Implementation of a VANET Geo-Fence Based Adaptive Traffic Light Control Scheme
In this thesis we extend the VANET-based approach to counting vehicles at a traffic light by implementing a Geo-fence Based Vehicle Counting Algorithm which supports the use of RFID technology. This implementation utilizes the concept of geo-fencing to create a Zone of Interest (ZOI) that section...
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| Format: | Others |
| Language: | English |
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Florida Atlantic University
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| Online Access: | http://purl.flvc.org/fau/fd/FA00004720 |
| Summary: | In this thesis we extend the VANET-based approach to counting vehicles at a traffic
light by implementing a Geo-fence Based Vehicle Counting Algorithm which supports the
use of RFID technology. This implementation utilizes the concept of geo-fencing to create
a Zone of Interest (ZOI) that sections off a roadway that is relevant to a traffic intersection.
All vehicles in this ZOI are used to determine the required length of the green-cycle time.
By utilizing vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) technologies, we
broadcast beacons that are propagated to all vehicles in the ZOI from the infrastructure
which in this case is the traffic light controller.
These beacons are used to determine the last vehicle location in the ZOI. A timing
algorithm ensures that the last vehicle broadcasts first. The beacons are sent using the
IEEE 1609.4 Wireless Access in Vehicular Environments Standard Vendor Specific Action
(VSA) frames on the Smart Drive Initiative Vehiclular Ad Hoc Networks testbed. This
work is implemented in conjunction with the Vehicular Multi-technology Communication
Device (VMCD) supported by the National Science Foundation. === Includes bibliography. === Thesis (M.S.)--Florida Atlantic University, 2016. === FAU Electronic Theses and Dissertations Collection |
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