Self-Driving Aircraft Towing Vehicles: A Preliminary Report

We introduce an application of self-driving vehicle technology to the problem of towing aircraft at busy airports from gate to runway and runway to gate. Autonomous towing can be supervised by human rampor ATC controllers, pilots, or ground crew. The controllers provide route information to the tugs, assisted by an automated route planning system. The planning system and tower and ground controllers work in conjunction with the tugs to make tactical decisions during operations to ensure safe and effective taxiing in a highly dynamic environment. We argue here for the potential for significantly reducing fuel emissions, fuel costs, and community noise, while addressing the added complexity of air terminal operations by increasing efficiency and reducing human workload. This paper describes work-in-progress for developing concepts and capabilities for autonomous engines-off taxiing using towing vehicles. Introduction Congestion at airports is recognized as one of the most prominent problem areas in the international airspace. Airports are expected to address this problem through expansion of their airfields. However, the addition of runways and taxiways will increase the complexity of air terminals, which will penalize the efficiency of the system by adding to human workload, thus restricting the potential benefits of the surface expansion. The increased complexity will also increase the risk of human error, resulting in potentially hazardous situations. In addition, the increasing number of taxiing aircraft will contribute significantly to an increase in fuel burn and emissions. The quantities of fuel burned as well as different pollutants, such as carbon dioxide, hydrocarbons, nitrogen oxides, sulfur oxides and particulate matter, increase with aircraft taxi duration, and also vary with throttle setting, number of running engines, and pilot and airline decisions regarding engine shutdown during delays. The economic pressures and increasing environmental awareness have recently fostered the development of new taxi operation technologies and procedures. The contribuCopyright © 2015, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved. 41 Artificial Intelligence for Transportation: Advice, Interactivity and Actor Modeling: Papers from the 2015 AAAI Workshop