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8The objective of this paper is to quantify and characterize driver behavior under different 9 roadway geometries and weather conditions. In order to explore how a driver perceives the 10 rapidly changing driving surrounding (i.e. different weather conditions and road geometry 11 configurations) and executes acceleration maneuvers accordingly, this paper extends a Prospect 12 Theory based acceleration modeling framework. A driving simulator is utilized to conduct 76 13 driving experiments. Foggy weather, icy and wet roadway surfaces, horizontal and vertical 14 curves, and different lane and shoulder widths are simulated while having participants driving 15 behind a yellow cab at speeds/headways of their choice. After studying the driving trends 16 observed in the different driving experiments, the extended Prospect Theory based acceleration 17 model is calibrated using the produced trajectory data. The extended Prospect Theory based 18 model parameters are able to reflect a change in risk-perception and acceleration maneuvering 19when receiving different parameterized exogenous information. The results indicate that drivers 20 invest more attention and effort to deal with the weather challenges (statistically significant 21 changes in behavior) compared to the effort to deal with the road-geometry conditions. 22Moreover, the calibrated model is used to simulate a highway segment and observe the produced 23 fundamental diagram. The preliminary results suggest that the model is capable of capturing 24 driver behavior under different roadway and weather conditions leading to changes in capacity 25 and traffic disruptions. 2 3 4 5 6 7 8