智能網(wǎng)聯(lián)交通系統(tǒng)的關(guān)鍵技術(shù)與發(fā)展

錢志鴻; 田春生; 郭銀景; 王雪

doi:10.11999/JEIT190787

智能網(wǎng)聯(lián)交通系統(tǒng)的關(guān)鍵技術(shù)與發(fā)展

doi: 10.11999/JEIT190787 cstr: 32379.14.JEIT190787

1.
吉林大學(xué)通信工程學(xué)院長春 130012
2.
山東科技大學(xué)信息與電氣工程學(xué)院青島 266510

基金項(xiàng)目: 國家自然科學(xué)基金(61771219)，吉林大學(xué)基礎(chǔ)科研項(xiàng)目(SXGJQY2017-9, 2017TD-19)，吉林大學(xué)研究生創(chuàng)新基金(101832018C022)

詳細(xì)信息

作者簡介:
錢志鴻：男，1957年生，教授，研究方向?yàn)闊o線網(wǎng)絡(luò)通信技術(shù)，包括藍(lán)牙、RFID, M2M, D2D、無線傳感器網(wǎng)絡(luò)及物聯(lián)網(wǎng)等

田春生：男，1993年生，博士生，研究方向?yàn)镈2D通信技術(shù)與物聯(lián)網(wǎng)

郭銀景：男，1966年生，教授，研究方向?yàn)榫W(wǎng)絡(luò)通信、電磁兼容等

王雪：女，1984年生，副教授，研究方向?yàn)?G通信中的關(guān)鍵技術(shù)，具體包括D2D通信的模式選擇、同步技術(shù)，以及物聯(lián)網(wǎng)技術(shù)

通訊作者:
王雪　jluwangxue@163.com

中圖分類號: TN92
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出版歷程
- 收稿日期: 2019-10-16
- 修回日期: 2019-11-22
- 網(wǎng)絡(luò)出版日期: 2019-11-30
- 刊出日期: 2020-01-21

The Key Technology and Development of Intelligent and Connected Transportation System

1.
College of Communication Engineering, Jilin University, Changchun 130012, China
2.
College of Information and Electrical Engineering, Shandong University of Science and Technology, Qingdao, 266510, China

Funds: The National Natural Science Foundation of China (61771219), The Fundamental Research of Jilin University (SXGJQY2017-9, 2017TD-19), The Graduate Innovation Fund of Jilin University (101832018C022)

摘要

摘要: 該文梳理了國內(nèi)外針對智能網(wǎng)聯(lián)交通系統(tǒng)的相關(guān)研究，闡述了智能網(wǎng)聯(lián)交通系統(tǒng)的架構(gòu)和關(guān)鍵技術(shù)，分析了外部環(huán)境感知技術(shù)、車輛自主決策技術(shù)、控制執(zhí)行技術(shù)以及車路協(xié)同技術(shù)等幾個(gè)重點(diǎn)方向的研究進(jìn)展。在分析總結(jié)已有文獻(xiàn)的基礎(chǔ)上，該文描述了未來智能網(wǎng)聯(lián)交通系統(tǒng)的方案及其工作原理。未來智能網(wǎng)聯(lián)交通系統(tǒng)應(yīng)具備全程路徑規(guī)劃和精準(zhǔn)定位功能，運(yùn)用實(shí)時(shí)動(dòng)態(tài)定位(RTK)技術(shù)和合成孔徑雷達(dá)(SAR)技術(shù)，對運(yùn)動(dòng)或非運(yùn)動(dòng)物體(包括未裝載GPS的物體)進(jìn)行探測和定位，并保證在GPS信號弱或無信號(如隧道、室內(nèi))環(huán)境下和近距離、非可視情況下探測信號的連續(xù)性。系統(tǒng)還將運(yùn)用移動(dòng)邊緣計(jì)算(MEC)理論，解決低時(shí)延、大規(guī)模網(wǎng)絡(luò)接入等關(guān)鍵問題，運(yùn)用大數(shù)據(jù)、云計(jì)算、物聯(lián)網(wǎng)(IoTs)和移動(dòng)通信技術(shù)，實(shí)現(xiàn)具有全局性、網(wǎng)絡(luò)化的智能網(wǎng)聯(lián)交通系統(tǒng)。
- 智能網(wǎng)聯(lián)交通 /
- 車聯(lián)網(wǎng) /
- V2X /
- 實(shí)時(shí)動(dòng)態(tài)定位 /
- 合成孔徑雷達(dá)
Abstract: Some current works on intelligent and connected transportation system are presented, particularly focusing on the state of the art of the framework and key technologies in China or internationally, and the research development in some critical directions are elaborated including external environment perception, autonomous decision of vehicles, control execution and cooperative vehicle infrastructure system. On the basis of analyzing and summarizing the existing literature, the scheme of the future intelligent and connected transportation system and its working principle are described. The future intelligent and connected transportation system have the function of full path planning and precise, and the Real-Time Kinematic (RTK) and Synthetic Aperture Radar (SAR) technologies are used to detect and locate moving or non-moving objects, including those without GPS. And the continuity of the detection signal can be guaranteed in the environment where GPS signals are weak or non-signaled (e.g., tunnel, indoor) and the situation of close-range and non-visual. The Mobile Edge Computing (MEC) theory can also be used in the system to solve the key problems such as low latency and large-scale network access, and the big data, cloud computing, Internet of Things (IoTs) and mobile communication technologies are used to realize the global and networked intelligent and connected transportation system.
- Intelligent and connected transportation /
- Internet of Vehioles (IoVs) /
- Vehicle to Everything (V2X) /
- Real-Time Kinematic (RTK) /
- Synthetic Aperture Radar (SAR)

HTML全文

圖 1 智能網(wǎng)聯(lián)交通系統(tǒng)結(jié)構(gòu)示意圖

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圖 2 直接式縱向結(jié)構(gòu)控制

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圖 3 分層式縱向結(jié)構(gòu)控制

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圖 4 V2X通信場景

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圖 5 SD-V2X通信基本結(jié)構(gòu)

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圖 6 智能網(wǎng)聯(lián)交通系統(tǒng)未來發(fā)展架構(gòu)

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圖 7 智能網(wǎng)聯(lián)交通移動(dòng)邊緣計(jì)算體系結(jié)構(gòu)

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表 1 3種不同感知技術(shù)對比

感知技術(shù)	優(yōu)點(diǎn)	缺點(diǎn)	感知范圍
視覺感知	實(shí)時(shí)性好，能耗較低，獲取的信息量豐富	感知結(jié)果易受外界環(huán)境影響，3維物體識別精度較低	最遠(yuǎn)可實(shí)現(xiàn)250 m范圍內(nèi)物體的感知
激光感知	可精準(zhǔn)識別3維物體距離信息，感知結(jié)果不易受外界環(huán)境影響	體積大，價(jià)格昂貴，無法完成無距離差異平面內(nèi)物體感知	可完成300 m范圍內(nèi)直徑1 cm物體的感知
微波感知	可精準(zhǔn)識別3維物體距離信息，感知結(jié)果不易受外界環(huán)境影響	無法完成無距離差異平面內(nèi)物體感知	取決于傳感器的波長，一般可完成8～ 10 m內(nèi)物體的感知

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表 2 不同控制執(zhí)行技術(shù)的對比

控制執(zhí)行技術(shù)			優(yōu)點(diǎn)	缺點(diǎn)
橫向控制	經(jīng)典控制理論	PID	結(jié)構(gòu)簡單，可操作性好	線性模型，在多變量以及時(shí)變控制系統(tǒng)中具有局限性
	現(xiàn)代控制理論	最優(yōu)控制	可使系統(tǒng)性能達(dá)到最優(yōu)	對數(shù)學(xué)模型的依賴性較高
		滑?？刂?/td>	非線性模型，系統(tǒng)魯棒性好，響應(yīng)速度較快	控制結(jié)果受外界不確定性影響較大
		自適應(yīng)控制	對外部環(huán)境變化具有較強(qiáng)的魯棒性	方法實(shí)時(shí)性相對較差
		模糊控制	無需借助精確的數(shù)學(xué)模型，對外部環(huán)境變化具有較強(qiáng)的魯棒性	需借助研究人員的經(jīng)驗(yàn)設(shè)置模糊規(guī)則
縱向控制	直接式結(jié)構(gòu)控制		系統(tǒng)集成度高	過于依賴系統(tǒng)狀態(tài)信息，模型非線性度較高
縱向控制	分層式結(jié)構(gòu)控制		結(jié)構(gòu)簡單，易于實(shí)現(xiàn)，開發(fā)難度較低	忽略了參數(shù)不確定性以模型誤差的影響，建模準(zhǔn)確性相對較低

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