Advanced Traveler Information Systems Research Articles

The impact of real-time information in a two-route scenario using agent-based simulation

Since advanced traveler information systems (ATIS) have been introduced, their potential benefits as well as their drawbacks have been discussed controversially. This will continue as long as the drivers’ reactions upon current or even predictive information about the traffic situation are not known. Thus, traffic models that also consider this feedback are necessary. In this paper, we address a basic two-route scenario with different types of information and study the impact of it using simulations. The road users are modeled as agents, a natural and promising approach to describe them. Different ways of generating current information are tested. It is pointed out that the nature of the information very much influences the potential benefits of the ATIS.

Designing Better Traveler Information Systems: Cognitive and Task-Related Factors

Advanced Traveler Information Systems (ATIS) attempt to enhance the navigational performance of drivers. Such assistance is greatly wanted and needed by drivers. In order to create systems that help, and not hinder, individuals, designers of ATIS should consider many aspects of human factors. One important issue of ATIS is the appropriate use and design of displays, particularly auditory displays. The use of landmarks in auditory displays may also augment navigation performance, safety, and cognitive maps. Moreover, an ATIS should be designed so that the user can perform tasks of navigation planning more naturally. Finally, the goals of an ATIS should be aligned as closely as possible to the goals of the user, in order to increase user acceptance. Consideration of the above issues will result in enhanced performance, safety, and usability of ATIS. Pilot questionnaire data has been collected that supports some of the ideas suggested in the paper.

Dynamic Bus Arrival Time Prediction with Artificial Neural Networks

Transit operations are interrupted frequently by stochastic variations in traffic and ridership conditions that deteriorate schedule or headway adherence and thus lengthen passenger wait times. Providing passengers with accurate vehicle arrival information through advanced traveler information systems is vital to reducing wait time. Two artificial neural networks (ANNs), trained by link-based and stop-based data, are applied to predict transit arrival times. To improve prediction accuracy, both are integrated with an adaptive algorithm to adapt to the prediction error in real time. The bus arrival times predicted by the ANNs are assessed with the microscopic simulation model CORSIM, which has been calibrated and validated with real-world data collected from route number 39 of the New Jersey Transit Corporation. Results show that the enhanced ANNs outperform the ones without integration of the adaptive algorithm.

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.

Reducing bias in probe-based arterial link travel time estimates

The use of probe vehicles to provide estimates of link travel times has been suggested as a means of obtaining travel times within signalized networks for use in advanced traveler information systems. Previous research has shown that bias in arrival time distributions of probe vehicles will lead to a systematic bias in the sample estimate of the mean. This paper proposes a methodology for reducing the effect of this bias. The method, based on stratified sampling techniques, requires that vehicle count data be obtained from an in-road loop detector or other traffic surveillance method. The effectiveness of the methodology is illustrated using simulation results for a single intersection approach and for an arterial corridor. The results for the single intersection approach indicate a correlation ( R 2) between the biased estimate and the population mean of 0.61, and an improved correlation between the proposed estimation method and the population mean of 0.81. Application of the proposed method to the arterial corridor resulted in a reduction in the mean travel time error of approximately 50%, further indicating that the proposed estimation method provides improved accuracy over the typical method of computing the arithmetic mean of the probe reports.

Emergence of Private Advanced Traveler Information System Providers and Their Effect on Traffic Network Performance

The emergence of supply-side competition in the advanced traveler information system (ATIS) industry and marketability of private ATIS service are examined. An architectural model in which the ATIS companies collect network information from their subscribers while providing them with real-time traffic information is described. A simulation study on competition and cooperation among multiple private and public information agencies follows. This study focuses on analyzing the interaction among information agencies and the effect of this interaction on traffic system performance.

Prediction of Recreational Travel Using Genetically Designed Regression and Time-Delay Neural Network Models

Selection of appropriate input variables is a crucial step in developing the statistical or neural network model for short-term traffic prediction. Recently, genetic algorithms have provided some success in input variable selection. Extensive experimentation with recreational traffic volume projections from Banff National Park in Alberta, Canada, is reported. Genetic algorithms (GAs) were used to select a set of historical traffic volumes that had higher correlation to the next hourly traffic volume. Universal models developed using GAs were accurate within 10%, on average. Separation of time series for individual hours revealed a linear trend in traffic volumes. Genetically designed regression submodels for individual hours had average prediction errors of less than 1% for the training sets. Even the 95th-percentile errors for the test sets were between 2% and 8%. Many highway agencies expect to deploy an advanced traveler information system (ATIS) for all highway categories. On the basis of such accurate predictions of traffic conditions from an ATIS, recreational drivers will be able to reschedule their travel time as well as routes. Such rescheduling will alleviate stress caused by traffic congestion during recreational travel.

Modeling Competitive Transit and Road Traffic Information Services with Heterogeneous Endogenous Demand

A new equilibrium model is proposed to determine the equilibrium market penetration of the advanced traveler information system (ATIS) in a network with heterogeneous users and elastic demand. User heterogeneity is considered by assuming a continuously distributed value of time (VOT) across users, and demand elasticity is considered by using a deterministic mode choice model for public transit and for equipped and unequipped private cars. The user equilibrium of mode choices for a given ATIS service charge, transit fare, and frequency is so determined that no one can reduce his or her generalized travel cost by changing to an alternative travel mode according to his or her own VOT. Furthermore, assuming provision of ATIS and transit services by competitive profit-maximizing firms, the market equilibrium is studied using game theory by determining each firm’s service charge and service quality and its resultant market shares. Through numerical simulation, the benefits generated from a given combination of service charges and service qualities to transit and road users, transit and ATIS service providers, and society as a whole are investigated.

Pseudo-dynamic travel model application to assess traveler information

This paper reports an effort to estimate potential benefits of Advanced Traveler Information Systems (ATIS) by combing regional travel demand and microscopic simulation models. The approach incorporates dynamic features not yet available in the commercial software market. The suggested technique employs data that are readily available to most urban planning organizations, and is straightforward in its application. The key reported measure of effectiveness is corridor and local system delay, and is sensitive to both the level of penetration of traveler information and the pre-trip and en-route choices drivers make based on this information. The technique is demonstrated on an urban freeway corridor in a medium sized mid-west city.

Analytical Modelling of Road-Side and In-Vehicle Driver Guidance Schemes With Compliance Considerations

Advanced Traveller Information Systems (ATIS) are likely to play an important role in alleviating traffic congestion and reducing delays on traffic networks by providing drivers with directives on alternative paths to their destinations. To be useful for dynamic traffic management, guidance has to be able to respond in real-time to emerging traffic conditions and anticipated demand levels. In this article, a small prototypical network is used to evaluate the potential benefits from and impacts of a number of traveller information schemes. The analysis develops models of the provision of road-side as well as in-vehicle guidance based on instantaneous (myopic) and predictive information, and compares these schemes to the base case of no guidance. The impact of complying and guided fraction of drivers on guidance efficiency is evaluated. The superiority of predictive information in maintaining guidance validity and mitigating the potential adverse impacts of information is demonstrated.

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.

IHE-compatible Radiology Information System

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.

A dynamic route guidance system based on real traffic data

Mobility is one of the vital goods of modern societies. One way to alleviate congestion and to utilise the existing infrastructure more efficiently are Advanced Traveller Information Systems (ATIS). To provide the road user with optimal travel routes, we propose a procedure in two steps. First on-line simulations supplemented by real traffic data are performed to calculate actual travel times and traffic loads. Afterwards these data are processed in a route guidance system which allows the road user an optimisation with regard to individual preferences. To solve this multiple criteria optimisation problem fuzzy set theory is applied to the dynamic routing problem.

Drivers' familiarity with urban route network layout in Amman, Jordan

Abstract Advanced traveler information systems (ATISs) have attracted a considerable amount of attention in recent years. By providing drivers with traffic information, these information systems are likely to help in reducing travel time, traffic-related congestion and consequently lead to reduced levels of vehicle emissions. With the presence of in-car navigation and communication systems, the ATIS can benefit commuters as well as unfamiliar drivers. However, in the absence of in-car navigation systems – the case in most developing countries, familiar drivers are likely to use these information systems more effectively and hence are likely to make well-informed route-diversion and other travel-oriented decisions. This paper is devoted to developing driver familiarity models to identify the factors that influence drivers' familiarity with the urban route network layout. A number of non-linear familiarity models are developed and coefficients are estimated. Estimation results indicate that travel characteristics such as familiarity with one alternative route, residence leaving times, travel time to job location and the presence of young children have a profound impact on the driver's level of familiarity. Separate familiarity models for male and female drivers are also specified and estimated. When subjected to the same set of predictors, the familiarity of male drivers turned out to be more responsive than the familiarity of female drivers. This result could reflect, among other things, the fact that male drivers have more frequent and diverse activity stops that expose them to different sections of the transportation network layout.

Comparative study of the effects of auditory, visual and multimodality displays on drivers' performance in advanced traveller information systems

A simulator study was conducted to compare 16 younger (mean age 22 years) and 16 older (mean age 68 years) drivers' ratings of workload (time, visual, psychological stress) and performance of navigation and button-pushing (identification of vehicle or road hazards) tasks under both high- and low-load driving conditions when simple or complex advanced traveller information (ATI) was presented visually only, aurally only or by multimodality (visual and auditory) display. For all participants, both the auditory and multimodality displays produced better performance in terms of response times, total number of correct turns and subjective workload ratings than those of using the visual-only display. Participants using the multimodality display also made the fewest errors related to push-button and navigation tasks, and controlled their vehicles properly. The visual display led to less safe driving, apparently because it imposed higher demands on the drivers' attention. An age effect was found in the present study, with younger drivers performing better and reporting less stress than older drivers. Notably, however, use of the multimodality display significantly improved the older drivers' performance in the button-pushing task.

A Mean-Variance Model for Route Guidance in Advanced Traveler Information Systems

Traditional models of route generation are based on choosing routes that minimize expected travel-time between origin and destination. Such approaches do not account for the fact that travelers often incorporate travel-time variability within their decision making. Thus, a route with lower travel-time variability is preferred by some travelers, even if such a route is not one with the lowest mean travel-time. Such traveler behavior is best captured by a multiobjective model in which the choice of a route is based on the mean as well as the variance of the path travel-time. Our route-planning model is intended to help travelers make choices that reflect their decision-making process better. We formulate a network flow multiobjective model in which one of the objectives (expectation) is linear, whereas, the other (variance) is quadratic. In order to present the user with a series of options, we solve a series of parametric 0-1 quadratic integer programs. By utilizing the network structure of the problem, we devise an effective algorithm in which the 0-1 quadratic program is solved by using a continuous relaxation together with an enumeration of some selected paths. Finally, we note that the data requirements for the model can be easily satisfied in practice.

Time Management Impacts of Pretrip Advanced Traveler Information Systems: Findings from a Washington, D.C., Case Study

Numerous consumer surveys conclude that users of advanced traveler information systems (ATIS) perceive benefits foremost in travel time, followed by benefits of stress reduction and on-time arrival. Efforts by ATIS evaluators to quantify or empirically validate these benefits through field trials have yielded findings in travel time savings that are inconsistent with findings from surveys. It is hypothesized that users of ATIS benefit in the form of time management and not necessarily by reducing in-vehicle travel time. A novel approach (the simulated yoked study) is presented to evaluate the benefits to commuters from regular ATIS use. To demonstrate the simulated yoked study approach and to test the hypothesis, a case study based on travel conditions in Washington, D.C., between August 1, 1999, and October 1, 1999, was conducted. The travel experiences of commuters regularly using pretrip ATIS are simulated and compared with those of similar commuters using no traveler information before or during their commute. Findings from the case study indicate that benefits are significant in terms of on-time reliability but not in terms of the most frequently used measure of ATIS effectiveness, reduction of in-vehicle travel time. On average, regular pretrip ATIS users can reduce late arrivals by 69 percent and total late schedule delay by 72 percent compared with their counterparts. The regional reliability of the pretrip ATIS service, defined as the percentage of trips using pretrip ATIS that have arrival expectations that are met, is estimated at 77 percent. Analyses of pretrip ATIS user expectations, outcomes, and counterpart outcomes indicated that users’ perceptions of ATIS satisfaction are accurate.

Using Human Information Processing Principles to Design Advanced Traveler Information Systems

The concepts of human information processing provide design recommendations for advanced traveler information systems (ATISs). A driver’s information processing model for the ATIS environment is proposed. This qualitative model explicitly depicts how drivers process ATIS information, from the moment it is received until a decision is made in response to the information. The model is supported by data collected with a driving simulator. The results of the driving simulator study indicate that, because of the limitations of human memory, drivers prefer to have short, simple ATIS information conveyed to them whenever the circumstance allows. Furthermore, drivers do not always need or want visually displayed information (e.g., an electronic map) to assist them in route navigation. In unfamiliar traffic networks, a motorist’s propensity to change routes is strongly correlated to the quality of ATIS information being processed. With the right amount of traffic information presented using an effective conveyance method, more drivers are likely to accept and use ATIS information and divert to alternate routes. The challenge for ATIS designers is to provide options that are acceptable to ATIS users.

Why Will Some Individuals Pay for Travel Information When It Can Be Free? Analysis of a Bay Area Traveler Survey

Substantial government resources are invested in the provision of dynamic travel information. This information may help travelers make better decisions, which can reduce traffic congestion and pollution. A survey of 1,000 San Francisco Bay Area residents was conducted in 1998 as part of the TravInfo field test, and the stated preference questions were analyzed. Respondents were asked whether they sought travel information and, if so, whether they were willing to pay for a hypothetical advanced traveler information system (ATIS) that provided automatic notification of unexpected congestion on their usual travel routes, estimated time of delay from unexpected congestion on their usual routes, automatic alternate route planning around congestion, and estimated travel time on their usual route and on any planned alternate routes. Overall, willingness to pay for an ATIS was higher than expected from the literature. Sixty-six percent of the respondents sought travel information, and, of these information seekers, 71 percent were willing to pay for an ATIS (average $3.84 per month, or $0.74 per call). Statistical analysis involved estimating binary and ordered probit models with and without sample selectivity. Propensity for seeking travel information was significantly related to respondents who were female, employed, took longer trips, faced unexpected congestion, and owned a cellular telephone. Increased willingness to pay for an ATIS was related to respondents who were young and male, altered trips in response to information, and stated a greater desirability for the hypothetical ATIS. Findings suggest that a market may exist for high-quality dynamic travel information.

Seattle Intelligent Transportation System Information Backbone

This case study involved the review of the advanced traveler information system (ATIS) and advanced traffic management system (ATMS) and the use of the information backbone (I2B) component of the intelligent transportation system of the Seattle Metropolitan Model Deployment Initiative. Through a survey of documents and other material combined with interviews of key participants, the nature of any increased benefits or reduced costs associated with ATIS and ATMS integration resulting from the I2B was examined. The results suggest that the distributed nature of the I2B provided for the coordination of responsibility among multiple information contributors and processors as well as geographic flexibility. The open nature of participation was also cited as a factor in making connection to the I2B a relatively easy matter since software tools for interfacing are provided. For contributors, the I2B has provided the ability to distribute information via a single access method, thereby reducing support effort. Processors can gain easier access to existing information in addition to being able to develop composite information from multiple sources. Comparison of costs between the I2B and alternative information system designs was difficult because of the differences in functionality provided. However, it appears likely that costs are shifted from the information contributors to the processors, who gain from the addition and realization of value in the marketplace.