Linearization of Nonlinear Conditions in Autonomous Vehicle Control Systems

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Growing interests and the needs for the next generation manufacturing and transportation means such as Industry 4.0, driverless vehicles, flying cars and ever growing desire to bring drones to our doors as a delivery option continue bringing challenging research questions to the academia and the industry. Autonomous vehicles (AVs) such as drones, unmanned aerial vehicles (UAVs), Automated Guided Vehicles (AGVs), Driverless cars and Airplanes all share three common characteristics. They are i) required to complete a journey from an origin to destination on time; ii) free of collision and conflict; and ii) using minimum energy. Industrial Engineering and Operations Research communities have provided several solution techniques to tackle vehicle routing and sequencing problems. On the other hand, researchers from aerospace and control filed have tackled collision and conflict avoidance issues in AV control systems independently from the path-planning problems. Very few researchers have looked into energy consumption problem as part of the vehicle operations planning process. While abundance of research work has been produced in these three traits related to AV control areas, organizations continue facing great challenges at the operation level particularly in air-transportation and AGV operations due to frequently faced congestion and deadlocks. Our research results have shown that the main problem in AV control systems is the lack of methods to consider all influential factors simultaneously in a unified mathematical model. Historically researchers have failed to combine energy consumption, collision avoidance and path planning objectives in the same linear programming model due to the nonlinear features in fuel consumption and collision avoidance problems. Hence, during next five years, we plan to investigate the linearization of various physical conditions which are inherently nonlinear phenomenon in various transportation systems so that the development of unified linear programming models to tackle AV control systems. In our case, we will focus on developing methodologies for the Air Traffic Management (ATM) problem which is a special class of the vehicle routing problem. Collision and Conflict avoidance and fuel consumption issues are crucial for the air transportation industry due to safety and cost concerns as well as their impacts on the environment. While our immediate focus will be the collision and conflict avoidance and fuel consumption problems in ATM problems; it is important to note that all other types of AV operations planning problem requires explicit consideration of collision avoidance and energy management at the planning phase in order to lay the grounds for successful implementations. Therefore, it is safe to claim that the outcome of the proposed research program has potentials to revolutionize the next generation AV control systems such as ATM, AGV, UAV, drone and driverless vehicle systems.