Optimal driving decision based on energy and time costs

Sammanfattning: Nowadays the industrial world has a common goal to build environment-friendly transportation and power-train systems. The first step for this aim is electrification of vehicles on the road which has remarkable influence on energy dependency and greenhouse gas emissions. Besides the first aspect the second most important factor is automation of driving technology. Self-driving technology is a significant sight for the industry to develop quality and reduce operation costs. These highlighted tendencies cooperate to enhance the sustainability along with intelligence of the modern transportation world. VERA is Volvo’s concept for driverless, electric truck technology. It holds the following tremendous advantages: automation, connectivity and electromobility – to accomplish optimal flows in transportation and logistics operations. The control is managed by autonomous electric vehicles equipped with refined systems for autonomous driving. Each vehicle is connected to a control centre. The transport control centre continuously regulates the progress of the transport and keeps an accurate supervision of each vehicle’s position, load content, the batteries’ charge and a number of other parameters. Despite the improvements performed to refine this technology, heavy batteries, long time charging and the cost of vehicle itself limit the wide usage of electric AV for long distances. The research of this paper illustrates one of the most substantial aspects in autonomous electrified driving which is the charging decision. There are several approaches used to solve this question. It is popular among contributions to provide a data-driven method, i.e by considering constraints from personal daily trips and existing charging infrastructure. As a solution, stochastic energy consumption models are designed within proposed dynamic and multi-stage optimization problems. This paper provides treatment through evaluation and optimization of expenditures for AV involved in a certain road trip.