Methodologically, traffic flow models can be divided into two categories: microscopic models and macroscopic models. The former group includes the cellular automaton models [
4] and car-following models [
5,
6], while the latter group includes the continuous models [
7-
9] and lattice models [
10-
16]. As opposed to the microscopic models, the macroscopic models are indifferent to the number of vehicles, such that less simulation and calculation time is required. This paper is concerned with the macroscopic models, more specifically the continuum models. The development of macro traffic flow models stems from the LWR model proposed by Lighthill, Whitham, and Richards [
17], which was constructed based on the principle of conservation of vehicle flow. However, it was found that the LWR model is incapable of simulating non-equilibrium traffic phenomena such as stop-and-go traffic behaviors. To conquer this drawback, in 1971, Payne proposed a higher-order traffic model by replacing the equilibrium speed-density relationship with a dynamic equation for speed [
18]. In 1995, Daganzo pointed out that the Payne model may violate the principle of anisotropy of traffic flow [
19]. Later, Zhang [
20] and Jiang
et al [
21] replaced the density gradient term in the Payne model with a velocity gradient term, such that the anisotropic characteristics of the traffic flow is satisfied, which paves the way for continuous flow modeling. Liu
et al [
22] proposed a continuum model considering the backward-looking effect, and they showed that the backward-looking effect can enhance the stability of traffic flow. Cheng
et al [
23], Zhai and Wu [
24] added the traffic jerk term into the continuum model, which showed that traffic jams can be suppressed efficiently when the drivers can avoid an unnecessary jerk effect. Liu
et al [
25] and Cheng
et al [
26] investigated the impact of curved road and slopes in continuum models, and the results showed that the provision of friction and radius in curved roads can suppress traffic congestion, while the angle and slope length in road slopes also greatly affect the stability of traffic flow. Cheng
et al [
27] presented an extended continuum model accounting for the drivers' timid or aggressive attributes. Considering that electronic throttle (ET) angle information is one of the most important items of vehicle information in connected automatic vehicles, Li
et al [
28] and Jiao
et al [
29] introduced ET difference information into the continuous model. Other related studies can be found in the literature [
8,
30-
39].