Advanced Traveler Information Systems Research Articles

Measurement of Uncertainty Costs with Dynamic Traffic Simulations

Nonrecurrent congestion in transportation networks occurs as a consequence of stochastic factors affecting demand and supply. Intelligent transportation systems such as advanced traveler information systems and advanced traffic management systems are designed to reduce the impacts of nonrecurrent congestion by providing information to a fraction of users or by controlling the variability of traffic flows. For these reasons, the design of these systems requires a reliable forecast of nonrecurrent congestion. A new method is proposed to measure the impacts of nonrecurrent congestion on travel costs by taking risk aversion into account. The traffic model is based on the dynamic traffic simulation model METROPOLIS. Incidents are generated randomly by reducing the capacity of the network. Users can instantaneously adapt to the unexpected travel conditions or can also change their behavior through a day-to-day adjustment process. Comparisons with incident-free simulations provide a benchmark for potential travel time savings that can be brought about by a state-of-the-art information system. The impact of variable travel conditions is measured by describing the willingness to pay to avoid risky or unreliable journeys. Indeed, for risk-averse drivers, any uncertainty corresponds to a utility loss. This utility loss is computed for several levels of network disruption. The main result of the study is that the utility loss due to uncertainty is of the same order of magnitude as the total travel costs.

Cross-Correlation Analysis and Multivariate Prediction of Spatial Time Series of Freeway Traffic Speeds

Short-term traffic prediction on freeways is one of the critical components of the advanced traveler information system (ATIS). The traditional methods of prediction have used univariate ARIMA time-series models based on the autocorrelation function of the time series of traffic variables at a location. However, the effect of upstream and downstream location information has been largely neglected or underused in the case of freeway traffic prediction. The purpose of this study is to demonstrate the effect of upstream as well as downstream locations on the traffic at a specific location. To achieve this goal, a section of five stations extending over 2.5 mi on I-4 in the downtown region of Orlando, Florida, was selected. The speeds from a station at the center of this location were then checked for cross-correlations with stations upstream and downstream. The cross-correlation function is analogous to the autocorrelation function extended to two variables. It indicates whether the past values of an input series influence the future values of a response series. It was found in this study that the past values of upstream as well as downstream stations influence the future values at a station and therefore can be used for prediction. A vector autoregressive model was found appropriate and better than the traditional ARIMA model for prediction at these stations.

The combined effect of information and experience on drivers’ route-choice behavior

Advanced travel information systems (ATIS) are designed to provide real time information enabling drivers to choose efficiently among routes and save travel time. Psychological research suggests that route-choice models can be improved by adding realistic behavioral assumptions. However, different generalizations imply deviations in different directions. Specifically, different choices arise when decisions are taken on the basis of information compared to those taken on the basis of personal experience. An experimental study of route choices investigates the combined effects of information and experience on route choice decisions in a simulated environment whereby the participants can rely on a description of travel time variability and at the same time can rely also on personal experience through feedback. The experiment consisted of a simple two route network, one route on average faster than the other with three traffic scenarios representing different travel time ranges. Respondents were divided to two groups: with real-time information and without. Both groups received feedback information of their actual travel time. During the experiment, participants chose repeatedly between the routes and across scenarios. The results show that effect of information is positive and more evident when participants lack long-term experience on the distributions of travel times. Furthermore, information seems to increase initial risk seeking behavior, reduce initial exploration and contribute to between subject differences. These findings have implications for cost-effective ATIS design especially in the conditions characterized by non-recurrent congestion.

Evaluation of a cellular phone-based system for measurements of traffic speeds and travel times: A case study from Israel

The purpose of this paper is to examine the performance of a new operational system for measuring traffic speeds and travel times which is based on information from a cellular phone service provider. Cellular measurements are compared with those obtained by dual magnetic loop detectors. The comparison uses data for a busy 14 km freeway with 10 interchanges, in both directions, during January–March of 2005. The dataset contains 1 284 587 valid loop detector speed measurements and 440 331 valid measurements from the cellular system, each measurement referring to a 5 min interval. During one week in this period, 25 floating car measurements were conducted as additional comparison observations. The analyses include visual, graphical, and statistical techniques; focusing in particular on comparisons of speed patterns in the time–space domain. The main finding is that there is a good match between the two measurement methods, indicating that the cellular phone-based system can be useful for various practical applications such as advanced traveler information systems and evaluating system performance for modeling and planning.

Development of a Mixed Multi-Nomial Logit Model to Capture the Impact of Information Systems on Travelers' Switching Behavior

The continuous growth of road traffic increases the delays that road users face and negatively affects the overall transportation system performance. Advanced Traveler Information Systems (ATIS) may offer significant benefits in terms of improving the travel experience of individuals, but their impact on individuals' travel behavior and on the whole transportation system mainly depends on how travelers respond to the acquired traffic information. This article presents a case study on travelers' response to traffic information for the Puget Sound Region (PSRC). The data used come from travel diaries (collected in 2000), in which individuals were asked about the traveler information sources consulted on each trip and how the information was used. Traveler information sources, available in the region, encompass both conventional forms of information, such as radio traffic reports and advanced traveler information systems, for example, variable message signs (VMS) and websites. The objective of this study is to examine the impact of information acquisition on switching travel behavior. Two models have been estimated: a multinomial logit model (MNL) and a mixed multinomial logit model (MMNL) that accounts for correlation among observations from the same individuals in the data set. The estimated models show that travel pattern characteristics, the time of information acquisition (pretrip vs. en-route), the source, and the content of provided information significantly affect commuters' response to information.

Mixed Travel Behavior in Networks with ATIS and Upper Bound of Efficiency Loss

Abstract In a transportation network supported by the Advanced Traveler Information Systems (ATIS), the drivers equipped with ATIS are directed by a control center to select their routes so as to minimize the total network travel time, while the unequipped ones make the route choice decisions on the base of minimizing their individual travel times. This article presents a variational inequality model to formulate the mixed travel behavior associated with both system optimum and user equilibrium, and derives a general formula for the upper bound of efficiency loss of the mixed behavior. The upper bounds when all link travel cost functions are polynomial are examined against different ATIS market penetrations. It is found that the upper bound is related to the ATIS market penetration and the corresponding mixed equilibrium flow pattern.

The effects of an advanced traveler information system on scenic beauty ratings and the enjoyment of a recreational drive

Accurately measuring scenic beauty has been the objective of many researchers since the mid 1970s. The scenic beauty estimation method ( Daniel and Boster, 1976) and its experimental procedures have been used extensively to establish relationships between a number of factors and respondents ratings of the scenic beauty of a variety of landscape stimuli, mostly photographs. This paper documents how landscape narrative information, presented in a driving simulator based laboratory setting caused significant elevations in scenic beauty ratings. In this study, geographic data sets were used to create a real time documentary style narrative for an entertainment-oriented advanced traveler information system or ATIS ( Campbell et al., 1999) interface developed in the IDEA laboratory at the University of British Columbia. This narrative was designed as a factual yet entertaining story about the many fascinating aspects of the natural world present on either side of a 60 km section of the sea to sky highway (the “route”) in British Columbia, Canada. Ratings of scenic beauty and driving experience were obtained for three different modes of delivery of this information and were compared to ratings obtained from a control condition. Reported scenic beauty and driving experience ratings for each of the three delivery modes were significantly higher than those in the control condition. Furthermore, the magnitude of these elevations was found to be highest in areas of low scenic beauty and poor driving experience.

Development of a probabilistic model to optimize disseminated real‐time bus arrival information for pre‐trip passengers

AbstractIn the advent of Advanced Traveler Information Systems (ATIS), the total wait time of passengers for buses may be reduced by disseminating real‐time bus arrival times for the next or series of buses to pre‐trip passengers through various media (e.g., internet, mobile phones, and personal digital assistants). A probabilistic model is desirable and developed in this study, while realistic distributions of bus and passenger arrivals are considered. The disseminated bus arrival time is optimized by minimizing the total wait time incurred by pre‐trip passengers, and its impact to the total wait time under both late and early bus arrival conditions is studied. Relations between the optimal disseminated bus arrival time and major model parameters, such as the mean and standard deviation of arrival times for buses and pre‐trip passengers, are investigated. Analytical results are presented based on Normal and Lognormal distributions of bus arrivals and Gumbel distribution of pre‐trip passenger arrivals at a designated stop. The developed methodology can be practically applied to any arrival distributions of buses and passengers.

A multiclass, multicriteria logit-based traffic equilibrium assignment model under ATIS

This paper presents a multiclass, multicriteria (cost versus time) logit-based traffic equilibrium assignment model in road networks served by advanced traveler information systems (ATIS). All users are differentiated by their own value of time (VOT) that follows some probability distribution. Users of each class, having their own VOT, are further divided into two groups, equipped and unequipped with ATIS respectively. The travel disutility received by each user is defined as a linear bi-criteria combination of travel time and monetary travel cost. It is assumed that all users make their route choices in a logit-based stochastic manner, but the equipped users have lower perception variation on the travel disutility than the unequipped due to the ATIS service. The model is formulated as a fixed-point problem and solved by the method of successive averages in conjunction with logit assignment. Numerical results show that the traditional single-class and/or single-criterion models may overestimate or underestimate the benefit from ATIS services.

Location configuration design for Dynamic Message Signs under stochastic incident and ATIS scenarios

This paper proposes a methodology for deploying permanent Dynamic Message Signs (DMS) in a vehicular traffic network. Of particular interest is the planning problem to optimize the number of DMS to deploy in conjunction with Advanced Traveler Information Systems (ATIS), operating and maintenance cost of DMS, and incident-related user cost under random traffic incident situations. The optimal DMS location design problem discussed herein is formulated as a two-stage stochastic program with recourse (SPR). A Tabu search algorithm combined with dynamic traffic simulation and assignment approaches are employed to solve this problem. A case study performed on the Fort-Worth, Texas network highlights the effectiveness of the proposed framework and illustrates the affect factors such as demand, network structure, DMS response rate, and incident characteristics have on the solution. The numerical results suggest that designing and deploying DMS and ATIS jointly is more cost-effective and efficient than the sequential build-out of the two from the system management perspective.

Risk Aversion, Road Choice, and the One-Armed Bandit Problem

This paper provides a theoretical analysis of advanced traveler information systems for road choice with risk-averse drivers who rationally learn over time, in a simple setting. For this purpose, we study the one-armed bandit problem where a driver selects, day after day, either a safe or a random road. Four information regimes are envisaged. The visionary driver knows beforehand, with certainty, the travel time on the random road, while the locally informed driver needs to select a road to acquire information on it. Two intermediary information regimes (fully and globally) are also envisaged. We analyze these four regimes and compare the optimal strategies and the individual benefits with respect to individual risk aversion. A numerical example also illustrates the impact of risk aversion on dynamic optimal strategies.

Drivers’ Preferences for Traffic Information for Nonrecurrent Traffic Situations

The field of advanced traveler information systems (ATIS) has seen many improvements in the past years. These systems are developed to allow drivers or travelers to make better travel choices about travel time reduction or route choice. If such a system is to be generally accepted by drivers, it is necessary to know drivers’ preferences for traffic information content, as well as the characteristics of the information the system provides. These preferences should be known for all types of drivers and for all kinds of situations. This paper presents results of a study of these preferences. Although several studies have addressed the subject, little is known about preferences in nonrecurrent traffic situations. By means of an Internet survey, Dutch drivers were asked for their preferences concerning the content of traffic information for different nonrecurrent traffic situations. Statistical testing shows that drivers’ preferences differ according to the situation. Important driver characteristics influencing these preferences are current use of the information, driver type, and driver age. Drivers were also asked to choose between different information types, with different characteristics for a generic situation. Results were analyzed with a multinomial logit model. The most important characteristic of the information was cost; however, reliability and timeliness also contributed significantly to the utility of traffic information. Findings indicate that ATIS should be strongly adaptive to the driver and to the traffic situations at hand.

APPLICATION OF THE KALMAN FILTER TO THE ARTERIAL TRAVEL TIME PREDICTION: A SPECIAL EVENT CASE STUDY

A sudden traffic surge immediately after special events (e.g., conventions, concerts) can create substantial traffic congestion in the area where the events are held. It is desirable that the special events-related traffic flow be monitored and measured so that available methods (e.g., a temporary traffic signal timing adjustment and coordination) can be used to alleviate congestion. The travel time variable is a good operational measure of effectiveness of traffic systems and can be used to detect incidents and quantify congestion. Effective prediction of travel times is crucial to many advanced traveller information and transportation management systems. This paper focuses on the arterial travel time prediction using the Kalman filtering and estimation technique, and a special event is selected as our case study. The global positioning system (GPS) test vehicle technique is used to collect after-events travel time data. Based on the field data collected, a discrete-time Kalman filter is implemented and applied to predict travel time exiting the area under study. The performance is assessed and its effectiveness at the test site is investigated. The available techniques to further improve the accuracy of the prediction error are also discussed. Although this paper presents a case study, the results can be easily applied to large-scale special events held in other metropolitan areas.

Urban Expressway-Arterial Corridor On-Line Control System Based on Advanced Traveler Information System

A novel on-line dynamic traffic control strategy for an urban expressway-arterial corridor system is proposed. The corridor system comprises an expressway mainline, on and off-ramps, and surface streets (arterial roads). The ramps are not subjected to any ramp metering control. Assuming that the real-time vehicle arrival and departure can be obtained from the loop detectors on the expressway, the proposed traffic control strategy aims to maintain a predetermined level of service on a congested expressway section by disseminating the congestion information to drivers through various advanced traveler information system means. This strategy consists of three components: expressway mainline control (EMC), on-ramp control (OnC), and off-ramp control (OffC) mechanisms. The EMC mechanism is the major component that diverts vehicles from the expressway to the surface streets, and the OnC and OffC procedures protect the ramps and surface streets from excessive flow. This is because diverting the vehicles without taking into consideration the surface street capacity may cause the overall performance of the corridor system to deteriorate. A simulation-based modeling methodology is developed to evaluate the on-line dynamic traffic control strategy. The evaluation is carried out by performing sensitivity analysis tests of the control parameters used in the strategy. A case study based on a corridor system in Singapore has shown that the traffic control strategy is effective.

Exploring User Behavior in Online Network Equilibrium Problems

The availability of advanced traveler information systems technologies has provided opportunities for travelers to obtain online travel information and thereby improve their travel experiences. The resulting change in user behavior because of such information needs to be accounted for in traffic assignment models. A methodology that accounts for user recourse in the traffic assignment problem is proposed. This methodology accounts for the heterogeneity in user information perception by using a sequential form of logit model. Hyperpaths instead of elementary paths are used in this approach. A key difficulty in modeling online recourse in network assignment problems is in obtaining efficient hyperpaths. A methodology that uses a sequential form of logit model that obviates explicit enumeration of hyperpaths is proposed. Computational results from a hypothetical transportation network are presented to demonstrate the application of the proposed assignment approach.

Evaluation of the Potential Benefits of Advanced Traveler Information Systems

This article evaluates the potential travel time savings from Advanced Traveler Information Systems (ATIS) that provide drivers with travel time and routing information. We classify ATIS in various levels based on the type of information they use to generate guidance and the timing of the dissemination of the generated guidance to drivers. We present a case study that examines the potential travel time savings of ATIS as well as the implications on travel time variability and reliability and the sensitivity of the results to the accuracy of the information, using real-world data collected from a freeway network in Los Angeles, California.

Bus Arrival Time Prediction Using Support Vector Machines

Effective prediction of bus arrival time is central to many advanced traveler information systems. This article presents support vector machines (SVM), a new neural network algorithm, to predict bus arrival time. The objective of this paper is to examine the feasibility and applicability of SVM in vehicle travel time forecasting area. Segment, the travel time of current segment, and the latest travel time of next segment are taken as three input features. Bus arrival time predicted by the SVM is assessed with the data of transit route number 4 in Dalian economic and technological development zone in China and conclusions are drawn.

Government policy of technology selection for advanced traveler information systems

Technology selection is widely recognized for its increasing importance in the field of technology management. Different from previous work that only used a single evaluation method, this study uses the grey statistics method with survey techniques and scenario approach to develop a three‐stage model for the technology selection issue. An empirical case of the Advanced Traveler Information System (ATIS) technology selection in Taiwan was chosen to illustrate the application of this model on the technology selection problem. The results indicate that GPS/GIS technology is the preferred ATIS technology developed in Taiwan. The application of the model provides an avenue for government policy makers and researchers to deal effectively with the technology selection issue.

Examination of Multiple Mode/Route-Choice Paradigms Under ATIS

The objective of this paper is to collect and analyze data that can be used to model mode- and different route-choice paradigms using same subjects and same experiment. In this paper, the authors estimated five models to address drivers' diversion, compliance, and route choice. In addition, the effect of advanced traveler information systems (ATIS) on the mode choice is also considered. A travel simulator was used as a dynamic data collection tool. The simulator uses a realistic network, two modes of travel, real historical volumes, and different weather conditions. It provides five different levels of traffic information/advice, one at a time, and collects dynamic mode choices and pretrip (long-term) and en-route (short-term) route choices. The binomial and multinomial generalized extreme equations (BGEE and MGEE) were used to account for the correlation between repeated choices made by the same subject. In addition, MGEE accounts for the correlation between alternatives in multidimensional route-choice models. The modeling results showed that travel time and familiarity with the device that provides the information had significant effects on the first four models. It is shown that developing in-vehicle information devices may lead to a less transit usage in some cases; this indicates a potential drawback of this technology. Expressway users are shown as the most travel-time savers who would divert if they are guided to a less-travel-time alternative. The number of traffic signals on the normal and advised routes affects the diversion from the normal route and compliance with the pretrip advised route. This paper underlines the importance of modeling correlation, if it exists, in mode/route-choice data

Evaluation of choice set generation algorithms for route choice models

This paper discusses choice set generation and route choice model estimation for large-scale urban networks. Evaluating the effectiveness of Advanced Traveler Information Systems (ATIS) requires accurate models of how drivers choose routes based on their awareness of the roadway network and their perceptions of travel time. Many of the route choice models presented in the literature pay little attention to empirical estimation and validation procedures. In this paper, a route choice data set collected in Boston is described and the ability of several different route generation algorithms to produce paths similar to those observed in the survey is analyzed. The paper also presents estimation results of some route choice models recently developed using the data set collected.