The design of a context-aware service system in intelligent transportation system - Jingkun Chang; Wenbin Yao; Xiaoyong Li (International Journal of Distributed Sensor Networks)
Various sensors have achieved large-scale deployment as important data sources in intelligent transportation systems, and abundant data are generated and processed into useful information and new services. The means by which to make effective use of this information and these services to benefit the driver and improve road safety is very important in an intelligent transportation system. This research aims to describe the design and implementation of a context-aware service system for perceiving the driving situation and providing the most appropriate function or information services to address the actual needs in a driving assistance environment. To describe various hazardous situations, the status-emphasized context model and reasoning rules are proposed to abstract the context information and facilitate better understanding the driver’s context. The approach of customized service invocation is proposed by the retrieval of the service configuration model, which builds the relationship between the driver’s status and appropriate business services. In addition, to address the situations with multiple hazards, a priority- and severity-based invocation control algorithm is proposed; through this algorithm, the invocation procedure can be determined based on the priority and severity of the hazards. An evaluation based on computational experiments is conducted to verify the availability and validity of the service system.