This paper presents a novel consensus control algorithm for a vehicle platoon, taking into account human physiological-psychological comfort. To this end, this paper incorporates state constraints into the optimal velocity-based platoon controller, which can effectively improve the comfort and consensus. Moreover, this paper employs the barrier Lyapunov function (BLF) to prove the stability of the proposed controller, providing more strict stability guarantees. According to theoretical analysis, numerical experiments are conducted to demonstrate the performance of the proposed control algorithm and the benchmark algorithm. The comparative results show that the proposed control algorithm can produce better-uniformed states and bounded state errors.

This paper proposes a generalized car-following (CF) model to depict the dynamics of traffic flow that includes human-driven vehicles (HDVs), connected vehicles (CVs) and connected and autonomous vehicles (CAVs). Notably, the model integrates human reaction times, information delays, and status data from multiple preceding vehicles endowed with communication capabilities. Then, by utilizing the perturbation method, the Intelligent Driver Model (IDM) as an example is taken in this CF model to determine the stability condition of the mixed traffic based on CAV penetration rate and their spatial distribution. Finally, comprehensive co-simulation using PreScan and MATLAB/Simulink is developed to explore the impact of varying CAV penetration rates across seven distinct spatial distributions on traffic capacity and dynamic performance. The findings underscore the efficacy of our proposed model in analyzing mixed traffic scenarios comprising HDVs, CVs, and CAVs. Increasing CAV penetration rates can lead to improved stability, capacity, and dynamic performance within mixed traffic environments. Notably, at the CAV penetration rate below 60%, the spatial distribution labeled as CAVs-HDVs-CVs (where CAVs lead the traffic flow, followed by HDVs, then CVs) demonstrates superior dynamic performance, whereas the HDVs-CVs-CAVs configuration (with HDVs leading, followed by CVs, then CAVs) performs worst. However, it’s noteworthy that spatial distribution scarcely affects dynamic performance when the CAV penetration rate exceeds 60%.

The paper aims to ensure that traffic parameters are simultaneously available between sparse sensors, and to improve the traffic efficiency of expressways and achieve the consistent driving state of mixed vehicle groups. Firstly, we propose a dynamic mixed segmental linear (DMSL) traffic model with external disturbances including automated vehicles (AVs) and connected automated vehicles (CAVs) as the composition of mixed vehicle groups on the expressway. Secondly, an observer-based double closed-loop control strategy is investigated by jointly controlling the on-ramp flow in the outer-loop control system and the driving state of mixed vehicle groups on the main section of the expressway in the inner-loop control system. Thirdly, the convergence and stability of the inner-loop control system and the outer-loop control system are analyzed by using Lyapunov stability theory, and the control gain and observation gain of the double closed-loop are obtained via adopting linear matrix inequality (LMI) method. Finally, numerical simulation experiments are executed to confirm the feasibility and accuracy of the proposed control algorithm. The results illustrate that the proposed control method is effective while the percentage of automated vehicles (AVs) is gradually increasing.

This paper proposes a new car-following (CF) model to capture the realistic behaviors of connected and automated vehicles (CAVs), whose communication topology (CT) among vehicles is characterized by graph theory in the V2V communication environment. By considering the heterogeneous time delays under the fixed and switching CTs, a generalized CF model is proposed. Based on the Lyapunov–Krasovskii method, a convergence analysis has been implemented for this new CF model with multiple time delays to obtain the convergence condition. Meanwhile, provides an estimate of the time delay bound. Finally, numerical experiments are performed under three typical fixed CTs (i.e., PF topology, BDLF topology, and TPLF topology) and the corresponding switching topology. Results support that the proposed CF model is capable of accurately reproducing the velocity, acceleration, position, and space headway profiles of CAVs traffic flow.

To guarantee vehicle platoon driven pattern in heterogeneous nodes of mixed vehicle platoon (composed of connected and automated vehicles and human-driven vehicles, CAVs and HVs) on curved roads, this study develops a combined longitudinal and lateral controller, which comprises of selecting the key points (KPs) from the trajectory points of detected HVs, correcting the reference trajectory and controlling CAVs with the aid of the corrected KPs. To this end, a new concept, called KPs matrix, is proposed to manage the physical components of every KP by using image processing and vehicle-to-infrastructure (V2I) communication technology. Then, a trajectory correction scheme is presented to suppress the influence of nonstandard human-driven behavior by point set mapping approach in Real Variable Function theory. Furthermore, a novel controller is designed by incorporating the corrected KPs matrix and communication time delay. The stability and convergence of the proposed controller are rigorously analyzed based on the Lyapunov-Krasovskii stability theorem. In addition, extensive experiments are conducted to test the performance including three parts: the first part investigates the feasibility of the corrected KPs matrix by analyzing a video on high-way; the next part illustrates the control performance of the proposed controller on handling the cutting-corner issue (i.e. turning in advance), compared with the conventional controller. Meanwhile, the influence of time delay on the control performance is also analyzed in this study. The last implements driver-in-loop comparative experiments such that the performance of the proposed controller on eliminating the influence of nonstandard human-driven behavior is verified.

Unstable vehicle-to-vehicle (V2V) communication connections are a vital phenomenon in connected vehicle (CV) environments which lead to the change of communication topologies and delays among electric connected vehicles (ECVs). This paper aims to evaluate the effects of the switching period of communication topology and delay on the dynamic performance and energy consumption of an ECV traffic stream considering the characteristics of car-following (CF) theory. To this end, a communication topology characterization method is developed by using the beacon transmission mechanism, graph theory, and probability theory. Then, a new CF model incorporating the effects of the communication topologies and delays is proposed to capture the interactions under a CV environment. The stability of the proposed model is analyzed by using the perturbation method. Finally, extensive simulations are implemented to be separately discussed by considering the effects of different switching periods of communication topologies and delays.

Since the unsaturating activation function is unbounded, more complex dynamics may exist in neural networks with this kind of activation function. In this article, monostability and multistability results of almost-periodic solutions are developed for fractional-order neural networks with unsaturating piecewise linear activation functions. Some globally Mittag-Leffler attractive sets are given, and the existence of globally Mittag-Leffler stable almost-periodic solution is demonstrated by using Ascoli-Arzela theorem. In particular, some sufficient conditions are provided to ascertain the multistability of almost-periodic solutions based on locally positively invariant set. It shows that there exists an almost-periodic solution in each positively invariant set, and all trajectories converge to this periodic trajectory in that rectangular area. Two illustrative examples are provided to demonstrate the effectiveness of the proposed sufficient criteria.