Connected automated vehicles(CAVs)serve as a promising enabler for future intelligent transportation systems because of their capabilities in improving traffic efficiency and driving safety,and reducing fuel consumpti...Connected automated vehicles(CAVs)serve as a promising enabler for future intelligent transportation systems because of their capabilities in improving traffic efficiency and driving safety,and reducing fuel consumption and vehicle emissions.A fundamental issue in CAVs is platooning control that empowers a convoy of CAVs to be cooperatively maneuvered with desired longitudinal spacings and identical velocities on roads.This paper addresses the issue of resilient and safe platooning control of CAVs subject to intermittent denial-of-service(DoS)attacks that disrupt vehicle-to-vehicle communications.First,a heterogeneous and uncertain vehicle longitudinal dynamic model is presented to accommodate a variety of uncertainties,including diverse vehicle masses and engine inertial delays,unknown and nonlinear resistance forces,and a dynamic platoon leader.Then,a resilient and safe distributed longitudinal platooning control law is constructed with an aim to preserve simultaneous individual vehicle stability,attack resilience,platoon safety and scalability.Furthermore,a numerically efficient offline design algorithm for determining the desired platoon control law is developed,under which the platoon resilience against DoS attacks can be maximized but the anticipated stability,safety and scalability requirements remain preserved.Finally,extensive numerical experiments are provided to substantiate the efficacy of the proposed platooning method.展开更多
Connected autonomous vehicles(CAVs)are a promising paradigm for implementing intelligent transportation systems.However,in CAVs scenarios,the sensing blind areas cause serious safety hazards.Existing vehicle-to-vehicl...Connected autonomous vehicles(CAVs)are a promising paradigm for implementing intelligent transportation systems.However,in CAVs scenarios,the sensing blind areas cause serious safety hazards.Existing vehicle-to-vehicle(V2V)technology is difficult to break through the sensing blind area and ensure reliable sensing information.To overcome these problems,considering infrastructures as a means to extend the sensing range is feasible based on the integrated sensing and communication(ISAC)technology.The mmWave base station(mmBS)transmits multiple beams consisting of communication beams and sensing beams.The sensing beams are responsible for sensing objects within the CAVs blind area,while the communication beams are responsible for transmitting the sensed information to the CAVs.To reduce the impact of inter-beam interference,a joint multiple beamwidth and power allocation(JMBPA)algorithm is proposed.By maximizing the communication transmission rate under the sensing constraints.The proposed non-convex optimization problem is transformed into a standard difference of two convex functions(D.C.)problem.Finally,the superiority of the lutions.The average transmission rate of communication beams remains over 3.4 Gbps,showcasing a significant improvement compared to other algorithms.Moreover,the satisfaction of sensing services remains steady.展开更多
Connected Automated Vehicles(CAVs)have drawn much attention in recent years.High reliable automatic technologies can help CAVs to follow given trajectories well.However,safety and efficiency are hard to be ensured sin...Connected Automated Vehicles(CAVs)have drawn much attention in recent years.High reliable automatic technologies can help CAVs to follow given trajectories well.However,safety and efficiency are hard to be ensured since the interactions between CAVs and pedestrians are complex problems.Thus,this study focuses on cooperative intersection management for CAVs and pedestrians.To avoid the effects of uncertainty about pedestrian behaviors,an indirect way is to use pedestrians’signal lights to guide the movements of pedestrians,and such lights with communication devices can share information with CAVs to make decisions together.In time domains,a general conflict-free rule is established depending on the positions of CAVs and crosswalks.Geometric analysis with coordinate calculation is used to accurately determine the feasible vehicle trajectories and the reasonable periods for signal lights turning green.Four control strategies for the same conditions are compared in simulation experiments,and their performances are analyzed.We demonstrate that the proposed cooperative strategy not only balances the benefits of vehicles and pedestrians but also improves the traffic efficiency at the intersection.展开更多
Safety and security are interrelated and both essential for connected automated vehicles(CAVs).They are usually investigated independently,followed by standards ISO 26262 and ISO/SAE 21434,respectively.However,more fu...Safety and security are interrelated and both essential for connected automated vehicles(CAVs).They are usually investigated independently,followed by standards ISO 26262 and ISO/SAE 21434,respectively.However,more functional safety and security fea-tures of in-vehicle components make existing safety mechanisms weaken security mechanisms and vice versa.This results in a dilemma that the safety-critical and security-critical in-vehicle components cannot be protected.In this paper,we propose a dynamic heterogeneous redundancy(DHR)architecture to enhance the safety and security of CAVs simultaneously.We first investigate the current status of integrated safety and security analysis and explore the relationship between safety and security.Then,we propose a new taxonomy of in-vehicle components based on safety and security features.Finally,a dynamic heterogeneous redun-dancy(DHR)architecture is proposed to guarantee integrated functional safety and cyber security of connected vehicles for the first time.A case study on an automated bus shows that DHR architecture can not only detect unknown failures and ensure functional safety but also detect unknown attacks to protect cyber security.Furthermore,we provide an in-depth analysis of quantification for CAVs performance using DHR architecture and identify chal-lenges and future research directions.Overall,integrated safety and security enhancement is an emerging research direction.展开更多
This paper investigates traffic flow of connected and automated vehicles at lane drop on two-lane highway. We evaluate and compare performance of an optimization-based control algorithm(OCA) with that of a heuristic r...This paper investigates traffic flow of connected and automated vehicles at lane drop on two-lane highway. We evaluate and compare performance of an optimization-based control algorithm(OCA) with that of a heuristic rules-based algorithm(HRA). In the OCA, the average speed of each vehicle is maximized. In the HRA, virtual vehicle and restriction of the command acceleration caused by the virtual vehicle are introduced. It is found that(i) capacity under the HRA(denoted as C_(H)) is smaller than capacity under the OCA;(ii) the travel delay is always smaller under the OCA, but driving is always much more comfortable under the HRA;(iii) when the inflow rate is smaller than C_(H), the HRA outperforms the OCA with respect to the fuel consumption and the monetary cost;(iv) when the inflow rate is larger than C_(H), the HRA initially performs better with respect to the fuel consumption and the monetary cost, but the OCA would become better after certain time. The spatiotemporal pattern and speed profile of traffic flow are presented, which explains the reason underlying the different performance. The study is expected to help for better understanding of the two different types of algorithm.展开更多
As a form of a future traffic system,a connected and automated vehicle(CAV)platoon is a typical nonlinear physical system.CAVs can communicate with each other and exchange information.However,communication failures ca...As a form of a future traffic system,a connected and automated vehicle(CAV)platoon is a typical nonlinear physical system.CAVs can communicate with each other and exchange information.However,communication failures can change the platoon system status.To characterize this change,a dynamic topology-based car-following model and its generalized form are proposed in this work.Then,a stability analysis method is explored.Finally,taking the dynamic cooperative intelligent driver model(DC-IDM)for example,a series of numerical simulations is conducted to analyze the platoon stability in different communication topology scenarios.The results show that the communication failures reduce the stability,but information from vehicles that are farther ahead and the use of a larger desired time headway can improve stability.Moreover,the critical ratio of communication failures required to ensure stability for different driving parameters is studied in this work.展开更多
This paper investigates the traffic flow of connected and automated vehicles(CAVs)inducing by a moving bottleneck on a two-lane highway.A heuristic rules-based algorithm(HRA)has been used to control the traffic flow u...This paper investigates the traffic flow of connected and automated vehicles(CAVs)inducing by a moving bottleneck on a two-lane highway.A heuristic rules-based algorithm(HRA)has been used to control the traffic flow upstream of the moving bottleneck.In the HRA,some CAVs in the control zone are mapped onto the neighboring lane as virtual ones.To improve the driving comfort,the command acceleration caused by virtual vehicle is restricted.Comparing with the benchmark in which the CAVs change lane as soon as the lane changing condition is met,the HRA significantly improves the traffic flow:the overtaking throughput as well as the outflow rate increases,the travel delay and the fuel consumption decrease,the comfort level could also be improved.展开更多
We propose pro-social control strategies for connected automated vehicles(CAVs)to mitigate jamming waves in mixed-autonomy multi-lane traffic,resulting from car-following dynamics of human-driven vehicles(HDVs).Differ...We propose pro-social control strategies for connected automated vehicles(CAVs)to mitigate jamming waves in mixed-autonomy multi-lane traffic,resulting from car-following dynamics of human-driven vehicles(HDVs).Different from existing studies,which focus mostly on ego vehicle objectives to control CAVs in an individualistic manner,we devise a pro-social control algorithm.The latter takes into account the objectives(i.e.,driving comfort and traffic efficiency)of both the ego vehicle and surrounding HDVs to improve smoothness of the entire observable traffic.Under a model predictive control(MPC)framework that uses acceleration and lane change sequences of CAVs as optimization variables,the problem of individualistic,altruistic,and pro-social control is formulated as a non-convex mixed-integer nonlinear program(MINLP)and relaxed to a convex quadratic program through converting the piece-wise-linear constraints due to the optimal velocity with relative velocity(OVRV)car-following model into linear constraints by introducing slack variables.Low-fidelity simulations using the OVRV model and high-fidelity simulations using PTV VISSIM simulator show that pro-social and altruistic control can provide significant performance gains over individualistic driving in terms of efficiency and comfort on both single-and multi-lane roads.展开更多
To address the driving conflicts of connected automated vehicles(CAVs)at unsignalized roundabouts,a cooperative decision-making framework is proposed.The personalized driving preferences of CAVs are considered in the ...To address the driving conflicts of connected automated vehicles(CAVs)at unsignalized roundabouts,a cooperative decision-making framework is proposed.The personalized driving preferences of CAVs are considered in the decision-making algorithm,which are reflected by different driving styles.A motion prediction algorithm is used to improve the decision-making performance.The effect of the motion prediction algorithm on the decisionmaking performance is evaluated,including the advancement of driving safety and the computational load for the hardware.The cooperative game theoretic approach is applied to the interaction modelling and collaborative decision making of CAVs.Finally,hardware-in-the-loop(HIL)tests are carried out to evaluate the feasibility and real-time performance of the proposed algorithm.展开更多
The connected and automated vehicles(CAVs)technologies provide more information to drivers in the car-following(CF)process.Unlike the human-driven vehicles(HVs),which only considers information in front,the CAVs circu...The connected and automated vehicles(CAVs)technologies provide more information to drivers in the car-following(CF)process.Unlike the human-driven vehicles(HVs),which only considers information in front,the CAVs circumstance allows them to obtain information in front and behind,enhancing vehicles perception ability.This paper proposes an intelligent back-looking distance driver model(IBDM)considering the desired distance of the following vehicle in homogeneous CAVs environment.Based on intelligent driver model(IDM),the IBDM integrates behind information of vehicles as a control term.The stability condition against a small perturbation is analyzed using linear stability theory in the homogeneous traffic flow.To validate the theoretical analysis,simulations are carried out on a single lane under the open boundary condition,and compared with the IDM not considering the following vehicle and the extended IDM considering the information of vehicle preceding and next preceding.Six scenarios are designed to evaluate the results under different disturbance strength,disturbance location,and initial platoon space distance.The results reveal that the IBDM has an advantage over IDM and the extended IDM in control of CAVs car-following process in maintaining string stability,and the stability improves by increasing the proportion of the new item.展开更多
The highway capacity manual(HCM)provides a formula to calculate the heavy vehicle adjustment factor(fHV)as a function of passenger car equivalent factors for the heavy vehicle(ET).However,a significant drawback is tha...The highway capacity manual(HCM)provides a formula to calculate the heavy vehicle adjustment factor(fHV)as a function of passenger car equivalent factors for the heavy vehicle(ET).However,a significant drawback is that the methodology was established solely based on human-driven passenger cars(HDPC)and human-driven heavy vehicles(HDHV).Due to automated passenger cars(APCs),a new adjustment factor(fAV)might be expected.This study simulated traffic flows at different percentages of HDHVs and APCs to investigate the impacts of HDHVs and APCs on freeway capacity by analyzing their influence on fHV and fAV values.The simulation determined observed adjustment factors at different percentages of HDHVs and APCs(fobserved).The HCM formula was used to calculate(fHCM).Modifications to the HCM formula are proposed,and vehicle adjustment factors due to HDHVs and APCs were calculated(fproposed).Results showed that,in the presence of APCs,while fobserved and fHCM were statistically significantly different,fobserved and fproposed were statistically equal.Hence,this study recommends using the proposed formula when determining vehicle adjustment factors(fproposed)due to HDHVs and APCs in the traffic stream.展开更多
Purpose–Freeway work zones have been traffic bottlenecks that lead to a series of problems,including long travel time,high-speed variation,driver’s dissatisfaction and traffic congestion.This research aims to develo...Purpose–Freeway work zones have been traffic bottlenecks that lead to a series of problems,including long travel time,high-speed variation,driver’s dissatisfaction and traffic congestion.This research aims to develop a collaborative component of connected and automated vehicles(CAVs)to alleviate negative effects caused by work zones.Design/methodology/approach–The proposed cooperative component is incorporated in a cellular automata model to examine how and to what scale CAVs can help in improving traffic operations.Findings–Simulation results show that,with the proposed component and penetration of CAVs,the average performances(travel time,safety and emission)can all be improved and the stochasticity of performances will be minimized too.Originality/value–To the best of the authors’knowledge,this is the first research that develops a cooperative mechanism of CAVs to improve work zone performance.展开更多
Through vehicle-to-vehicle(V2V)communication,autonomizing a vehicle platoon can significantly reduce the distance between vehicles,thereby reducing air resistance and improving road traffic efficiency.The gradual matu...Through vehicle-to-vehicle(V2V)communication,autonomizing a vehicle platoon can significantly reduce the distance between vehicles,thereby reducing air resistance and improving road traffic efficiency.The gradual maturation of platoon control technology is enabling vehicle platoons to achieve basic driving functions,thereby permitting large-scale vehicle platoon scheduling and planning,which is essential for industrialized platoon applications and generates significant economic benefits.Scheduling and planning are required in many aspects of vehicle platoon operation;here,we outline the advantages and challenges of a number of the most important applications,including platoon formation scheduling,lane-change planning,passing traffic light scheduling,and vehicle resource allocation.This paper’s primary objective is to integrate current independent platoon scheduling and planning techniques into an integrated architecture to meet the demands of large-scale platoon applications.To this end,we first summarize the general techniques of vehicle platoon scheduling and planning,then list the primary scenarios for scheduling and planning technique application,and finally discuss current challenges and future development trends in platoon scheduling and planning.We hope that this paper can encourage related platoon researchers to conduct more systematic research and integrate multiple platoon scheduling and planning technologies and applications.展开更多
Connected and automated vehicles(CAVs)are expected to reshape traffic flow dynamics and present new challenges and opportunities for traffic flow modeling.While numerous studies have proposed optimal modeling and cont...Connected and automated vehicles(CAVs)are expected to reshape traffic flow dynamics and present new challenges and opportunities for traffic flow modeling.While numerous studies have proposed optimal modeling and control strategies for CAVs with various objectives(e.g.,traffic efficiency and safety),there are uncertainties about the flow dynamics of CAVs in real-world traffic.The uncertainties are especially amplified for mixed traffic flows,consisting of CAVs and human-driven vehicles,where the implications can be significant from the continuum-modeling perspective,which aims to capture macroscopic traffic flow dynamics based on hyperbolic systems of partial differential equations.This paper aims to highlight and discuss some essential problems in continuum modeling of real-world freeway traffic flows in the era of CAVs.We first provide a select review of some existing continuum models for conventional human-driven traffic as well as the recent attempts for incorporating CAVs into the continuum-modeling framework.Wherever applicable,we provide new insights about the properties of existing models and revisit their implications for traffic flows of CAVs using recent empirical observations with CAVs and the previous discussions and debates in the literature.The paper then discusses some major problems inherent to continuum modeling of real-world(mixed)CAV traffic flows modeling by distinguishing between two major research directions:(a)modeling for explaining purposes,where making reproducible inferences about the physical aspects of macroscopic properties is of the primary interest,and(b)modeling for practical purposes,in which the focus is on the reliable predictions for operation and control.The paper proposes some potential solutions in each research direction and recommends some future research topics.展开更多
Platooning has emerged to be one of the most promising applications for connected and automated vehicles(CAVs).However,there is still limited research on the effect of platooning configurations.This study sets out to ...Platooning has emerged to be one of the most promising applications for connected and automated vehicles(CAVs).However,there is still limited research on the effect of platooning configurations.This study sets out to investigate the effect of CAV platoon configurations at a typical isolated roundabout in a mixed traffic environment.Investigated platoon configurations include maximum platoon size,platoon willingness,and platoon type.Extensive simulation experiments are carried out in simulation of urban mobility(SUMO),considering various traffic conditions,including different penetration rates,traffic flows,and turning percentages.Results show that:(1)increasing the maximum platoon size and platoon willingness generally improves the throughput increment and delay reduction;and(2)heterogeneous platoons outperform homogeneous platoons in all traffic conditions.展开更多
Potential field theory,as a theory that can also be applied to vehicle control,is an emerging risk quantification approach to accommodate the connected and self-driving vehicle environment.Vehicles have different risk...Potential field theory,as a theory that can also be applied to vehicle control,is an emerging risk quantification approach to accommodate the connected and self-driving vehicle environment.Vehicles have different risk impact effects on other road participants in each direction under the influence of road rules.This variability exhibited by vehicles in each direction is not considered in the previous potential field model.Therefore,this paper proposed a potential field model that takes the anisotropy of vehicle impact into account:(1)introducing equivalent distances to separate the potential field area in the different directions before and after the vehicle;(2)introducing co-virtual forces to characterize the effect of the side-by-side travel phenomenon on vehicle car-following travel;(3)introducing target forces and lane resistance,which regress the control of desired speed to control the acceptable risk of drivers.The Next Generation Simulation(NGSIM)dataset is used in this study to create the model's initial parameter values based on the artificial swarm algorithm.The simulation findings indicate that when the vehicle is given the capacity to perceive the surrounding traffic environment,the suggested the anisotropic safety potential field model(ASPFM)performs better in terms of driving safety.展开更多
Improper handling of vehicle on-ramp merging may hinder traffic flow and contribute to lower fuel economy,while also increasing the risk of collisions.Cooperative control for connected and automated vehicles(CAVs)has ...Improper handling of vehicle on-ramp merging may hinder traffic flow and contribute to lower fuel economy,while also increasing the risk of collisions.Cooperative control for connected and automated vehicles(CAVs)has the potential to significantly reduce negative environmental impact while also improve driving safety and traffic efficiency.Therefore,in this paper,we focus on the scenario of CAVs on-ramp merging and propose a centralized control method.Merging sequence(MS)allocation and motion planning are two key issues in this process.To deal with these problems,we first propose an MS allocation method based on a complete information static game whereby the mixed-strategy Nash equilibrium is calculated for an individual vehicle to select its strategy.The on-ramp merging problem is then formulated as a bi-objective(total fuel consumption and total travel time)optimization problem,to which optimal control based on Pontryagin's minimum principle(PMP)is applied to solve the motion planning issue.To determine the proper parameters in the bi-objective optimization problem,a varying-scale grid search method is proposed to explore possible solutions at different scales.In this method,an improved quicksort algorithm is designed to search for the Pareto front,and the(approximately)unbiased Pareto solution for the bi-objective optimization problem is finally determined as the optimal solution.The proposed on-ramp merging strategy is validated via numerical simulation,and comparison with other strategies demonstrates its effectiveness in terms of fuel economy and traffic efficiency.展开更多
Purpose–This paper aims to review the studies on intersection control with connected and automated vehicles(CAVs).Design/methodology/approach–The most seminal and recent research in this area is reviewed.This study ...Purpose–This paper aims to review the studies on intersection control with connected and automated vehicles(CAVs).Design/methodology/approach–The most seminal and recent research in this area is reviewed.This study specifically focuses on two categories:CAV trajectory planning and joint intersection and CAV control.Findings–It is found that there is a lack of widely recognized benchmarks in this area,which hinders the validation and demonstration of new studies.Originality/value–In this review,the authors focus on the methodological approaches taken to empower intersection control with CAVs.The authors hope the present review could shed light on the state-of-the-art methods,research gaps and future research directions.展开更多
Autonomous driving is an active area of research in artificial intelligence and robotics.Recent advances in deep reinforcement learning(DRL)show promise for training autonomous vehicles to handle complex real-world dr...Autonomous driving is an active area of research in artificial intelligence and robotics.Recent advances in deep reinforcement learning(DRL)show promise for training autonomous vehicles to handle complex real-world driving tasks.This paper reviews recent advancement on the application of DRL to highway lane change,ramp merge,and platoon coordination.In particular,similarities,differences,limitations,and best practices regarding the DRL formulations,DRL training algorithms,simulations,and metrics are reviewed and discussed.The paper starts by reviewing different traffic scenarios that are discussed by the literature,followed by a thorough review on the DRL technology such as the state representation methods that capture interactive dynamics critical for safe and efficient merging and the reward formulations that manage key metrics like safety,efficiency,comfort,and adaptability.Insights from this review can guide future research toward realizing the potential of DRL for automated driving in complex traffic under uncertainty.展开更多
In this paper,we propose a real-time energy-efficient anticipative driving control strategy for connected and automated hybrid electric vehicles(HEVs).Considering the inherent complexities brought about by the velocit...In this paper,we propose a real-time energy-efficient anticipative driving control strategy for connected and automated hybrid electric vehicles(HEVs).Considering the inherent complexities brought about by the velocity profile optimization and energy management control,a hierarchical control architecture in the model predictive control(MPC)framework is developed for real-time implementation.In the higher level controller,a novel velocity optimization problem is proposed to realize safe and energy-efficient anticipative driving.The real-time control actions are derived through a computationally efficient algorithm.In the lower level controller,an explicit solution of the optimal torque split ratio and gear shift schedule is introduced for following the optimal velocity profile obtained from the higher level controller.The comparative simulation results demonstrate that the proposed strategy can achieve approximately 13%fuel consumption saving compared with a benchmark strategy.展开更多
基金supported in part by Australian Research Council Discovery Early Career Researcher Award(DE210100273)。
文摘Connected automated vehicles(CAVs)serve as a promising enabler for future intelligent transportation systems because of their capabilities in improving traffic efficiency and driving safety,and reducing fuel consumption and vehicle emissions.A fundamental issue in CAVs is platooning control that empowers a convoy of CAVs to be cooperatively maneuvered with desired longitudinal spacings and identical velocities on roads.This paper addresses the issue of resilient and safe platooning control of CAVs subject to intermittent denial-of-service(DoS)attacks that disrupt vehicle-to-vehicle communications.First,a heterogeneous and uncertain vehicle longitudinal dynamic model is presented to accommodate a variety of uncertainties,including diverse vehicle masses and engine inertial delays,unknown and nonlinear resistance forces,and a dynamic platoon leader.Then,a resilient and safe distributed longitudinal platooning control law is constructed with an aim to preserve simultaneous individual vehicle stability,attack resilience,platoon safety and scalability.Furthermore,a numerically efficient offline design algorithm for determining the desired platoon control law is developed,under which the platoon resilience against DoS attacks can be maximized but the anticipated stability,safety and scalability requirements remain preserved.Finally,extensive numerical experiments are provided to substantiate the efficacy of the proposed platooning method.
基金China Tele-com Research Institute Project(Grants No.HQBYG2200147GGN00)National Key R&D Program of China(2020YFB1807600)National Natural Science Foundation of China(NSFC)(Grant No.62022020).
文摘Connected autonomous vehicles(CAVs)are a promising paradigm for implementing intelligent transportation systems.However,in CAVs scenarios,the sensing blind areas cause serious safety hazards.Existing vehicle-to-vehicle(V2V)technology is difficult to break through the sensing blind area and ensure reliable sensing information.To overcome these problems,considering infrastructures as a means to extend the sensing range is feasible based on the integrated sensing and communication(ISAC)technology.The mmWave base station(mmBS)transmits multiple beams consisting of communication beams and sensing beams.The sensing beams are responsible for sensing objects within the CAVs blind area,while the communication beams are responsible for transmitting the sensed information to the CAVs.To reduce the impact of inter-beam interference,a joint multiple beamwidth and power allocation(JMBPA)algorithm is proposed.By maximizing the communication transmission rate under the sensing constraints.The proposed non-convex optimization problem is transformed into a standard difference of two convex functions(D.C.)problem.Finally,the superiority of the lutions.The average transmission rate of communication beams remains over 3.4 Gbps,showcasing a significant improvement compared to other algorithms.Moreover,the satisfaction of sensing services remains steady.
基金supported by the Science and Technology Commission of Shanghai Municipality(Nos.22YF1461400 and 22DZ1100102)the National Natural Science Foundation of China(No.72001007).
文摘Connected Automated Vehicles(CAVs)have drawn much attention in recent years.High reliable automatic technologies can help CAVs to follow given trajectories well.However,safety and efficiency are hard to be ensured since the interactions between CAVs and pedestrians are complex problems.Thus,this study focuses on cooperative intersection management for CAVs and pedestrians.To avoid the effects of uncertainty about pedestrian behaviors,an indirect way is to use pedestrians’signal lights to guide the movements of pedestrians,and such lights with communication devices can share information with CAVs to make decisions together.In time domains,a general conflict-free rule is established depending on the positions of CAVs and crosswalks.Geometric analysis with coordinate calculation is used to accurately determine the feasible vehicle trajectories and the reasonable periods for signal lights turning green.Four control strategies for the same conditions are compared in simulation experiments,and their performances are analyzed.We demonstrate that the proposed cooperative strategy not only balances the benefits of vehicles and pedestrians but also improves the traffic efficiency at the intersection.
基金supported by the Shanghai Sailing Program(21YF1413800 and 20YF1413700)the National Science Foundation of China(no.62002213)+1 种基金the Program of Industrial Internet Visualized Asset Management and Operation Technology and Products,Shanghai Science and Technology Innovation Action Plan(No.21511102502,No.21511102500)Henan Science and Technology Major Project(No.221100240100).
文摘Safety and security are interrelated and both essential for connected automated vehicles(CAVs).They are usually investigated independently,followed by standards ISO 26262 and ISO/SAE 21434,respectively.However,more functional safety and security fea-tures of in-vehicle components make existing safety mechanisms weaken security mechanisms and vice versa.This results in a dilemma that the safety-critical and security-critical in-vehicle components cannot be protected.In this paper,we propose a dynamic heterogeneous redundancy(DHR)architecture to enhance the safety and security of CAVs simultaneously.We first investigate the current status of integrated safety and security analysis and explore the relationship between safety and security.Then,we propose a new taxonomy of in-vehicle components based on safety and security features.Finally,a dynamic heterogeneous redun-dancy(DHR)architecture is proposed to guarantee integrated functional safety and cyber security of connected vehicles for the first time.A case study on an automated bus shows that DHR architecture can not only detect unknown failures and ensure functional safety but also detect unknown attacks to protect cyber security.Furthermore,we provide an in-depth analysis of quantification for CAVs performance using DHR architecture and identify chal-lenges and future research directions.Overall,integrated safety and security enhancement is an emerging research direction.
基金Project supported in part by the Fundamental Research Funds for the Central Universities (Grant No.2021JBZ107)the National Natural Science Foundation of China (Grant Nos.72288101 and 71931002)。
文摘This paper investigates traffic flow of connected and automated vehicles at lane drop on two-lane highway. We evaluate and compare performance of an optimization-based control algorithm(OCA) with that of a heuristic rules-based algorithm(HRA). In the OCA, the average speed of each vehicle is maximized. In the HRA, virtual vehicle and restriction of the command acceleration caused by the virtual vehicle are introduced. It is found that(i) capacity under the HRA(denoted as C_(H)) is smaller than capacity under the OCA;(ii) the travel delay is always smaller under the OCA, but driving is always much more comfortable under the HRA;(iii) when the inflow rate is smaller than C_(H), the HRA outperforms the OCA with respect to the fuel consumption and the monetary cost;(iv) when the inflow rate is larger than C_(H), the HRA initially performs better with respect to the fuel consumption and the monetary cost, but the OCA would become better after certain time. The spatiotemporal pattern and speed profile of traffic flow are presented, which explains the reason underlying the different performance. The study is expected to help for better understanding of the two different types of algorithm.
基金Project supported by the National Key Research and Development Project of China(Grant No.2018YFE0204300)the Beijing Municipal Science&Technology Commission(Grant No.Z211100004221008)the National Natural Science Foundation of China(Grant No.U1964206).
文摘As a form of a future traffic system,a connected and automated vehicle(CAV)platoon is a typical nonlinear physical system.CAVs can communicate with each other and exchange information.However,communication failures can change the platoon system status.To characterize this change,a dynamic topology-based car-following model and its generalized form are proposed in this work.Then,a stability analysis method is explored.Finally,taking the dynamic cooperative intelligent driver model(DC-IDM)for example,a series of numerical simulations is conducted to analyze the platoon stability in different communication topology scenarios.The results show that the communication failures reduce the stability,but information from vehicles that are farther ahead and the use of a larger desired time headway can improve stability.Moreover,the critical ratio of communication failures required to ensure stability for different driving parameters is studied in this work.
基金the National Natural Science Foundation of China(Grant Nos.71931002 and 72288101)。
文摘This paper investigates the traffic flow of connected and automated vehicles(CAVs)inducing by a moving bottleneck on a two-lane highway.A heuristic rules-based algorithm(HRA)has been used to control the traffic flow upstream of the moving bottleneck.In the HRA,some CAVs in the control zone are mapped onto the neighboring lane as virtual ones.To improve the driving comfort,the command acceleration caused by virtual vehicle is restricted.Comparing with the benchmark in which the CAVs change lane as soon as the lane changing condition is met,the HRA significantly improves the traffic flow:the overtaking throughput as well as the outflow rate increases,the travel delay and the fuel consumption decrease,the comfort level could also be improved.
基金supported and funded by the Transport Area of Advance.The project IRIS is acknowledged for financial support.
文摘We propose pro-social control strategies for connected automated vehicles(CAVs)to mitigate jamming waves in mixed-autonomy multi-lane traffic,resulting from car-following dynamics of human-driven vehicles(HDVs).Different from existing studies,which focus mostly on ego vehicle objectives to control CAVs in an individualistic manner,we devise a pro-social control algorithm.The latter takes into account the objectives(i.e.,driving comfort and traffic efficiency)of both the ego vehicle and surrounding HDVs to improve smoothness of the entire observable traffic.Under a model predictive control(MPC)framework that uses acceleration and lane change sequences of CAVs as optimization variables,the problem of individualistic,altruistic,and pro-social control is formulated as a non-convex mixed-integer nonlinear program(MINLP)and relaxed to a convex quadratic program through converting the piece-wise-linear constraints due to the optimal velocity with relative velocity(OVRV)car-following model into linear constraints by introducing slack variables.Low-fidelity simulations using the OVRV model and high-fidelity simulations using PTV VISSIM simulator show that pro-social and altruistic control can provide significant performance gains over individualistic driving in terms of efficiency and comfort on both single-and multi-lane roads.
基金A*STAR,Singapore,under Grant SERC 1922500046 and Grant A2084c0156the SUG-NAP,Nanyang Technological University,under Grant M4082268.050.
文摘To address the driving conflicts of connected automated vehicles(CAVs)at unsignalized roundabouts,a cooperative decision-making framework is proposed.The personalized driving preferences of CAVs are considered in the decision-making algorithm,which are reflected by different driving styles.A motion prediction algorithm is used to improve the decision-making performance.The effect of the motion prediction algorithm on the decisionmaking performance is evaluated,including the advancement of driving safety and the computational load for the hardware.The cooperative game theoretic approach is applied to the interaction modelling and collaborative decision making of CAVs.Finally,hardware-in-the-loop(HIL)tests are carried out to evaluate the feasibility and real-time performance of the proposed algorithm.
基金Project(2018YFB1600600)supported by the National Key Research and Development Program,ChinaProject(20YJAZH083)supported by the Ministry of Education,China+1 种基金Project(20YJAZH083)supported by the Humanities and Social Sciences,ChinaProject(51878161)supported by the National Natural Science Foundation of China。
文摘The connected and automated vehicles(CAVs)technologies provide more information to drivers in the car-following(CF)process.Unlike the human-driven vehicles(HVs),which only considers information in front,the CAVs circumstance allows them to obtain information in front and behind,enhancing vehicles perception ability.This paper proposes an intelligent back-looking distance driver model(IBDM)considering the desired distance of the following vehicle in homogeneous CAVs environment.Based on intelligent driver model(IDM),the IBDM integrates behind information of vehicles as a control term.The stability condition against a small perturbation is analyzed using linear stability theory in the homogeneous traffic flow.To validate the theoretical analysis,simulations are carried out on a single lane under the open boundary condition,and compared with the IDM not considering the following vehicle and the extended IDM considering the information of vehicle preceding and next preceding.Six scenarios are designed to evaluate the results under different disturbance strength,disturbance location,and initial platoon space distance.The results reveal that the IBDM has an advantage over IDM and the extended IDM in control of CAVs car-following process in maintaining string stability,and the stability improves by increasing the proportion of the new item.
文摘The highway capacity manual(HCM)provides a formula to calculate the heavy vehicle adjustment factor(fHV)as a function of passenger car equivalent factors for the heavy vehicle(ET).However,a significant drawback is that the methodology was established solely based on human-driven passenger cars(HDPC)and human-driven heavy vehicles(HDHV).Due to automated passenger cars(APCs),a new adjustment factor(fAV)might be expected.This study simulated traffic flows at different percentages of HDHVs and APCs to investigate the impacts of HDHVs and APCs on freeway capacity by analyzing their influence on fHV and fAV values.The simulation determined observed adjustment factors at different percentages of HDHVs and APCs(fobserved).The HCM formula was used to calculate(fHCM).Modifications to the HCM formula are proposed,and vehicle adjustment factors due to HDHVs and APCs were calculated(fproposed).Results showed that,in the presence of APCs,while fobserved and fHCM were statistically significantly different,fobserved and fproposed were statistically equal.Hence,this study recommends using the proposed formula when determining vehicle adjustment factors(fproposed)due to HDHVs and APCs in the traffic stream.
文摘Purpose–Freeway work zones have been traffic bottlenecks that lead to a series of problems,including long travel time,high-speed variation,driver’s dissatisfaction and traffic congestion.This research aims to develop a collaborative component of connected and automated vehicles(CAVs)to alleviate negative effects caused by work zones.Design/methodology/approach–The proposed cooperative component is incorporated in a cellular automata model to examine how and to what scale CAVs can help in improving traffic operations.Findings–Simulation results show that,with the proposed component and penetration of CAVs,the average performances(travel time,safety and emission)can all be improved and the stochasticity of performances will be minimized too.Originality/value–To the best of the authors’knowledge,this is the first research that develops a cooperative mechanism of CAVs to improve work zone performance.
基金funded by the Shanghai Municipal Science and Technology Major Project(2018SHZDZX01)of Zhang Jiang Laboratory and Shanghai Center for Brain Science and Brain-Inspired TechnologyShanghai Rising Star Program(21QC1400900)Tongji–Westwell Autonomous Vehicle Joint Lab Project。
文摘Through vehicle-to-vehicle(V2V)communication,autonomizing a vehicle platoon can significantly reduce the distance between vehicles,thereby reducing air resistance and improving road traffic efficiency.The gradual maturation of platoon control technology is enabling vehicle platoons to achieve basic driving functions,thereby permitting large-scale vehicle platoon scheduling and planning,which is essential for industrialized platoon applications and generates significant economic benefits.Scheduling and planning are required in many aspects of vehicle platoon operation;here,we outline the advantages and challenges of a number of the most important applications,including platoon formation scheduling,lane-change planning,passing traffic light scheduling,and vehicle resource allocation.This paper’s primary objective is to integrate current independent platoon scheduling and planning techniques into an integrated architecture to meet the demands of large-scale platoon applications.To this end,we first summarize the general techniques of vehicle platoon scheduling and planning,then list the primary scenarios for scheduling and planning technique application,and finally discuss current challenges and future development trends in platoon scheduling and planning.We hope that this paper can encourage related platoon researchers to conduct more systematic research and integrate multiple platoon scheduling and planning technologies and applications.
基金partially funded by the Australian Research Council(ARC)through the Discovery Project(DP210102970)Dr.Zuduo Zheng's Discovery Early Career Researcher Award(DECRADE160100449).
文摘Connected and automated vehicles(CAVs)are expected to reshape traffic flow dynamics and present new challenges and opportunities for traffic flow modeling.While numerous studies have proposed optimal modeling and control strategies for CAVs with various objectives(e.g.,traffic efficiency and safety),there are uncertainties about the flow dynamics of CAVs in real-world traffic.The uncertainties are especially amplified for mixed traffic flows,consisting of CAVs and human-driven vehicles,where the implications can be significant from the continuum-modeling perspective,which aims to capture macroscopic traffic flow dynamics based on hyperbolic systems of partial differential equations.This paper aims to highlight and discuss some essential problems in continuum modeling of real-world freeway traffic flows in the era of CAVs.We first provide a select review of some existing continuum models for conventional human-driven traffic as well as the recent attempts for incorporating CAVs into the continuum-modeling framework.Wherever applicable,we provide new insights about the properties of existing models and revisit their implications for traffic flows of CAVs using recent empirical observations with CAVs and the previous discussions and debates in the literature.The paper then discusses some major problems inherent to continuum modeling of real-world(mixed)CAV traffic flows modeling by distinguishing between two major research directions:(a)modeling for explaining purposes,where making reproducible inferences about the physical aspects of macroscopic properties is of the primary interest,and(b)modeling for practical purposes,in which the focus is on the reliable predictions for operation and control.The paper proposes some potential solutions in each research direction and recommends some future research topics.
基金supported by Singapore Ministry of Education Academic Research Fund(Tier 1 RG79/21).
文摘Platooning has emerged to be one of the most promising applications for connected and automated vehicles(CAVs).However,there is still limited research on the effect of platooning configurations.This study sets out to investigate the effect of CAV platoon configurations at a typical isolated roundabout in a mixed traffic environment.Investigated platoon configurations include maximum platoon size,platoon willingness,and platoon type.Extensive simulation experiments are carried out in simulation of urban mobility(SUMO),considering various traffic conditions,including different penetration rates,traffic flows,and turning percentages.Results show that:(1)increasing the maximum platoon size and platoon willingness generally improves the throughput increment and delay reduction;and(2)heterogeneous platoons outperform homogeneous platoons in all traffic conditions.
基金sponsored by the National Key R&D Program of China(Grant No.2018YFB160220600)MOE(Ministry of Education in China)Project of Humanities,National Natural Science Foundation of China(Grant No.52202408)Social Sciences23(Project No.20YJAZH083).
文摘Potential field theory,as a theory that can also be applied to vehicle control,is an emerging risk quantification approach to accommodate the connected and self-driving vehicle environment.Vehicles have different risk impact effects on other road participants in each direction under the influence of road rules.This variability exhibited by vehicles in each direction is not considered in the previous potential field model.Therefore,this paper proposed a potential field model that takes the anisotropy of vehicle impact into account:(1)introducing equivalent distances to separate the potential field area in the different directions before and after the vehicle;(2)introducing co-virtual forces to characterize the effect of the side-by-side travel phenomenon on vehicle car-following travel;(3)introducing target forces and lane resistance,which regress the control of desired speed to control the acceptable risk of drivers.The Next Generation Simulation(NGSIM)dataset is used in this study to create the model's initial parameter values based on the artificial swarm algorithm.The simulation findings indicate that when the vehicle is given the capacity to perceive the surrounding traffic environment,the suggested the anisotropic safety potential field model(ASPFM)performs better in terms of driving safety.
基金supported in by National Natural Science Foundation of China (No.61903046)Key Research and Development Program of Shaanxi Province (No.2021GY-290)+2 种基金Youth Talent Lift Project of Shaanxi Association for Science and Technology (No.20200106)Joint Laboratory for Internet of Vehicles,Ministry of Education-China Mobile Communications Corporation (No.213024170015)Fundamental Research Funds for the Central Universities (No. 300102240106)
文摘Improper handling of vehicle on-ramp merging may hinder traffic flow and contribute to lower fuel economy,while also increasing the risk of collisions.Cooperative control for connected and automated vehicles(CAVs)has the potential to significantly reduce negative environmental impact while also improve driving safety and traffic efficiency.Therefore,in this paper,we focus on the scenario of CAVs on-ramp merging and propose a centralized control method.Merging sequence(MS)allocation and motion planning are two key issues in this process.To deal with these problems,we first propose an MS allocation method based on a complete information static game whereby the mixed-strategy Nash equilibrium is calculated for an individual vehicle to select its strategy.The on-ramp merging problem is then formulated as a bi-objective(total fuel consumption and total travel time)optimization problem,to which optimal control based on Pontryagin's minimum principle(PMP)is applied to solve the motion planning issue.To determine the proper parameters in the bi-objective optimization problem,a varying-scale grid search method is proposed to explore possible solutions at different scales.In this method,an improved quicksort algorithm is designed to search for the Pareto front,and the(approximately)unbiased Pareto solution for the bi-objective optimization problem is finally determined as the optimal solution.The proposed on-ramp merging strategy is validated via numerical simulation,and comparison with other strategies demonstrates its effectiveness in terms of fuel economy and traffic efficiency.
文摘Purpose–This paper aims to review the studies on intersection control with connected and automated vehicles(CAVs).Design/methodology/approach–The most seminal and recent research in this area is reviewed.This study specifically focuses on two categories:CAV trajectory planning and joint intersection and CAV control.Findings–It is found that there is a lack of widely recognized benchmarks in this area,which hinders the validation and demonstration of new studies.Originality/value–In this review,the authors focus on the methodological approaches taken to empower intersection control with CAVs.The authors hope the present review could shed light on the state-of-the-art methods,research gaps and future research directions.
基金SECS Faculty Startup Fund at Oakland University and in party by National Science Foundation through Award#2237317.
文摘Autonomous driving is an active area of research in artificial intelligence and robotics.Recent advances in deep reinforcement learning(DRL)show promise for training autonomous vehicles to handle complex real-world driving tasks.This paper reviews recent advancement on the application of DRL to highway lane change,ramp merge,and platoon coordination.In particular,similarities,differences,limitations,and best practices regarding the DRL formulations,DRL training algorithms,simulations,and metrics are reviewed and discussed.The paper starts by reviewing different traffic scenarios that are discussed by the literature,followed by a thorough review on the DRL technology such as the state representation methods that capture interactive dynamics critical for safe and efficient merging and the reward formulations that manage key metrics like safety,efficiency,comfort,and adaptability.Insights from this review can guide future research toward realizing the potential of DRL for automated driving in complex traffic under uncertainty.
基金supported by in part by the China Automobile Industry Innovation and Development Joint Fund(No.U1864206)in part by the National Nature Science Foundation of China(No.62003244)+1 种基金in part by the Jilin Provincial Science and Technology Department(No.20200301011RQ)in part by the Jilin Provincial Science Foundation of China(No.20200201062JC).
文摘In this paper,we propose a real-time energy-efficient anticipative driving control strategy for connected and automated hybrid electric vehicles(HEVs).Considering the inherent complexities brought about by the velocity profile optimization and energy management control,a hierarchical control architecture in the model predictive control(MPC)framework is developed for real-time implementation.In the higher level controller,a novel velocity optimization problem is proposed to realize safe and energy-efficient anticipative driving.The real-time control actions are derived through a computationally efficient algorithm.In the lower level controller,an explicit solution of the optimal torque split ratio and gear shift schedule is introduced for following the optimal velocity profile obtained from the higher level controller.The comparative simulation results demonstrate that the proposed strategy can achieve approximately 13%fuel consumption saving compared with a benchmark strategy.
