Understanding the human behaviors in driving is a highly complex topic but on the other hand, extremely important for improving human's driving competence by developing driver assistant systems accordingly and finally accomplishing fully autonomous vehicles and road systems. There are many excellent researches in this area for decades. However, by building a comprehensive system to evaluate human driver's behavior, we found that none of the existing model can reflect the same outcome as our observation from the real world in the multiplex traffic scenario. But this is indeed important for us to find the right way to improve road traffic efficiency as well as develop autonomous vehicles. In this work, we combined couple of previous approaches to a single model with some improvements and successfully implemented it into a new simulator which can be used to evaluate other traffic applications upon the driver behavior model. We focused on lane changing decision of the driver behavior since it is the most complex part and causes the most problem and inconsistency in previous researches. After comparing the result getting from the simulation based on the new model with the real world observation, we can conclude that the new driver behavior model does reflect the real world scenario. And the model and simulator also helps us in our further researches in intelligent traffic control area.