This paper describes an application of dynamic programming to determining optimal driver control of an automobile for fuel economy. The objective function is provided by a simulator that uses vehicle performance maps derived from statistical analysis of road data collected by the authors. One dynamic program controls acceleration as a function of time subject to constraints on speed, acceleration, and distance covered. Another controls acceleration and gearshift subject to constraints on speed, acceleration, and time required to shift gears. Results are presented for acceleration to a given cruising speed, driving over hills while achieving a given average speed, and driving from one stop sign to another.

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A team of Systems Engineering students at George Mason University have developed an initial design for an integrated system, the Airport Departure Arrival Management System (ADAMS), which provides information and decision support capabilities to air traffic managers, ground controllers, and National Central Flow Control. The objective of ADAMS is to decrease the net arrival-departure delay for a network of airports by leveraging high fidelity weather forecasts, capacity optimization algorithms, and ground sequencing guidance. This paper presents the results of the design efforts, with a brief look at functional architecture, and preliminary simulation results to evaluate the impact of ADAMS on net flight delay and network stability in a six-node network of airports.