As lane-changing behavior has received increasing attention during the recent years, various algorithms have been developed. However, most of these models were derived and validated using data such as vehicle trajectories, with no consideration of driver characteristics. In this research, focus group studies were conducted to obtain driver-related information so that the driver characteristics can be incorporated into lane-changing models. Different urban lane-changing scenarios were examined and discussed in the focus group meetings. The likelihood for initiating lane changes under each scenario was obtained. The participating drivers were categorized according to their background information and verbal responses, so that the lane-changing behavior can be related to driver characteristics for each group. Two types of information, quantitative and qualitative responses from participants, were used to establish this relationship. The paper concludes by providing recommendations related to the implementation of study findings into micro-simulators to better replicate driver behavior in urban street networks.
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