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The engine operating point (EOP), which is determined by the engine speed and torque, is an important part of a vehicle's powertrain performance and it impacts FC, available propulsion power, and emissions. Predicting instantaneous EOP in real-time subject to dynamic driver behaviour and environmental conditions is a challenging problem, and in existing literature, engine performance is predicted based on internal powertrain parameters. However, a driver cannot directly influence these internal parameters in real-time and can only accommodate changes in driving behaviour and cabin temperature. It would be beneficial to develop a direct relationship between the vehicle-level parameters that a driver could influence in real-time, and the instantaneous EOP. Such a relationship can be exploited to dynamically optimize engine performance.

This paper presents a simulation and comparison of two different infra-red imaging systems in terms of their use in automotive collision avoidence applications. The first half of this study concerns the simulations of an “cooled” focal plane array infra-red imaging system, and an “uncooled” focal plane array infra-red imaging system. This is done using the United States Army's Tank-Automotive Command Thermal Image Model - (TTIM). Visual images of automobiles - as seen through a forward looking infra-red sensor - are generated, by using TTIM, under a variety of viewing range, and rain conditions. The second half of the study focuses on a comparison between the two simulated sensors. This comparison is undertaken from the standpoint of the ability of a human observer to detect potential (collision) targets, when seeing through the two different sensors.