The traffic rules governing the passage of different types of vehicles at signal-free intersections are distinct,especially for the emergency vehicles.Although these traffic rules can be described through deliberate m...The traffic rules governing the passage of different types of vehicles at signal-free intersections are distinct,especially for the emergency vehicles.Although these traffic rules can be described through deliberate mathematical expressions,but showing limitations in terms of the userfriendliness of rule description.This paper proposes an improved STL-based trajectory planning method for CAVs at signal-free intersections,describing traffic rules with STL formulas,which bridges the gap between human-understandable and machine-understandable traffic rules.The MPC framework is utilised to guarantee real-time trajectory planning by reducing travel time of vehicles passing through the intersection.Simulation results show improved traffic efficiency compared with other methods while ensuring adherence to yielding rules for emergency CAVs.展开更多
Connected and autonomous vehicles(CAVs)are expected to coexist alongside humandriven vehicles on roads for the foreseeable future.This study explores the stability and safety of mixed traffic streams,including traditi...Connected and autonomous vehicles(CAVs)are expected to coexist alongside humandriven vehicles on roads for the foreseeable future.This study explores the stability and safety of mixed traffic streams,including traditional trucks and cars alongside CAVs.The study utilizes the intelligent driver model and cooperative adaptive cruise control model to characterize human-driven vehicles(including cars and trucks)and CAVs,respectively.It investigates how different ratios of trucks and penetration rates of CAVs impact the linear stability of mixed traffic flows and delineate their stability domains.Additionally,a simulation experiment is conducted using SUMO software to assess the safety implications of traffic congestion at on-ramp bottlenecks,specifically analyzing the safety dynamics of mixed traffic streams.The findings indicate that CAVs enhance both the stability and safety of mixed traffic flows.The presence of trucks is associated with reduced stability values at similar CAVs penetration rates.In scenarios without trucks,CAVs can elevate traffic safety by 58.28%-71.28%,whereas in the presence of trucks,although the enhancement diminishes,safety levels can still improve by 48.67%-65.11%.展开更多
To fully utilize the computational resources in the cooperative control environment and achieve global optimization for connected and automated vehicles,a parallel distributed computing framework is presented by a dec...To fully utilize the computational resources in the cooperative control environment and achieve global optimization for connected and automated vehicles,a parallel distributed computing framework is presented by a decomposition strategy.This strategy converts the original centralized optimization problem into a separable form by introducing a set of auxiliary variables and consensus equality constraints to address the coupling components necessary for collision avoidance.Based on the numerical analysis of communication resource consumption in this distributed framework,an information filtering strategy is further designed to enhance communication efficiency by limiting the transmission of consensus variables.Consequently,the global convergence of this parallel algorithm with filtered information is theoretically analyzed under the assumption that the feasible domain is convex.The communication traffic,cooperative control,numerical optimization performance of the proposed framework and parallel algorithm are validated and assessed through several simulation and experimental tests with the intersection scenario.展开更多
Background Hypertension is associated with an increased risk of calcific aortic valve stenosis(CAVS).However,the directionality of causation between blood pressure traits and aortic stenosis is unclear,as is the benef...Background Hypertension is associated with an increased risk of calcific aortic valve stenosis(CAVS).However,the directionality of causation between blood pressure traits and aortic stenosis is unclear,as is the benefit of antihypertensive drugs for CAVS.Methods Using genome-wide association studies(GWAS)summary statistics,we performed bidirectional two-sample univariable mendelian randomization(UVMR)to assess the causal associations of systolic blood pressure(SBP),diastolic blood pressure(DBP),and pulse pressure(PP)with CAVS.Multivariable mendelian randomization(MVMR)was conducted to evaluate the direct effect of hypertension on CAVS,adjusting for confounders.Drug target mendelian randomization(MR)and summary-level MR(SMR)were used to estimate the effects of 12 classes of antihypertensive drugs and their target genes on CAVS risk.Inverse variance weighting was the primary MR method,with sensitivity analyses to validate results.Results UVMR showed SBP,DBP,and PP have causal effects on CAVS,with no significant reverse causality.MVMR confirmed the causality between hypertension and CAVS after adjusting for confounders.Drug-target MR analyses indicated that calcium channel blockers(CCBs),loop diuretics,and thiazide diuretics via SBP lowering exerted protective effects on CAVS risk.SMR analysis showed that the CCBs target gene CACNA2D2 and ARBs target gene AGTR1 were positively associated with CAVS risk,while diuretics target genes SLC12A5 and SLC12A1 were negatively associated with aortic stenosis risk.Conclusions Hypertension has a causal relationship with CAVS.Managing SBP in hypertensive patients with CCBs may prevent CAVS.ARBs might exert protective effects on CAVS independent of blood pressure reduction.The relationship between diuretics and CAVS is complex,with opposite effects through different mechanisms.展开更多
人类驾驶的不可控性使得间歇优先公交专用道(Bus Lanes with Intermittent Priority,BLIP)不能被有效利用。为解决该问题,本文提出智能网联车辆(Connected and Automated Vehicles,CAV)复用BLIP的控制方法。CAV借道控制考虑了公交车间...人类驾驶的不可控性使得间歇优先公交专用道(Bus Lanes with Intermittent Priority,BLIP)不能被有效利用。为解决该问题,本文提出智能网联车辆(Connected and Automated Vehicles,CAV)复用BLIP的控制方法。CAV借道控制考虑了公交车间移动区间的约束,还道控制考虑了与旁道CAV队列的协同,以应对还道安全距离不足的情况。并利用开放边界元胞自动机模型对提出的方法进行仿真。结果表明:同等流量下,CAV复用BLIP可大幅提高道路通行效率,且中等CAV渗透率下最显著,道路平均速度从6.67 km·h^(-1)提高至30.53 km·h^(-1);无论CAV渗透率高低,CAV队列协同换道都比单个CAV协同换道更有助于提高道路通行效率,相较之下将道路平均速度提高8%~19%。展开更多
自动驾驶车辆(Connected and Autonomous Vehicles,CAVs)利用车联万物(Vehicle-to-Everything,V2X)和6G网络数据实现合作感知服务(Cooperative Perception Service,CPS)。在实际交通系统中,会出现多个CAVs同时感知并分享同一对象的情况...自动驾驶车辆(Connected and Autonomous Vehicles,CAVs)利用车联万物(Vehicle-to-Everything,V2X)和6G网络数据实现合作感知服务(Cooperative Perception Service,CPS)。在实际交通系统中,会出现多个CAVs同时感知并分享同一对象的情况,导致在网络中交换了许多不相关的冗余信息,从而增加了额外的通信开销。为了解决这个问题,提出了一种基于信息价值(Value of Information,VoI)的冗余压缩策略。首先,通过数学方法来量化感知信息的价值;接着,当CAV向基站发送上传请求时,信息价值汇总到基站;然后,将CPS的满意度表示为基站控制下的一个最大化问题,并通过模拟退火(Simulated Annealing,SA)算法进行求解。该策略允许基站最优地控制CAV上传的信息,最大限度地提高CAV协作感知的效用,并最小化V2X网络中的冗余。仿真结果表明,与现有策略相比,该策略能有效降低目标冗余,使平均减少22.3%的传输延迟,使CPS质量提高21.6%。展开更多
为提升高速公路通行效率,优化网联自动驾驶车辆(connected and autonomous vehicle,CAV)专用道设置条件下的交织区时空资源配置,以保证CAV高效安全汇入主线专用道,提出了一种基于深度强化学习的交织区集成控制策略。以主线三车道高速公...为提升高速公路通行效率,优化网联自动驾驶车辆(connected and autonomous vehicle,CAV)专用道设置条件下的交织区时空资源配置,以保证CAV高效安全汇入主线专用道,提出了一种基于深度强化学习的交织区集成控制策略。以主线三车道高速公路为研究对象,并设置内侧车道为CAV专用道,设计了充分考虑CAV专用道汇入需求同时兼顾主线通行效率和匝道排队长度的多目标奖励函数,利用深度确定性策略梯度(deep deterministic policy gradient,DDPG)算法实现包括入口匝道信号控制、主线车道级可变限速以及CAV车队间隙调整的集成控制策略,最后使用SUMO和Python搭建高速公路交织区仿真场景,验证所提集成控制策略的有效性。研究结果表明:CAV渗透率为30%时,在低、中、高不同水平交通需求场景下,对比无控制情况集成控制策略可使CAV汇入专用道的纵向位置有所提前,CAV汇入专用道成功率分别增加了19.34%、22.86%、25.55%;此外,车辆平均行程时间也分别降低了5.42%、17.41%、20.65%。所提出的交织区集成控制策略效果显著,不仅实现了CAV汇入专用道的有效引导,还提升了主线的通行效率及运行安全,为改善CAV专用道设置条件下高速公路交织区交通运行状况提供了理论依据和技术参考。展开更多
随着信息通信技术的发展,自动驾驶车辆(Autonomous Vehicle,AV)和网联自动驾驶车辆(Connected and Autonomous Vehicle,CAV)的出现为解决道路拥堵,提高交通安全性和效率提供了新途径。为全面综述CAV专用车道的设置方法,本文首先介绍CAV...随着信息通信技术的发展,自动驾驶车辆(Autonomous Vehicle,AV)和网联自动驾驶车辆(Connected and Autonomous Vehicle,CAV)的出现为解决道路拥堵,提高交通安全性和效率提供了新途径。为全面综述CAV专用车道的设置方法,本文首先介绍CAV专用车道的演变过程,阐述CAV专用车道设置的背景与意义;接着,基于相关文献详细介绍道路通行能力计算方法的研究,为预测设置CAV专用车道对交通运行的影响,评估并调整设置策略提供依据;然后,深入分析CAV专用车道的设置策略,包括基于CAV渗透率和交通需求等的设置条件,在不同因素下的车道设置数量和位置以及车道接入方式和分隔方式;最后,建议未来研究应重点关注设置CAV专用车道后各影响因素的变化与实际交通状况,制定CAV专用车道的具体标准,使CAV专用车道根据不同交通场景发挥其功能与作用。展开更多
With the development of fast communication technology between ego vehicle and other traffic participants,and automated driving technology,there is a big potential in the improvement of energy efficiency of hybrid elec...With the development of fast communication technology between ego vehicle and other traffic participants,and automated driving technology,there is a big potential in the improvement of energy efficiency of hybrid electric vehicles(HEVs).Moreover,the terrain along the driving route is a non-ignorable factor for energy efficiency of HEV running on the hilly streets.This paper proposes a look-ahead horizon-based optimal energy management strategy to jointly improve the efficiencies of powertrain and vehicle for connected and automated HEVs on the road with slope.Firstly,a rule-based framework is developed to guarantee the success of automated driving in the traffic scenario.Then a constrained optimal control problem is formulated to minimize the fuel consumption and the electricity consumption under the satisfaction of inter-vehicular distance constraint between ego vehicle and preceding vehicle.Both speed planning and torque split of hybrid powertrain are provided by the proposed approach.Moreover,the preceding vehicle speed in the look-ahead horizon is predicted by extreme learning machine with real-time data obtained from communication of vehicle-to-everything.The optimal solution is derived through the Pontryagin’s maximum principle.Finally,to verify the effectiveness of the proposed algorithm,a traffic-in-the-loop powertrain platform with data from real world traffic environment is built.It is found that the fuel economy for the proposed energy management strategy improves in average 17.0%in scenarios of different traffic densities,compared to the energy management strategy without prediction of preceding vehicle speed.展开更多
基金supported in part by the National Science Foundation of China(Grant No.62333015),the Science Foundation of Shanghai(Grant No.24ZR1438800).
文摘The traffic rules governing the passage of different types of vehicles at signal-free intersections are distinct,especially for the emergency vehicles.Although these traffic rules can be described through deliberate mathematical expressions,but showing limitations in terms of the userfriendliness of rule description.This paper proposes an improved STL-based trajectory planning method for CAVs at signal-free intersections,describing traffic rules with STL formulas,which bridges the gap between human-understandable and machine-understandable traffic rules.The MPC framework is utilised to guarantee real-time trajectory planning by reducing travel time of vehicles passing through the intersection.Simulation results show improved traffic efficiency compared with other methods while ensuring adherence to yielding rules for emergency CAVs.
基金Supported by the National Social Science Foundation of China(22BGL007)。
文摘Connected and autonomous vehicles(CAVs)are expected to coexist alongside humandriven vehicles on roads for the foreseeable future.This study explores the stability and safety of mixed traffic streams,including traditional trucks and cars alongside CAVs.The study utilizes the intelligent driver model and cooperative adaptive cruise control model to characterize human-driven vehicles(including cars and trucks)and CAVs,respectively.It investigates how different ratios of trucks and penetration rates of CAVs impact the linear stability of mixed traffic flows and delineate their stability domains.Additionally,a simulation experiment is conducted using SUMO software to assess the safety implications of traffic congestion at on-ramp bottlenecks,specifically analyzing the safety dynamics of mixed traffic streams.The findings indicate that CAVs enhance both the stability and safety of mixed traffic flows.The presence of trucks is associated with reduced stability values at similar CAVs penetration rates.In scenarios without trucks,CAVs can elevate traffic safety by 58.28%-71.28%,whereas in the presence of trucks,although the enhancement diminishes,safety levels can still improve by 48.67%-65.11%.
基金supported by Advanced Power Transmission System Fundamental Theory and Technology(Grant No.T2421001)Science and Technology Innovation Key R&D Program of Chongqing(Grant No.CSTB2023TIAD-STX0028 and CSTB2023TIAD-STX0029).
文摘To fully utilize the computational resources in the cooperative control environment and achieve global optimization for connected and automated vehicles,a parallel distributed computing framework is presented by a decomposition strategy.This strategy converts the original centralized optimization problem into a separable form by introducing a set of auxiliary variables and consensus equality constraints to address the coupling components necessary for collision avoidance.Based on the numerical analysis of communication resource consumption in this distributed framework,an information filtering strategy is further designed to enhance communication efficiency by limiting the transmission of consensus variables.Consequently,the global convergence of this parallel algorithm with filtered information is theoretically analyzed under the assumption that the feasible domain is convex.The communication traffic,cooperative control,numerical optimization performance of the proposed framework and parallel algorithm are validated and assessed through several simulation and experimental tests with the intersection scenario.
基金supported by the National Natural Science Foundation of China(82170375,U23A20395)1.3.5 project for disciplines of excellence from West China Hospital of Sichuan University(ZYGD23021,23HXF-H009)Sichuan Science and Technology Program 2023NSFSC1645。
文摘Background Hypertension is associated with an increased risk of calcific aortic valve stenosis(CAVS).However,the directionality of causation between blood pressure traits and aortic stenosis is unclear,as is the benefit of antihypertensive drugs for CAVS.Methods Using genome-wide association studies(GWAS)summary statistics,we performed bidirectional two-sample univariable mendelian randomization(UVMR)to assess the causal associations of systolic blood pressure(SBP),diastolic blood pressure(DBP),and pulse pressure(PP)with CAVS.Multivariable mendelian randomization(MVMR)was conducted to evaluate the direct effect of hypertension on CAVS,adjusting for confounders.Drug target mendelian randomization(MR)and summary-level MR(SMR)were used to estimate the effects of 12 classes of antihypertensive drugs and their target genes on CAVS risk.Inverse variance weighting was the primary MR method,with sensitivity analyses to validate results.Results UVMR showed SBP,DBP,and PP have causal effects on CAVS,with no significant reverse causality.MVMR confirmed the causality between hypertension and CAVS after adjusting for confounders.Drug-target MR analyses indicated that calcium channel blockers(CCBs),loop diuretics,and thiazide diuretics via SBP lowering exerted protective effects on CAVS risk.SMR analysis showed that the CCBs target gene CACNA2D2 and ARBs target gene AGTR1 were positively associated with CAVS risk,while diuretics target genes SLC12A5 and SLC12A1 were negatively associated with aortic stenosis risk.Conclusions Hypertension has a causal relationship with CAVS.Managing SBP in hypertensive patients with CCBs may prevent CAVS.ARBs might exert protective effects on CAVS independent of blood pressure reduction.The relationship between diuretics and CAVS is complex,with opposite effects through different mechanisms.
文摘人类驾驶的不可控性使得间歇优先公交专用道(Bus Lanes with Intermittent Priority,BLIP)不能被有效利用。为解决该问题,本文提出智能网联车辆(Connected and Automated Vehicles,CAV)复用BLIP的控制方法。CAV借道控制考虑了公交车间移动区间的约束,还道控制考虑了与旁道CAV队列的协同,以应对还道安全距离不足的情况。并利用开放边界元胞自动机模型对提出的方法进行仿真。结果表明:同等流量下,CAV复用BLIP可大幅提高道路通行效率,且中等CAV渗透率下最显著,道路平均速度从6.67 km·h^(-1)提高至30.53 km·h^(-1);无论CAV渗透率高低,CAV队列协同换道都比单个CAV协同换道更有助于提高道路通行效率,相较之下将道路平均速度提高8%~19%。
文摘自动驾驶车辆(Connected and Autonomous Vehicles,CAVs)利用车联万物(Vehicle-to-Everything,V2X)和6G网络数据实现合作感知服务(Cooperative Perception Service,CPS)。在实际交通系统中,会出现多个CAVs同时感知并分享同一对象的情况,导致在网络中交换了许多不相关的冗余信息,从而增加了额外的通信开销。为了解决这个问题,提出了一种基于信息价值(Value of Information,VoI)的冗余压缩策略。首先,通过数学方法来量化感知信息的价值;接着,当CAV向基站发送上传请求时,信息价值汇总到基站;然后,将CPS的满意度表示为基站控制下的一个最大化问题,并通过模拟退火(Simulated Annealing,SA)算法进行求解。该策略允许基站最优地控制CAV上传的信息,最大限度地提高CAV协作感知的效用,并最小化V2X网络中的冗余。仿真结果表明,与现有策略相比,该策略能有效降低目标冗余,使平均减少22.3%的传输延迟,使CPS质量提高21.6%。
文摘随着信息通信技术的发展,自动驾驶车辆(Autonomous Vehicle,AV)和网联自动驾驶车辆(Connected and Autonomous Vehicle,CAV)的出现为解决道路拥堵,提高交通安全性和效率提供了新途径。为全面综述CAV专用车道的设置方法,本文首先介绍CAV专用车道的演变过程,阐述CAV专用车道设置的背景与意义;接着,基于相关文献详细介绍道路通行能力计算方法的研究,为预测设置CAV专用车道对交通运行的影响,评估并调整设置策略提供依据;然后,深入分析CAV专用车道的设置策略,包括基于CAV渗透率和交通需求等的设置条件,在不同因素下的车道设置数量和位置以及车道接入方式和分隔方式;最后,建议未来研究应重点关注设置CAV专用车道后各影响因素的变化与实际交通状况,制定CAV专用车道的具体标准,使CAV专用车道根据不同交通场景发挥其功能与作用。
文摘With the development of fast communication technology between ego vehicle and other traffic participants,and automated driving technology,there is a big potential in the improvement of energy efficiency of hybrid electric vehicles(HEVs).Moreover,the terrain along the driving route is a non-ignorable factor for energy efficiency of HEV running on the hilly streets.This paper proposes a look-ahead horizon-based optimal energy management strategy to jointly improve the efficiencies of powertrain and vehicle for connected and automated HEVs on the road with slope.Firstly,a rule-based framework is developed to guarantee the success of automated driving in the traffic scenario.Then a constrained optimal control problem is formulated to minimize the fuel consumption and the electricity consumption under the satisfaction of inter-vehicular distance constraint between ego vehicle and preceding vehicle.Both speed planning and torque split of hybrid powertrain are provided by the proposed approach.Moreover,the preceding vehicle speed in the look-ahead horizon is predicted by extreme learning machine with real-time data obtained from communication of vehicle-to-everything.The optimal solution is derived through the Pontryagin’s maximum principle.Finally,to verify the effectiveness of the proposed algorithm,a traffic-in-the-loop powertrain platform with data from real world traffic environment is built.It is found that the fuel economy for the proposed energy management strategy improves in average 17.0%in scenarios of different traffic densities,compared to the energy management strategy without prediction of preceding vehicle speed.
