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A knowledge-based database is developed to support the proposed framework.
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Theoretical analysis indicates that for the high accuracy of the spectrum map, the number of WSAPs supporting the proposed framework should be greater than 0.4 times the total number of all registered and unregistered WSAPs to the RRM server.
Aspects identified as requiring assessment in terms of driver-support within the proposed framework are Accident Avoidance, gained Situation Awareness (SA) and Concept Acceptance.
For example, the sensing data captured by the combination of a digital camera and a terrestrial laser scanner are also supported by the proposed framework, if the color images captured by the digital camera are well calibrated with the data captured by the laser scanner.
To support selection variety, the proposed framework can operate by tuning and using the most preferable among these SFC methods, as space traversal quality and computation performance may differ according to the data context.
Comparison of the resulting association networks from these two approaches also supports the validity of the proposed framework.
The proposed framework supports different affordances for play.
The proposed framework supports a balanced approach between development needs and the natural environment.
The proposed framework supports extensible, module-based and layered modeling, and scalable, accurate and efficient simulation of vehicular scenarios integrated with wireless communication and mobile services/applications.
By separating data and view, the proposed framework supports view-wandering between different perspectives so that designers can adjust their behaviors to avoid conflicts.
The proposed framework supports seamless communication among the widely adopted Constrained Application Protocol (CoAP), Representational State Transfer (REST) over Hypertext Transfer protocol HTTP, and the Message Queue Telemetry Transport protocol (MQTT).
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