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.     

Dynamics of commuting decision behaviour under advanced traveller information systems

This paper addresses departure time and route switching decisions made by commuters in response to Advanced Traveller Information Systems (ATIS). It is based on the data collected from an experiment using a dynamic interactive travel simulator for laboratory studies of user responses under real-time information. The experiment involves actual commuters who simultaneously interact with each other within a simulated traffic corridor that consists of alternative travel facilities with differing characteristics. These commuters can determine their departure time and route at the origin and their path en-route at various decision nodes along their trip. A multinomial probit model framework is used to capture the serial correlation arising from repeated decisions made by the same respondent. The resulting behavioural model estimates support the notion that commuters' route switching decisions are predicated on the expectation of an improvement in trip time that exceeds a certain threshold (indifference band), which varies systematically with the remaining trip time to the destination, subject to a minimum absolute improvement (about 1 min).     

A monopolistic market for advanced traveller information systems and road use efficiency

Advanced traveller information systems (ATIS) are likely to exhibit significant economies of scale in production and operation. Private provision would therefore typically occur under considerable market power. An important policy question is whether the resulting distortions would aggravate or reduce distortions in the transport market itself, notably external effects such as congestion. We consider such questions by presenting an integrated model that captures the interactions between a congested transport market and a monopolistic market for advanced traveller information systems (ATIS). Three market failures operate simultaneously: congestion on the road, a declining average benefit of information when information penetration rises, and monopolistic pricing by the provider of information. Some key results are as follows. Monopoly information pricing appears not to be the most attractive option from a system efficiency viewpoint. A subsidy in the information market can help realise a second-best optimum of road use. Relatively low uncertainty on the road and high information costs limit the monopolist’s profit on the information market, as well as relative system efficiency. While relatively inelastic demand for mobility, counter intuitively, negatively affects the monopolist’s profit, the relative social benefits from private information peak at intermediate demand elasticities.     

Recent success stories on integrated optimization of railway systems

Planning and operating railway transportation systems is an extremely hard task due to the combinatorial complexity of the underlying discrete optimization problems, the technical intricacies, and the immense size of the problem instances. Because of that, however, mathematical models and optimization techniques can result in large gains for both railway customers and operators, e.g., in terms of cost reductions or service quality improvements. In the last years a large and growing group of researchers in the OR community have devoted their attention to this domain developing mathematical models and optimization approaches to tackle many of the relevant problems in the railway planning process. However, there is still a gap to bridge between theory and practice (e.g. Cacchiani et al., 2014; Borndörfer et al., 2010), with a few notable exceptions. In this paper we address three individual success stories, namely, long-term freight train routing (part I), mid-term rolling stock rotation planning (part II), and real-time train dispatching (part III). In each case, we describe real-life, successful implementations. We will discuss the individual problem setting, survey the optimization literature, and focus on particular aspects addressed by the mathematical models. We demonstrate on concrete applications how mathematical optimization can support railway planning and operations. This gives proof that mathematical optimization can support the planning of railway resources. Thus, mathematical models and optimization can lead to a greater efficiency of railway operations and will serve as a powerful and innovative tool to meet recent challenges of the railway industry.     

Modeling user adoption of advanced traveler information systems: dynamic evolution and stationary equilibrium

This paper models the growth rate and the saturation market penetration level for advanced traveler information system (ATIS) products/services with heterogeneous drivers. The price of using and the benefit gained from ATIS services are considered two key factors in explaining the growth of adoption of ATIS products. The information benefit is measured as the travel time saving between equipped and unequipped drivers and evaluated by a mixed stochastic and deterministic network equilibrium model. A modified logistic type growth model is adopted to describe the cumulative adoption of ATIS products over years. The final stationary equilibrium level of ATIS market penetration is so determined that the value of the information provided will decline to the point at which no new users will find it advantageous to purchase that service. The endogenous growth and stationary equilibrium model of market penetration of ATIS services is useful for forecasting the growth process and the impacts on the system performance of ATIS.     

Exploration of route choice behavior with advanced traveler information using neural network concepts

A model of driver's route choice behavior under advanced traveler information system (ATIS) is developed based on data collected from learning experiments using interactive computer simulation. The experiment subjected drivers to 32 simulated days in which they were to choose between the freeway or a side road. A neural network model is used as a convenient modeling technique in this initial phase of the analysis. The results indicated that most subjects made route choices based mainly on their recent experiences. It was also demonstrated that route choice behaviors are related to the personal characteristics as well as the characteristics of the respective routes. Travel experiences have less effect on the choice of the side road compared to the freeway and the results indicate that the prediction accuracy of the model, the acceptance rate of advice, and the quality of advice are closely correlated. The model developed here was for advice consistently provided at a level of 75 percent accuracy. The paper concludes with a discussion of experimental limitations and suggestions for future research.     

Effect of advanced traveler information systems and road pricing in a network with non-recurrent congestion

The effect of the application of advanced transport information system (ATIS) and road pricing is studied in a transportation system under non-recurrent congestion. A stochastic network deterministic user equilibrium model (SNDUE) with elastic demand is formulated and used to evaluate the welfare and private impacts of different market penetrations of ATIS, together with road pricing for a simple network. Both marginal first-best road pricing and a second-best fixed road pricing are considered. The incentives of private users to use ATIS are analyzed and the characteristics of optimum tolls as a function of ATIS market penetration are shown. We conclude that ATIS is an efficient and necessary tool to reduce the effects of non-recurrent incidents in a transportation network, especially when non-recurrent congestion causes a significant deterioration of operational conditions of the network. If the impact of non-recurrent incidents on free flow costs is small or is reduced only to congestion effects, the use of road pricing would be more efficient. Social benefits obtained when jointly implementing ATIS and road pricing are practically the same whether first-best or second-best road pricing is used. Considering the private costs perceived by the network users, and the benefits experienced by equipped users, the maximum level of market penetration achieved could be limited because private benefits disappear after certain market penetration is obtained.     

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.     

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.     

Modeling user adoption of advanced traveler information systems: a control theoretic approach for optimal endogenous growth

This study is a subsequent development of the dynamic evolution model of the market penetration of advanced traveler information systems (ATIS) proposed by Yang and Meng [Transport. Res. A 35 (2001) 895]. In previous study we have shown that a benefit-driven, user-optimal ATIS market does not necessarily lead to a socially optimal growth and optimal stationary equilibrium level of market penetration of ATIS products or services. The current study proposes an optimal time-dependent service pricing strategy so as to minimize total system cost throughout the time horizon of growth or optimally reach a socially desirable target level of ATIS market penetration in a final stationary equilibrium. We formulate the problem of interest as an optimal control problem and propose an efficient solution algorithm together with a numerical demonstration of the characteristics of the study problem.     

Hierarchical evaluation scheme on technology sourcing for advanced public transport systems

Advanced public transport system (APTS) technologies have received much attention from industry researchers in recent years for their evident importance to economic growth. The development of critical APTS technology, such as the contact-less smart card (CSC), in newly industrialized areas receives its impetus from the experience of developed countries. The evaluation of technology sourcing with a higher growth potential in CSC technology has become a critical issue for Taiwanese firms. However, past research rarely emphasized it. This paper utilizes the grey statistical method with survey techniques and the analytic hierarchy process to develop an integrated evaluation model for solving the technology-sourcing problem. An empirical case of the CSC technology sourcing in Taiwan was chosen to demonstrate the application of the proposed model on this issue. The research results suggest that the application of the model provides a sensible path for company policy makers to effectively cope with the technology-sourcing evaluation problem.     

About the possibilities of using the renewable energy power sources on railway transport

Several electrification systems based on renewable energy power sources (first of all, solar energy) are discussed in respect to their applicability to railway transport and, in particular, to suburban electric trains. Two systems are considered with basic technical details and economic estimation, both including the onboard bank of batteries and the photovoltaic converters (PVC) of solar energy for compensation of energy expenses, which could be positioned either on stations or on wagon's roofs. Sun‐tracking systems and their effect on the solar energy conversion efficiency are discussed in application to stationary and moving PVC platforms. An analysis made shows that introduction of the “green” systems discussed will not only have positive ecological impact, but also can bring a notable economical effect even with today's components, while it could be considerably greater with the usage of new PVCs, which are being developed by the authors. Copyright © 2011 John Wiley & Sons, Ltd.     

The effects of information bias and riding frequency on noise annoyance to a new railway extension in Hong Kong

We investigate how two non-acoustic factors, information bias and riding frequency, can affect the annoyance response of an urban population to noise created by a new railway line. The study shows that information bias is asymmetrical. Respondents receiving only information on positive measures taken by the authority to reduce noise emission are more tolerant of the noise impact, but those receiving only critical views tend to be more annoyed because they feel that not all measures to reduce noise have been employed. Additionally people who use the line frequently are more tolerant to the noise impact than those who do not. Information bias seems to have a temporary masking effect over riding frequency lasting for a few weeks after railway opening. This suggest that whilst free flow of information provided by the authority can help alleviate annoyance response, encouraging the people affected to make use of the new infrastructure may be useful to reduce public resistance and noise annoyance.     

Interactive geovisualization of activity-travel patterns using three-dimensional geographical information systems: a methodological exploration with a large data set

A major difficulty in the analysis of disaggregate activity-travel behavior in the past arises from the many interacting dimensions involved (e.g. location, timing, duration and sequencing of trips and activities). Often, the researcher is forced to decompose activity-travel patterns into their component dimensions and focus only on one or two dimensions at a time, or to treat them as a multidimensional whole using multivariate methods to derive generalized activity-travel patterns. This paper describes several GIS-based three-dimensional (3D) geovisualization methods for dealing with the spatial and temporal dimensions of human activity-travel patterns at the same time while avoiding the interpretative complexity of multivariate pattern generalization or recognition methods. These methods are operationalized using interactive 3D GIS techniques and a travel diary data set collected in the Portland (Oregon) metropolitan region. The study demonstrates several advantages in using these methods. First, significance of the temporal dimension and its interaction with the spatial dimension in structuring the daily space-time trajectories of individuals can be clearly revealed. Second, they are effective tools for the exploratory analysis of activity diary data that can lead to more focused analysis in later stages of a study. They can also help the formulation of more realistic computational or behavioral travel models.     

Real options and flexibility analysis in design and management of one-way mobility on-demand systems using decision rules

This study explores the concepts of real options and flexibility analysis as an approach to address uncertain demand growth in mobility on-demand (MoD) vehicle-sharing systems, with the goal of improving expected lifecycle performance. As MoD systems are gaining popularity worldwide, they inevitably face significant uncertainty in terms of needs and customer demands. Designing, planning capacity deployment, and operating such system can be challenging, and require significant capital investments for companies and cities. Two distinct real options analysis (ROA) models are developed to evaluate and optimize flexible strategies for these systems, relying on a novel methodological approach to value flexibility based on decision rules. The decision-rule-based approach differs from standard ROA approaches used to quantify the value of flexibility in irreversible investment projects, typically based on dynamic programming. It emulates the decision-making process by capturing mathematically a triggering mechanism that determines when it is best to exercise the flexibilities embedded in the system design. Two prevalent types of MoD systems are studied in this paper as demonstration of the methodological framework: a station-based system where customers must pick up and return the vehicle at specific locations, and a free-floating system, where customers may pick up and drop the car anywhere within a certain area. A simulation-based approach is used to analyze the station-based system, which models the rebalancing operations from a micro-level perspective. The approach consists of a discrete event simulator for performance estimation, and an optimization algorithm for design space exploration that integrates a population-based search algorithm with Optimal Computing Budget Allocation (OCBA). For the free-floating system, an analytical model is developed where the decision rule is formulated into and solved using stochastic mixed integer programming (MIP). The study provides guidance to system operators on potential strategies for deploying MoD systems, considering explicitly uncertainty and flexibility as a value enhancing mechanism.     

Demand management of congested public transport systems: a conceptual framework and application using smart card data

Transportation - Transportation demand management, long used to reduce car traffic, is receiving attention among public transport operators as a means to reduce congestion in crowded public...     

Effects on driving behavior of congestion information and of scale of in-vehicle navigation systems

The purpose of this research was to compare the usage of a traditional paper map and electronic route maps during driving, and to consider the effects of congestion information and map scale sizes on driving performance, workload and subjective feelings. Experiments were conducted in desktop virtual driving environments with a 17-in. color monitor simulating driving environments and a 14-in. color monitor showing different kinds of navigation systems. A total of 20 undergraduate students of National Tsing Hua University were paid to participate in the Experiment I. The criteria for driving performance were trip duration, driving speed and number of navigation errors. Heart rate was measured as an index for workload. The 5-point Likert-type questionnaire was used to reflect the perceived nervousness, fatigue and task difficulty. Results indicated that the performance difference between a paper map and electronic route maps depended on the design characteristics of electronic route maps. Comparisons among four electronic maps revealed two significant main effects of congestion information and scale sizes on trip duration. Besides, it seemed that the availability of congestion information was useful for reducing navigation errors. Neither statistically significant main effects nor interaction was found on subjective feelings and driving speed. Another 18 subjects were used in the Experiment II to determine the optimum map scale size. Finally, the implications of the findings may provide suggestions on designing safer and more efficient in-vehicle navigation systems.     

Link travel time inference using entry/exit information of trips on a network

This paper studies link travel time estimation using entry/exit time stamps of trips on a steady-state transportation network. We propose two inference methods based on the likelihood principle, assuming each link associates with a random travel time. The first method considers independent and Gaussian distributed link travel times, using the additive property that trip time has a closed-form distribution as the summation of link travel times. We particularly analyze the mean estimates when the variances of trip time estimates are known with a high degree of precision and examine the uniqueness of solutions. Two cases are discussed in detail: one with known paths of all trips and the other with unknown paths of some trips. We apply the Gaussian mixture model and the Expectation–Maximization (EM) algorithm to deal with the latter. The second method splits trip time proportionally among links traversed to deal with more general link travel time distributions such as log-normal. This approach builds upon an expected log-likelihood function which naturally leads to an iterative procedure analogous to the EM algorithm for solutions. Simulation tests on a simple nine-link network and on the Sioux Falls network respectively indicate that the two methods both perform well. The second method (i.e., trip splitting approximation) generally runs faster but with larger errors of estimated standard deviations of link travel times.     

Evaluation of driver satisfaction of travel information on variable message signs using fuzzy aggregation

Driver satisfaction regarding travel information provided by variable message signs (VMS), which are part of the Nam‐Mountain Tunnel ATIS, was evaluated using fuzzy aggregation. Application of fuzzy aggregation to analyze driver satisfaction allows one to represent the variability and complexity of human perception with great fidelity. A fuzzy weighted average using two sets of fuzzy membership functions was applied to evaluate individual satisfactions of delay and travel time information provided. Then, those individual satisfactions were aggregated to estimate the driver group's overall satisfaction. The evaluated overall satisfaction was 0.65 for delay information and 0.63 for travel time information. Through these results, it was found that users of the travel information provided by the VMS in the Nam‐Mountain Tunnel ATIS were somewhat satisfied with the service quality. Those overall satisfactions were compared with a conventional weighted average and traffic operational effects to demonstrate the usefulness of the developed fuzzy method.     

Study on the framework of hybrid collision warning system using loop detectors and vehicle information

Safety warning systems generally operate based on information from sensors attached to individual vehicles. Various types of data used for collision risk calculation can be categorized into two types, microscopic or macroscopic, depending on how the sensors collect the information of traffic state. Most collision warning systems use only either of these types of data, but they all have limitations imposed by the data, such as requirement of high installation cost and high market penetration rate of devices. In order to overcome these limits, we propose a collision warning system that utilizes the integrated information of macroscopic data and microscopic data, from loop detectors and smartphones respectively. The proposed system is evaluated by simulating a real vehicle trip based on the NGSIM data. We compare the results against collision warning systems based on macroscopic data from infrastructure and microscopic data from Vehicle-to-Vehicle information. The analysis of three systems shows two findings that (a) ICWS (Infrastructure-based Collision Warning System) is inadequate for immediate collision warning system and (b) VCWS (V2V communication based Collision Warning System) and HCWS (Hybrid Collision Warning System) produce collision warning at very similar timing, even with different behavior of individual drivers. Advantages of HCWS are that it can be directly applied to existing system with small additional cost, because data of loop detector are already available to be used in Korea and smartphones are widely spread. Also, the computation power distributed to each individual smartphone greatly increases the efficiency of the system by distributing the computation resources and load.