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In a traffic-aware route search (TARS), the user provides start and target locations and sets of search terms. The goal is to find the fastest route from the start location to the target via geographic entities (points of interest) that correspond to the search terms, while taking into account variations in the travel speed due to changes in traffic conditions, and the possibility that some visited entities will not satisfy the search requirements. A TARS query may include temporal constraints and order constraints that restrict the order by which entities are visited. Since TARS generalizes the Traveling-Salesperson Problem, it is an NP-hard problem. Thus, it is unlikely to find a polynomial-time algorithm for evaluating TARS queries. Hence, we present in this paper three heuristics to answer TARS queries-a local greedy approach, a global greedy approach and an algorithm that computes a linear approximation to the travel speeds, formulates the problem as a Mixed Integer Linear Programming (MILP) problem and uses a solver to find a solution. We provide an experimental evaluation based on actual traffic data and show that using a MILP solver to find a solution is effective and can be done within a limited running time in many real-life scenarios. The local-greedy approach is the least effective in finding a fast route, however, it has the best running time and it is the most scalable. [ABSTRACT FROM AUTHOR]

One of the impediments to the implementation of ITS is the lack of map database interoperability. Centreline databases are available from a number of sources, but few were designed specifically for ITS. Consequently there are a variety of problems—coordinate inaccuracy, errors of omission and commission, missing or wrong street names, incorrect topology—that are compounded when communicating parties use databases from different vendors. Many ITS applications (e.g., emergency response, ATIS) rely on the exchange of messages in which location is a component. Map error and interoperability problems can result in a variety of practical difficulties, from inappropriate vehicle routing to delays in delivery of critical services. These problems can be addressed by (a) standards for map databases, (b) intelligent messaging, (c) national integration efforts to improve database quality in the long term. This paper examines the dimensions of the problem, and describes solutions currently under development. [ABSTRACT FROM AUTHOR]

Dynamic traffic assignment (DTA) is at the heart of much ITS research. Assigning traffic, whether for planning purposes or for real time route guidance, is a difficult problem. Recent advances in user-optimal dynamic traffic assignment have built on the methods developed for static user-optimal assignments. Since assignment models are complex, they will not use many of the network analysis functions found in commercial GIS packages. Custom software will have to be developed. In this paper we explore the problems faced in solving static and dynamic assignments and relate those problems to information that is likely to be based in a traffic control center’s GIS database. Because of the size of the problem and the need for faster-than-real-time analysis, how and when data is transferred between a GIS to analysis modules is important. Further, many approaches for GIS software design and spatial data handling, such as OOP and dynamic segmentation, may impose too much overhead to be of much use in time-sensitive ITS applications. [ABSTRACT FROM AUTHOR]

The evolution of GIS-T is characterized in three stages: the map view, the navigational view, and the behavioral view. The static nature of the map view favors applications related to inventory and description, and raises difficult questions of accuracy and interoperability. The navigational view adds concerns for connectivity and planarity, and the storage of time-dependent attributes. Navigation also raises issues of representation related to scale, including the need for lane-level connectivity. The behavioral view stems from the work of Hägerstrand, treating transportation events as dynamic and occurring within the largely static transportation space. Appropriate representations for the behavioral view have still to be worked out. In all three cases the legacies of prior technologies and perspectives are still evident. The paper presents a series of research challenges, dealing with standards, representation, unambiguous communication, economic models, response to new technologies, and application of knowledge gained from GIS-T and ITS research to other fields. [ABSTRACT FROM AUTHOR]

Disaggregate travel data is not new to urban transportation planning studies, but it is infrequently handled in a GIS environment. With the evolution of urban travel demand models from aggregate models to disaggregate models and from a trip-based paradigm to an activity-based paradigm, there is a growing need of managing disaggregate travel data with spatial and temporal components in a GIS environment. At the data organization level, the main challenge is to efficiently store the data by minimizing redundancy while maintaining the complex relationships among the data items. The data organization should allow users to retrieve and visualize disaggregate travel data according to various possible combinations of spatial, temporal, and attribute criteria. This paper presents an implementation that employs a relational database approach and dynamic segmentation to organize the spatial, temporal, and attribute components in a sample travel diary data set. Discussions of the benefits and shortcomings associated with this approach are provided, along with suggestions for future research. [ABSTRACT FROM AUTHOR]

Comments on transportation as one of the most important geographic phenomenon. Emergence of the term intelligent transportation systems; Exploration of the issue evolving rules for geographic information systems; Impact of the emergence of geographic information and intelligent transportation systems on the way people deal with transportation.