Effectiveness Analysis on Human-Machine Information Interaction of Intelligent Highway

被引:2
作者
Zhou, Yicheng [1 ]
Sun, Tuo [2 ]
Wen, Shunzhi [1 ]
Zhong, Hao [2 ]
Cui, Youkai [1 ]
Xie, Jiemin [3 ]
Wu, Wei [1 ]
Ma, Wanjing [2 ]
机构
[1] Zhejiang Inst Commun Co Ltd, Hangzhou 310030, Zhejiang, Peoples R China
[2] Tongji Univ, Key Lab Rd & Traff Engn, Minist Educ, Shanghai 201804, Peoples R China
[3] Sun Yat Sen Univ, Sch Intelligent Syst Engn, Guangzhou 510275, Peoples R China
基金
中国国家自然科学基金;
关键词
NASA;
D O I
10.1155/2022/2728984
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Different human-machine collaboration modes and driving simulation tests with the orthogonal method considered are designed for a series of typical intelligent highway landscapes. The feedback of drivers under different interaction modes is evaluated through NASA-LTX questionnaire, driving simulator, eye tracker, and electroencephalograph (EEG). This optimal interaction mode (including voice form, broadcasting timing, and frequency) of each driving assistance scene in CVI (Cooperative Vehicle Infrastructure) environment under the conditions of high and low traffic is determined from subjective and objective perspectives. In accordance with feedback of these subjects on each set scene, the voice information structure of each assistance mode plays the most important role on drivers followed by the broadcasting timing and frequency. These broadcasts which provide good effects include scenarios such as various assistance scenes at curves and an early warning timing at a long-distance trip as well as a high early warning frequency; in addition, as for an exit-tip assistance scenario, a voice mode assistance is preferred; and for various speed assistance scenes, the beep mode is better. Furthermore, it is found that, at a higher traffic level but a short-distance trip, an early warning timing is favored generally for various scenes while under a low traffic level, a long-distance early warning timing is better.
引用
收藏
页数:9
相关论文
共 12 条
  • [1] [Anonymous], 2005, P 19 INT TECHN C ENH
  • [2] Evaluation of Driver Performance and Distraction During Use of In-Vehicle Signing Information
    Creaser, Janet
    Manser, Michael
    [J]. TRANSPORTATION RESEARCH RECORD, 2013, (2365) : 1 - 9
  • [3] A Novel Active Heads-Up Display for Driver Assistance
    Doshi, Anup
    Cheng, Shinko Yuanhsien
    Trivedi, Mohan Manubhai
    [J]. IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 2009, 39 (01): : 85 - 93
  • [4] Fung C.P., 2007, P 20 INT TECHN C ENH, P1
  • [5] Galy E., 2018, ERGONOMICS, V61, P517, DOI DOI 10.1080/00140139.2017.1369583
  • [6] Cooperation between driver and automated driving system: Implementation and evaluation
    Guo, Chunshi
    Sentouh, Chouki
    Popieul, Jean-Christophe
    Haue, Jean-Baptiste
    Langlois, Sabine
    Loeillet, Jean-Jacques
    Soualmi, Boussaad
    Thomas Nguyen That
    [J]. TRANSPORTATION RESEARCH PART F-TRAFFIC PSYCHOLOGY AND BEHAVIOUR, 2019, 61 : 314 - 325
  • [7] Augmented Reality Through the Lens of Eye Tracking
    Josephson, Sheree
    Myers, Melina
    [J]. VISUAL COMMUNICATION QUARTERLY, 2019, 26 (04) : 208 - 222
  • [8] Katona J, 2016, INT CONF COGN INFO, P251, DOI 10.1109/CogInfoCom.2016.7804557
  • [9] Lu X., 2014, RAILWAY TRANSPORT EC, V36, P15
  • [10] Auditory alerts for in-vehicle information systems: The effects of temporal conflict and sound parameters on driver attitudes and performance
    Wiese, E
    Lee, J
    [J]. ERGONOMICS, 2004, 47 (09) : 965 - 986