Study on the impact of connected automated vehicle position on mixed traffic flow stability

• Main Author: Tan, Kenneth Chiao Wee
• Other Authors: Zhu Feng
• Format: Final Year Project
• Language: English
• Published: Nanyang Technological University 2021
• Subjects: Engineering::Civil engineering
• Online Access: https://hdl.handle.net/10356/149349
• Institution: Nanyang Technological University

Traffic stability is of paramount importance because unnecessary traffic congestion due to unstable traffic flow worsens the performance of road transportation networks. Connected automated vehicles (CAV) is one of the emerging developments of information technology brought in to significantly improve road safety and efficiency. Car-following and vehicle control models are also incorporated into these vehicles in efforts to heavily improve future transportation network performance. However, despite the numerous research done on CAVs, the impact of CAVs’ position in a mixed traffic stream on traffic stability has not been heavily studied. The objective of this report is to investigate the impact of CAVs’ position on mixed traffic flow stability. Because CAVs utilise vehicle controls such as Cooperative Adaptive Cruise Control (CACC) and Adaptive Cruise Control (ACC) while human-driven vehicles (HDV) utilise driving models such as Intelligent Driving Model (IDM), these vehicles controls and models are also being examined in this study. In this report, Python programme is adopted in the simulation to achieve the project objectives. The entire simulation started with code-writing the above-mentioned vehicle controls and driving model (IDM, CACC and ACC) algorithms. This is followed by creating traffic stream scenarios in which positions of CAVs and HDVs are specifically generated for 5-vehicle and 10-vehicle mixed traffic streams. Ultimately, codes were also written for speed and statistical analysis of this simulation to make conclusions on how CAVs’ position in a mixed traffic flow can affect traffic stability. These conclusions were presented based on platooning CAVs and distance from CAV position to the leading vehicle. It is found that when a single CAV is placed furthest away from the leading HDV and when the leading vehicle is a CAV with another CAV being positioned as the following vehicle, optimum traffic flow stability is achieved. Likewise, when platooning CAVs are furthest away from the leading HDV and when all vehicles are platooning CAVs, traffic flow stability is likely to be in smooth condition.