Testing a novel platoon management protocol on the simulation platform
Autonomous vehicles have gained popularity over the years due to its increasing credibility and reliability. As the world moves towards automation, with artificial intelligence and machine learning being the need of the hour, the motivation to develop an autonomous vehicle can be visualized as a rev...
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| Format: | Theses and Dissertations |
| Language: | English |
| Published: |
2018
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| Online Access: | http://hdl.handle.net/10356/73122 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | Autonomous vehicles have gained popularity over the years due to its increasing credibility and reliability. As the world moves towards automation, with artificial intelligence and machine learning being the need of the hour, the motivation to develop an autonomous vehicle can be visualized as a revolution in the automotive industry. This dissertation, focuses on one such attribute of self-driving vehicles that is predominantly deployed by many heavy duty vehicles in recent times, on automated highways for transporting goods and people. Vehicle platooning is an attribute of self-driving vehicles that provide high efficiency and reduce traffic congestion. It consists of a group of vehicles travelling closely and at high speeds on highways. This Thesis, aims to test an existing platoon management protocol on a novel simulation platform for merging two platoons into one single platoon. It involves using a communication protocol that has been adopted from literature, for the vehicles to communicate and facilitate the merging operation. In order to accomplish the simulation task, three software packages are used that work together namely, MATLAB (Application simulator), NS3 (Traffic simulator) and VISSIM (Traffic simulator). The control algorithm for platoon merging is developed using MATLAB, the communication protocol is modeled using NS3 and the simulation of real-time traffic is done using VISSIM. The platoon behavior is examined using various profiles, such as the velocity profile (velocity of vehicles as a function of time) and inter-vehicular distance profile (distance between a vehicle and its preceding vehicle as a function of time). |
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