Cooperative Adaptive Cruise Control Vehicles Research Articles

Stability and safety analysis of mixed traffic flow considering network function degradation and platoon driving on the road with a slope

Considering the influence of slope sections and random degradation of the communication function of cooperative adaptive cruise control vehicles and the effect of the cooperative adaptive cruise control vehicle group driving, a linear stability criterion for heterogeneous traffic flow composed of cooperative adaptive cruise control vehicles and humanly-driven vehicles on slopes is derived, and a parameter sensitivity analysis is carried out. On this foundation, the safety of traffic flow on two-lane roads up and down hills is simulated while considering the lane-changing behavior of automobiles. The stability study shows increased cooperative adaptive cruise control vehicle penetration and uphill gradient will help improve traffic flow stability. In contrast, the increase in the downhill slope will intensify the transmission amplitude of the disturbance. When vehicle starting sensitivity is 2.5, and the gradient is 60, the minimum cooperative adaptive cruise control vehicle penetration required for mixed traffic flow to maintain stability on a downhill at any initial equilibrium speed is 85%, and the minimum penetration required on an uphill is 73%, and this proportion decreases with the increase in the uphill gradient and increases with the rise in the downhill slope. According to the safety study, increasing cooperative adaptive cruise control vehicle penetration and implementing lane-changing rules will improve traffic flow safety. Compared with the straight section, under the same conditions, the traffic flow safety of the uphill section is the best, and the safety of the downhill section is poor, which is consistent with the stability analysis results. This study is of great significance for future traffic control strategies for mountain roads.

Stability Analysis of Mixed Traffic Flow Considering Personal Space under the Connected and Automated Environment

A traffic survey using an unmanned aerial vehicle on the Haixia road in Chongqing, China found a significant correlation between the velocity of the vehicle and the distance of the vehicle when moving forward and laterally. To mitigate driving disruptions owing to vehicle intrusion at a desired distance, personal space (PS) is introduced to analyze the car-following behavior of continuous mixed traffic flow formed by human-driven (HD) vehicles and cooperative adaptive cruise control (CACC) vehicles. PS is a virtual boundary that refers to the space where psychological tension is caused by the invasion of others. Further, an intelligent driver model (IDM) was used to establish a mixed traffic car-following PS-IDM. The stability of the disturbance transfer function analytical model in homogeneous and heterogeneous traffic flows was used to calculate the traffic flow stability region under different CACC vehicle permutations. The results show that the PS-IDM-based car-following model effectively improves the stability fitting effect of mixed traffic flow, and the driving comfort is increased by up to 20.7% when compared with that of the single car-following model. In addition, there is a negative correlation between the PS and the unstable velocity range of the traffic flow. Compared with the homogeneous HD traffic flow, the average intrusion rate of homogeneous CACC traffic flow is reduced by 4.6%, and the driving comfort of vehicles is improved by approximately 65%.

An Evolutionary Learning Framework of Lane-Changing Control for Autonomous Vehicles at Freeway Off-Ramps

This paper proposes a lateral control strategy for autonomous vehicles (AVs) and develops an evolutionary learning framework for off-ramps. Random forest (RF) and back-propagation neural network (BPNN) integrated with model predictive control (MPC) algorithm are respectively used to capture the decision-making and trajectory characteristics during the lane-changing maneuver based on the Next Generation Simulation (NGSIM) dataset. Then, a running cost function is calculated to optimize the trajectory dataset. Finally, the numerical simulation is conducted to investigate the characteristics of the proposed framework. Simulation results indicate that the performance of our method is much better than some other methods in lane-changing gap choice and trajectory execution. Moreover, the traffic system controlled by the evolutionary algorithms reaches the highest capacity and safest level when all vehicles are equipped with cooperative adaptive cruise control (CACC) systems. On the contrary, the scenario with 50% CACC vehicles shows the lowest travel efficiency and the worst safety because of the CACC vehicles’ degradation. Furthermore, three iterations and 500 vehicle trajectories at each optimization cycle are recommended for the application in the off-ramp traffic control.

Data‐iteration cooperative adaptive cruise control of mixed heterogeneous vehicle platoons with unknown dynamic characteristics

AbstractThis paper considers the cooperative adaptive cruise control (CACC) problem of mixed heterogeneous vehicle platoons composed of human‐driven and CACC vehicles with unknown dynamic characteristics and an alternative to CACC for platooning of the heterogeneous vehicle platoon is presented. Adaptive dynamic programming is firstly used to learn the dynamic characteristics of acceleration of vehicles from the sampled data. Then the data‐iteration optimal CACC controller is computed to ensure that each CACC vehicle can reach a desired inter‐vehicle distance and desired common velocity with no prior knowledge of the dynamics of vehicles in the mixed platoon. Moreover, the string stability of the mixed vehicle platoon is derived by establishing some sufficient conditions on the acceleration transfer function of adjacent vehicles. Two simulation experiments of a six‐vehicle mixed platoon are used to illustrate the effectiveness of the proposed CACC method.

Stability and capacity for heterogeneous traffic flow mixed with vehicles in multiple controls

Cooperative adaptive cruise control (CACC) is regarded as a promising approach to improve traffic stability and capacity by operating vehicle-to-vehicle (V2V) communication. However, the beneficial effect of CACC vehicles is greatly reduced due to the influence of manually driven vehicles (MDVs) in the heterogeneous traffic flow, in which the degradation of CACC vehicles is a considerable problem. One proposed solution is to install communication devices for MDVs, called IMDVs, to propagate information to CACC vehicles and prevent the degradation. This study analyzed the traffic flow configuration by introducing IMDVs and considering multiple traffic flow operations, e.g. vehicle degradation and platoon formation. Then, multiple factors, including market penetration rate, platoon length, and information flow topology, were taken into consideration in the theoretical modelling of linear stability and fundamental diagram. Finally, we verified the high accuracy of theoretical analysis by numerical experiments and gave some reasonable recommendations for traffic management.

Impacts of Cooperative Adaptive Cruise Control Links on Driving Comfort under Vehicle-to-Vehicle Communication

Although automated vehicles could release drivers from the driving task, there are still passengers sitting in the vehicle. It is required that the driving comfort of passengers should be guaranteed. Cooperative adaptive cruise control (CACC) vehicle is of the one important type of automated vehicles using vehicle-to-vehicle (V2V) communications with various communication links. Different V2V communication links might have different driving comfort. Then, this paper focuses on exploring which link type for CACC vehicles is better from the perspective of improving driving comfort. To deal with this, car-following models of manual-driven vehicles (MDV) and CACC vehicles were first described. Then, simulations were performed using these car-following models, in which various CACC feedback link types, CACC penetration rates, and flow scenarios were taken into consideration. Simulations outputted microcosmic trajectory data of vehicles, based on which the driving comfort was evaluated using the comfort index described by the International Organization for Standardization (ISO) 2631-1. From the driving comfort perspective, simulation results suggest that CACC should monitor the immediately preceding vehicle and the third vehicle ahead when CACC penetration rates are less than approximately 50%. Additionally, if CACC penetration rates exceed 50%, the better choice is that CACC receives feedback links from two immediately successive vehicles ahead.

Stability Analysis of Heterogeneous Traffic Flow with Connected and Automated Vehicles: Joint Consideration of Communication Failures and Driver Takeover

As a primary stage of connected and automated vehicles (CAVs), the cooperative adaptive cruise control (CACC) system takes some outstanding advantages such as accurate perception and timely reaction, which benefit from vehicular communication, over human-driven vehicles (HDVs). However, these advantages will turn into stability risks in case of communication failures caused by malicious attacks. Thus, this study aims at analyzing the stability of heterogeneous traffic flow with communication failures. We model two types of communication failures: bogus messages and transmission delay, and introduce drivers’ takeovers to react to communication failures. As a result, heterogeneous traffic flow consists of normal CACC vehicles, CACC vehicles with communication failures, and HDVs. Then, a series of numerical analyses, including startup and braking analysis, incidents analysis, and density wave, are proposed to verify the theoretical models and demonstrate their major properties. Besides, a discussion on traffic capacity is presented to analyze the overall impact of communication failures on traffic flow characteristics. The findings can help to investigate the stability evolution of heterogeneous traffic flow and determine the appropriate traffic flow configuration under communication failures.

False Data Injection Attack in a Platoon of CACC: Real-Time Detection and Isolation With a PDE Approach

Connected vehicles are potential solutions to address some of the existing challenges in transportation systems, such as emission, traffic congestion, and fuel consumption. However, vehicular communication networks endure from reliability and security issues. Cyber-attacks with performance-disrupting purposes can lead to catastrophic collisions in connected vehicles and increase traffic congestion. To ensure safety and reliability, a monitoring system with the capability of diagnosing cyber-attacks is necessary for connected vehicles. In this study, we consider a platoon of connected vehicles equipped with cooperative adaptive cruise control (CACC) that is subjected to a specific type of cyber-attack, namely <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">“False Data Injection”</i> (FDI) attack. A smart FDI attack is modeled with ghost vehicles injection into the connected vehicles network to disrupt the performance of the whole system. To ease the analysis, we develop a partial differential equation (PDE) model for the CACC vehicle dynamics using its ordinary differential equations (ODE). Furthermore, a PDE observer is designed to detect the FDI attack and locate the attack’s injection point in the platoon. Lyapunov stability theory has been utilized to verify the observer’s convergence under no-attack scenario and study residuals’ behaviors in the presence of the attack. A non-zero constant threshold is considered to provide robustness in attack detection despite the measurement noises. Eventually, the effectiveness of the proposed algorithm is evaluated with simulation studies.

Impact of Cooperative Adaptive Cruise Control on Traffic Stability

Cooperative adaptive cruise control (CACC) is one of the popular connected and automated vehicle (CAV) applications for cooperative driving automation with combined connectivity and automation technologies to improve string stability. This study aimed to derive the string stability conditions of a CACC controller and analyze the impacts of CACC on string stability for both a fleet of homogeneous CAVs and for heterogeneous traffic with human-driven vehicles (HDVs), connected vehicles (CVs) with connectivity technologies only, and autonomous vehicles (AVs) with automation technologies only. We mathematically analyzed the impact of CACC on string stability for both homogeneous and heterogeneous traffic flow. We adopted parameters from literature for HDVs, CVs, and AVs for the heterogeneous traffic case. We found there was a minimum constant time headway required for each parameter design to ensure stability in homogeneous CACC traffic. In addition, the constant time headway and the length of control time interval had positive correlation with stability, but the control parameter had a negative correlation with stability. The numerical analysis also showed that CACC vehicles could maintain string stability better than CVs and AVs under low HDV market penetration rates for the mixed traffic case.

Improving the Safety of Cooperative Adaptive Cruise Control Vehicle Platoons: A Relative Time Headway Policy

Improving the Safety of Cooperative Adaptive Cruise Control Vehicle Platoons: A Relative Time Headway Policy

Safety impact of cooperative adaptive cruise control vehicles’ degradation under spatial continuous communication interruption

Cooperative adaptive cruise control is recognised as an effective means to reduce the rear-end collision caused by the delayed reaction and improper driving behaviours of manually driven vehicles. However, vehicle-to-vehicle communication, as the key to collect information for the cooperative adaptive cruise control system, is likely to be interrupted by malicious attacks and equipment failures. When communication interruption occurs, sensors of the adaptive cruise control system will replace vehicle-to-vehicle communication for information collection, that is, cooperative adaptive cruise control vehicles degrade to adaptive cruise control vehicles automatically, causing an increased rear-end collision risk. This study aims to investigate the safety impact of cooperative adaptive cruise control vehicles’ degradation under spatial continuous communication interruption. A mixed platoon, consisting of cooperative adaptive cruise control vehicles, adaptive cruise control vehicles, manually driven vehicles, and improved manually driven vehicles with information-sending devices, is simulated with the realistic cooperative adaptive cruise control and adaptive cruise control model, and the intelligent driver model. Different platoon forms are discussed by adjusting the quantity and position of manually driven vehicles in the mixed platoon. The results show that manually driven vehicles can effectively block the backward extension of speed fluctuation and reduce the rear-end collision risk under the spatial continuous communication interruption. Nevertheless, equipping manually driven vehicles with information-sending devices weakens the ability to defend against communication interruption.

Fundamental diagram and stability analysis for heterogeneous traffic flow considering human-driven vehicle driver’s acceptance of cooperative adaptive cruise control vehicles

With cooperative adaptive cruise control vehicles (CACC) development, the heterogeneous traffic flow of human-driven vehicles (HV) and CACC will appear on the same road. Although numerous studies have carefully analyzed the characteristic of the heterogeneous traffic flow, none of them considered the effect of the differences in acceptance of CACC by HV drivers on the heterogeneous traffic flow. In terms of the differences in car-following behaviors of HV drivers with diverse CACC acceptances, this paper deduces the capacity and stability of the heterogeneous traffic flow under different CACC penetration rates. Firstly, the HV driver’s car-following behavior model with different CACC acceptability is calibrated through a questionnaire. Then, the analytical framework of the fundamental diagram and stability of the heterogeneous traffic flow is derived, according to the differences of HV drivers’ acceptance of CACC. Finally, the paper analyzes the influence factors and effects of the heterogeneous traffic flow capacity and stability. The results indicate under different CACC penetration rates, the improvement of HV drivers’ acceptance of CACC increases the capacity and stability of the heterogeneous traffic flow. When CACC penetration rate is lower than 96.35% and HV drivers’ acceptance level of CACC is lower than the critical ratio, the popularity of CACC will decrease the stability of traffic flow. When the penetration rate of CACC is less than 34.76%, and HV drivers’ acceptance level of CACC is lower than the critical proportion, the popularization of CACC will decrease the capacity of heterogeneous traffic.

Stabilizing mixed cooperative adaptive cruise control traffic flow to balance capacity using car-following model

String stability is important for understanding traffic flow dynamics, while its analytical study for mixed traffic is deficient. We focus on an analytical framework on string stability of mixed traffic consisting of cooperative adaptive cruise control (CACC), adaptive cruise control (ACC), and human vehicles. The analytical framework was conducted based on generalized car-following model formulations of the three vehicular types. Then string stability criterions of one-class traffic flow, mixed traffic flow, and local CACC/ACC platoons were derived. Taking into account the mixed flow with partial degenerations of CACC and three concrete car-following models, an example application was studied. The example application analyzed the string stability from the perspectives of the homogeneous flow, the mixed traffic flow, and the local CACC/ACC platoon, respectively. The example application also studied balance between stability and capacity for the mixed traffic with CACC vehicles. Results show the usefulness of the proposed analytical framework, in term of not only analyzing string stability but also providing suggestions for dynamic regulations of CACC/ACC management strategy to balance string stability and traffic capacity for the mixed CACC-human flow.

Modeling of cooperative adaptive cruise control vehicle and its effect on traffic flow

In this paper, an improved multianticipative cooperative adaptive cruise control (CACC) model is proposed based on fully utilizing multivehicle information obtained by vehicle-to-vehicle communication. More flexible, effective and practical spacing strategy is embedded into the model. We design a new lane-changing rule for CACC vehicles on the freeway. The rule considers that CACC vehicles are more inclined to form a platoon for coordinated control. Furthermore, we investigate the effect of CACC vehicles on two-lane traffic flow. The results demonstrate that introducing CACC vehicles into mixed traffic and forming CACC platoon to cooperative control can improve traffic efficiency and enhance road capacity to a certain extent.

Lighthill-Whitham-Richards Model for Traffic Flow Mixed with Cooperative Adaptive Cruise Control Vehicles

In the future, road traffic will incorporate a random mix of manual vehicles and cooperative adaptive cruise control (CACC) vehicles, where a CACC vehicle will degrade to an adaptive cruise control (ACC) vehicle when vehicle-to-vehicle communications are not available. This paper proposes a generalized framework of the Lighthill-Whitham-Richards (LWR) model for such mixed vehicular flow under different CACC penetration rates. In this approach, the kinematic wave speed propagating through the mixed platoon was theoretically proven to be the slope of mixed fundamental diagram. In addition, the random degradation from CACC to ACC was captured in mathematical expectation for traffic scenarios where the CACC only monitors one vehicle ahead. Three concrete car-following models, the intelligent driver model (IDM) and CACC/ACC models validated by Partners for Advanced Transit and Highways (PATH) program, were selected as examples to investigate the propagation of small perturbations and shock waves. Numerical simulations were also performed based on the selected car-following models. Moreover, the derived mixed LWR model was applied to solve some traffic flow problems. It indicates that the proposed LWR model is able to describe the propagation properties of both small perturbations and shock waves. The mixed LWR model can also be used to solve some practical problems, such as the queue caused by a traffic accident and the impact of a moving bottleneck. More importantly, the proposed generalized framework admits other CACC/ACC/regular car-following models, including those developed from further experiments.

Investigating the Longitudinal Impact of Cooperative Adaptive Cruise Control Vehicle Degradation Under Communication Interruption

Cooperative adaptive cruise control (CACC), which is recognized as an extension of adaptive cruise control (ACC) through the addition of vehicle-to-vehicle (V2V) communication, is promoted for application in the near future. Nevertheless, V2V communication is unreliable due to the communication interruption caused by cyberattacks and information congestion. When communication interruption occurs, a CACC vehicle cannot receive the travel information of the preceding vehicle and automatically degrades to an ACC vehicle, leading to the instability of the CACC fleet. This research aims to investigate the longitudinal impact of CACC vehicle degradation under communication interruption. The realistic CACC model and ACC model are used for constructing simulation experiments with a fleet of 10 CACC vehicles. By simulating multiple driving, degradation, and communication-interruption scenarios, we investigate the impact of CACC degradation on fleet stability, energy consumption, and exhaust emissions. Finally, we conduct sensitivity analysis on the key factors of driving models and simulation scenarios. The result shows that CACC vehicle degradation, especially the successive degradation of adjacent vehicles under the acceleration scenario, would reduce average travel speed and increase energy consumption and exhaust emissions. The findings highlight some key scenarios for actively monitoring communication interruption and provide some prospective actions to reduce the impact of CACC degradation.

Improving comfort level in traffic flow of CACC vehicles at lane drop on two-lane highways

This paper studies traffic flow of cooperative adaptive cruise control (CACC) vehicles at lane drop on two-lane highways. A constant time gap algorithm has been used for the upper level longitudinal control of the CACC vehicles. In the control zone upstream of the lane drop, a heuristic control scheme of the CACC vehicles has been used, in which virtual leading vehicle has been introduced by mapping a vehicle on the neighboring lane to the present lane. To improve the passenger comfort, a restriction of the command acceleration caused by virtual leading vehicle, denoted as acmd,lim, has been introduced. It is shown that with the decrease of |acmd,lim|, while the capacity does not change, the comfort of passengers significantly improves.

Modeling and Simulating Urban Traffic Flow Mixed With Regular and Connected Vehicles

In the upcoming decades, connected vehicles will join regular vehicles on the road, and the characteristics of traffic flows will change accordingly. To better understand mixed traffic flow (regular vehicles and connected vehicles) characteristics, a generic car-following modeling framework for this new mixed traffic flow on an urban road under a connected vehicle environment is proposed in this paper. Considering a vehicle’s speed, which is affected by the speed of the preceding vehicle, an improved intelligent driver model (IDM) is used as the car-following model for regular vehicles. An extended cooperative adaptive cruise control (CACC) based on the nonlinear dynamic headway strategy was established as the car-following model for connected vehicles. The fundamental diagram model of mixed traffic flow under different market penetration rates of CACC vehicles is investigated, and the traffic flow operation mechanism of connected vehicles is analyzed to improve the capacity. In addition, simulation experiments on urban roads are designed to evaluate the queue time and length of vehicles passing through congested sections under different market penetration rates of CACC vehicles. The results demonstrate that the proposed model can effectively describe the current situation of traffic flow on urban roads under different market penetration rates of CACC vehicles. The increase in the market penetration rates of CACC vehicles can significantly improve the traffic flow efficiency. When CACC vehicles reach 100% of all vehicles, the queue length on congested roads can be shortened by 64.6%, and the total travel time on congested roads can be reduced by 48.3%.

Stability and safety evaluation of mixed traffic flow with connected automated vehicles on expressways

Introduction: Connected automated vehicles (CAVs) technology has deeply integrated advanced technologies in various fields, providing an effective way to improve traffic safety. However, it would take time for vehicles on the road to vehicles from human-driven vehicles (HDVs) progress to CAVs. Moreover, the Cooperative Adaptive Cruise Control (CACC) vehicle would degrade into the Adaptive Cruise Control (ACC) vehicle due to communication failure. Method: First, the different car-following models are used to capture characteristics of different types of vehicles (e.g., HDVs, CACC, and ACC). Second, the stability of mixed traffic flow is analyzed under different penetration rates of CAVs. Then, multiple safety measures, such as standard deviation of vehicle speed (SD), time exposed rear-end crash risk (TER), time exposed time-to-collision (TET), and time-integrated time-to-collision (TIT) are used to evaluate the safety of mixed traffic flow on expressways. Finally, the sensitivity of traffic demand, the threshold of time-to-collision (TTC), and the parameters of car-following models are analyzed based on a numerical simulation. Results: The results show that the ACC vehicle has no significant impact on the SD of mixed traffic flows, but it leads to the deterioration of TET and TIT, making the reduction proportion of TER slower. When the penetration rate exceeds 50%, the increase of CACC vehicles reduces traffic safety risks significantly. Furthermore, the increase in traffic demand and car-following parameters worsens traffic safety on expressways. Conclusions: This paper suggests that the CACC vehicles degenerate into ACC vehicles due to communication failure, and the safety risk of mixed traffic flow increases significantly. Practical Applications: The application of CAVs can improve the stability and safety of traffic flow.

A generic simulation platform for cooperative adaptive cruise control under partially connected and automated environment

Cooperative Adaptive Cruise Control (CACC) has been regarded as the most promising technology that can be carried out in field earliest under partially connected and automated environment, and is one of the few Connected and Automated Vehicle (CAV) applications closest to its final shape. Therefore, validation of CACC running in real traffic is in urgent need. To support the validation, simulation plays a key role. This paper proposes a next-generation simulation platform for CACC evaluation and validation. It is able to not only validate the performance of a CACC platoon by itself, but also evaluate its performance when being released into the traffic. In addition, it can also quantify the impact of CACC vehicles on transportation systems. The proposed platform is generic in terms of CACC control system, background traffic condition, road geometry, and traffic control scheme. Furthermore, it is capable of capturing the dynamics of platoon formation and disengagement when CACC equipped vehicles are mixed up with human-driven vehicles. The proposed platform is validated by comparing against actual field data and previously published theoretical studies. The results confirm the credibility of the proposed platform in terms of: i) CACC control system embedded; ii) CAV and Human-driven Vehicle (HV) mixed traffic simulation; iii) managed lane simulation. It is also revealed that current CACC technology without upgrade may be a safety hazard and permitting CACC only on a dedicated CACC lane might be a good first step for CACC commercialization at this moment.