MATEC Web Conf.
Volume 192, 2018The 4th International Conference on Engineering, Applied Sciences and Technology (ICEAST 2018) “Exploring Innovative Solutions for Smart Society”
|Number of page(s)||4|
|Section||Track 1: Industrial Engineering, Materials and Manufacturing|
|Published online||14 August 2018|
Allocation strategy for an ambulance base under traffic congestion
Department of Industrial Engineering, Faculty of Engineering, King Mongkut’s Institute of Technology Ladkrabang, Bangkok, Thailand
2 Department of Information technology, Faculty of Science and Arts, Burapha University, Chanthaburi, Thailand
3 Department of Industrial Engineering & Management National Taipei University of Technology (Taipei Tech), Taipei, Taiwan
Corresponding author : email@example.com
One of crucial issues for emergency medical service (EMS) is to reduce response time. However, in metropolis city, a traffic congestion is an obstacle for an ambulance to responsively reach at the scene, then patient mortality and disability rates increase. Traffic congestion is considered as a complex spatial–temporal situation. It is often triggered by repeating factors, such as car lane capacity, weather, and unexpected events. Therefore, a real-time traffic condition is required to effectively determine the location of an ambulance. The current ambulance base allocation strategy model considers only demand point, resulting inability to handle high traffic congestion. This paper proposed a covering model based on traffic congestion (using Google map API) to allocate ambulance bases that covering all demand point, while minimizing the number of the ambulance. In addition, our model was applied to the case study of Bangkok EMS.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.