• <tr id="yyy80"></tr>
  • <sup id="yyy80"></sup>
  • <tfoot id="yyy80"><noscript id="yyy80"></noscript></tfoot>
  • 99热精品在线国产_美女午夜性视频免费_国产精品国产高清国产av_av欧美777_自拍偷自拍亚洲精品老妇_亚洲熟女精品中文字幕_www日本黄色视频网_国产精品野战在线观看 ?

    Key Challenges and Chinese Solutions for SOTIF in Intelligent Connected Vehicles

    2023-03-22 08:04:44JunLiWenboShaoHongWang
    Engineering 2023年12期

    Jun Li, Wenbo Shao, Hong Wang

    Tsinghua Intelligent Vehicle Design and Safety Research Institute, School of Vehicle and Mobility, Tsinghua University, Beijing 100084, China

    Intelligent connected vehicles (ICVs) [1] represent a crucial strategic focus for global automobile industrial transformation and advancement.ICVs also play a significant role in enhancing driving safety, improving traffic efficiency, and enabling lowcarbon transportation.Consequently, numerous countries worldwide are expediting their efforts to establish a strong foundation for ICVs, progressing from technology research, development, and testing to widespread application and commercialization.This global momentum has resulted in a thriving ICV industry, demonstrating substantial growth and encouraging prospects.

    In developing ICVs,one of the original intentions was to reduce traffic accidents caused by human error,which account for approximately 94% of total accidents.In recent years, an increasing focus on ICV safety by governments, enterprises, and academia has emerged resulting in the implementation of various policies,regulations,technical products,and research findings.However,significant challenges remain for ICV safety, particularly regarding functional safety (FuSa), cybersecurity, and safety of the intended function(SOTIF)issues.FuSa has been addressed to a certain extent through the application of mature standards and regulations,while cybersecurity is being reinforced by government legislation.However, as ICV systems increase in complexity and intelligence, with more dynamic and challenging operating environments, the SOTIF problem arising from functional insufficiencies of the intended functionality or its implementation has emerged as one of the most critical obstacles in ICV research and commercialization.Since 2016,some ICV-related traffic accidents have been reported worldwide, as illustrated in Table 1.The main causes of these accidents include insufficient perception, prediction, decision-making functions, and reasonably foreseeable misuse, all of which are categorized as typical SOTIF problems [2].Furthermore, as shown in Fig.1 [3], over 90% of intelligent driving system disengagements are attributable to SOTIF-related software issues.The SOTIF problem has become a pressing concern in ICV development, necessitating effective SOTIF solution proposals to ensure smooth industrialization progress.

    1.Key challenges for SOTIF in ICVs

    ICV can be classified as a multidisciplinary subject area that encompasses various traditional and emerging research fields,including mechanics, communication, electronics, computer science, and artificial intelligence (AI).Consequently, addressing SOTIF problems in ICVs necessitates collaborative efforts from stakeholders spanning multiple domains.Since the initiation of the development of International Organization for Standardization(ISO) 21448 [4] in 2016, research on SOTIF has made some advancements [5].However, significant challenges persist in transitioning from simple and specific to complex,open scenarios,from low-level to high-level automation, and from laboratory research to industrial applications.Three key challenges are highlighted as follows.

    1.1.The ICV long-tail scenario problem

    During ICV industrialization and deployment, long-tail challenges were inevitably encountered in the real world [6].Such real-world scenarios are complex, including special road conditions, extreme weather conditions, and unexpected road user behaviors, which can all trigger SOTIF-related hazards.Moreover,real-world scenarios exhibit significant diversity and variation in traffic conditions, and different driving habits have been observed across different countries, cities, and rural areas.Furthermore, the real world is dynamic,with the publication of policies and regulations, infrastructure developments, and the introduction of new technologies to the evolving characteristics of driving scenarios.These factors collectively contribute to the challenges associated with long-tail scenarios in SOTIF research.Specifically, long-tail scenarios that are difficult to anticipate effectively can evolve into numerous unknown and potentially dangerous situations,substantially increasing the complexity of safety analysis and design during the ICV development process.Long-tail scenarios pose obstacles to ensuring sufficient ICV safety test coverage, becauseconducting testing spanning billions of kilometers [7] is impractical in terms of cost and feasibility.Failure to effectively address long-tail scenarios challenges the proactive mitigation of unknown risks arising from real-world operations,thus,significantly impeding ICV industrialization.Furthermore,remarkably,researchers are also increasing focus on the ‘‘long tail” problem, which is evident based on a steady increase observed in the number of publications on related topics in recent years.

    Table 1SOTIF-related intelligent vehicle safety accidents.

    1.2.ICV system complexity and diversity

    ICVs are highly complex systems that integrate software and hardware [8,9].Equipped with advanced onboard sensors, controllers, and actuators, they employ various intelligent algorithms and integrate modern communication and network technologies,whose overall complexity is significantly higher than that of traditional vehicles.To illustrate, considering solely the Baidu Apollo system code volume, Apollo 1.0 comprised only 35 000 lines of code,whereas Apollo 8.0 exceeded 750 000.Moreover,the possible adoption of an ICV foundation model can cause a sharp increase in system complexity.This elevated complexity significantly increases the difficulty of SOTIF design, development, testing, certification, and online protection [10].Furthermore, currently no consensus has emerged as yet from academia or industry regarding the technical approach that should be adopted for ICVs.Variation also exists in terms of sensor configurations, system architectures,and functional modules.According to a report by GreyB [11], over 250 companies worldwide were actively striving to achieve autonomous driving, with each company’s product undergoing rapid iteration, similar to different Apollo system versions.Additionally,ICV research continually introduces new paradigms and algorithms.This level of system diversity contributes toward the unfortunate absence of a unified SOTIF development process and specification.

    1.3.AI algorithm inexplicability and uncertainty

    With outstanding advantages for handling complex tasks, AI algorithms have been widely adopted in functional modules such as ICV perception, prediction, and decision-making, and produced significant performance improvements[12].However,as complexity including the number of model parameters continues to increase,the AI interpretability[13]issue has become increasingly prominent.In particular, deep learning models, which have recently demonstrated significant performance benefits,frequently function as opaque black boxes,posing challenges for the specification, analysis, verification, and validation of relevant modules.For example,the lack of AI model interpretability impedes the effective identification of its limitations, hampers the establishment of reliable safety analysis methods, significantly raises the challenge of verification and validation, and hinders the explicit modeling and targeted mitigation of AI-related SOTIF risks.In recent years, concepts such as trustworthy AI have increasingly gained traction,particularly in safety-critical fields such as ICVs.In addition,AI models are predominantly learned based on a significant amount of data and frequently show high uncertainty [14] with insufficient data or when the learning processes or models are unreasonable,which leads to unpredictable performance degradation.These circumstances are not conducive to the requirement of adequate protection for SOTIF in ICVs.

    2.Chinese solutions for SOTIF in ICVs

    As shown in Fig.2,to effectively ensure ICV safety and management of SOTIF risks within acceptable limits, Chinese solutions have been proposed to form a full lifecycle SOTIF research foundation for an offline safety development, online safety control, and active ongoing learning system.It is anticipated that these topics will ignite valuable discussion and further research in the SOTIF community.

    Fig.1.Statistics on causes of intelligent driving systems disengagement [3].

    Fig.2.Chinese solutions for SOTIF in ICVs.

    2.1.Offline safety design and development

    Constructing a systematic, comprehensive, and actionable SOTIF design and development process represents a fundamental step in addressing the aforementioned key challenges.While standards such as ISO 21448 introduce the fundamental SOTIF activities, a lack of sufficient detail and practical guidance remains.Regarding traditional FuSa, a mature development process has been established, accompanied by a range of supporting methods and technologies, including fault tree analysis (FTA) and failure mode and effect analysis (FMEA).However, owing to the differentiation, complexity, and uncertainty associated with SOTIF development, the applicability of traditional processes and methods is considerably limited.In response to the specific requirements for ICV development, it is essential to explore SOTIF forward design and development specifications and technologies.This involves clarifying ICV SOTIF goals, identifying safety risks alongside their contributing factors,establishing safety metrics and design criteria,developing computer-aided engineering (CAE) tools for safety analysis, and completing a SOTIF forward closed-loop design.The final step before release,namely,testing and certification,occupies a crucial role in determining whether an ICV can be formally approved for market entry.Therefore,testing and certification processes and results directly affect the accident rate and societal acceptance of approved ICVs.However,SOTIF testing and certification is a complex issue that cannot be solved from within a single group.This requires collaborative efforts from governments, standards organizations, enterprises, and universities to appropriately address this challenge in an effective manner.Furthermore, for future AI,there is a necessity for effective interpretability methods to assist in the system development process, which includes AI model explanation before, during, and after the modeling phase.This is expected to ultimately improve the transparency and controllability of models used during the development process.

    2.2.Online safety monitoring and protection

    The long-tail scenarios and uncertainty of autonomous driving complicate the elimination of residual risks during development.Therefore, it is necessary to ensure SOTIF through effective risk monitoring and protection during the operational phase.To address potential functional insufficiencies that may arise during autonomous driving control system operation, a parallel SOTIF real-time protection system is designed, to act as the ICV ‘‘safety control system”.This system continuously monitors Object and Event Detection and Response (OEDR) accuracy, AI model health status,and ICV compliance with road regulations in real time,thereby providing effective protection strategies.Moreover, for unavoidable risks or accidents that may occur during ICV driving,online monitoring,and recording are utilized to capture SOTIF risk sources,trigger conditions, system failure causes, real-time compliance with road regulations assessments, and other pertinent information in autonomous driving mode.This information is subsequently used to enable timely interventions and support accident cause identification and appropriate oversight by public safety departments.

    2.3.Active ongoing learning

    It is difficult for a fixed ICV safety system to manage constantly emergent long-tail scenarios, dynamically changing driving environments,and increasing functional requirements.Thus,establishing a flexible and efficient SOTIF improvement mechanism is crucial for advancing ICVs in this respect.In recent years, both industry and academia have explored various approaches in the field of autonomous driving learning and growth.Examples include Tesla’s fleet learning, Cruise’s continuous learning machine,and research topics such as continuous learning that have garnered significant attention.This study proposes the construction of a discovery mechanism for unknown-unsafe scenarios and a safety continuous learning growth model for continuous improvement of SOTIF in ICV.This aims to enhance the efficiency of identifying unknown-unsafe high-value scenarios and address the problem of ‘‘catastrophic forgetting”, where a model may forget previously learned information when learning from new data.By establishing a trinity of learning and growth processes encompassing data, models, and platforms, ICV’s continuous learning capability can be realized.Furthermore,the ongoing learning experience can be continuously and instantly fed back to offline design and development departments, offering real-time guidance for iterative upgrades in the development process.This closed-loop approach facilitates the establishment of comprehensive solutions to address SOTIF in ICVs.

    In summary, although ICVs must confront multiple challenges from the external environment and the system itself, the pursuit of SOTIF solutions has been relentless and has yielded some advancement.The proposed solutions for SOTIF in ICVs present notable advantages.Through the integration of key elements, the solutions ensure a systematic design and development process,real-time protection, and ongoing risk reduction, thereby expediting the safe industrialization of ICVs.In addition, the collaborative efforts of industry, universities, and research institutes, under the leadership of the government, serve to enhance the effectiveness and applicability of the solution.

    Acknowledgments

    This work was supported by the National Natural Science Foundation of China (NSFC; 52072215, U1964203, and 52221005), the National Key Research and Development Program of China (2022YFB2503003 and 2020YFB1600303), and the State Key Laboratory of Intelligent Green Vehicle and Mobility.

    成人国产麻豆网| 1024视频免费在线观看| 美女内射精品一级片tv| 美女脱内裤让男人舔精品视频| 丰满少妇做爰视频| 亚洲精品,欧美精品| 亚洲精品成人av观看孕妇| 少妇人妻 视频| 熟女av电影| 在线免费观看不下载黄p国产| 午夜久久久在线观看| 成人午夜精彩视频在线观看| 99久久综合免费| 观看av在线不卡| 久久婷婷青草| 久久热在线av| 街头女战士在线观看网站| 亚洲精品中文字幕在线视频| 免费高清在线观看视频在线观看| 中文字幕免费在线视频6| 免费观看av网站的网址| 熟女人妻精品中文字幕| 中文字幕人妻熟女乱码| 日本91视频免费播放| 校园人妻丝袜中文字幕| 90打野战视频偷拍视频| 丰满饥渴人妻一区二区三| 欧美精品国产亚洲| 精品酒店卫生间| 久热久热在线精品观看| 成人漫画全彩无遮挡| 在线观看免费日韩欧美大片| 国产av一区二区精品久久| 日韩欧美精品免费久久| 久久这里只有精品19| 国产不卡av网站在线观看| 色婷婷久久久亚洲欧美| 色吧在线观看| 欧美日本中文国产一区发布| 国产精品一区www在线观看| 成人影院久久| 亚洲一码二码三码区别大吗| www.av在线官网国产| 在线观看人妻少妇| 三级国产精品片| 国内精品宾馆在线| 18禁裸乳无遮挡动漫免费视频| 欧美xxⅹ黑人| 久久久久精品人妻al黑| 久久毛片免费看一区二区三区| 天天影视国产精品| 久久国内精品自在自线图片| 国产永久视频网站| 宅男免费午夜| 最后的刺客免费高清国语| 老司机影院毛片| 老司机亚洲免费影院| 免费女性裸体啪啪无遮挡网站| 飞空精品影院首页| 欧美xxⅹ黑人| 热99久久久久精品小说推荐| 美女福利国产在线| 成人黄色视频免费在线看| 青春草视频在线免费观看| 亚洲五月色婷婷综合| 青青草视频在线视频观看| 欧美日韩成人在线一区二区| 亚洲人成网站在线观看播放| 国产精品一二三区在线看| 在线观看国产h片| 伦理电影大哥的女人| 婷婷色av中文字幕| 多毛熟女@视频| 日韩一本色道免费dvd| a级毛色黄片| 九色成人免费人妻av| 久久99一区二区三区| 涩涩av久久男人的天堂| 看免费av毛片| 国产极品天堂在线| 尾随美女入室| 久久99热6这里只有精品| 国产片内射在线| 中文天堂在线官网| 在线观看人妻少妇| 丝袜美足系列| 制服诱惑二区| 欧美日本中文国产一区发布| 免费黄网站久久成人精品| 亚洲婷婷狠狠爱综合网| 一区二区三区四区激情视频| 一区在线观看完整版| 免费av不卡在线播放| 日日啪夜夜爽| 中文字幕精品免费在线观看视频 | 免费在线观看完整版高清| 九色亚洲精品在线播放| 国产麻豆69| 99精国产麻豆久久婷婷| 午夜福利视频在线观看免费| 亚洲av免费高清在线观看| 少妇的逼好多水| 亚洲精品久久久久久婷婷小说| 欧美激情 高清一区二区三区| 国产精品一区www在线观看| 久久热在线av| 两性夫妻黄色片 | 天堂8中文在线网| 精品久久久久久电影网| 精品少妇黑人巨大在线播放| 免费在线观看完整版高清| 丰满饥渴人妻一区二区三| 看免费av毛片| 中国三级夫妇交换| 久久久久久久久久人人人人人人| 啦啦啦中文免费视频观看日本| 高清av免费在线| 亚洲成国产人片在线观看| 香蕉丝袜av| 精品国产一区二区三区久久久樱花| videos熟女内射| 久久青草综合色| 亚洲欧美成人综合另类久久久| 国产精品一区二区在线观看99| 免费黄色在线免费观看| 国产成人精品婷婷| 中文字幕另类日韩欧美亚洲嫩草| 亚洲人成网站在线观看播放| 青春草国产在线视频| 久久午夜福利片| 久久久精品94久久精品| 人成视频在线观看免费观看| 99re6热这里在线精品视频| 亚洲精品第二区| av国产精品久久久久影院| 亚洲综合色网址| 又大又黄又爽视频免费| 国产精品国产三级专区第一集| 国产精品久久久久久久电影| 国产一区有黄有色的免费视频| 啦啦啦啦在线视频资源| 国产亚洲精品久久久com| xxxhd国产人妻xxx| 一级a做视频免费观看| 成人国产av品久久久| 高清av免费在线| 只有这里有精品99| 日本黄大片高清| 亚洲久久久国产精品| 亚洲国产看品久久| 香蕉精品网在线| 色婷婷久久久亚洲欧美| 视频中文字幕在线观看| 亚洲国产欧美在线一区| 最新的欧美精品一区二区| 99视频精品全部免费 在线| 成人午夜精彩视频在线观看| 国产精品久久久久久精品古装| 美国免费a级毛片| 国产精品女同一区二区软件| 亚洲伊人久久精品综合| 91国产中文字幕| 亚洲av日韩在线播放| 纵有疾风起免费观看全集完整版| 亚洲国产精品一区二区三区在线| 亚洲精品美女久久久久99蜜臀 | 欧美亚洲 丝袜 人妻 在线| 亚洲成av片中文字幕在线观看 | 日本91视频免费播放| 亚洲人与动物交配视频| 亚洲成人手机| 精品第一国产精品| 99热国产这里只有精品6| 天天躁夜夜躁狠狠久久av| 久久精品人人爽人人爽视色| 亚洲欧美成人精品一区二区| 久久精品国产鲁丝片午夜精品| 男人爽女人下面视频在线观看| √禁漫天堂资源中文www| 日本av免费视频播放| 亚洲欧美一区二区三区黑人 | 国产日韩欧美在线精品| 人妻少妇偷人精品九色| 免费观看性生交大片5| 久久久久人妻精品一区果冻| 99香蕉大伊视频| 伦理电影大哥的女人| 久久狼人影院| 晚上一个人看的免费电影| 欧美人与性动交α欧美软件 | 亚洲伊人久久精品综合| 两性夫妻黄色片 | 久久国产亚洲av麻豆专区| 男男h啪啪无遮挡| 国产视频首页在线观看| 人人妻人人澡人人看| 日本黄色日本黄色录像| 国产爽快片一区二区三区| 99久久精品国产国产毛片| 在线观看三级黄色| 久久99一区二区三区| 国产白丝娇喘喷水9色精品| 秋霞伦理黄片| 最近手机中文字幕大全| 久久久久人妻精品一区果冻| 大片电影免费在线观看免费| 欧美bdsm另类| 男的添女的下面高潮视频| 午夜日本视频在线| 国产一区二区在线观看av| 亚洲精品色激情综合| 国产亚洲欧美精品永久| 精品第一国产精品| 一级片'在线观看视频| 综合色丁香网| 亚洲高清免费不卡视频| 熟女人妻精品中文字幕| 97精品久久久久久久久久精品| 日本欧美国产在线视频| 成人无遮挡网站| 国内精品宾馆在线| av国产久精品久网站免费入址| 国产成人精品婷婷| 精品人妻偷拍中文字幕| 在线天堂中文资源库| 伦精品一区二区三区| 久久久久久久久久成人| 久久av网站| videosex国产| 亚洲中文av在线| 国产精品一区二区在线观看99| 免费看av在线观看网站| 精品久久国产蜜桃| 精品一品国产午夜福利视频| 亚洲,欧美,日韩| 亚洲四区av| av网站免费在线观看视频| 18禁国产床啪视频网站| 欧美国产精品一级二级三级| 中国美白少妇内射xxxbb| 女人被躁到高潮嗷嗷叫费观| 男人爽女人下面视频在线观看| 精品一区二区三区视频在线| 欧美精品亚洲一区二区| 免费日韩欧美在线观看| 咕卡用的链子| 国产精品久久久久久精品电影小说| 在现免费观看毛片| 成年人午夜在线观看视频| 国产成人aa在线观看| 亚洲精品456在线播放app| 久久久久久人妻| 激情视频va一区二区三区| av电影中文网址| 大香蕉97超碰在线| 毛片一级片免费看久久久久| 日本欧美国产在线视频| 老司机影院成人| 97精品久久久久久久久久精品| 亚洲国产色片| 国产老妇伦熟女老妇高清| 精品少妇内射三级| av不卡在线播放| 亚洲欧美日韩另类电影网站| 18禁观看日本| 男女午夜视频在线观看 | 久久人人97超碰香蕉20202| 少妇熟女欧美另类| 美女视频免费永久观看网站| 十八禁高潮呻吟视频| 亚洲图色成人| tube8黄色片| 国产精品人妻久久久久久| 大香蕉久久网| videosex国产| 国产精品不卡视频一区二区| 两个人免费观看高清视频| 国产极品粉嫩免费观看在线| 久久99蜜桃精品久久| 大香蕉久久成人网| 亚洲精品久久久久久婷婷小说| 最黄视频免费看| 国产欧美另类精品又又久久亚洲欧美| 自拍欧美九色日韩亚洲蝌蚪91| 天堂8中文在线网| 69精品国产乱码久久久| 亚洲欧美成人综合另类久久久| 国产成人精品福利久久| 国产精品久久久久久久电影| 1024视频免费在线观看| 国产一区二区在线观看av| 日韩三级伦理在线观看| 青春草亚洲视频在线观看| 一区二区三区乱码不卡18| 亚洲欧美中文字幕日韩二区| 建设人人有责人人尽责人人享有的| 久久久久久久大尺度免费视频| 免费黄频网站在线观看国产| 美女中出高潮动态图| 在线观看人妻少妇| 国产色爽女视频免费观看| 成人毛片a级毛片在线播放| 黑人猛操日本美女一级片| 性色avwww在线观看| 黄网站色视频无遮挡免费观看| 久久精品熟女亚洲av麻豆精品| 国产熟女午夜一区二区三区| 日韩免费高清中文字幕av| 人人妻人人澡人人看| 国产男女内射视频| 在线 av 中文字幕| 午夜福利视频在线观看免费| 黄色 视频免费看| 美女国产高潮福利片在线看| 国产乱来视频区| 男女午夜视频在线观看 | 侵犯人妻中文字幕一二三四区| 九九爱精品视频在线观看| 欧美精品高潮呻吟av久久| 男女无遮挡免费网站观看| 青春草视频在线免费观看| 丝袜喷水一区| 久久国内精品自在自线图片| 日韩免费高清中文字幕av| 亚洲精品久久午夜乱码| 一级a做视频免费观看| 欧美日韩精品成人综合77777| 日韩精品有码人妻一区| 亚洲av日韩在线播放| 五月开心婷婷网| 美女中出高潮动态图| 亚洲人与动物交配视频| 卡戴珊不雅视频在线播放| 伦精品一区二区三区| 亚洲成人一二三区av| 赤兔流量卡办理| 久久鲁丝午夜福利片| 又大又黄又爽视频免费| 在线 av 中文字幕| 国产一区有黄有色的免费视频| 国产一区二区三区综合在线观看 | 女人久久www免费人成看片| 久久99精品国语久久久| 我的女老师完整版在线观看| 久久久久久久精品精品| av天堂久久9| 日韩欧美精品免费久久| 菩萨蛮人人尽说江南好唐韦庄| www.色视频.com| 国产免费福利视频在线观看| 欧美日韩一区二区视频在线观看视频在线| 亚洲性久久影院| 精品酒店卫生间| 日韩av不卡免费在线播放| 汤姆久久久久久久影院中文字幕| 大片电影免费在线观看免费| 久久99热6这里只有精品| 欧美97在线视频| 在线精品无人区一区二区三| 这个男人来自地球电影免费观看 | 国产成人精品在线电影| 色哟哟·www| 丁香六月天网| 搡女人真爽免费视频火全软件| 久久久久久久国产电影| 99香蕉大伊视频| 黄色 视频免费看| 午夜av观看不卡| 狂野欧美激情性bbbbbb| 亚洲av欧美aⅴ国产| 夜夜骑夜夜射夜夜干| 色94色欧美一区二区| 男男h啪啪无遮挡| 亚洲精品成人av观看孕妇| 最近中文字幕2019免费版| 精品少妇久久久久久888优播| 久久久久久久久久成人| 亚洲欧美日韩卡通动漫| 中国美白少妇内射xxxbb| 亚洲国产精品一区三区| 久久av网站| 一级毛片电影观看| 国产伦理片在线播放av一区| 青青草视频在线视频观看| 一本一本久久a久久精品综合妖精 国产伦在线观看视频一区 | 亚洲综合色惰| 国产在线一区二区三区精| 国产麻豆69| 日韩制服丝袜自拍偷拍| 亚洲综合色惰| 国产xxxxx性猛交| 日韩三级伦理在线观看| h视频一区二区三区| 夫妻午夜视频| 久久av网站| 2018国产大陆天天弄谢| 国产成人午夜福利电影在线观看| 久久综合国产亚洲精品| 黄色一级大片看看| 91精品国产国语对白视频| 欧美激情极品国产一区二区三区 | 在线看a的网站| a级毛片黄视频| 欧美精品人与动牲交sv欧美| 国产精品国产三级国产专区5o| 精品福利永久在线观看| 麻豆精品久久久久久蜜桃| 91国产中文字幕| 久热久热在线精品观看| 精品一区二区免费观看| 国产又爽黄色视频| 激情五月婷婷亚洲| 免费看光身美女| xxxhd国产人妻xxx| 波野结衣二区三区在线| 最后的刺客免费高清国语| av.在线天堂| 男人爽女人下面视频在线观看| 一级片免费观看大全| 久久精品夜色国产| 亚洲色图 男人天堂 中文字幕 | 1024视频免费在线观看| 亚洲四区av| 国产成人精品无人区| 国产黄色视频一区二区在线观看| 亚洲精品久久久久久婷婷小说| 99久久精品国产国产毛片| 久久毛片免费看一区二区三区| 十八禁网站网址无遮挡| 熟女电影av网| 七月丁香在线播放| 高清欧美精品videossex| 精品国产一区二区三区四区第35| 一级毛片黄色毛片免费观看视频| 国产国拍精品亚洲av在线观看| 狂野欧美激情性bbbbbb| 久久精品人人爽人人爽视色| 啦啦啦在线观看免费高清www| 热re99久久精品国产66热6| 看十八女毛片水多多多| 国产精品免费大片| 免费黄网站久久成人精品| 亚洲av欧美aⅴ国产| 国产成人a∨麻豆精品| 一区二区日韩欧美中文字幕 | 黄色毛片三级朝国网站| 少妇被粗大的猛进出69影院 | 欧美国产精品va在线观看不卡| 久久久久精品人妻al黑| 有码 亚洲区| videos熟女内射| 精品国产乱码久久久久久小说| 韩国av在线不卡| 国产成人精品无人区| 久久 成人 亚洲| 巨乳人妻的诱惑在线观看| 丝袜在线中文字幕| av在线老鸭窝| 国产 一区精品| 2021少妇久久久久久久久久久| 国产色婷婷99| 亚洲精品,欧美精品| 99久久综合免费| 久久久久久久亚洲中文字幕| 国产精品国产三级专区第一集| 大片免费播放器 马上看| 日韩一区二区视频免费看| 成人国产麻豆网| 久久久久国产精品人妻一区二区| 伦理电影大哥的女人| 日本猛色少妇xxxxx猛交久久| 欧美丝袜亚洲另类| 亚洲第一区二区三区不卡| 丰满迷人的少妇在线观看| 国产深夜福利视频在线观看| av网站免费在线观看视频| 嫩草影院入口| 国产精品国产av在线观看| 日韩中字成人| 免费黄色在线免费观看| 最黄视频免费看| av在线app专区| 精品久久国产蜜桃| 亚洲,欧美,日韩| 国产免费一区二区三区四区乱码| 久久99一区二区三区| 建设人人有责人人尽责人人享有的| 26uuu在线亚洲综合色| 国产一区有黄有色的免费视频| av一本久久久久| www.av在线官网国产| 又黄又粗又硬又大视频| 日产精品乱码卡一卡2卡三| 天天躁夜夜躁狠狠躁躁| 国产一区亚洲一区在线观看| 18+在线观看网站| 日本av手机在线免费观看| 美女脱内裤让男人舔精品视频| 国产成人aa在线观看| 69精品国产乱码久久久| 亚洲第一av免费看| 国产成人av激情在线播放| 99精国产麻豆久久婷婷| 侵犯人妻中文字幕一二三四区| 看非洲黑人一级黄片| 午夜影院在线不卡| 人人澡人人妻人| 美女脱内裤让男人舔精品视频| 51国产日韩欧美| 国产精品无大码| 中文字幕制服av| 亚洲国产欧美在线一区| 精品少妇黑人巨大在线播放| 美国免费a级毛片| 这个男人来自地球电影免费观看 | 好男人视频免费观看在线| 在线看a的网站| 韩国高清视频一区二区三区| 精品一区二区免费观看| 成年女人在线观看亚洲视频| 国产一级毛片在线| 亚洲av.av天堂| 久久毛片免费看一区二区三区| 美女福利国产在线| 国产精品 国内视频| 久久久久久久国产电影| 国产激情久久老熟女| 在线天堂中文资源库| 五月天丁香电影| 一区在线观看完整版| 国产成人精品一,二区| 青青草视频在线视频观看| 全区人妻精品视频| 热re99久久精品国产66热6| 日韩大片免费观看网站| 人人妻人人爽人人添夜夜欢视频| 亚洲精品国产av成人精品| 国产黄色免费在线视频| 十八禁高潮呻吟视频| 欧美精品av麻豆av| 精品国产一区二区三区久久久樱花| 秋霞在线观看毛片| 国产成人免费观看mmmm| 欧美激情 高清一区二区三区| 咕卡用的链子| 亚洲精品久久久久久婷婷小说| 亚洲少妇的诱惑av| 欧美精品av麻豆av| 熟女电影av网| 亚洲av综合色区一区| 777米奇影视久久| 亚洲,欧美,日韩| 街头女战士在线观看网站| 午夜福利视频在线观看免费| 免费大片18禁| 寂寞人妻少妇视频99o| 免费看av在线观看网站| 自拍欧美九色日韩亚洲蝌蚪91| 在线天堂中文资源库| 国产精品一区www在线观看| 国产国语露脸激情在线看| 国产av一区二区精品久久| 18禁在线无遮挡免费观看视频| 亚洲av中文av极速乱| 精品亚洲成a人片在线观看| 久久综合国产亚洲精品| 国产成人精品久久久久久| 国产精品蜜桃在线观看| 成人国产av品久久久| 免费看av在线观看网站| 五月玫瑰六月丁香| 久久精品国产亚洲av涩爱| 精品一区二区三区视频在线| 这个男人来自地球电影免费观看 | 午夜福利影视在线免费观看| 亚洲精品美女久久久久99蜜臀 | 国产成人精品婷婷| 精品人妻在线不人妻| 黑人欧美特级aaaaaa片| 欧美激情国产日韩精品一区| 国产成人免费无遮挡视频| 免费av不卡在线播放| 国产精品久久久久成人av| 亚洲欧美一区二区三区黑人 | 毛片一级片免费看久久久久| 国产探花极品一区二区| 国产国拍精品亚洲av在线观看| 18禁观看日本| 欧美日韩成人在线一区二区| 97人妻天天添夜夜摸| 国产女主播在线喷水免费视频网站| 99久久精品国产国产毛片| 日本免费在线观看一区| 美女福利国产在线| 国产精品.久久久| 毛片一级片免费看久久久久| 成人免费观看视频高清| 亚洲,一卡二卡三卡| 精品国产一区二区三区四区第35| 免费大片黄手机在线观看| 丰满迷人的少妇在线观看| videos熟女内射| 中文字幕最新亚洲高清| 成人免费观看视频高清| 我要看黄色一级片免费的| 日本免费在线观看一区| 精品一区二区三区视频在线| 国产成人精品无人区| 97人妻天天添夜夜摸| 国产免费一级a男人的天堂| 欧美精品亚洲一区二区| 免费人妻精品一区二区三区视频| 激情视频va一区二区三区| av在线观看视频网站免费| 欧美xxxx性猛交bbbb|