Pedestrian network map generation approaches and recommendation

被引:43
作者
Karimi, Hassan A. [1 ]
Kasemsuppakorn, Piyawan [2 ]
机构
[1] Univ Pittsburgh, Sch Informat Sci, Geoinformat Lab, Pittsburgh, PA 15260 USA
[2] Univ Thai Chamber Commerce, Sch Sci & Technol, Bangkok, Thailand
关键词
pedestrian network; collaborative mapping; image processing; map generation; location-based social networking; PHYSICAL-ACTIVITY;
D O I
10.1080/13658816.2012.730148
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
With the advanced capabilities of mobile devices and the success of car navigation systems, interest in pedestrian navigation systems is on the rise. A critical component of any navigation system is a map database, which represents a network (e.g., road networks for car navigation) and supports key functionality such as map display, geocoding, and routing. Road networks, mainly due to the popularity of car navigation systems, are well defined and publicly available. However, in pedestrian navigation systems, as well as other applications including urban planning and physical activity studies, road networks do not adequately represent the paths that pedestrians usually travel. Currently, there is a void in literatures discussing the challenges, methods, and best practices for pedestrian network map generation. This coupled with the increased demand for pedestrian networks is the prime motivation for development of new approaches and algorithms to automatically generating pedestrian networks. Three approaches, network buffering, using existing road networks, collaborative mapping, using Global Positioning System (GPS) traces collected by volunteers, and image processing, using high-resolution satellite and laser imageries, were implemented and evaluated with a pedestrian network baseline as a ground truth. The results of the experiments indicate that these three approaches, while differing in complexity and outcome, are viable for automatic pedestrian network map generation. The recommendation of a suitable approach for generating pedestrian networks for a given set of sources and requirements is provided.
引用
收藏
页码:947 / 962
页数:16
相关论文
共 26 条
  • [1] [Anonymous], P 2 INT CONV REH ENG
  • [2] [Anonymous], PHOTOGRAMMETRIC ENG
  • [3] [Anonymous], 1980, Multivariate Analysis
  • [4] [Anonymous], 2009, P 2009 INT WORKSH LO
  • [5] Mapping for wheelchair users: Route navigation in urban spaces
    Beale, L
    Field, K
    Briggs, D
    Picton, P
    Matthews, H
    [J]. CARTOGRAPHIC JOURNAL, 2006, 43 (01) : 68 - 81
  • [6] Accessibility and connectivity in physical activity studies: The impact of missing pedestrian data
    Chin, Gary K. W.
    Van Niel, Kimberly P.
    Giles-Corti, Billie
    Knuiman, Mathew
    [J]. PREVENTIVE MEDICINE, 2008, 46 (01) : 41 - 45
  • [7] DCNR, 2011, PAMAP DIG BAS MAP PE
  • [8] Extracting road information from recorded GPS data using snap-drift neural network
    Ekpenyong, Frank
    Palmer-Brown, Dominic
    Brimicombe, Allan
    [J]. NEUROCOMPUTING, 2009, 73 (1-3) : 24 - 36
  • [9] Elias B, 2007, WORKS POSIT NAVIGAT, P41
  • [10] Obesity relationships with community design, physical activity, and time spent in cars
    Frank, LD
    Andresen, MA
    Schmid, TL
    [J]. AMERICAN JOURNAL OF PREVENTIVE MEDICINE, 2004, 27 (02) : 87 - 96