Analysis on vehicle and walking speeds of search and rescue ground crews in mountainous areas

Ciesa, Marta; Grigolato, Stefano; Cavalli, Raffaele

doi:10.1016/j.jort.2014.03.004

Cited by 18 publications

(15 citation statements)

References 27 publications

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“…It is a mainly rocky area with a network of steep trails in a wilderness environment that discourages hiking by the inexperienced. 15 The Altopiano dei Sette Comuni is a karst plateau. This topography and a good forest road network enabled the development of more than 300 km of trails and approximately 430 km of forest roads, which both provide easy walks for the inexperienced.…”

Section: Study Areasmentioning

confidence: 99%

“…15 The first goal of the study was to gain an understanding of the rescue missions by analyzing the CNSAS SAR reports in 2 recreational and wilderness forest areas of the Veneto Prealps in Italy, one with a network of steep trails in a wild and rocky environment and the other with a network of gentle trails often in dense forest or areas of shrubs. A second goal was to highlight whether there were any differences between casualties and medical diagnoses for hiking and mountaineering activities in the 2 areas.…”

Section: Introductionmentioning

confidence: 99%

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Retrospective Study on Search and Rescue Operations in Two Prealps Areas of Italy

Ciesa

Grigolato

Cavalli

2015

Wilderness & Environmental Medicine

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Search and rescue missions in mountain areas are dangerous for rescuers and made difficult by the severe environment. The knowledge of accident characteristics is therefore very important and is necessary to reduce risks for tourists and healthcare costs. To tackle the problem of safety there is also a need for more information in the form of preventive education and publicity about the typical hazards.

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Section: Study Areasmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Retrospective Study on Search and Rescue Operations in Two Prealps Areas of Italy

Ciesa

Grigolato

Cavalli

2015

Wilderness & Environmental Medicine

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“…Secondly the knowledge of the roughness of specific roads can be implemented to help prediction of vibration intensities on different vehicles. Since induced vibrations are connected to several safety issues for the drivers and for the vehicles themselves, the availability of roughness data can allow an a priori definition of driving conditions (for instance in terms of maximum speed) and of access time (for instance in term of average speed and the consequent average time to travel one distance unit as suggested by Ciesa et al 2014).…”

Section: Discussionmentioning

confidence: 99%

“…In particular, road surface maintenance is often neglected, with the consequent rapid degradation of the base course by formation of potholes, surface ruts or corrugations (Mills et al 2007) and increment of the sediment production (Reid & Dunne 1984, Thompson et al 2010. A good gravel road maintenance level is also fundamental in areas with a strong propensity towards nature-based tourism and recreational activities (Sitzia et al 2016) as well for rapid search and rescue responses by ground transportation such as 4WD vehicles or All-Terrain Vehicles (ATV) (Ciesa et al 2014, Lischke et al 2001.…”

Section: Introductionmentioning

confidence: 99%

Determination of forest road surface roughness by Kinect depth imaging

et al. 2017

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Abstract. Roughness is a dynamic property of the gravel road surface that affects safety, ride comfort as well as vehicle tyre life and maintenance costs. A rapid survey of gravel road condition is fundamental for an effective maintenance planning and definition of the intervention priorities. Different non-contact techniques such as laser scanning, ultrasonic sensors and photogrammetry have recently been proposed to reconstruct three-dimensional topography of road surface and allow extraction of roughness metrics. The application of Microsoft Kinect™ depth camera is proposed and discussed here for collection of 3D data sets from gravel roads, to be implemented in order to allow quantification of surface roughness. The objectives are to: i) verify the applicability of the Kinect sensor for characterization of different forest roads, ii) identify the appropriateness and potential of different roughness parameters and iii) analyse the correlation with vibrations recoded by 3-axis accelerometers installed on different vehicles. The test took advantage of the implementation of the Kinect depth camera for surface roughness determination of 4 different forest gravel roads and one well-maintained asphalt road as reference. Different vehicles (mountain bike, off-road motorcycle, ATV vehicle, 4WD car and compact crossover) were included in the experiment in order to verify the vibration intensity when travelling on different road surface conditions. Correlations between the extracted roughness parameters and vibration levels of the tested vehicles were then verified. Coefficients of determination of between 0.76 and 0.97 were detected between average surface roughness and standard deviation of relative accelerations, with higher values in the case of lighter vehicles.

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“…This type of disasters need search for shortest/fastest evacuation routes and rescue routes. From the information of the beginning and terminal points of the remaining (after disaster) roads and bridges, the smallest route and distance can be computed for fastest rescue [41,42]. However, this information is not precise.…”

Section: Introductionmentioning

confidence: 99%

Interval Type 2 Fuzzy Set in Fuzzy Shortest Path Problem

Dey¹,

Pal

2016

Mathematics

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Abstract:The shortest path problem (SPP) is one of the most important combinatorial optimization problems in graph theory due to its various applications. The uncertainty existing in the real world problems makes it difficult to determine the arc lengths exactly. The fuzzy set is one of the popular tools to represent and handle uncertainty in information due to incompleteness or inexactness. In most cases, the SPP in fuzzy graph, called the fuzzy shortest path problem (FSPP) uses type-1 fuzzy set (T1FS) as arc length. Uncertainty in the evaluation of membership degrees due to inexactness of human perception is not considered in T1FS. An interval type-2 fuzzy set (IT2FS) is able to tackle this uncertainty. In this paper, we use IT2FSs to represent the arc lengths of a fuzzy graph for FSPP. We call this problem an interval type-2 fuzzy shortest path problem (IT2FSPP). We describe the utility of IT2FSs as arc lengths and its application in different real world shortest path problems. Here, we propose an algorithm for IT2FSPP. In the proposed algorithm, we incorporate the uncertainty in Dijkstra's algorithm for SPP using IT2FS as arc length. The path algebra corresponding to the proposed algorithm and the generalized algorithm based on the path algebra are also presented here. Numerical examples are used to illustrate the effectiveness of the proposed approach.

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Analysis on vehicle and walking speeds of search and rescue ground crews in mountainous areas

Cited by 18 publications

References 27 publications

Retrospective Study on Search and Rescue Operations in Two Prealps Areas of Italy

Retrospective Study on Search and Rescue Operations in Two Prealps Areas of Italy

Determination of forest road surface roughness by Kinect depth imaging

Interval Type 2 Fuzzy Set in Fuzzy Shortest Path Problem

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