Abstract In large crowd events, there is always a potential possibility that a stampede accident will occur. The accident may cause injuries or even death. Approaches for controlling crowd flows and predicting dangerous congestion spots would be a boon to on-site authorities to manage the crowd and to prevent fatal accidents. One of the most popular approaches is real-time crowd simulation based on position data from personal Global Positioning System (GPS) devices. However, the accuracy of spatial data varies for different GPS devices, and it is also affected by an environment in which an event takes place. In this paper, we would like to assess the effect of position errors on stampede prediction. We propose an Automatic Real-time dEtection of Stampedes (ARES) method to predict stampedes for large events. We implement three different stampede assessment methods in Menge framework and incorporate position errors. Our analysis suggests that the probability of simulated stampede changes significantly with the increase of the magnitude of position errors, which cannot be eliminated entirely with the help of classic techniques, such as the Kalman filter. Thus, it is our position that novel stampede assessment methods should be developed, focusing on the detection of position noise and the elimination of its effect.
@cite_37: Utilizing both Assisted GPS (A-GPS) techniques and new high-sensitivity embedded GPS hardware, mobile phones are now able to achieve positioning in harsh environments such as urban canyons and indoor locations where older embedded GPS chips could not. This paper presents an empirical analysis of the positional accuracy of location data gathered using a high-sensitivity GPS-enabled mobile phone. The performance of the mobile phone is compared to that of regular recreational grade GPS receivers. Availability of valid GPS position fixes on the mobile phones tested was consistently close to 100 both outdoors and indoors. During static outdoor testing, positions provided by the mobile phones revealed a median horizontal error of between 5·0 and 8·5 m, substantially larger than those for regular autonomous GPS units by a factor of 2 to 3. Horizontal errors during static indoor testing were larger compared to outdoors, but the difference in accuracy between mobile phones and regular GPS receivers was reduced. Despite the modest performance of A-GPS on mobile phones, testing under various conditions revealed that very large errors are not very common. The maximum horizontal error during outdoor testing never exceeded 30 metres and during indoor testing never exceeded 100 metres. Combined with the relatively consistent availability of valid GPS position fixes under varying conditions, the current study has confirmed the reliability of A-GPS on mobiles phones as a source of location information for a range of different LBS applications.
@cite_12: The research tests the accuracy of two consumer grade GPS devices and two GPS-enabled Apple i-devices within an urban landscape. Data collection is an integral component to many GIS mapping projects, specifically within a community-based GIS mapping project. Access to reliable and spatially accurate data is key to the success of GIS mapping projects that require data collection. The relative low cost and availability of consumer grade GPS units and Apple i-devices with GPS capabilities are abundant, making the devices very attractive to community-based mapping projects. The comparison of four receivers utilized 15 locations, occurring over an 8-week period. Overall results indicated that the Garmin 78sc GPS receiver provided the greatest relative accuracy within an urban landscape, with the four devices mean relative accuracy ranging from 3.65 metres to 6.50 metres. The Apple i-devices maintained a relative accuracy and reliability for the needs of community-based mapping approaches, such as those being u...
@cite_7: At present GPS is applied to various situations because of its confidence and usefulness. Position calculated by GPS makes some errors caused from many different factors which GPS signals made. The greatest error factor which affects the accuracy and the precision of positioning by GPS is lack of the number of satellites you can see in the sky. To reduce this error factor and to improve the precision and accuracy of GPS positioning many projects are carried out research, such as QZSS, pseudolite system. These systems have potentiality to make the precision of GPS positioning under worse situation that you can see few GPS satellites because they increase the number of satellites which are available to use for position calculating. However, they require much time and expensive device for their infrastructure. We paid attention to GPS calculating method itself. We adapted Kalman filter to GPS positioning calculation. We improved the precision and accuracy of SPS positioning in stand-alone mode under worse situation adapted the Kalman filter parameter.
As a rule of thumb, the accuracy of GPS can be hugely affected by the environment. The U.S. government claimed that GPS-enabled smartphones are typically accurate to within 4.9 m; however, their accuracy worsens near buildings or other obstacles @cite_7 . Zandbergen and Barbeau's research showed that the horizontal error of GPS-enabled smartphones ranges from 5.0 m to 8.5 m @cite_37 . In 2015, Garnett and Stewart tested two personal GPS devices and two GPS-enabled mobile devices, and they found that the mean relative accuracy ranges from 3.65 m to 6.50 m @cite_12 .