Abstract
The driver route choice problem under real-time information provision is characterized by subjectively interpreted and/or linguistically expressed data in addition to quantitative inputs. In previous work, the authors propose a hybrid probabilistic-possibilistic model which treats qualitative and quantitative data simultaneously in a single framework. This paper presents experimental insights on the performance of the hybrid model based on extensive simulation analysis under potential real-world scenarios. It performs sensitivity analyses on the associated driver behavior model parameters, and investigates the model’s ability to capture dynamic qualitative phenomena under information provision. The results highlight the flexibility of the hybrid model in addressing a broad range of driver behavior characteristics and network conditions. They also suggest that the hybrid model can capture the evolution of the driver behavior characteristics over time and the influence of the randomness in network conditions on route choice behavior.
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