Integrated vehicle routing: a case study of unmanned aerial vehicle decision making

Abstract

Time critical vehicle routings, such as with unmanned aerial vehicle (UAV) routing, are considered as integrated location routing problems where the objective is to simultaneously optimise the location and the routing. Although computer systems are good at providing solutions for optimised routing, they may not have the expert knowledge as that of human operators. Human operators play an important role in ensuring the safety and in achieving operational effectiveness in such systems. Problems such as increased human error, lack of situational awareness, and opacity from poorly automated systems remain; particularly in scenarios where human operators must make decisions in time-pressured planning. Hence, we study joint cognitive problem solving for a class of problems related to supervisory control of integrated vehicle routing. Results indicate that the graphical representation of the routing alternatives led to quicker evaluation time by the operator than tabular representation.