Analysis of vehicle stability loss due to strong crosswind gusts using web services in the route planning process

Igor Betkier; Szymon Mitkow; Magdalena Kijek

doi:10.5604/01.3001.0014.0207

Authors

Igor Betkier Military Transportation Headquarter in Warsaw, Warsaw, Poland Author https://orcid.org/0000-0002-5437-7669
Szymon Mitkow Military University of Technology, Faculty of Logistics, Institute of Logistics, Warsaw, Poland Author https://orcid.org/0000-0003-2845-2589
Magdalena Kijek Military University of Technology, Faculty of Logistics, Institute of Logistics, Warsaw, Poland Author https://orcid.org/0000-0002-2557-5287

DOI:

https://doi.org/10.5604/01.3001.0014.0207

Keywords:

crosswind, transportation planning, vehicle stability, web applications, route planning

Abstract

Weather conditions play a significant role in road safety. One of its component is a wind influence, which may be affected the moving vehicle from different angles. The final result of such action can take typical kinds of behavior like overturn, slideslip and rotation. Accordingly, vehicles with high side profile are particularly vulnerable to such specific phenomena, what made the planning process more difficult and complex. The article analyses possibilities of a stability loss of a truck vehicle due to strong crosswind gusts. The authors synthesized the model proposed in the literature with available web technologies and the needs of a transport market. Moreover, a method which evaluate a danger of reaching the friction limit by all of the vehicle wheels (slideslip) was developed and is practicable to use. The proposed solution is based on the RESTful API of the weather and web mapping services which allows to collate a direction and a force of wind with a direction of movement and a side profile of the vehicle moving between two locations. What is more a weather forecast is allowed to adopt appropriate variables to compute the air density and evaluate friction coefficients. From the other hand the method uses actual parameters of a vehicle such as axle loads, distance between axles, center of mass location and kind of axle (driven or not). The assumption, which consist in sequencing routes for smaller parts, made it possible to achieve the high accuracy of results on tested areas. The proposed method is simple to implement in any programming language and it can be extended by new functionalities. The analyzed issue can also be a starting point for intelligent systems that can be used in autonomous vehicles.

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