Abstract
As the accident-prone sections and bottlenecks, highway weaving sections will become more complicated when it comes to the mixed-traffic environments with connected and automated vehicles (CAVs) and human-driven vehicles (HVs). In order to make CAVs accurately identify the driving behavior of manual-human vehicles to avoid traffic accidents caused by lane changing, it is necessary to analyze the characteristics of the mandatory lane-changing (MCL) process in the weaving area. An analytical MCL method based on the driver’s psychological characteristics is proposed in this study. Firstly, the driver’s MLC pressure concept was proposed by leading in the distance of the off-ramp. Then, the lane-changing intention was quantified by considering the driver’s MLC pressure and tendentiousness. Finally, based on the lane-changing intention and the headway distribution of the target lane, an MLC positions probability density model was proposed to describe the distribution characteristics of the lane-changing position. Through the NGSIM data verification, the lane-changing analysis models can objectively describe the vehicle lane-changing characteristics in the actual scenarios. Compared with the traditional lane-changing model, the proposed models are more interpretable and in line with the driving intention. The results show significant improvements in the lane-changing safe recognition of CAVs in heterogeneous traffic flow (both CAVs and HVs) in the future.
Highlights
As one of the basic driving behaviors, lane-changing manoeuver directly affects the fluency and safety of traffic flow
It can be seen from the figure that the segment has a weaving section and the collected trajectory data is complete. 157 cars which have finished mandatory lane change (MLC) were extracted from the data
Inspired by the principle of discretionary lane change models, this paper proposes a method based on driver’s psychological pressure to analysis MLC. e main factor for driving the driver to DLC is the lanes’ utility, and the main factor for driving the driver to MLC is the lane-changing pressure. erefore, this paper proposes a new concept named lane-changing pressure to analyze the MLC stages
Summary
As one of the basic driving behaviors, lane-changing manoeuver directly affects the fluency and safety of traffic flow. Based on the above research foundation, this paper will use the traffic flow theory and driver characteristics to analyze the vehicles’ lane-changing behavior in expressway weaving area. The existing models have not fully analyzed the influence of the driver’s psychological characteristics on the lane-changing process [13]. To address this challenge, the concept of lane-changing pressure is introduced to describing the drivers’ pressure fluctuation in MLC. Combining the target lane headway distribution and MLC intention, a lane change probability density model is proposed to describe the lane-changing characteristics in the weaving area.
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