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In a traffic system with HOV lanes, considering two modes of driving alone and carpooling, we proposed three kinds of travel cost functions for potential commuters such as carpoolers in HOV lanes, driving alone users and carpoolers in general purpose lanes. Assume that all commuters will experience a random travel time with discrete distribution during their trip, this paper compared the commuters' equilibrium choices of travel mode and travel route under the framework of cumulative prospect theory and expected utility theory. In addition, the sensitivity analysis on the proportion of driving alone users, the individual preference such as the reference point were conducted. The resultant observations show that the individuals' risk preference and reference dependence definitely affect the commuters' choices on the travel mode and travel route. When the proportion of driving alone users exceeds a critical value, the carpooling users will be better than driving alone users since they have higher cumulative prospect value. However, this critical value will be slightly overestimated under the framework of expected utility theory. [ABSTRACT FROM AUTHOR]

Taking the commuters' travel mode choice behaviors as the research subject, we assume that there are three possible travel modes of transit mode, solo-driving mode and park-and-ride mode. Without loss of generality, the travel time for transit mode is assumed fixed while the travel time for other two modes are assumed stochastic. With this consideration, we first establish the travel mode choice models and compared the difference between the optimal choices in different scenarios under the framework of cumulative prospect theory (CPT) and expected utility theory (EUT), respectively. Then, the empirical investigation is conducted to verify the previous theoretical results. The empirical results show that, the individuals' decisions change with the scenarios, and they are consistent with the choices under the framework of CPT. In this sense, the transportation administrators should manage and optimize the road resources based on individuals' risk preferences. [ABSTRACT FROM AUTHOR]