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.     

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.     

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.     

A day-to-day route flow evolution process towards the mixed equilibria

This study investigates a travelers’ day-to-day route flow evolution process under a predefined market penetration of advanced traveler information system (ATIS). It is assumed that some travelers equipped with ATIS will follow the deterministic user equilibrium route choice behavior due to the complete traffic information provided by ATIS, while the other travelers unequipped with ATIS will follow the stochastic user equilibrium route choice behavior. The interaction between these two groups of travelers will result in a mixed equilibrium state. We first propose a discrete day-to-day route flow adjustment process for this mixed equilibrium behavior by specifying the travelers’ route adjustment principle and adjustment ratio. The convergence of the proposed day-to-day flow dynamic model to the mixed equilibrium state is then rigorously demonstrated under certain assumptions upon route adjustment principle and adjustment ratio. In addition, without affecting the convergence of the proposed day-to-day flow dynamic model, the assumption concerning the adjustment ratio is further relaxed, thus making the proposed model more appealing in practice. Finally, numerical experiments are conducted to illustrate and evaluate the performance of the proposed day-to-day flow dynamic model.     

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.     

Vertical separation as means to establish interoperability in road tolling in Europe

As more European roads become tolled by various means, an increasing share of road users become subject to more than one tolling scheme in their regular driving. This can be especially burdensome for long distance hauliers, who may pass several countries and tolled motorway systems during the course of 1 day. For this reason, a range of projects have been initiated attempting to increase the level of interoperability between tolling systems, many of which with only limited success. By analyzing current incentives, costs and benefits for toll operators and road users, we conclude firstly that the current level of interoperability is likely to be lower than socially optimal, and secondly that a direct regulation making the provision of interoperability mandatory is likely to be in excess of what is socially optimal. We argue that vertically separating the monopolistic toll operators could be a cost-efficient way to achieve a socially optimal level of interoperability as a equilibrium market outcome.     

On the relationship between airport pricing models

Airport pricing papers can be divided into two approaches. In the traditional approach the demand for airport services depends on airport charges and on congestion costs of both passengers and airlines; the airline market is not formally modeled. In the vertical-structure approach instead, airports provide an input for an airline oligopoly and it is the equilibrium of this downstream market which determines the airports’ demand. We prove, analytically, that the traditional approach to airport pricing is valid if air carriers have no market power, i.e. airlines are atomistic or they behave as price takers (perfect competition) and have constant marginal operational costs. When carriers have market power, this approach may result in a surplus measure that falls short of giving a true measure of social surplus. Furthermore, its use prescribes a traffic level that is, for given capacity, smaller than the socially optimal level. When carriers have market power and consequently both airports and airlines behave strategically, a vertical-structure approach appears a more reasonable approach to airport pricing issues.     

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.     

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.     

Modeling the evolutions of day‐to‐day route choice and year‐to‐year ATIS adoption with stochastic user equilibrium

Suppose that in an urban transportation network there is a specific advanced traveler information system (ATIS) which acts for reducing the drivers' travel time uncertainty through provision of pre‐trip route information. Because of the imperfect information provided, some travelers are not in compliance with the ATIS advice although equipped with the device. We thus divide all travelers into three groups, one group unequipped with ATIS, another group equipped and in compliance with ATIS advice and the third group equipped but without compliance with the advice. Each traveler makes route choice in a logit‐based manner and a stochastic user equilibrium with multiple user classes is reached for every day. In this paper, we propose a model to investigate the evolutions of daily path travel time, daily ATIS compliance rate and yearly ATIS adoption, in which the equilibrium for every day's route choice is kept. The stability of the evolution model is initially analyzed. Numerical results obtained from a test network are presented for demonstrating the model's ability in depicting the day‐to‐day and year‐to‐year evolutions.     

Eco approaching at an isolated signalized intersection under partially connected and automated vehicles environment

This research proposed an eco-driving system for an isolated signalized intersection under partially Connected and Automated Vehicles (CAV) environment. This system prioritizes mobility before improving fuel efficiency and optimizes the entire traffic flow by optimizing speed profiles of the connected and automated vehicles. The optimal control problem was solved using Pontryagin’s Minimum Principle. Simulation-based before and after evaluation of the proposed design was conducted. Fuel consumption benefits range from 2.02% to 58.01%. The CO₂ emissions benefits range from 1.97% to 33.26%. Throughput benefits are up to 10.80%. The variations are caused by the market penetration rate of connected and automated vehicles and v/c ratio. No adverse effect is observed. Detailed investigation reveals that benefits are significant as long as there is CAV and they grow with CAV’s market penetration rate (MPR) until they level off at about 40% MPR. This indicates that the proposed eco-driving system can be implemented with a low market penetration rate of connected and automated vehicles and could be implemented in a near future. The investigation also reveals that the proposed eco-driving system is able to smooth out the shock wave caused by signal controls and is robust over the impedance from conventional vehicles and randomness of traffic. The proposed system is fast in computation and has great potential for real-time implementation.     

Effectiveness of en route traffic information in developing countries using conventional discrete choice and neural‐network models

Providing commuters with traffic information or advising them of alternative routes during traffic incidents can alleviate congestion. For decades, advanced traveler information services (ATIS) have been devised and dedicated to this role. ATIS comprises a wide variety of technologies across the world, including radio traffic information (RTI) advisory service. RTI is common in both developed and developing countries. Although extensive literature and evaluation results of ATISs and RTI are available in developed countries, little attention has been devoted to that in developing countries. This work provides a modeling platform to study drivers' response to en route traffic information provided by Radio‐Payam broadcasting service in Tehran, the capital city of the developing country of Iran. The results are compared with counterpart cases in developed countries. Past studies and this study have employed conventional discrete models for drivers' response, such as ordered logit and ordered probit. This work evaluates the accuracy level of these conventional models in comparison with a developed neural‐network (NN) model, because it has been widely proven that NN models are highly precise. It has also been found that, apart from reliability, the conventional models are within an acceptable level of prediction accuracy compared with the NN models. The results show a high degree of similarities between the case of Tehran and its counterparts in the developing countries. The results also deliver some insights on how to improve or better implement the ATIS technologies. Copyright © 2012 John Wiley & Sons, Ltd.     

Impact of congestion charging on the transit market: An inter-modal equilibrium model

An inter-modal equilibrium model links an urban road network subject to a congestion charge to a parallel urban transit market, with a view to finding the optimum congestion charge consistent with the commercial decisions of the transit operator(s). A congestion charge is set to maximise social surplus. Travel behaviour is assumed to conform to elastic-demand user equilibrium traffic assignment. The transit market is assumed to be either a profit maximising monopoly or a profit maximising duopoly competing non-cooperatively. The operator(s) set the fares to maximise profits and the supply of transit services are determined by the resulting demand. The problem has been formulated as a bi-level programme with the determination of the congestion charge on the upper level and the setting of transit fares on the lower level. In the case of non-cooperating operators, the Bertrand–Nash equilibrium fares are sought. The results of the model are analysed for a small example based loosely on Edinburgh. This reveals the importance of competition in the transit market for the trade off between the government, the transit provider(s) and the travellers.     

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.     

Miles,speed, and technology: Traffic safety under oligopolistic insurance

We study road safety when insurance companies have market power, and can influence drivers’ behavior via insurance premiums. We obtain first- and second-best premiums for different insurance market structures. The insurance program consists of an insurance premium, and marginal dependencies of that premium on speed and own safety technology choice of drivers. A private monopolist internalizes collision externalities up to the point where compensations to users’ benefit matches the full (intangible) costs; in oligopolistic markets, insurers do not fully internalize collision externalities. Analytical results demonstrate how insurance firms’ incentives to influence traffic safety coincide with or deviate from socially optimal incentives. Our results may be useful for design of pay-as-you-speed and alike insurances as well as policies related to driving safety.     

Airline network choice and market coverage under high-speed rail competition

While the existing literature has focused on the short-term impacts, this paper investigates the long-term impacts of high-speed rail (HSR) competition on airlines. An analytical model is developed to study how an airline may change its network and market coverage when facing HSR competition on trunk routes. We show that prior to HSR competition, an airline is more likely to adopt a fully-connected network and cover fewer fringe markets if the trunk market is large. Under HSR competition, the airline will, for a given network structure, have a greater incentive to cover more fringe (regional or foreign) markets if the trunk market is large, or the airline network is close to hub-and-spoke. Further, the airline will, for any given market coverage, move towards a hub-and-spoke network when the trunk market is large, or the number of fringe markets covered by the airline network is large. Both effects are more prominent when the decreasing rate of airline density economies is large. We further show that HSR competition can induce the airline to adopt network structure and market coverage that are closer to the socially optimal ones, thereby suggesting a new source of welfare gain from HSR based on its long-term impacts on airlines. Implications for operators, policy makers and specific countries (such as China) are also discussed.     

Second best toll pricing within the framework of bounded rationality

The network design problem is usually formulated as a bi-level program, assuming the user equilibrium is attained in the lower level program. Given boundedly rational route choice behavior, the lower-level program is replaced with the boundedly rational user equilibria (BRUE). The network design problem with boundedly rational route choice behavior is understudied due to non-uniqueness of the BRUE. In this study, thus, we mainly focus on boundedly rational toll pricing (BR-TP) with affine link cost functions. The topological properties of the lower level BRUE set are first explored. As the BRUE solution is generally non-unique, urban planners cannot predict exactly which equilibrium flow pattern the transportation network will operate after a planning strategy is implemented. Due to the risk caused by uncertainty of people’s reaction, two extreme scenarios are considered: the traffic flow patterns with either the minimum system travel cost or the maximum, which is the “risk-prone” (BR-TP-RP) or the “risk-averse” (BR-TP-RA) scenario respectively. The upper level BR-TP is to find an optimal toll minimizing the total system travel cost, while the lower level is to find the best or the worst scenario. Accordingly BR-TP can be formulated as either a min –min or a min –max program. Solution existence is discussed based on the topological properties of the BRUE and algorithms are proposed. Two examples are accompanied to illustrate the proposed methodology.     

A new era for airport regulators through capacity investments

Private and public airports’ optimal actions may not coincide. While private airports usually pursue profit maximization, publicly owned airports look for maximum social welfare. Thus, the prices charged by private airports may differ from the socially optimal charges and public intervention may be needed. In this paper, we analyze airport charges when an increase in frequency produces positive or negative externalities and carriers have market power. We use the methodology of game theory to show that there may exist a level of capacity for which private and social objectives coincide, so no price regulation is needed. Thus, the usual role of regulators and planners could be modified in order to decide the appropriate capacity investments for which airport regulation is no longer necessary.     

Roads in transition: Integrated modeling of a manufacturer-traveler-infrastructure system in a mixed autonomous/human driving environment

This paper develops an integrated model to characterize the market penetration of autonomous vehicles (AVs) in urban transportation networks. The model explicitly accounts for the interplay among the AV manufacturer, travelers with heterogeneous values of travel time (VOTT), and road infrastructure capacity. By making in-vehicle time use more leisurely or productive, AVs reduce travelers’ VOTT. In addition, AVs can move closer together than human-driven vehicles because of shorter safe reaction time, which leads to increased road capacity. On the other hand, the use of AV technologies means added manufacturing cost and higher price. Thus, traveler adoption of AVs will trade VOTT savings with additional out-of-pocket cost. The model is structured as a leader (AV manufacturer)-follower (traveler) game. Given the cost of producing AVs, the AV manufacturer sets AV price to maximize profit while anticipating AV market penetration. Given an AV price, the vehicle and routing choice of heterogeneous travelers are modeled by combining a multinomial logit model with multi-modal multi-class user equilibrium (UE). The overall problem is formulated as a mathematical program with complementarity constraints (MPCC), which is challenging to solve. We propose a solution approach based on piecewise linearization of the MPCC as a mixed-integer linear program (MILP) and solving the MILP to global optimality. Non-uniform distribution of breakpoints that delimit piecewise intervals and feasibility-based domain reduction are further employed to reduce the approximation error brought by linearization. The model is implemented in a simplified Singapore network with extensive sensitivity analyses and the Sioux Falls network. Computational results demonstrate the effectiveness and efficiency of the solution approach and yield valuable insights about transportation system performance in a mixed autonomous/human driving environment.     

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.