智能汽车:我们做到了吗?

Gordana S. Velikic
{"title":"智能汽车:我们做到了吗?","authors":"Gordana S. Velikic","doi":"10.1109/mce.2020.2972084","DOIUrl":null,"url":null,"abstract":"& THE AUTOMOTIVE INDUSTRY is experiencing disruptive changes at all levels—from design, and production, to community and business models. A previously rigid and very closed business environment is forced to open and embrace new methods to survive. In particular, it has become clear that a previously strongly deterministic approach has to be replaced with flexible adaptive approaches. This opened a path to newmethods, which are reportedly necessary to bring the industry to the ultimate goal—driverless vehicles in any driving condition. The artificial intelligence (AI) has a significant role in this development, but it has not reached the full potential yet due to rigorous requirements that automotive-grade outputs need to satisfy. Nevertheless, an access to a paramount source of data has pushedAImethods to front rows, while all other processing methods are grouped in the “pre-AI era,” or even labeled as “vintagemethods.” Futuristic predictions just a few years ago were very optimistic, and foreseen time span until deployment decreased from several decades to several years. After the first wave of the excitement has passed, the closer look at the whole picture revealed that the problems of the ecosystem apply not just to actual engineering of the vehicles, but to the impacts this technology has on the society. This made us aware, that although we have a technology to answer to the challenge, the technology needs to mature further to cover all critical use cases. An automotive field has always been classified as an industry, rather than consumer, although a consumer mass market of a final product—a vehicle, is huge: according to theworld association of car manufacturers Organisation Internationale des Constructeurs d’Automobiles (OICA), in 2017, the global average annual turnover was 2.75 trillion, with production of 73.4 million cars and 23.84 million trucks. As modern vehicles architecture changes inside, and hardware and software take roles of mechanical parts, so changes the interior of the vehicle. We witness the integration of products and services from creative industries and other common consumer electronics products and services into cabins [1]. This affected terminology and expectations. This nicely illustrates why the term “consumer electronics” (CE) has become obsolete and the term “consumer technology” has become more appropriate, reflecting the social changes due to technology accomplishments and shifts in consumer expectations. Thus, before we hit the big milestone—complete switch to driverless vehicles, also known as L5, we are continuing research to make this experience better, smoother, and safer. The articles in this special section are carefully chosen with the help of the Editor-in-Chief (EIC), are part of this legacy. The articles are extended versions of presentations at the Digital Object Identifier 10.1109/MCE.2020.2972084","PeriodicalId":179001,"journal":{"name":"IEEE Consumer Electron. Mag.","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Intelligent Cars: Are We There Yet?\",\"authors\":\"Gordana S. Velikic\",\"doi\":\"10.1109/mce.2020.2972084\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"& THE AUTOMOTIVE INDUSTRY is experiencing disruptive changes at all levels—from design, and production, to community and business models. A previously rigid and very closed business environment is forced to open and embrace new methods to survive. In particular, it has become clear that a previously strongly deterministic approach has to be replaced with flexible adaptive approaches. This opened a path to newmethods, which are reportedly necessary to bring the industry to the ultimate goal—driverless vehicles in any driving condition. The artificial intelligence (AI) has a significant role in this development, but it has not reached the full potential yet due to rigorous requirements that automotive-grade outputs need to satisfy. Nevertheless, an access to a paramount source of data has pushedAImethods to front rows, while all other processing methods are grouped in the “pre-AI era,” or even labeled as “vintagemethods.” Futuristic predictions just a few years ago were very optimistic, and foreseen time span until deployment decreased from several decades to several years. After the first wave of the excitement has passed, the closer look at the whole picture revealed that the problems of the ecosystem apply not just to actual engineering of the vehicles, but to the impacts this technology has on the society. This made us aware, that although we have a technology to answer to the challenge, the technology needs to mature further to cover all critical use cases. An automotive field has always been classified as an industry, rather than consumer, although a consumer mass market of a final product—a vehicle, is huge: according to theworld association of car manufacturers Organisation Internationale des Constructeurs d’Automobiles (OICA), in 2017, the global average annual turnover was 2.75 trillion, with production of 73.4 million cars and 23.84 million trucks. As modern vehicles architecture changes inside, and hardware and software take roles of mechanical parts, so changes the interior of the vehicle. We witness the integration of products and services from creative industries and other common consumer electronics products and services into cabins [1]. This affected terminology and expectations. This nicely illustrates why the term “consumer electronics” (CE) has become obsolete and the term “consumer technology” has become more appropriate, reflecting the social changes due to technology accomplishments and shifts in consumer expectations. Thus, before we hit the big milestone—complete switch to driverless vehicles, also known as L5, we are continuing research to make this experience better, smoother, and safer. The articles in this special section are carefully chosen with the help of the Editor-in-Chief (EIC), are part of this legacy. The articles are extended versions of presentations at the Digital Object Identifier 10.1109/MCE.2020.2972084\",\"PeriodicalId\":179001,\"journal\":{\"name\":\"IEEE Consumer Electron. Mag.\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Consumer Electron. Mag.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/mce.2020.2972084\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Consumer Electron. Mag.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/mce.2020.2972084","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

汽车工业正经历着从设计、生产到社区和商业模式等各个层面的颠覆性变革。以前僵化和非常封闭的商业环境被迫开放并接受新的生存方法。特别是,很明显,以前的强确定性方法必须被灵活的适应性方法所取代。这为新方法开辟了一条道路,据报道,这些新方法对于实现行业的最终目标——任何驾驶条件下的无人驾驶汽车——是必要的。人工智能(AI)在这一发展中发挥着重要作用,但由于汽车级输出需要满足的严格要求,它尚未充分发挥其潜力。然而,对重要数据来源的访问将ai方法推到了最前面,而所有其他处理方法都被归为“前ai时代”,甚至被标记为“复古方法”。就在几年前,对未来的预测还非常乐观,预计部署的时间跨度将从几十年缩短到几年。在第一波兴奋过后,仔细观察整个情况就会发现,生态系统的问题不仅适用于车辆的实际工程,还适用于这项技术对社会的影响。这让我们意识到,尽管我们有技术来应对挑战,但技术需要进一步成熟,以覆盖所有关键用例。汽车领域一直被归类为一个行业,而不是消费者,尽管最终产品——汽车的消费大众市场是巨大的:根据世界汽车制造商协会国际汽车制造商组织(OICA)的数据,2017年,全球平均年营业额为2.75万亿美元,汽车产量为7340万辆,卡车产量为2384万辆。随着现代汽车内部结构的变化,硬件和软件扮演了机械部件的角色,汽车内部也发生了变化。我们见证了创意产业的产品和服务与其他普通消费电子产品和服务的融合[1]。这影响了术语和期望。这很好地说明了为什么“消费电子”(CE)一词已经过时,而“消费技术”一词变得更合适,反映了由于技术成就和消费者期望的转变而导致的社会变化。因此,在我们完成向无人驾驶汽车(也称为L5)的重大里程碑式转变之前,我们仍在继续研究,以使这种体验更好、更顺畅、更安全。在主编(EIC)的帮助下,这个特别部分的文章是精心挑选的,是这一遗产的一部分。这些文章是数字对象标识符10.1109/MCE.2020.2972084的扩展版本
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Intelligent Cars: Are We There Yet?
& THE AUTOMOTIVE INDUSTRY is experiencing disruptive changes at all levels—from design, and production, to community and business models. A previously rigid and very closed business environment is forced to open and embrace new methods to survive. In particular, it has become clear that a previously strongly deterministic approach has to be replaced with flexible adaptive approaches. This opened a path to newmethods, which are reportedly necessary to bring the industry to the ultimate goal—driverless vehicles in any driving condition. The artificial intelligence (AI) has a significant role in this development, but it has not reached the full potential yet due to rigorous requirements that automotive-grade outputs need to satisfy. Nevertheless, an access to a paramount source of data has pushedAImethods to front rows, while all other processing methods are grouped in the “pre-AI era,” or even labeled as “vintagemethods.” Futuristic predictions just a few years ago were very optimistic, and foreseen time span until deployment decreased from several decades to several years. After the first wave of the excitement has passed, the closer look at the whole picture revealed that the problems of the ecosystem apply not just to actual engineering of the vehicles, but to the impacts this technology has on the society. This made us aware, that although we have a technology to answer to the challenge, the technology needs to mature further to cover all critical use cases. An automotive field has always been classified as an industry, rather than consumer, although a consumer mass market of a final product—a vehicle, is huge: according to theworld association of car manufacturers Organisation Internationale des Constructeurs d’Automobiles (OICA), in 2017, the global average annual turnover was 2.75 trillion, with production of 73.4 million cars and 23.84 million trucks. As modern vehicles architecture changes inside, and hardware and software take roles of mechanical parts, so changes the interior of the vehicle. We witness the integration of products and services from creative industries and other common consumer electronics products and services into cabins [1]. This affected terminology and expectations. This nicely illustrates why the term “consumer electronics” (CE) has become obsolete and the term “consumer technology” has become more appropriate, reflecting the social changes due to technology accomplishments and shifts in consumer expectations. Thus, before we hit the big milestone—complete switch to driverless vehicles, also known as L5, we are continuing research to make this experience better, smoother, and safer. The articles in this special section are carefully chosen with the help of the Editor-in-Chief (EIC), are part of this legacy. The articles are extended versions of presentations at the Digital Object Identifier 10.1109/MCE.2020.2972084
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Enhancing Diversity of Consumer Technologies IEEE Consumer Technology Society Awards Presented At ICCE 2023 Smart Consumer Healthcare Technologies 2023 41st IEEE International Conference on Consumer Electronics (ICCE) Success of CTSoc Over the Last Four Years (2019-2022): Transformation From Obscurity to Prominence Moving CTSoc Forward Onto the International Stage
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1