Amid Maghsoudi - Assistant Professor, School of Mechanical Engineering, Iran University of Science and Technology, Tehran, Iran
Esmaeel Khanmirza - PhD. Candidate, School of Mechanical Engineering, Iran University of Science and Technology, Tehran, Iran
Farshad Gholami - PhD. Candidate, School of Mechanical Engineering, Iran University of Science and Technology, Tehran, Iran

Traffic control is a major and common problem in large-scale urban decision-making, particularly in metropolises. Several models of intelligent highways have been proposed to tackle the issue, and the longitudinal speed control of vehicles remains a key issue in the field of intelligent highways. Many researchers have been investigating the longitudinal speed control of vehicles. However, their proposed models disregard important and influential presumptions. In the present study, the longitudinal dynamics control of vehicles in the presence of nonlinear factors, such as air resistance, rolling resistance, a not ideal gearbox, an internal combustion engine and a torque converter, is investigated. Moreover, considering the presented model and using model reference adaptive control, a proper controller is designed to control the longitudinal speed of intelligent vehicles. The results of the proposed model, which is validated by commercial software, are in good agreement with real-world situations. Hence, a positive step is taken for controlling longitudinal speed of intelligent vehicles on an intelligent highway platform.

Intelligent Highway, Intelligent Vehicle, Longitudinal Speed Control, Model Reference Adaptive Control