Modeling Multi-Objective Optimization Algorithms for Autonomous Vehicles to Enhance Safety and Energy Efficiency

Multiple optimization controls are associated with autonomous vehicles’ movement. These control systems are employed to enhance the comfort of passengers in commercial vehicles or to avoid enemy areas for unmanned military convoys. However, having multiple objectives for optimization can greatly enhance the perception and applicability of these algorithms. This paper involves demonstrating a multi-layered optimization framework which can achieve both and efficiently navigate autonomous vehicles. Other than the primary objective of reducing the probability of intersection crashes, minimizing individual vehicle delay and additionally minimizing energy consumption are the objectives of this example. Primarily this application consists of two parts: a multi-objective optimization framework and individual mathematical models that define vehicle parameters at intersections including vehicle dynamics model and vehicle energy consumption models. Such optimization framework could enhance driving algorithms of militarized convoys. Look-ahead controls would help them optimize both their distance as well as their energy consumption, thereby increasing convoy range and operational energy efficiency as well as decreasing costly convoy halts.