<p dir="ltr">Cellular-Vehicle to Everything or C-V2X refers to vehicles connected to their surroundings using cellular based networks. With the rise of connected vehicles, C-V2X is emerging as one of the major standards for message transmission in automotive scenarios. The project aims to study the feasibility of C-V2X-based message transmission by building a prototype system, named <b>RampCast</b>, for transmitting traffic information from roadside message boards to vehicles. The RampCast framework would also implement geocasting-based algorithms to deliver messages to targeted vehicles. These algorithms focus on improving location-based message delivery using retransmission and prioritization strategies. The messages used for transmission are selected from the 511 web application built by INDOT, which contains the live traffic information for the state of Indiana which includes Travel Time information, Crash Alerts, Construction Alerts etc.</p><p dir="ltr">The major objectives of this project consist of building the RampCast prototype, a system implementing C-V2X networks using a Software Defined Radio(SDR). The RampCast system implements a Publisher-subscriber messaging architecture with the primary actors being a Road Side Unit(RSU) and a Vehicle Onboard Unit(OBU). A data store containing traffic messages sourced from the 511 API is set up to be the input to the RampCast system. An end-to-end message transmission pipeline is built that would implement message transmission algorithms on the RSU and OBU side. Finally, the performance of message transmission on the RampCast system is evaluated using a metrics-capturing module. The system was evaluated on a test track in Columbus, Indiana. The performance metrics of the system were captured and analyzed, and the system met the key performance indicators for Latency, Packet Delivery Rate, and Packet Inter-reception Rate. The results indicate the satisfactory performance of the C-V2X standard for message transmission in the RampCast traffic guidance scenarios.</p>
Identifer | oai:union.ndltd.org:purdue.edu/oai:figshare.com:article/26031382 |
Date | 03 September 2024 |
Creators | Abin Mathew (18823303) |
Source Sets | Purdue University |
Detected Language | English |
Type | Text, Thesis |
Rights | CC BY 4.0 |
Relation | https://figshare.com/articles/thesis/GEOCASTING-BASED_TRAFFIC_MANAGEMENT_MESSAGE_DELIVERY_USING_C-V2X/26031382 |
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