V2X communication enables vehicles to share real-time traffic and road-condition data,but binding messages to persistent identifiers enables location tracking.Furthermore,since forged reports from malicious vehicles c...V2X communication enables vehicles to share real-time traffic and road-condition data,but binding messages to persistent identifiers enables location tracking.Furthermore,since forged reports from malicious vehicles can distort trust decisions and threaten road safety,privacy-preserving trust management is essential.Lu et al.previously presented BARS,an anonymous reputation mechanism founded on blockchain technology to establish a privacy-preserving trust architecture for V2X communication.In this system,reputation certificates without a vehicle identifier ensure anonymity,while two authorities jointly manage certificate issuance and reputation updates.However,the centralized certificate updates introduce scalability limitations,and the authorities can trace vehicle behavioral information,which threatens privacy guarantees.Several subsequent systems derived from BARS still rely on centralized certificate management and are subject to authority-side privacy leakage.As a result,a key challenge in this line of research remains unresolved:how to decentralize the certificate-update process while preserving privacy against the authorities in privacy-preservingV2X trustmanagement.In this paper,we propose a distributed anonymous reputation system for V2X communication,based on an anonymous reputation system for crowdsensing.In our proposed system for V2X communication,the server is distributed to a certificate authority(CA)and roadside units(RSUs).Each vehicle shows the reputation level to the nearest RSU at the beginning of each time interval,and registers a short-time public key.In the interval,the messages from the vehicle are authenticated under the public key and are scored.At the end of the interval,the nearest RSU updates the certificate anonymously.Our solution decentralizes the certificate-update process by assigning each update to the nearest RSU.A zero-knowledge-proof-based show protocol removes the need for any central authority to handle vehicle certificates and thus prevents the authorities from tracing vehicle activities.Compared with BARS,where centralized authorities must update the reputation certificates of many vehicles and may incur communication and processing delays,our system performs each update locally at the nearest RSUonce per interval.The required interaction consists only of a fewkilobytes of communication and a zero-knowledge proof that is almost fully precomputed on the vehicle side,while the RSU-side processing is estimated to take about 40 ms based on timingmeasurements of the underlying cryptographic operations.This distributed updatemodel avoids the centralized bottleneck of BARS and simultaneously removes the privacy risk arising from authority collusion.展开更多
精确的环境感知是实现自主代客泊车(automated valet parking,AVP)功能的基础,传统的AVP系统主要依赖于单车的感知,但随着场端智能技术的不断发展,车端与场端之间协同交互成为自主代客泊车落地的必然趋势。本文提出了一种基于V2X车场协...精确的环境感知是实现自主代客泊车(automated valet parking,AVP)功能的基础,传统的AVP系统主要依赖于单车的感知,但随着场端智能技术的不断发展,车端与场端之间协同交互成为自主代客泊车落地的必然趋势。本文提出了一种基于V2X车场协同的地下停车场全域感知方法,该方法将地下停车场的全域感知问题转化为大规模图模型的构建与优化问题。通过输入场端激光雷达、摄像头的传感器信息以及智能网联车的感知数据,以车辆位姿为节点,建立多种边约束关系。为了提高感知精度,本文提出了一种融合车道级地图信息的大规模图模型方法,通过将停放车辆作为半静态信息约束,并结合车道级地图信息构建横向约束,在求解过程中引入滑动窗口以减小图模型的规模,最终以地图形式输出感知结果供车端使用。通过仿真实验和在占地面积为2 500 m^(2)以上的地下停车场场景中进行实地实验,结果表明,该方法显著提升了在复杂停车场环境下的感知能力,实现了地下停车场的全域感知。展开更多
为了提高远程驾驶过程中道路信息的获取量进而提高远程驾驶的安全性,提出基于车用无线通信技术(Vehicle to X,V2X)、边缘计算技术和云平台组合而成的“云-边-V2X”技术架构用于智能公交车远程驾驶,即驾驶员在模拟驾驶舱由5G网络实现人...为了提高远程驾驶过程中道路信息的获取量进而提高远程驾驶的安全性,提出基于车用无线通信技术(Vehicle to X,V2X)、边缘计算技术和云平台组合而成的“云-边-V2X”技术架构用于智能公交车远程驾驶,即驾驶员在模拟驾驶舱由5G网络实现人车交互,靠常规摄像头、激光雷达和超声波等传感器捕获道路传感信息的同时,通过“云-边-V2X”架构实时获取道路事件状况提示为远程驾驶提供安全保障,并在此基础上搭建模拟驾驶舱对远端道路上的车辆进行操作控制。已有研究结果表明,论文提出的方法在不影响原有远程驾驶功能的前提下,加入道路事件信息提高远程驾驶安全冗余且远程驾驶系统的性能不受影响。展开更多
文摘V2X communication enables vehicles to share real-time traffic and road-condition data,but binding messages to persistent identifiers enables location tracking.Furthermore,since forged reports from malicious vehicles can distort trust decisions and threaten road safety,privacy-preserving trust management is essential.Lu et al.previously presented BARS,an anonymous reputation mechanism founded on blockchain technology to establish a privacy-preserving trust architecture for V2X communication.In this system,reputation certificates without a vehicle identifier ensure anonymity,while two authorities jointly manage certificate issuance and reputation updates.However,the centralized certificate updates introduce scalability limitations,and the authorities can trace vehicle behavioral information,which threatens privacy guarantees.Several subsequent systems derived from BARS still rely on centralized certificate management and are subject to authority-side privacy leakage.As a result,a key challenge in this line of research remains unresolved:how to decentralize the certificate-update process while preserving privacy against the authorities in privacy-preservingV2X trustmanagement.In this paper,we propose a distributed anonymous reputation system for V2X communication,based on an anonymous reputation system for crowdsensing.In our proposed system for V2X communication,the server is distributed to a certificate authority(CA)and roadside units(RSUs).Each vehicle shows the reputation level to the nearest RSU at the beginning of each time interval,and registers a short-time public key.In the interval,the messages from the vehicle are authenticated under the public key and are scored.At the end of the interval,the nearest RSU updates the certificate anonymously.Our solution decentralizes the certificate-update process by assigning each update to the nearest RSU.A zero-knowledge-proof-based show protocol removes the need for any central authority to handle vehicle certificates and thus prevents the authorities from tracing vehicle activities.Compared with BARS,where centralized authorities must update the reputation certificates of many vehicles and may incur communication and processing delays,our system performs each update locally at the nearest RSUonce per interval.The required interaction consists only of a fewkilobytes of communication and a zero-knowledge proof that is almost fully precomputed on the vehicle side,while the RSU-side processing is estimated to take about 40 ms based on timingmeasurements of the underlying cryptographic operations.This distributed updatemodel avoids the centralized bottleneck of BARS and simultaneously removes the privacy risk arising from authority collusion.
文摘精确的环境感知是实现自主代客泊车(automated valet parking,AVP)功能的基础,传统的AVP系统主要依赖于单车的感知,但随着场端智能技术的不断发展,车端与场端之间协同交互成为自主代客泊车落地的必然趋势。本文提出了一种基于V2X车场协同的地下停车场全域感知方法,该方法将地下停车场的全域感知问题转化为大规模图模型的构建与优化问题。通过输入场端激光雷达、摄像头的传感器信息以及智能网联车的感知数据,以车辆位姿为节点,建立多种边约束关系。为了提高感知精度,本文提出了一种融合车道级地图信息的大规模图模型方法,通过将停放车辆作为半静态信息约束,并结合车道级地图信息构建横向约束,在求解过程中引入滑动窗口以减小图模型的规模,最终以地图形式输出感知结果供车端使用。通过仿真实验和在占地面积为2 500 m^(2)以上的地下停车场场景中进行实地实验,结果表明,该方法显著提升了在复杂停车场环境下的感知能力,实现了地下停车场的全域感知。
文摘为了提高远程驾驶过程中道路信息的获取量进而提高远程驾驶的安全性,提出基于车用无线通信技术(Vehicle to X,V2X)、边缘计算技术和云平台组合而成的“云-边-V2X”技术架构用于智能公交车远程驾驶,即驾驶员在模拟驾驶舱由5G网络实现人车交互,靠常规摄像头、激光雷达和超声波等传感器捕获道路传感信息的同时,通过“云-边-V2X”架构实时获取道路事件状况提示为远程驾驶提供安全保障,并在此基础上搭建模拟驾驶舱对远端道路上的车辆进行操作控制。已有研究结果表明,论文提出的方法在不影响原有远程驾驶功能的前提下,加入道路事件信息提高远程驾驶安全冗余且远程驾驶系统的性能不受影响。
