In-vehicle Route Guidance Systems Research Articles

Competitive Traffic Assignment in Road Networks

Abstract Recently in-vehicle route guidance and information systems are rapidly developing. Such systems are expected to reduce congestion in an urban traffic area. This social benefit is believed to be reached by imposing the route choices on the network users that lead to the system optimum traffic assignment. However, guidance service could be offered by different competitive business companies. Then route choices of different mutually independent groups of users may reject traffic assignment from the system optimum state. In this paper, a game theoretic approach is shown to be very efficient to formalize competitive traffic assignment problem with various groups of users in the form of non-cooperative network game with the Nash equilibrium search. The relationships between the Wardrop’s system optimum associated with the traffic assignment problem and the Nash equilibrium associated with the competitive traffic assignment problem are investigated. Moreover, some related aspects of the Nash equilibrium and the Wardrop’s user equilibrium assignments are also discussed.

A Mobile Application for Real-Time Multimodal Routing Under a Set of Users’ Preferences

In this article an application for mobile navigation is introduced with the intention to serve users who either do not have access to a private vehicle or prefer combining a vehicle with a public transport mode provided that it yields a reduction to their total travel time. This application guides users to their destination by integrating the use of private and public transport and differs from in-vehicle route guidance systems that suggest routes only for private vehicle users, and from other conventional mobile route guidance systems that propose either a route for public transport users or a route for private vehicle users. In addition, the proposed application suggests intermodal routes that comply with each individual's preferences in an attempt to fulfill the user's needs in complex, urban networks. The data requirements for the mobile application are covered by a real-time database that is handled by a central server (processor) and contains information about traffic congestion, train and bus schedules, and more. Finally, two algorithms are presented in order to serve the computational part of the application and determine optimal paths in intermodal networks with respect to a predetermined set of users’ preferences. The data requirements, the structure and the architecture of the application, the required technologies, the underpinning mathematical context of the proposed algorithms, and the performance of this application in random networks are also presented.

Probabilistic Modeling of Erroneous Human Response to In-Vehicle Route Guidance Systems: A First Look

An integral component of (in-vehicle) navigation systems is the determination of optimal routes to the desired destination. An implicit assumption in the underlying algorithms is that people do not make mistakes when following the prescribed routes. This is, however, not always consistent with reality, especially when driving in unfamiliar environments. This article presents a first look at the possibility of mistakes when driving. This possibility is formalized in a Markov decision process. It is demonstrated that quite paradoxical situations can occur when accounting for mistakes. As the most interesting—but perhaps extreme—example, we have shown that under certain conditions, it is no longer optimal to recommend drivers to take the shortest route. Instead, a longer route (in certain cases even the longest!) becomes optimal. Numerical results are provided throughout the article to reveal the fundamental properties of this problem.

Study of in-vehicle route guidance systems for improvement of right-side drivers in the Japanese traffic system

A country can adopt one of two standards for traffic flow — cars may travel on the left or right side of the road. When drivers who are accustomed to driving on the right side of the road drive on the left side, and vice versa, the mental workload is likely increased due to the driver’s unfamiliarity with a new language, the position of the driver’s seat, different driving directions, and other factors that differ from those of their home country. One method of doing this is to make sure that the in-vehicle route guidance information (RGI) is not overly complicated — thereby assisting drivers in improving their safety. Consequently, the aim of this study was to facilitate mobility and improve safety for natural right-side drivers driving temporarily in left-side traffic. In this study, driver behavior and workload — given various types of RGI — were evaluated in a driving simulator with a variety of prescribable test conditions. This research was composed of two experiments. In the first, various types of in-vehicle route guidance systems were tested and evaluated in terms of their characteristics and associated driver behaviors (while driving). In the second experiment, systemic factors and effectiveness were evaluated by two combined systems, arrow and map-type information, based on the results of the first experiment. In light of both experiments, the various types of route guidance systems were discussed in terms of their results. A navigation system was proposed to alleviate some of the secondary tasks such as route selection.

An experimental analysis of intelligibility and efficiency of in-vehicle route guidance system displays

This study focuses on the user-interface of the route guidance system with an electronic map display. The ultimate goal of the study is to aid in designing electronic map displays that can deliver information to the user most efficiently and expeditiously with minimum confusion. To evaluate the efficiency and understandability of a map display, laboratory experiments were designed and conducted in this study. In the experiments the subjects were presented with electronic map displays of different attributes and performed a set of tasks. Their understanding of the information contents was measured based on the outcomes of the tasks, and subjective ratings of the ease of using the maps were obtained. Using the experimental data obtained, a structural equations model system is developed to explain the understandability of a map display in terms of the subject’s attributes and the characteristics of the map display. The experimental procedure and the modeling results are presented in this paper.

Location-based dynamic route guidance system of Korea: System design, algorithms and initial results

Over the last two years, the Korean Expressway Corporation (KEC) has developed a location-based dynamic route guidance system. The targets of the new system are the users of mobile-phones, the internet, and PDAs (Personal Digital Assistant), etc. Spatially the system covers 2,804 km of expressway and 484 km of national highway where the travel time collection systems are installed. The developed routing system is in many aspects different from the existing telematics-related services in Korea. It is based on predicted traffic information rather than real-time traffic information, and provides web and location based in-vehicle route guidance system. It utilizes GML (Geographical Markup Language) and GIS (Geographical Information System) in order to create GML DB (Data Base), and follows the standard format of the ISO (International Standard Organization) for GDF (Geographic Data File). Initial results of the proposed system including the accuracy of route travel time forecasts and the soundness of suggested routes were found to be acceptable. After development, the KEC has successfully tested a pilot service of the new system and is currently preparing for a full-scale implementation.

Heuristic shortest path algorithms for transportation applications: State of the art

There are a number of transportation applications that require the use of a heuristic shortest path algorithm rather than one of the standard, optimal algorithms. This is primarily due to the requirements of some transportation applications where shortest paths need to be quickly identified either because an immediate response is required (e.g., in-vehicle route guidance systems) or because the shortest paths need to be recalculated repeatedly (e.g., vehicle routing and scheduling). For this reason a number of heuristic approaches have been advocated for decreasing the computation time of the shortest path algorithm. This paper presents a survey review of various heuristic shortest path algorithms that have been developed in the past. The goal is to identify the main features of different heuristic strategies, develop a unifying classification framework, and summarize relevant computational experience.

A multi-agent approach to cooperative traffic management and route guidance

This paper explores the use of cooperative, distributed multi-agent systems to improve dynamic routing and traffic management. On the supply-side, real-time control over the transportation network is accomplished through an agent-based distributed hierarchy of system operators. Allocation of network capacity and distribution of traffic advisories are performed by agents that act on behalf of information service providers. Driver needs and preferences are represented by agents embedded in intelligent in-vehicle route guidance systems. Negotiation between ISP and driver agents seek a more efficient route allocation across time and space. Results from simulation experiments suggest that negotiation can achieve more optimal network performance and increased driver satisfaction.

Intelligent Route Selection for In-vehicle Navigation Systems

Driving is a demanding task which requires constant concentration and appropriate maneuvers of a vehicle on the road. The introduction of in-vehicle navigation and route guidance system should be carried out with utmost care because of the abundant information that can be provided to a driver. In order to increase the acceptance level and lower the negative safety impacts of in-vehicle navigation systems, the psychological consideration and study of model of driver behavior is crucial. The focus of this article is on the design of a route selection function for an in-vehicle navigation system. The issue of route selection criteria and decision-making by drivers is discussed and an adaptive route selection algorithm presented. The objective is to develop a system function which can act as a driver's assistant and helps in the evaluation of alternate routes. Such a system can help to filter and interpret information to lessen stress on drivers. In this article, the philosophical consideration of drivers' route selection is discussed. The concept of primary attributes is introduced. Also, a review of route selection studies, together with the results from three previous surveys, are presented.

An adaptive routing algorithm for in-vehicle route guidance systems with real-time information

This paper examines the problem of routing a given vehicle through a traffic network in which travel time on each link can be modeled as a random variable and its realization can be estimated in advance and made available to the vehicle’s routing system before it enters the link. The underlying problem is formulated as the closed-loop adaptive shortest path routing problem (CASPRP) with the objective of identifying only the immediate link, instead of a whole path, to account for the future availability of travel time information on individual links. Having formulated the problem as a dynamic program and identified the associated difficulties, we apply an approximate probabilistic treatment to the recurrent relations and propose a labeling algorithm to solve the resultant equations. The proposed algorithm is proved theoretically to have the same computational complexity as the traditional label-correcting (LC) algorithm for the classic shortest path problems. Computational experiments on a set of randomly generated networks and a realistic road network demonstrate the efficiency of the proposed algorithm and the advantage of adaptive routing systems.

Real-Time Multiple-Objective Path Search for In-Vehicle Route Guidance Systems

The application of multiple-objective route choice for in-vehicle route guidance systems is discussed. A bi-objective path search algorithm is presented and its use demonstrated. A concept of trip quality is introduced that is composed of two objectives: minimizing travel time and minimizing trip complexity. Trade-offs between the objectives are examined. The concept is illustrated through simulation modeling on a test network. The experiments serve to demonstrate the effects on the trip performance of pretrip routing and dynamic routing strategies under full market penetration (an idealized condition) and under varying levels of demand and trade-offs between time and complexity.

Simulation study of driving performance with selected route guidance systems

Experiments were conducted in a driving simulator developed by the Hughes Aircraft Corporation to study the human factors aspects of route guidance systems. The primary objective of this research was to study how in-vehicle route guidance system attributes, driver characteristics, and traffic conditions affect driving performance. Four types of route guidance systems were tested. They are: (1) Paper Map, (2) Heads Down Electronic Map, (3) Heads Up Display (HUD) in combination with Electronic Map, and (4) Voice Guidance in combination with Electronic Map. Data were collected for a total of 18 subjects, 9 male and 9 female. All subjects were tested in all four route guidance systems. The following performance measures were collected in the simulator: Number of Navigation Errors and Reaction times to external events. Apart from these, an unobstrusive eye tracker was also used to monitor eye fixations. Data were also collected on driver preferences and subjective workload associated with each of the four route guidance systems. The results of the study can be summarized as follows: (a) Subjective workload, user perceptions, eye tracker dwelling times, and number of errors all indicated that the voice guidance/electronic map combination performed the best, and the paper map the worst. The electronic map was found to be the second best, closely followed by the HUD electronic map. (b) The reaction time modelling yielded slightly different device performance depending on the event being reacted to. The heads up display/electronic map combination performed much better in comparison to its performance in the other performance measures, with voice/electronic map also doing well. The paper map again consistently performed the worst. (c) Driving performance did vary with gender and experience. Not surprisingly, drivers with higher experience performed better than drivers with lower experience. This effect was more prominent among females than males.

An information discounting routing strategy for advanced traveler information systems

Although there is a lot of enthusiasm and hope that in-vehicle information and route guidance systems will become an integral part of the solution to the traffic congestion problem, there are still a lot of technological and other problems that need to be addressed before such systems operate successfully. This paper examines design aspects of advanced traveler information systems (ATIS) such as frequency of information update, location of information nodes and, most importantly, approaches to estimate the travel times for use in routing decisions and suggestions. In particular, a routing strategy based on information discounting for travel time projection is developed. The importance of the above issues and their implications on the effectiveness of ATIS are demonstrated with a small network.