destination demands has been integrated in the estimation framework. The proposed methodology is evaluated using data obtained from a microscopic traffic simulator, INTEGRATION. Experimental results on a freeway corridor in northwest Indiana establish that significant improvement in Origin–Destination demand prediction can be achieved by explicitly accounting for route diversion behavior.     

Simultaneous determination of the equilibrium market penetration and compliance rate of advanced traveler information systems

We consider a specific advanced traveler information systems (ATIS) whose objective is to reduce drivers’ travel time uncertainty with recurrent network congestion through provision of traffic information. Since the provided information is still partial or imperfect, drivers equipped with an ATIS cannot always find the shortest travel time route and thus may not always comply with the advice provided by ATIS. Thus, there are three classes of drivers on a specific day: drivers without ATIS, drivers with ATIS but without compliance with ATIS advice, drivers with ATIS and in compliance with ATIS advice. All three classes of drivers make route choice in a stochastic manner, but with different degree of uncertainty of travel time on the network. In this paper we investigate the interactions among the three classes of drivers in an ATIS environment using a multiple behavior stochastic user equilibrium model. By assuming that the market penetration of ATIS is an increasing function of the actual private gain (time saving minus the cost associated with system use) derived from ATIS service, and the ATIS compliance rate of equipped drivers is given as the probability of the actual travel time of complied drivers being less than that of non-complied drivers, we determine the equilibrium market penetration and compliance rate of ATIS and the resulting equilibrium network flow pattern using an iterative solution procedure.