# Modeling of Lane Changing Behavior of Connected Driving Based on Vehicle Interaction Potential
## 5 Conclusions  
1. The establishment of vehicle interaction potential based on Lennard-Jones potential introduced the correction of vehicle shape, speed, acceleration, and steering angle, which made up for the previous research on the molecular lane changing model directly based on the Lennard-Jones 6-12 potential function that ignored the huge differences between particles and vehicles in parameters such as mass and velocity. By drawing the spatial distribution map of the vehicle action potential field under  
Figure 14: Experimental data of vehicle action potential lane changing model.  
Figure 15: Comparison of average speeds of different models.  
different motion states, the changes in the vehicle action potential field with vehicle speed, acceleration, and steering angle can be directly analyzed, which makes the study of vehicle microscopic behavior based on molecular dynamics more realistic.
2. In the previous study of the molecular dynamics lane changing model, the setting of longitudinal critical distance after lane changing only considered the speed and acceleration of the current vehicle, ignoring the influence of the running state of the leading vehicle on the critical safety distance after lane changing. In this paper, the acceleration of the front vehicle is introduced into the longitudinal critical distance, and the relationship between the acceptable clearance of lane changing and the speed difference and acceleration difference of the interacting vehicle is clarified through the analysis of the safe critical time of lane changing. The acceptable gap expressions between lane changing vehicle \(M\) and leading vehicle \(L\) and target lane leading vehicle \(TL\) and target lane following vehicle \(TF\) were constructed, respectively. Through simulation analysis of different motion states of interactive vehicles, reasonable suggestions were put forward for lane changing behavior in the networked environment.
3. A lane changing model based on vehicle interaction potential is established, the action potential and potential field force generated by the surrounding interacting vehicles of the lane changing vehicle are analyzed, and the driving decision of vehicle \(M\) under different potential field forces is given. Compared with the molecular dynamicsbased lane changing model and LS2015 model, the effectiveness of the proposed method is verified. It has theoretical guiding significance for vehicle lane changing behavior decisions in future intelligent network environments.
4. The following problems should be considered in the following research: First, the paper compares the vehicle as a molecule. In order to simplify the model, the center of mass of the vehicle is taken as the coordinate point, and the influence of the vehicle shape on the distance is ignored. Second, the end of the paper uses simulation tests to verify the analysis, not using the data of natural experiments to verify, and there may be more uncertain factors in the actual driving environment; in following research, still needed is the use of data of natural experiments to verify the effectiveness.  
Conceptualization, D.Q.; methodology, S.C.; software, Y.C.; validation, Y.Y.; writing--original draft and writing--review and editing J.L. All authors have read and agreed to the published version of the manuscript.  
This research was funded by [National Natural Science Foundation of China] grant number [52272311].  
Not applicable.  
Note applicable.  
Where no new data were created.  
The authors declare no conflict of interest.