# Vehicle Lane Change Models--A Historical Review
## 2 Vehicle Lane Change Models
### Physical Models of Lane Change
#### 2.2.2 Dynamic Models
The decision model depends on the change in traffic environment, the condition model describes different types of lane change conditions, and the maneuver model describes the change in speed and lane change duration. Frequent lane changes by vehicles in the diverging, confluence, and intersection areas of expressways may increase the traffic accident rate. [PERSON] [88] proposed a moving wave model to describe the traffic dynamics, and studied the bottleneck effect of lane change traffic and the aggregate traffic dynamics of roads with lane change areas. [PERSON], [PERSON] et al. [91] conducted a study based on [PERSON]'s [88] idea to obtain the lateral interaction through the intensity variable of lane change, with the main purpose of describing the process of lane change by constructing a microscopic lane change model. Different from [PERSON] [88], who described lateral interactions at the level of macroscopic polymerization, [PERSON], [PERSON] et al. [91] described microscopic lane change decisions and maneuvers. They proposed a new idea of transforming the lane change process into the vehicle-following process through the simulation environment. In order to verify the effectiveness of the model, traffic flow, lane change frequency, and vehicle speed were obtained from the experiment and compared with the results in the simulation environment. With the maturing of intelligent technology, intelligent cars have begun to be slowly integrated into our travel. In the process of intelligent vehicle driving on the road, the success of lane changing plays a decisive role in driving safety. In order to achieve the ideal driving experience on the road, drivers often choose to avoid slower vehicles, pedestrians, obstacles that interfere with normal driving, or lane closures. In order to cope with mobility bottleneck and lane reduction, [PERSON] et al. [92] studied the theory of micro-dynamic vehicle following and lane changing, proposed additional lane-changing rules, and analyzed the impact of lane changing on traffic safety, traffic efficiency, and economy. Through the simulation of different traffic scenarios, some factors affecting traffic were obtained. The results have important implications for the efficiency and safety of transport and commuting. In order to improve the safety, comfort, and energy saving of vehicle lane change, [PERSON] et al. [93] proposed a multi-objective collaborative optimization lane change trajectory-planning algorithm. The constraints of the trajectory-planning method depend on variables such as vehicle lane change time, longitudinal and lateral velocity, and acceleration. On the basis of vehicle kinematic and dynamic theory, the safe range of vehicle lane change [94] was analyzed, a sixth-degree polynomial lane change trajectory model was established, and the lane change trajectory cluster was obtained by using the genetic algorithm-BP neural network to predict the lane change completion time and target position. By analyzing performance indicators such as vehicle lane change safety, comfort, and economy, the multi-performance collaborative optimization objective function and constraint conditions were constructed, and the whale optimization algorithm [95] was used to optimize the lane change trajectory cluster. Finally, the multi-performance target collaborative vehicle lane change trajectory-planning algorithm was obtained. In order to verify its accuracy, an experiment was carried out using an L3 intelligent vehicle. The test results showed that the simulation of vehicle lane change trajectory planning is effectively improved. [PERSON] et al. [96] analyzed and summarized the situation of vehicle lane change, and found that vehicle lane change is influenced by surrounding vehicles; based on this finding, the characteristics of low-carbon lane change were further improved. When a vehicle changes lanes, the dynamics of the surrounding vehicles play a decisive role in whether the vehicle successfully changes lanes.