Cooperative Adaptive Cruise Control Vehicles Research Articles

Integrated Cooperative Adaptive Cruise and Variable Speed Limit Controls for Reducing Rear-End Collision Risks Near Freeway Bottlenecks Based on Micro-Simulations

Freeway bottlenecks lead to traffic congestion and speed reduction, resulting in increased risks of rear-end collision. This paper aimed to develop a control strategy of an integrated system of cooperative adaptive cruise control (CACC) and variable speed limit (VSL) to reduce rear-end collision risks near freeway bottlenecks. A microscopic simulation testbed was first constructed, in which the realistic PATH CACC models and surrogate safety measures of the time exposed time-to-collision (TET) and time integrated time-to-collision (TIT) were used. A feedback control algorithm was then developed for the proposed vehicle to infrastructure system of CACC and VSL. The simulation results showed that the proposed integration system with 100% CACC penetration rate can reduce the rear-end collision risks effectively, with the TIT and TET declined by 98%. The average travel time was also decreased by 33%, compared with the manual vehicles without any control. Moreover, the safety improvements of the proposed integrated system are quite stable at the various bottlenecks with different magnitudes of speed reductions. The sensitivity analyses suggested that the penetration rate of CACC has significant impact on safety performance. The VSL control plays an important role in reducing rear-end collision risks when the penetration rate of CACC is low. The combination of CACC and VSL controls mitigates the negative effects of the mixed traffic flow of the manual and CACC vehicles.

Stability analysis and fundamental diagram of heterogeneous traffic flow mixed with cooperative adaptive cruise control vehicles

This paper is aimed at building a framework for string stability analysis of traffic flow mixed with different cooperative adaptive cruise control (CACC) market penetration rates. In addition to the string stability, the fundamental diagram of the mixed flow is also taken into consideration for evaluating the effect of CACC vehicles on capacity. In order to describe the car-following dynamics of real CACC vehicles, the CACC model proposed by PATH is employed, which is validated by real experimental data. The intelligent driver model (IDM) is used as a surrogate car-following model for traditional manual driven vehicles. Based on the guidelines proposed by Ward[Ward J A 2009 Ph. D. Dissertation (Bristol:University of Bristol)], a framework is developed for the analytical investigation of heterogeneous traffic flow string stability. The framework presented considers the instability condition of traffic flow as a linear function of CACC market penetration rate. Following the framework, the string stabilities of the mixed traffic flow under different CACC market penetration rates and equilibrium velocities are analyzed. For fundamental diagram of the heterogeneous traffic flow, the equilibrium velocity-spacing functions of manual vehicles and CACC vehicles are obtained respectively based on car-following model. Then, the fundamental diagram of the density-velocity relationship of the heterogeneous traffic flow is derived based on the definition of traffic flow density. In addition, the theoretical fundamental diagram is plotted to show the property of traffic throughput. The numerical simulations are also carried out in order to investigate the effect of CACC vehicle on the characteristics of fundamental diagram. Besides, sensitivity analyses on CACC desired time gap are conducted for both string stability and fundamental diagram. Analytical studies and simulation results are as follows. 1) The heterogeneous traffic flow is stable for different equilibrium velocities and CACC market penetration rates, if manual driven vehicles are stable. Otherwise, the instability of traditional traffic flow is improved gradually with the increase of the CACC market penetration rate. Additionally, the stability will become better when equilibrium velocity is away from the velocity range of 9.6-18.6 m/s. 2) Because CACC vehicles can travel at free-flow speed in a relatively small headway, CACC vehicles can improve the capacity of heterogeneous traffic flow. 3) The results of sensitivity analysis indicate that with the increase of the CACC desired time gap, the stable region of heterogeneous traffic flow increases. However, the capacity of the fundamental diagram drops. Therefore, the value of the desired time gap should be determined with considering the effects of the two aspects on the heterogeneous traffic flow. It is noted that the CACC model used in this paper is based on the current state-of-the-art real CACC vehicle experiments. In the future, more experimental observations will yield new CACC models. However, the framework presented in this paper can still be used for the analytical investigation of string stability of the heterogeneous traffic flow at that time.

Evaluation of Driver Car-Following Behavior Models for Cooperative Adaptive Cruise Control Systems

A cooperative adaptive cruise control (CACC) system targeted to obtain a high level of user acceptance must replicate the driving experience in each CACC vehicle without compromising the occupant’s comfort. “User acceptance” can be defined as the safety and comfort of the occupant in the CACC vehicle in terms of acceptable vehicle dynamics (i.e., the maximum acceleration or deceleration) and string stability (i.e., the fluctuations in the vehicle’s position, speed, and acceleration). The primary objective of this study was to develop an evaluation framework for the application of a driver car-following behavior model in CACC system design to ensure user acceptance in terms of vehicle dynamics and string stability. The authors adopted two widely used driver car-following behavior models, ( a) the optimum velocity model (OVM) and ( b) the intelligent driver model (IDM), to prove the efficacy of the evaluation framework developed in this research for CACC system design. A platoon of six vehicles was simulated for three traffic flow states (uniform speed, speed with constant acceleration, and speed with constant deceleration) with different acceleration and deceleration rates. The maximum acceleration or deceleration and the sum of the squares of the errors of the follower vehicle speed were measured to evaluate user acceptance in terms of vehicle dynamics and string stability. Analysis of the simulation results revealed that the OVM performed better at modeling a CACC system than did the IDM in terms of acceptable vehicle dynamics and string stability.

Multiobjective Optimization Framework for Cooperative Adaptive Cruise Control Vehicles in the Automated Vehicle Platooning Environment

Automated longitudinal control technology has been tested through cooperative adaptive cruise control (CACC), which is envisioned to improve highway mobility drastically by forming a vehicle platoon with short headway while maintaining stable traffic flow under disturbances. Compared with previous research efforts with the pseudomultiobjective optimization process, this paper proposes an automated longitudinal control framework based on multiobjective optimization (MOOP) for CACC by taking into consideration four optimization objectives: mobility, safety, driver comfort, and fuel consumption. Of the target time headways that have been tested, the proposed CACC platoon control method achieved the best performance with 0.9- and 0.6-s target time headways. Compared with a non-optimization-based CACC, the MOOP CACC achieved 98%, 93%, 42%, and 33% objective value reductions of time headway deviation, unsafe condition, jitter, and instantaneous fuel consumption, respectively. In comparison with a single-objective-optimization-based approach, which optimized only one of the four proposed objectives, it was shown that the MOOP-based CACC maintained a good balance between all of the objective functions and achieved Pareto optimality for the entire platoon.

Realistic Car-Following Models for Microscopic Simulation of Adaptive and Cooperative Adaptive Cruise Control Vehicles

Adaptive cruise control (ACC) and cooperative adaptive cruise control (CACC) are important technologies for the achievement of vehicle automation, and their effect on traffic systems generally is evaluated with microscopic traffic simulations. A successful simulation requires realistic vehicle behavior and minimal vehicle collisions. However, most existing ACC-CACC simulation studies used simplified models that were not based on real vehicle response. The studies rarely addressed collision avoidance in the simulation. The study presented in this paper developed a realistic and collision-free car-following model for ACC-CACC vehicles. A multiregime model combining a realistic ACC-CACC system with driver intervention for vehicle longitudinal motions is proposed. This model assumes that a human driver resumes vehicle control either according to his or her assessment or after a collision warning asks the driver to take over. The proposed model was tested in a wide range of scenarios to explore model performance and collision possibilities. The testing scenarios included three regular scenarios of stop-and-go, approaching, and cut-out maneuvers, as well as two extreme safety-concerned maneuvers of hard brake and cut-in. The simulation results show that the proposed model is collision free in the full-speed-range operation with leader accelerations within −1 to 1 m/s2 and in approaching and cut-out scenarios. Those results indicate that the proposed ACC-CACC car-following model can produce realistic vehicle response without causing vehicle collisions in regular scenarios for vehicle string operations.

Macroscopic traffic flow modeling with adaptive cruise control: Development and numerical solution

The incorporation of two macroscopic approaches reflecting Adaptive Cruise Control (ACC) and Cooperative Adaptive Cruise Control (CACC) traffic dynamics in a gas-kinetic (GKT) traffic flow model is presented. The first approach was recently analyzed in the literature aiming to describe the effects induced by the ACC and CACC systems due to changes of the speed of the leading car(s) by the introduction of an acceleration/deceleration term. The second approach is a novel one and is based on the introduction of a relaxation term that satisfies the time/space-gap principle of ACC or CACC systems. In both approaches, the relaxation time is assigned on multiple leading vehicles in the CACC case; whereas in the ACC case this relaxation time is only assigned to the direct leading vehicle. We numerically approximate the resulting models by an accurate and robust high-resolution finite volume relaxation scheme, where the nonlinear system of partial differential equations is first recast to a diagonalizable semi-linear system and is then discretized by a higher-order WENO scheme. Numerical simulations investigate the effect of the different ACC and CACC approaches to traffic flow macroscopic stability with respect to perturbations introduced in a ring road and to flow characteristics in open freeways with merging flows at an on-ramp. Following from the numerical results, it can be concluded that CACC vehicles increase the stabilization of traffic flow, with respect to both small and large perturbations, compared to ACC ones. Further, the proposed CACC approach can better improve the dynamic equilibrium capacity and traffic dynamics, especially at the on-ramp bottleneck.

Handling Cut-In Vehicles in Strings of Cooperative Adaptive Cruise Control Vehicles

Cooperative adaptive cruise control (CACC) systems are a candidate to improve highway capacity by shortening headways and attenuating traffic disturbances. Although encouraging results have been obtained until now, a wide range of traffic circumstances has to be investigated in order to get reliable CACC systems driving on real roads. Among them, handling both vehicle-to-vehicle (V2V) communications-equipped and unequipped vehicles merging into the string of CACC vehicles is a commonly mentioned challenge. In this article, an algorithm for managing the transitions in response to cut-ins from V2V- or non-V2V-equipped vehicles is developed and tested using a string of four CACC vehicles. A CACC controller is implemented in four production Infiniti M56s vehicles and tested in real traffic, where non-V2V-equipped vehicles can cut in. The effects of a vehicle performing a cut-out are also investigated. Then responses to cut-ins by equipped and nonequipped vehicles are simulated for longer strings of vehicles using car-following models for both the production adaptive cruise control (ACC) system and the newly developed CACC controller. Results demonstrate that the CACC system is able to handle cut-in vehicles without causing major perturbations, while also reducing significantly the impact of this maneuver on the following vehicles, improving traffic flow.

Platoon management with cooperative adaptive cruise control enabled by VANET

Previous studies have shown the ability of vehicle platooning to improve highway safety and throughput. With Vehicular Ad-hoc Network (VANET) and Cooperative Adaptive Cruise Control (CACC) system, vehicle platooning with small headway becomes feasible. In this paper, we developed a platoon management protocol for CACC vehicles based on wireless communication through VANET. This protocol includes three basic platooning maneuvers and a set of micro-commands to accomplish these maneuvers. Various platooning operations such as vehicle entry and vehicle (including platoon leader) leaving can be captured by these basic platoon maneuvers. The protocol operation is described in detail using various Finite State Machines (FSM), and can be applied in collaborative driving and intelligent highway systems. This protocol is implemented in an integrated simulation platform, VENTOS, which is developed based on SUMO and OMNET++. The validity and effectiveness of our approach is shown by means of simulations, and different platooning setting are calibrated.

Cooperative Adaptive Cruise Control

Cooperative adaptive cruise control (CACC) includes multiple concepts of communication-enabled vehicle following and speed control. Definitions and classifications are presented to help clarify the distinctions between types of automated vehicle-following control that are often conflated with each other. A distinction is made between vehicle-to-vehicle (V2V) CACC, based on vehicle–vehicle cooperation, and infrastructure-to-vehicle CACC, in which the infrastructure provides information or guidance to the CACC system (such as the target set speed value). In V2V CACC, communication provides enhanced information so that vehicles can follow their predecessors with higher accuracy, faster response, and shorter gaps; the result would be enhanced traffic flow stability and possibly improved safety. A further distinction is made between CACC, which uses constant-time-gap vehicle following (forming CACC strings), and automated platooning, which uses tightly coupled, constant-clearance, vehicle-following strategies. Although adaptive cruise control (ACC) and CACC are examples of Level 1 automation as defined by both SAE and NHTSA, the vehicle-following performance that can be achieved under each scenario is representative of the performance that should be expected at higher levels of automation. Implementation of CACC in practice will also require consideration of more than the lowest level of vehicle-following and speed regulation performance. Because CACC requires interactions between adjacent equipped vehicles, strategies are needed such as ad hoc, local, or global coordination to cluster CACC vehicles. Some of the challenges that must be overcome to implement the clustering strategies are discussed as well as strategies for separating CACC clusters as they approach their destinations, as potential traffic improvements from CACC will be negated if the vehicles cannot disperse effectively.

A Progressive Deployment Strategy for Cooperative Adaptive Cruise Control to Improve Traffic Dynamics

Cooperative adaptive cruise control (CACC) vehicles are intelligent vehicles that use vehicular ad hoc networks (VANETs) to share traffic information in real time. Previous studies have shown that CACC could have an impact on increasing highway capacities at high market penetration. Since reaching a high CACC market penetration level is not occurring in the near future, this study presents a progressive deployment approach that demonstrates to have a great potential of reducing traffic congestions at low CACC penetration levels. Using a previously developed microscopic traffic simulation model of a freeway with an on-ramp — created to induce perturbations and trigger stop-and-go traffic, the CACC system’s effect on the traffic performance is studied. The results show significance and indicate the potential of CACC systems to improve traffic characteristics which can be used to reduce traffic congestion. The study shows that the impact of CACC is positive and not only limited to a high market penetration. By giving CACC vehicles priority access to high-occupancy vehicle (HOV) lanes, the highway capacity could be significantly improved with a CACC penetration as low as 20%.

Exploring the effects of cooperative adaptive cruise control on highway traffic flow using microscopic traffic simulation

This paper examines the impact of having cooperative adaptive cruise control (CACC) embedded vehicles on traffic flow characteristics of a multilane highway system. The study identifies how CACC vehicles affect the dynamics of traffic flow on a complex network and reduce traffic congestion resulting from the acceleration/deceleration of the operating vehicles. An agent-based microscopic traffic simulation model (Flexible Agent-based Simulator of Traffic) is designed specifically to examine the impact of these intelligent vehicles on traffic flow. The flow rate of cars, the travel time spent, and other metrics indicating the evolution of traffic congestion throughout the lifecycle of the model are analyzed. Different CACC penetration levels are studied. The results indicate a better traffic flow performance and higher capacity in the case of CACC penetration compared to the scenario without CACC-embedded vehicles.

Simulation Framework for Vehicle Platooning and Car-following Behaviors Under Connected-vehicle Environment

This paper studies the traffic assistance system consisting of different kinds of vehicles (manual, Adaptive Cruise Control (ACC) and Cooperative Adaptive Cruise Control (CACC) vehicle). By using the application programming interface in microscopic-traffic simulation, the aim that constructing simulation framework of CACC platoon is achieved. Maneuvers like forming, adjusting, splitting, dismissing and joining in a platoon are implemented under the simulation platform. Then a platoon with 6 CACC vehicles is simulated to examine the interactions in a platoon and how they react to shockwaves microscopically, which in turn verify the driver model partly. Finally different market penetration and platoon size of CACC are tested. Results illustrate the lane capacity increased significantly when market penetration of CACC vehicles added, however platoon size have little impact on traffic capacity. These preliminary working will be a foundation for our future work in this area.

Instability of cooperative adaptive cruise control traffic flow: A macroscopic approach

This paper proposes a macroscopic model to describe the operations of cooperative adaptive cruise control (CACC) traffic flow, which is an extension of adaptive cruise control (ACC) traffic flow. In CACC traffic flow a vehicle can exchange information with many preceding vehicles through wireless communication. Due to such communication the CACC vehicle can follow its leader at a closer distance than the ACC vehicle. The stability diagrams are constructed from the developed model based on the linear and nonlinear stability method for a certain model parameter set. It is found analytically that CACC vehicles enhance the stabilization of traffic flow with respect to both small and large perturbations compared to ACC vehicles. Numerical simulation is carried out to support our analytical findings. Based on the nonlinear stability analysis, we will show analytically and numerically that the CACC system better improves the dynamic equilibrium capacity over the ACC system. We have argued that in parallel to microscopic models for CACC traffic flow, the newly developed macroscopic will provide a complete insight into the dynamics of intelligent traffic flow.

Impacts of Cooperative Adaptive Cruise Control on Freeway Traffic Flow

This study used microscopic simulation to estimate the effect on highway capacity of varying market penetrations of vehicles with adaptive cruise control (ACC) and cooperative adaptive cruise control (CACC). Because the simulation used the distribution of time gap settings that drivers from the general public used in a real field experiment, this study was the first on the effects of ACC and CACC on traffic to be based on real data on driver usage of these types of controls. The results showed that the use of ACC was unlikely to change lane capacity significantly. However, CACC was able to increase capacity greatly after its market penetration reached moderate to high percentages. The capacity increase could be accelerated by equipping non-ACC vehicles with vehicle awareness devices so that they could serve as the lead vehicles for CACC vehicles.

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.