A critical problem facing U.S. airports as they respond to growth in services and operations is the limitation of curbside parking for shuttles to pick-up and drop-off passengers during peak hours. Today, shuttle companies and airport operations work independently without any schedule coordination, leading to frequent congestion near the pick-up and drop-off points that negatively affects passenger traffic leading to unnecessary idling, delays, and congestion with negative impact on air quality and quality of service to passengers. Accurate prediction of arrival times at the pick-up and drop-off points depends on traffic conditions, which are time varying, as well as on the schedules of other shuttles sharing the same curbside spots. Without any form of central coordination, a single shuttle company cannot accurately develop a schedule that maintains a high quality of service at a reduced operational cost. This problem is exacerbated by existing and growing shuttle services provided by the airports themselves, centralized car rental facilities, and public transportation hubs. Furthermore, the transition of conventional shuttles to electric ones and the possibility of autonomous shuttles adds additional complexities that necessitate the use of a centralized shuttle coordination system for optimum performance.
The purpose of this project is to develop a CENtrally COordinated Shuttle system (CENCOS) which can effectively coordinate shuttle schedules and routes in order to minimize curb congestion at the pick-up and drop-off points, reduce operational cost, improve quality of service with considerable benefits to mobility and environment. CENCOS will be designed using a co-simulation load balancing approach where the digital twin of the traffic network is part of the optimization procedure in order to take into account complex traffic dynamics and interactions of vehicles and generate accurate predictions of traffic states at the various links to be used by the optimizer. The system will receive demands and desired schedules from all shuttle companies and generate schedules and routes that minimize an overall system cost while meeting the performance and operational cost goals of each shuttle provider. As shuttle companies shift to electric shuttles and/or autonomous shuttles, CENCOS will take these technologies into account and evaluate their impact on the system performance, operational cost, and impact to the environment.
CENCOS will be demonstrated using a “digital twin” of the Los Angeles World Airport (LAWA) traffic network developed in a previous project supported by LAWA. The CENCOS, however, if successful, can be applied to a wide range of applications involving pick-up and drop-off points and shuttles in airports and other places. The quantification of benefits using CENCOS of current and new technologies will help speed up implementations.