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V2I Based Environment Perception for Autonomous Vehicles at Intersections

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China Communications 2021年第7期18卷 1-12页

作者： xuting duan Hang Jiang Daxin Tian Tianyuan Zou Jianshan Zhou Yue Cao Beijing Advanced Innovation Center for Big Data and Brain Computing Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems&Safety ControlSchool of Transportation Science and EngineeringBeihang UniversityBeijing 100191China School of Cyber Science and Engineering Wuhan UniversityWuhan 430072China

In recent years,autonomous driving technology has made good progress,but the noncooperative intelligence of vehicle for autonomous driving still has many technical bottlenecks when facing urban road autonomous driving challenges.V2I(Vehicle-to-Infrastructure)communication is a potential solution to enable cooperative intelligence of vehicles and *** this paper,the RGB-PVRCNN,an environment perception framework,is proposed to improve the environmental awareness of autonomous vehicles at intersections by leveraging V2I communication *** framework integrates vision feature based on *** normal distributions transform(NDT)point cloud registration algorithm is deployed both on onboard and roadside to obtain the position of the autonomous vehicles and to build the local map objects detected by roadside multi-sensor system are sent back to autonomous vehicles to enhance the perception ability of autonomous vehicles for benefiting path planning and traffic efficiency at the *** field-testing results show that our method can effectively extend the environmental perception ability and range of autonomous vehicles at the intersection and outperform the PointPillar algorithm and the VoxelRCNN algorithm in detection accuracy.

关键词： V2I environmental perception autonomous vehicles 3D objects detection

Cooperative Channel Assignment for VANETs Based on Dual Reinforcement Learning

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Computers, Materials & Continua 2021年第2期66卷 2127-2140页

作者： xuting duan Yuanhao Zhao Kunxian Zheng Daxin Tian Jianshan Zhou Jian Gao Beijing Advanced Innovation Center for Big Data and Brain Computing Beijing100191China School of Transportation Science and Engineering Beihang UniversityBeijing100191China Department of Engineering and Design University of SussexBrightonBN19RHUK Research Institute of Highway Ministry of Transport Beijing100088China

Dynamic channel assignment(DCA)is significant for extending vehicular ad hoc network(VANET)capacity and mitigating ***,the un-known global state information and the lack of centralized control make channel assignment performances a challenging task in a distributed vehicular direct communication *** our preliminary field test for communication under V2X scenario,we find that the existing DCA technology cannot fully meet the communication performance requirements of *** order to improve the communication performance,we firstly demonstrate the feasibility and potential of reinforcement learning(RL)method in joint channel selection decision and access fallback adaptation design in this ***,a dual reinforcement learning(DRL)-based cooperative DCA(DRL-CDCA)mechanism is ***,DRL-CDCA jointly optimizes the decision-making behaviors of both the channel selection and back-off adaptation based on a multi-agent dual reinforcement learning ***,nodes locally share and incorporate their individual rewards after each communication to achieve regional consistency *** results show that the proposed DRL-CDCA can better reduce the one-hop packet delay,improve the packet delivery ratio on average when compared with two other existing mechanisms.

关键词： Vehicular ad hoc networks reinforcement learning dynamic channel assignment

Adaptive Handover Decision Inspired By Biological Mechanism in Vehicle Ad-hoc Networks

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Computers, Materials & Continua 2019年第9期61卷 1117-1128页

作者： xuting duan Jingyi Wei Daxin Tian Jianshan Zhou Haiying Xia Xin Li Kunxian Zheng Beijing Advanced Innovation Center for Big Data and Brain Computing Beijing100191China Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems&SafetyControl Beijing100191China School of Transportation Science and Engineering Beihang UniversityBeijing100191China Department of Engineering and Design University of SussexBrightonBN19RHUK Research Institute of Highway Ministry Transport Beijing100088China Department of Computer Science and Technology Tsinghua UniversityHaidian DistrictBeijing100088China

In vehicle ad-hoc networks(VANETs),the proliferation of wireless communication will give rise to the heterogeneous access environment where network selection becomes *** by the self-adaptive paradigm of cellular attractors,this paper regards an individual communication as a cell,so that we can apply the revised attractor selection model to induce each connected *** at improving the Quality of Service(QoS),we presented the bio-inspired handover decision-making *** addition,we employ the Technique for Order Preference by Similarity to an Ideal Solution(TOPSIS)for any vehicle to choose an access *** paper proposes a novel framework where the bio-inspired mechanism is combined with *** a dynamic and random mobility environment,our method achieves the coordination of performance of heterogeneous networks by guaranteeing the efficient utilization and fair distribution of network resources in a global *** experimental results confirm that the proposed method performs better when compared with conventional schemes.

关键词： Revised attraction selection model TOPSIS VANETs QoS

Applications of intelligent computing in vehicular networks

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Journal of Intelligent and Connected Vehicles 2018年第2期1卷 66-76页

作者： Daxin Tian Weiqiang Gong Wenhao Liu xuting duan Yukai Zhu Chao Liu Xin Li Beihang University BeijingChina Nanjing LES Information Technology Co. LtdNanjingChina Department of Computer Science and Technology Tsinghua UniversityBeijingChina

Purpose–This paper aims to introduce vehicular network platform,routing and broadcasting methods and vehicular positioning enhancement technology,which are three aspects of the applications of intelligent computing in vehicular *** this paper,the role of intelligent algorithm in theﬁeld of transportation and the vehicular networks can be ***/methodology/approach–In this paper,the authors introduce three different methods in three layers of vehicle networking,which are data cleaning based on machine learning,routing algorithm based on epidemic model and cooperative localization algorithm based on the connect ***–In Section 2,a novel classiﬁcation-based framework is proposed to efﬁciently assess the data quality and screen out the abnormal vehicles in *** Section 3,the authors canﬁnd when trafﬁc conditions varied from freeﬂow to congestion,the number of message copies increased dramatically and the reachability also *** error of vehicle positioning is reduced by 35.39%based on the CV-IMM-EKF in Section ***,it can be concluded that the intelligent computing in the vehicle network system is effective,and it will improve the development of the car networking ***/value–This paper reviews the research of intelligent algorithms in three related areas of vehicle *** theﬁeld of vehicle networking,these research results are conducive to promoting data processing and algorithm optimization,and it may lay the foundation for the new methods.

关键词： Intelligent computing Vehicular ad hoc networks

Pre-training with asynchronous supervised learning for reinforcement learning based autonomous driving

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Frontiers of Information Technology & Electronic Engineering 2021年第5期22卷 673-686页

作者： Yunpeng WANG Kunxian ZHENG Daxin TIAN xuting duan Jianshan ZHOU Beijing Advanced.Innovation Center for Big Data and Brain Computing School of Transportation Science and EngineeringBeihang UniversityBeijing 100191China

Rule-based autonomous driving systems may suffer from increased complexity with large-scale intercoupled rules,so many researchers are exploring learning-based *** learning(RL)has been applied in designing autonomous driving systems because of its outstanding performance on a wide variety of sequential control ***,poor initial performance is a major challenge to the practical implementation of an RL-based autonomous driving *** training requires extensive training data before the model achieves reasonable performance,making an RL-based model inapplicable in a real-world setting,particularly when data are *** propose an asynchronous supervised learning(ASL)method for the RL-based end-to-end autonomous driving model to address the problem of poor initial performance before training this RL-based model in real-world ***,prior knowledge is introduced in the ASL pre-training stage by asynchronously executing multiple supervised learning processes in parallel,on multiple driving demonstration data *** pre-training,the model is deployed on a real vehicle to be further trained by RL to adapt to the real environment and continuously break the performance *** presented pre-training method is evaluated on the race car simulator,TORCS(The Open Racing Car Simulator),to verify that it can be sufficiently reliable in improving the initial performance and convergence speed of an end-to-end autonomous driving model in the RL training *** addition,a real-vehicle verification system is built to verify the feasibility of the proposed pre-training method in a real-vehicle *** results show that using some demonstrations during a supervised pre-training stage allows significant improvements in initial performance and convergence speed in the RL training stage.

关键词： Self-driving Autonomous vehicles Reinforcement learning Supervised learning

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基于V2X通信网络的车辆协同定位增强方法

汽车工程 2018年第8期40卷 947-951,959页

作者：段续庭田大新王云鹏北京航空航天大学交通科学与工程学院车路协同与安全控制北京市重点实验室北京100191

鉴于车辆位置精度对车联网应用的重要性和传统的卫星定位系统在城市"高楼峡谷"或隧道等弱卫星信号覆盖区域失效或定位精度不足等问题,本文中研究了基于V2X通信网络的车辆定位方法,研发了专用短程通信和多模式通信网络定位终端,完成了终... 详细信息

鉴于车辆位置精度对车联网应用的重要性和传统的卫星定位系统在城市"高楼峡谷"或隧道等弱卫星信号覆盖区域失效或定位精度不足等问题,本文中研究了基于V2X通信网络的车辆定位方法,研发了专用短程通信和多模式通信网络定位终端,完成了终端的性能测试和应用部署,设计了基于多模型滤波算法的车辆协作定位增强方法。结果显示,与传统GPS定位相比,本文方法能提升定位精度近40%。

关键词：车联网协同定位增强车辆自组织网络

基于链路质量评估的飞行自组网抗干扰多路径路由协议

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无人系统技术 2022年第2期5卷 80-92页

作者：张傲段续庭田大新北京航空航天大学交通科学与工程学院北京102206

随着通信网络不断向各领域延伸,飞行自组网作为一种新型移动自组织网络,以飞行器作为空中无线通信节点建立网络,实现网络层高效通信。首先,通过考虑链路质量、流量负载和空间距离构建多路径路由模型,并设计抗干扰的多路径路由算法;其次... 详细信息

随着通信网络不断向各领域延伸,飞行自组网作为一种新型移动自组织网络,以飞行器作为空中无线通信节点建立网络,实现网络层高效通信。首先,通过考虑链路质量、流量负载和空间距离构建多路径路由模型,并设计抗干扰的多路径路由算法;其次,构建基于源节点路由回复包接收速率的解析模型;然后,对模型进行分析与评价;最后,通过仿真实验验证所提出路由协议的效能。仿真结果表明,所提出的协议与传统协议相比,当节点数相同时,数据包传递率可提升约4.04%~12.13%;干扰器数量为6时,数据包传输延迟可提升约38.48%~52.53%,并且端到端通信中断率降低约34.54%~41.67%,在各项性能指标中都具备优势。所提出的抗干扰多路径路由协议可以为飞行器提供有效且可靠的通信数据传输,并在存在恶意干扰的情况下为飞行自组网提供网络弹性保证。未来将考虑更复杂的链路情况,使其具有更大的实际应用价值。

关键词：飞行自组网路由协议恶意干扰多路径路由链路质量流量负载

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民用机场飞行区风险因素及耦合关系分析

指挥信息系统与技术 2024年第5期15卷 44-52页

作者：张欣葛昊段续庭赵一翰北京航空航天大学交通科学与工程学院北京100191 中国电子科技集团公司第二十八研究所南京210023

为提高民用机场安全管理水平,需对机场飞行区安全风险因素及其耦合关系进行分析。将民用机场飞行区风险因素分为人员因素、设施设备因素和环境因素,并根据风险因素的数量和种类,将耦合风险划分为单因素耦合风险、双因素耦合风险和多因... 详细信息

为提高民用机场安全管理水平,需对机场飞行区安全风险因素及其耦合关系进行分析。将民用机场飞行区风险因素分为人员因素、设施设备因素和环境因素,并根据风险因素的数量和种类,将耦合风险划分为单因素耦合风险、双因素耦合风险和多因素耦合风险。基于系统动力学模型定性分析了同质和异质风险因素间的相互关系,建立了风险耦合模型。采用蒙特卡洛模拟方法对风险因素进行了定量分析,生成了风险因素关联系数。计算得出的评判风险阈值,可为机场管理部门及时发现风险和解决问题提供依据。

关键词：风险因素耦合关系系统动力学模型蒙特卡洛模拟机场安全管理

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立体交通系统通感算一体化关键技术

移动通信 2024年第3期48卷 14-20页

作者：李晨玮周建山田大新段续庭北京航空航天大学交通科学与工程学院车路协同与安全控制北京市重点实验室车路一体智能交通全国重点实验室北京102206

以无人机、智能网联汽车、道路基础设施等空地平台为载体的立体交通系统是智慧城市综合交通在6G网络中发展的前沿方向。随着海量无线通信终端、智能传感器等物理设备与交通运输环境、载运工具和道路基础设施深度融合,立体交通系统对通... 详细信息

以无人机、智能网联汽车、道路基础设施等空地平台为载体的立体交通系统是智慧城市综合交通在6G网络中发展的前沿方向。随着海量无线通信终端、智能传感器等物理设备与交通运输环境、载运工具和道路基础设施深度融合,立体交通系统对通信感知的需求日益增长;然而,当前系统的发展受网络体系结构、通信资源、计算资源和感知能力的制约,其信息交互与综合处理能力亟待协同提高。另一方面,通信感知与边缘计算一体化(ISACEC)技术发展及其在空地协同网络中应用,为立体交通系统演进提供了新的推动力。面向立体交通系统应用场景,总结了ISAC-EC技术发展与应用现状,然后构建了空对地、地对空通信感知联合优化模型,给出了通信波束和雷达波束联合设计的关键技术思路;最后,针对典型应用场景开展仿真实验,结果展现了通感算一体化关键技术在立体交通系统中的应用潜力和优势,可为系统发展建设提供指导。

关键词：立体交通系统无人机智能网联汽车通信感知与边缘计算一体化凸优化