Abstract
Intelligent Transportation Systems envision a networked environment consisting of vehicles, the infrastructure, and hand-held devices (e.g., smart-phones). The environment will enable numerous safety, mobility, and environmental improvement applications. For example, drivers can be warned of dangers in their local environment or when risking to leave their lane. Furthermore, their visibility range can be expanded by providing highly up-to-date information from areas that are currently invisible. For another example, the road weather—up-to-the-minute visibility, precipitation, and pavement condition information—can be provided at high spatial resolution.Intelligent Transportation efforts are currently being undertaken throughout the world. In addition to the IntelliDrive initiative of the US Department of Transportation, similar efforts exist in Europe, Japan, and China. But these efforts are largely decoupled from, and often incognizant of, the advances in spatio-temporal information management.This paper outlines a spatio-temporal data management language, Transportation Query Language (TranQuyl), which will facilitate the specification of a wide variety of queries of interest to travelers, to transportation agencies, and to industry. Queries in TranQuyl may be processed in either client server mode, or mobile peer-to-peer (P2P) mode, or both. TranQuyl will provide support for the specification of uncertainty either quantitatively or qualitatively as fuzzy queries, for example: “retrieve safety/emergency information around me”. In response, query processing should avoid overloading the traveler with information, and instead present only the most relevant answers to the query.
Highlights
The impact of Computer Science (CS) and Information Technology (IT) on transportation systems is not as dramatic as the one on science, finance or business in general
Intelligent Transportation Systems envision a networked environment consisting of vehicles, the infrastructure, and hand-held devices
Intelligent Transportation efforts are currently being undertaken throughout the world
Summary
The impact of Computer Science (CS) and Information Technology (IT) on transportation systems is not as dramatic as the one on science, finance or business in general. In addition to the IntelliDrive initiative of the U.S Department of Transportation (RITA 2010) mentioned above, similar efforts exist in Europe, Japan, and China These efforts are largely decoupled from, and often incognizant of, the advances in spatio-temporal information management and ubiquitous sensing. Things are starting to change in the sense that the Civil Engineering community, which is driving the Intelligent Transportation efforts, becomes aware of the potential of spatio-temporal information tools to facilitate the large scale deployment of Intelligent Transportation applications Towards this end, i.e. facilitating Intelligent Transportation applications, we propose three objectives, corresponding to query-language design, query-processing, and answer filtering. The system should provide language mechanisms for querying all such data including trips in a multi-modal (e.g. car, bus, and train) transportation network It should allow queries about available resources, traffic conditions, dynamic route planning, etc.
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