Cooperative Adaptive Cruise Control Algorithm Research Articles

A Nonlinear Control Design for Cooperative Adaptive Cruise Control with Time-Varying Communication Delay

Cooperative adaptive cruise control (CACC) is one of the main features of connected and autonomous vehicles (CAVs), which uses connectivity to improve the efficiency of adaptive cruise control (ACC). The addition of reliable communication systems to ACC reduces fuel consumption, maximizes road capacity, and ensures traffic safety. However, the performance, stability, and safety of CACC could be affected by the transmission of outdated data caused by communication delays. This paper proposes a Lyapunov-based nonlinear controller to mitigate the impact of time-varying delays in the communication channel of CACC. This paper uses Lyapunov–Krasovskii functionals in the stability analysis to ensure semi-global uniformly ultimately bounded tracking. The efficaciousness of the proposed CACC algorithm is demonstrated in simulation and through experimental implementation.

Exploring the effects of cooperative adaptive cruise control-based transit bus operation on signalized corridors

The world’s transportation system is overburdened by ever-growing travel demand, which brings mobility, safety, and pollution problems. To combat these issues and make better use of existing road capacity on urban arterials, public transit buses are designed to carry more people in fewer vehicles. However, transit buses travel slowly and make frequent intermittent stops, resulting in unreliable travel times and inconvenient riding experiences; this hinders people from choosing to travel on public transit buses. However, a research gap exists in using connected and automated vehicle (CAV) technologies specifically for transit bus operation optimization. To bridge this gap, the present study extended CAV applications to transit bus operation and developed a transit bus control method based on cooperative adaptive cruise control (CACC). The proposed model first optimized bus segment speeds to minimize schedule deviations and fuel consumption. Then, a CACC algorithm was integrated with optimal segment speed. The proposed control method was implemented through micro-simulations of an actual corridor in Jinan, Shandong, China. The evaluation results indicate that the proposed control method reduced the total arrival deviation up to 65.1% and total fuel consumption up to 6.8%. The study adapts CAV technologies to transit bus operation. The findings in this study validate CAV applications in transit bus operation.

Connected Vehicle-Cooperative Adaptive Cruise Control Algorithm to Divide and Reform Connected Vehicle Platoons at Signalized Intersections to Improve Traffic Throughput and Safety

The cooperative adaptive cruise control (CACC) algorithm is a simple and effective way to form small-headway platoons so that road capacity and traffic throughput can be improved. The CACC algorithm has been broadly discussed in relation to the highway driving environment where frequent stopping and merging are uncommon. This paper proposes that CACC can also benefit urban arterials, using the appropriate algorithm to predict platoon behavior with optimized trajectories to divide and reform platoons before and after signalized intersections, thus maintaining small, safe headways. Connected vehicle (CV) technology is the key to adapting and improving the CACC algorithm, as it enables the signal phasing plan to be sent to a target CACC platoon and allows vehicles to acquire real-time information from other vehicles in the platoon. In this research, a CV-CACC algorithm is proposed consisting of two functions: platoon division and platoon reforming. The new algorithm is also equipped with acceleration as a new control variable instead of speed, so that the platoon is able to accommodate sharp speed changes around intersections, something the baseline CACC is unable to accommodate. In this study, computer simulations have been conducted to test the reliability of the CV-CACC algorithm and compare its performance against the baseline CACC algorithm.

Cooperative Adaptive Cruise Control With Unconnected Vehicle in the Loop

To improve the usability of cooperative adaptive cruise control (CACC) in the mixed traffic, a CACC algorithm with unconnected vehicle in the loop (CACCu) is proposed. Unlike the traditional CACC that requires a connected preceding vehicle or otherwise degrades to adaptive cruise control (ACC), CACCu aims to closely follow an unconnected preceding vehicle utilizing the information from the further (connected) preceding vehicle. Moreover, CACCu can robustly maintain string stability given various behaviors of unconnected preceding vehicles, without requiring identification process or extra information on the unconnected vehicles. For the sake of simplicity, this paper starts with CACCu in the three-vehicle sandwich scenario (i.e., one unconnected vehicle is in between of two connected vehicles), but derivatively, this control design is extended and evaluated in multiple-unconnected-vehicle cases. It is proven that by attaching a filter of ``virtual preceding vehicle'' to the original feedforward filter, the CACCu vehicle can stay string-stable at a gap significantly shorter than that required by ACC, given almost all kinds of car-following behaviors of the unconnected vehicle. At last, the favorable properties of CACCu are validated in high-fidelity simulations using real vehicle trajectory data and a physics-based vehicle dynamics model. The results show that CACCu outperforms existing ACC and acceleration-based connected cruise control (CCC) in string stability, ride comfort, safety maintenance, and fuel consumption.

Safety Analysis of a Modified Cooperative Adaptive Cruise Control Algorithm Accounting for Communication Delay

Cooperative adaptive cruise control (CACC) is a promising technology to improve traffic efficiency and enhance road safety. In this paper, a modified CACC control model considering the communication time delay is proposed, which is used to investigate the longitudinal safety impacts of the communication time delay to the CACC platoon. Then, the communication time delay model is integrated into the CACC model to simulate the realistic information transfer process in the CACC platoon. Then a microscopic CACC platoon simulation is designed and conducted to verify the feasibility and reliability of the modified CACC control algorithm. The obtained results reveal that the modified CACC control algorithm can not only reduce about 96.6% of inter-vehicle spacing error, but also enhance the vehicles’ ability to sense the upstream traffic changes. Furthermore, to quantitatively analyze the longitudinal safety influence of the time delay caused by representative communication systems, sensitivity analysis experiments of headway time were designed and conducted. In the sensitivity analysis, the time exposed time-to-collision (TET) and the time-integrated time-to-collision (TIT) were introduced as the key performance indicators (KPIs) to quantify the rear-end collision risks. Sensitivity analysis results demonstrate that the performance of the CACC platoon is strictly related to the applied wireless communication style. Furthermore, the CACC system supported by the 5th generation (5G) communication system shows great advantages in narrowing the minimal headway time gap and reducing the rear-end collision risks.

Gap Opening Controller Design to Accommodate Merges in Cooperative Autonomous Platoons

Abstract In this paper, a cooperative platoon-based gap opening controller is developed. The intended application is gap creation in cooperative platoons to accommodate merges with spatial restrictions. Therefore, the main objective is to execute the maneuver in a predefined time. The controller design is based on a regular cooperative adaptive cruise control algorithm with an additional feedforward term for a desired gap. Experimental validation of the controller is performed with small mobile robots. The proposed control strategy is capable of opening the gap in a predefined time. In future work, this strategy can be used in the design of a merging algorithm specifically for CACC platoons.

Combined Cooperative Adaptive Cruise Control using Collective Initial Excitation based Distributed Parameter Estimator

In cooperative adaptive cruise control (CACC), autonomous vehicles are grouped into a string of platoon and, the main objective is to automatically adapt their speed using on-board sensors and communication with the preceding vehicle to maintain a desired inter-vehicle distance. Cruise control is achieved in the presence of parametric uncertainty in the vehicle dynamics using principles of adaptive control. This work proposes a novel combined CACC strategy for an uncertain homogeneous platoon with guaranteed parameter convergence and asymptotic string stability. A novel distributed consensus-based parameter estimator is proposed in conjunction with a model reference adaptive control (MRAC) algorithm using a direct control-gain update law. The algorithm ensures exponential parameter estimation error convergence to zero as well as asymptotic convergence of tracking-error to zero. Conventional CACC protocols require a condition of persistence of excitation (PE) for parameter convergence, which is required for better transient performance in converging to a string stable configuration. The PE condition is highly restrictive in the context of cruise control since velocity profiles which are demanded in the platoon model do not typically satisfy the PE condition. In contrast, the proposed scheme can ensure parameter convergence under a significantly milder condition, coined as collective initial excitation (C-IE). The C-IE condition is an extension of the concept of initial excitation (IE), which is recently proposed in the context of adaptive control of single agent system. Unlike IE, the C-IE condition caters to distributed estimation in the context of multi-agent systems. As far as the authors are aware, this is the first work on CACC framework, which ensures exponential convergence of parameter estimation error of each vehicle under the mild condition of C-IE, which further leads to asymptotic convergence of the entire vehicle platoon to a string stable configuration. Simulation study dictates that the proposed CACC architecture outperforms the existing CACC algorithms in terms of tracking and estimation performance.

Communication Aspects of a Modified Cooperative Adaptive Cruise Control Algorithm

This paper investigates the ability of modified cooperative adaptive cruise control to support high-density car platooning. We first use a simplistic communication model to study the impact of actuation lag, message periodicity, and communication delay on the minimum feasible inter-car spacing. We then use a detailed IEEE 802.11p simulation model to evaluate platooning performance in realistic highway scenarios. Different highway traffic intensities are simulated to observe the impact of increasing contention on the wireless channel with two different transceiver configurations: a single-transceiver operating on the common safety channel and a dual-transceiver operating, simultaneously, on the common safety channel and a dedicated service channel.

Reinforcement-Learning-Based Cooperative Adaptive Cruise Control of Buses in the Lincoln Tunnel Corridor with Time-Varying Topology

The exclusive bus lane (XBL) is one of the most popular bus transit systems in the U.S. The Lincoln Tunnel utilizes an XBL through the tunnel in the AM peak period. This paper proposes a novel data-driven cooperative adaptive cruise control (CACC) algorithm that aims to minimize a cost function for connected and autonomous buses along the XBL. Different from existing model-based CACC algorithms, the proposed approach employs the idea of reinforcement learning, which does not rely on accurate knowledge of bus dynamics. Considering a time-varying topology, where each autonomous vehicle can only receive information from preceding vehicles that are within its communication range, a distributed controller is learned real-time by online headway, velocity, and acceleration data collected from the system trajectories. The convergence of the proposed algorithm and the stability of the closed-loop system are rigorously analyzed. The effectiveness of the proposed approach is demonstrated using a well-calibrated Paramics microscopic traffic simulation model of the XBL corridor. The simulation results show that the travel time in the autonomous version of the XBL are close to the present day travel time even when the bus volume is increased by 30%.

Implementation and evaluation of cooperative adaptive cruise control functionalities

This study summarises the implementation of software system architecture and relevant modules to enable cooperative adaptive cruise control (CACC) functionalities as an extension of adaptive cruise control (ACC), thereby leveraging the lessons learned from prototype ACC vehicle testing as well as ideas from prior research. These activities were conducted in the United States under a cooperative agreement between the Crash Avoidance Metrics Partners, LLC and the Federal Highway Administration. A key outcome of this project was to understand the implementation of advanced capabilities for the CACC algorithm in a very structured manner. With the introduction of each CACC module, the impacts on the behaviours of vehicles following in a string (or string stability) were quantified to establish potential performance enhancements to automated following systems.

Simple synchronization protocols for heterogeneous networks: beyond passivity

Synchronization among autonomous agents via local interactions is one of the benchmark problems in multi-agent control. Whereas synchronization algorithms for identical agents have been thoroughly studied, synchronization of heterogeneous networks still remains a challenging problem. The existing algorithms primarily use the internal model principle, assigning to each agent a local copy of some dynamical system (internal model). Synchronization of heterogeneous agents thus reduces to global synchronization of identical generators and local synchronization between the agents and their internal models. The internal model approach imposes a number of restrictions and leads to sophisticated dynamical (and, in general, nonlinear) controllers. At the same time, passive heterogeneous agents can be synchronized by a very simple linear protocol, which is used for consensus of first-order integrators. A natural question arises whether analogous algorithms are applicable to synchronization of agents that do not satisfy the passivity condition. In this paper, we study the synchronization problem for heterogeneous agents that are not passive but satisfy a weaker input feedforward passivity (IFP) condition. We show that such agents can also be synchronized by a simple linear protocol, provided that the interaction graph is strongly connected and the couplings are sufficiently weak. We demonstrate how stability of cooperative adaptive cruise control algorithms and some microscopic traffic flow models reduce to synchronization of heterogeneous IFP agents.

Experimental Testing of Cooperative Adaptive Cruise Control using Small Electric Vehicles

This paper reports on development of Cooperative Adaptive Cruise Control (CACC) algorithm for small Electric Vehicles (EVs), and on evaluation of the algorithm using the small EVs. In order to enhance availability of vehicles’ autonomous driving systems, both ride comfortable which depends on longitudinal control, and maintaining vehicle-to-vehicle (V2V) distance are essential. CACC is researched and developed to solve the technical issues. Generally, in obtaining state quantities of the preceding vehicle, the method which receive internal sensors of the preceding vehicle via V2V communication can acquire more accurate information than the method which obtains the information with external sensors of the vehicle. CACC is a kind of ACC which uses state quantities of the preceding vehicle obtained via V2V communication, thus CACC is capable for coexistence of the two points; ride comfortable and maintaining V2V distance. On the other hand, knowledge on evaluation of the points using actual vehicles has not enough stacked yet. This study therefore develops CACC for small EVs and accomplishes evaluation using several vehicles. In this paper, backgrounds surrounding driving assistant systems, such as CACC, are explained at first. Next, related works on the CACC focused on this study are introduced and their technological issues are clarified. CACC algorithm for evaluation using small EVs is then explained. Finally, experimental evaluation using four small EVs which performs the CACC algorithm developed in this study is explained. This evaluation certificates CACC’s capability of ensuring both ride comfortable and string stability.

V2X-Based Decentralized Cooperative Adaptive Cruise Control in the Vicinity of Intersections

Cooperative driving with V2X communication is widely researched due to its considerable potential to improve the safety and efficiency of road transportation systems. In this paper, a decentralized cooperative adaptive cruise control algorithm using V2X for vehicles in the vicinity of intersections (CACC-VI) is proposed. This algorithm is designed to improve the throughput of intersection by reorganizing the vehicle platoons around it, in consideration of safety, fuel consumption, speed limit, heterogeneous features of vehicles, and passenger comfort. Within a platoon, vehicles try to find the optimal control input by a distributed particle swarm optimization (PSO) algorithm, in order to reduce tracking errors, while respecting different constraints. A concept of opportunity space is proposed to facilitate platoon reorganization, in which a subplatoon or an individual vehicle can choose to accelerate to join in the preceding platoon or to decelerate to depart from the current one. The main idea is to make full use of the road capacity and to distribute it to most vehicles that are capable to find an accelerating trajectory to get through the intersection within a limited period. The originality of our algorithm is the introduction of a novel application of V2X communication to make the traffic more intelligent, in terms of safety, time saving, and environment friendly.

Improving the Intersection’s Throughput using V2X Communication and Cooperative Adaptive Cruise Control

In this paper, a decentralized cooperative adaptive cruise control algorithm for vehicles in the vicinity of intersections (CACC-VI) is proposed. This algorithm is designed to make use of the road capacity to let more vehicles get through the intersection within a limited traffic signal period in consideration of safety, fuel consumption, speed limit and heterogeneous features of vehicles, and passenger comfort. Within a platoon, vehicles try to find the optimal control input by a distributed PSO algorithm in order to reduce tracking errors while respecting different constraints. A concept of opportunity space is proposed to facilitate platoon reorganization in which a sub-platoon or an individual vehicle can choose to accelerate to join in the preceding platoon or to decelerate to depart from the current one. It is found that the throughput of the intersection during the green phase can be improved, and an optimal control input can be found for each vehicle within the defined constraints.

Sampled-Data Cooperative Adaptive Cruise Control of Vehicles With Sensor Failures

This paper investigates sampled-data cooperative adaptive cruise control (CACC) of vehicles with sensor failures. A novel switched sampled-data CACC system model is established, in which the effect of sensor failure is involved. Based on the new model, a design method of state feedback controllers that can robustly stabilize the CACC system is presented via the switched system approach. The obtained controller is complemented by additional conditions that are established for guaranteeing string stability and zero steady-state velocity error, which yields a useful string stable CACC algorithm. Several quantitative relations of parameters, including the sensor complete-failure rate, the system decay rate, and sampling period, are also derived. The effectiveness and advantage of the presented methodology are demonstrated by both numerical simulations and experiments with laboratory-scale Arduino cars.

An improved cooperative adaptive cruise control (CACC) algorithm considering invalid communication

For the Cooperative Adaptive Cruise Control (CACC) Algorithm, existing research studies mainly focus on how inter-vehicle communication can be used to develop CACC controller, the influence of the communication delays and lags of the actuators to the string stability. However, whether the string stability can be guaranteed when inter-vehicle communication is invalid partially has hardly been considered. This paper presents an improved CACC algorithm based on the sliding mode control theory and analyses the range of CACC controller parameters to maintain string stability. A dynamic model of vehicle spacing deviation in a platoon is then established, and the string stability conditions under improved CACC are analyzed. Unlike the traditional CACC algorithms, the proposed algorithm can ensure the functionality of the CACC system even if inter-vehicle communication is partially invalid. Finally, this paper establishes a platoon of five vehicles to simulate the improved CACC algorithm in MATLAB/Simulink, and the simulation results demonstrate that the improved CACC algorithm can maintain the string stability of a CACC platoon through adjusting the controller parameters and enlarging the spacing to prevent accidents. With guaranteed string stability, the proposed CACC algorithm can prevent oscillation of vehicle spacing and reduce chain collision accidents under real-world circumstances. This research proposes an improved CACC algorithm, which can guarantee the string stability when inter-vehicle communication is invalid.

Towards reducing traffic congestion using cooperative adaptive cruise control on a freeway with a ramp

Purpose: In this paper, the impact of Cooperative Adaptive Cruise Control (CACC) systems on traffic performance is examined using microscopic agent-based simulation. Using a developed traffic simulation model of a freeway with an on-ramp - created to induce perturbations and to trigger stop-and-go traffic, the CACC system’s effect on the traffic performance is studied. The previously proposed traffic simulation model is extended and validated. By embedding CACC vehicles in different penetration levels, the results show significance and indicate the potential of CACC systems to improve traffic characteristics and therefore can be used to reduce traffic congestion. The study shows that the impact of CACC is positive but is highly dependent on the CACC market penetration. The flow rate of the traffic using CACC is proportional to the market penetration rate of CACC equipped vehicles and the density of the traffic. Design/methodology/approach: This paper uses microscopic simulation experiments followed by a quantitative statistical analysis. Simulation enables researchers manipulating the system variables to straightforwardly predict the outcome on the overall system, giving researchers the unique opportunity to interfere and make improvements to performance. Thus with simulation, changes to variables that might require excessive time, or be unfeasible to carry on real systems, are often completed within seconds. Findings: The findings of this paper are summarized as follow: • Provide and validate a platform (agent-based microscopic traffic simulator) in which any CACC algorithm (current or future) may be evaluated. • Provide detailed analysis associated with implementation of CACC vehicles on freeways. • Investigate whether embedding CACC vehicles on freeways has a significant positive impact or not. Research limitations/implications: The main limitation of this research is that it has been conducted solely in a computer laboratory. Laboratory experiments and/or simulations provide a controlled setting, well suited for preliminary testing and calibrating of the input variables. However, laboratory testing is by no means sufficient for the entire methodology validation. It must be complemented by fundamental field testing. As far as the simulation model limitations, accidents, weather conditions, and obstacles in the roads were not taken into consideration. Failures in the operation of the sensors and communication of CACC design equipment were also not considered. Additionally, the special HOV lanes were limited to manual vehicles and CACC vehicles. Emergency vehicles, buses, motorcycles, and other type of vehicles were not considered in this dissertation. Finally, it is worthy to note that the human factor is far more sophisticated, hard to predict, and flexible to be exactly modeled in a traffic simulation model perfectly. Some human behavior could occur in real life that the simulation model proposed would fail to model. Practical implications: A high percentage of CACC market penetration is not occurring in the near future. Thus, reaching a high penetration will always be a challenge for this type of research. The public accessibility for such a technology will always be a major practical challenge. With such a small headway safety gap, even if the technology was practically proven to be efficient and safe, having the public to accept it and feel comfortable in using it will always be a challenge facing the success of the CACC technology. Originality/value: The literature on the impact of CACC on traffic dynamics is limited. In addition, no previous work has proposed an open-source microscopic traffic simulator where different CACC algorithms could be easily used and tested. We believe that the proposed model is more realistic than other traffic models, and is one of the very first models to model the behavior CACC vehicles on freeways.