Local traffic condition: improvement of a vehicle-based measurement approach

被引:1
|
作者
Knake-Langhorst, S. [1 ]
Schissel, C. [1 ]
机构
[1] German Aerosp Ctr DLR, Inst Transportat Syst, D-38108 Braunschweig, Germany
关键词
D O I
10.1049/iet-its:20070041
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Advanced driver assistance systems (ADAS) can be designed to adapt to the driver's current needs, for example, taking the traffic conditions in the immediate vicinity of the ego vehicle into account. This motivates the design of a system intended to measure the local traffic conditions in a way, which corresponds to the driver's perception of traffic conditions. A new method of measurement is introduced. It is based on automotive sensor technology. A stochastic approach is employed to optimise and evaluate the relationship between the subjective measurements made by the driver and the objective measurements presented. To this end, the drivers' subjective ratings are taken as reference. The analysis presented here is based on simulation data. The outcomes show that the design of the developed simulation environment is applicable to this work. It is shown that the objective measures correspond to the driver's subjective ratings. Thus, it is possible to estimate the driver's perception of traffic conditions using a technical measurement. The algorithm in its presented form is appropriate to give an estimation, which can be used as an input parameter for ADAS.
引用
收藏
页码:32 / 41
页数:10
相关论文
共 50 条
  • [41] Unmanned Aerial Vehicle-Based Traffic Analysis Methodological Framework for Automated Multivehicle Trajectory Extraction
    Khan, Muhammad Arsalan
    Ectors, Wim
    Bellemans, Tom
    Janssens, Davy
    Wets, Geert
    TRANSPORTATION RESEARCH RECORD, 2017, (2626) : 25 - 33
  • [42] Incorporating sustainability assessment in transportation planning: an urban transportation vehicle-based approach
    Mitropoulos, Lambros K.
    Prevedouros, Panos D.
    TRANSPORTATION PLANNING AND TECHNOLOGY, 2016, 39 (05) : 439 - 463
  • [43] Vehicle-based Hybrid Route Guidance System
    Jin, Qin
    Feng, Shi
    Hou Guirong
    PROCEEDINGS OF THE 27TH CHINESE CONTROL CONFERENCE, VOL 6, 2008, : 438 - 441
  • [44] Evaluation of Vehicle-Based Crash Severity Metrics
    Tsoi, Ada H.
    Gabler, Hampton C.
    TRAFFIC INJURY PREVENTION, 2015, 16 : S132 - S139
  • [45] KISTI Vehicle-based Urban Sensing Dataset
    Park, Minwoo
    Lee, Ryong
    Jang, Rae-young
    Lee, Sang-hwan
    2020 IEEE INTERNATIONAL CONFERENCE ON BIG DATA AND SMART COMPUTING (BIGCOMP 2020), 2020, : 601 - 604
  • [46] Autonomous underwater vehicle-based hydrographic sampling
    Levine, ER
    Connors, DN
    Shell, RR
    JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY, 1997, 14 (06) : 1444 - 1454
  • [47] Attitudes Toward Vehicle-Based Sensing and Recording
    Sleeper, Manya
    Schnorf, Sebastian
    Kemler, Brian
    Consolvo, Sunny
    PROCEEDINGS OF THE 2015 ACM INTERNATIONAL JOINT CONFERENCE ON PERVASIVE AND UBIQUITOUS COMPUTING (UBICOMP 2015), 2015, : 1017 - 1028
  • [48] Evaluation of vehicle-based tyre testing methods
    Albinsson, Anton
    Bruzelius, Fredrik
    Jacobson, Bengt
    Bakker, Egbert
    PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING, 2019, 233 (01) : 4 - 17
  • [49] A Method of Field Calibration For Vehicle-based SINS
    Li, Zheng
    Yang, Zheng-wei
    Zhang, Wei
    Shao, Ya-jun
    Li, Yin
    He, Hao-hao
    2016 13TH INTERNATIONAL CONFERENCE ON UBIQUITOUS ROBOTS AND AMBIENT INTELLIGENCE (URAI), 2016, : 42 - 46
  • [50] Analysis of time- and space-domain sampling for probe vehicle-based traffic information system
    Hong, Jun
    Zhang, Xuedan
    Chen, Jianshu
    Wei, Zhongya
    Cao, Jiannong
    Ren, Yong
    2007 IEEE INTELLIGENT TRANSPORTATION SYSTEMS CONFERENCE, VOLS 1 AND 2, 2007, : 433 - +