Abstract
Beside human factors, driver behavior characteristics are influenced by many other factors, including vehicle, road, environment, traffic situation, etc. To investigate and study the driver behavior characteristics influenced by different factors using a comparative analysis approach, experiments involving a total of 73 test drivers using multi-objects have been conducted on diverse road types. Some representative parameters such as host vehicle speed (V), distance headway (DHW), time to collision (TTC) and time headway (THW), and test methods such as the u-test, were adopted to analyze and compare the effect on driver behavior for relative factors, which include vehicle factors (e.g. truck vs. saloon, with vs. without Advance Driver Assistance System (ADAS)), road factors (e.g. intercity road vs. local road, curve vs. straight), and maneuvers (e.g. car following vs. lane change). Finally, an approach using an artificial neural network is proposed to model driver behavior during car-following scenarios. Simulations with different leading vehicle speeds have also been conducted, and the results show that the neural network model was capable of simulating the driver’s car-following behavior and was adaptable to normal car-following situations.
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