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With the development of autonomous driving technology, autonomous vehicles (AV) will gradually replace human-driven vehicles (HDV), but it will still be a mixed traffic flow of autonomous vehicles with different levels of automation for a long time. In addition to cars, trucks regarded as moving bottleneck are also an important part of traffic flow of expressway. In this paper, the elimination rule of moving bottleneck is introduced into the traffic flow model, and the improved hybrid traffic flow cellular automata model is proposed. Next, through numerical simulation, the existence and influence of moving bottleneck caused by heavy duty trucks are hypothesized and verified. The simulation results show that with the proportion of trucks increases, the influence range of moving bottleneck expands, resulting in the decrease of capacity and traffic congestion. Then, the impact of Level 2 autonomous vehicles (hereinafter referred to as L2 AVs) on the traffic flow of moving bottlenecks is explored. The simulation results show that with the proportion of L2 AVs increases, traffic capacity increases, and traffic congestion ratio at medium and high density decreases. Under medium density, the average velocity fluctuates greatly, while under high density, the average velocity decreases due to limitation of density. In summary, L2 AVs can alleviate influence of moving bottlenecks, increase traffic capacity, improve traffic congestion, and lift road safety. The cellular automata model of traffic flow including moving bottleneck proposed in this paper is based on the actual road situation, considering the fact that most of autonomous vehicles on the expressway currently are L2 AVs, and moving bottleneck is mainly caused by heavy trucks. This research contributes to an in-depth analysis of L2 AVs on heterogeneous traffic flows under moving bottleneck environment. • The recognition rules of moving bottleneck are proposed. • The impact of L2 AVs on heterogeneous traffic flow involving heavy trucks and human-driven vehicles is explored. • The congestion caused by heavy trucks running in parallel can be effectively alleviated by L2 AVs. [ABSTRACT FROM AUTHOR]

This article aims to explore the stability, energy consumption and CO 2 emissions of a novel discrete car-following model with time delay. Under the assumption that the preceding two successive vehicles can realize the communication through V2V (Vehicle to Vehicle) communication environment. Moreover, the time-delayed average optimal velocity difference control scheme is also considered. Based on the proposed discrete car-following model, error dynamical system is formulated and asymptotic stability is developed. The sufficient condition for the time-delayed average optimal velocity difference control scheme of the discrete car-following model with time delay is obtained, the asymptotic stability is ensured. In addition, numerical simulations are constructed and further illustrated the cooperative driving by V2V communication can improve stability, reduce energy consumption and CO 2 emissions of traffic system. Moreover, the time-delayed average optimal velocity control scheme is also conductive to improve stability, reduce energy consumption and CO 2 emissions of traffic system. • A discrete-time car-following model with time delay is proposed. • The delayed average optimal velocity difference control is considered. • The stability is developed and stability condition is obtained. • The effects of time delay and control scheme on dynamics are studied. [ABSTRACT FROM AUTHOR]

In order to explore the influence of electric vehicles on the traffic flow characteristics of traditional fuel vehicles, this paper proposes an improved cellular automata model considering the physical properties of vehicles, such as, the acceleration and deceleration amplitude, relative speed and safety distance etc. Based on the sensitivity analysis of the randomization probability, combined with the actual data, the model parameters are quantified to simulate the electric-fuel vehicle mixed traffic flow. Through numerical simulation, the results show that compared with NS (Nagel–Schreckenberg) model and VE(Velocity Effect) model, the improved model can reproduce rich traffic phenomena and is closer to the measured data. With the increase of electric vehicle permeability, the flow rate and speed are increased, the congestion near the critical density is reduced and the traffic safety is improved. At high density, the congestion shows a trend of decreasing first, then increasing and then decreasing again, and the safety is lower than that of homogeneous traffic flow. The speed fluctuation of fuel vehicles is enlarged, and the speed of the overall traffic flow shows an upward trend. In addition, it is found that the TIT curve can identify the state change of traffic flow, and electric vehicles in high-density mixed flow cause greater disturbance to the speed of traffic flow and reduces traffic safety. The results of this paper can provide a basis for further research of electric-fuel vehicle hybrid traffic flow. • A heterogeneous traffic flow model mixed with EVs considering the amplitude of acceleration and deceleration is proposed. • Under medium and high density, the greater the penetration rate of EVs, the greater the vehicle speed and flow rate. • Near the critical density, the threshold of congestion occured increases with the proportion of electric vehicles. • The speed fluctuation of EVs decreases with the increase of its permeability, while fuel vehicles is the opposite. [ABSTRACT FROM AUTHOR]