Development of statistical models for improving efficiency of emergency evacuation in areas with vulnerable population. (February 2019)

• Record Type: Journal Article
• Authors: Dulebenets, Maxim A.; Abioye, Olumide F.; Ozguven, Eren Erman; Moses, Ren; Boot, Walter R.; Sando, Thobias
• Is Part Of: Reliability engineering & system safety. Volume 182(2019)
• Page Start: 233
• Page End: 249
• Publication Date: 2019-02
• Subjects: Emergency evacuation -- Evacuation routes -- Driving ability -- Driver characteristics -- Vulnerable population -- Natural hazard preparedness; Reliability (Engineering) -- Periodicals; System safety -- Periodicals; Industrial safety -- Periodicals; Fiabilité -- Périodiques; Sécurité des systèmes -- Périodiques; Sécurité du travail -- Périodiques; 620.00452
• DOI: 10.1016/j.ress.2018.09.021
• Languages: English
• ISSNs: 0951-8320

Abstract

Highlights: The driving ability of individuals is assessed under emergency evacuation. A wide range of factors is considered in the analysis. A driving simulator is used to collect the required data. A set of statistical models is developed to identify the most significant factors. The results from a statistical analysis reveal important managerial insights. Abstract: Different parts of the world are characterized by frequent occurrences of natural hazards. As such, evacuation planning is an essential part of the natural hazard preparedness, especially in hazard-prone areas. Numerous research efforts have been directed towards improving the efficiency of the evacuation process. However, only a limited number of studies have specifically aimed to identify factors, influencing the driving ability of individuals under emergency evacuation and the occurrence of crashes along the evacuation routes. Furthermore, previous research efforts have focused on a relatively narrow range of factors (primarily driver and traffic flow characteristics). This study aims to fill the existing gap in the state-of-the-art by investigating the effects of a wide range of different factors (including driver characteristics, evacuation route characteristics, driving conditions, and traffic characteristics) on the major driving performance indicators under emergency evacuation. The considered driving performance indicators include travel time, lane deviation, crash occurrence, collision speed, average acceleration pedal pressure, and average braking pedal pressure. A set of statistical models is developed to identify the most significant factors that influence the major driving performance indicators. These models are tested using the data collected from the driving simulator and participants with various socio-demographic characteristics. The results indicate that age, gender, visual disorders, number of lanes, and space headway may substantially impact the driving ability of individuals throughout the emergency evacuation process. Findings from this research can be incorporated within the existing transportation planning models to facilitate the natural hazard preparedness, ensure safety of evacuees, including vulnerable populations, and reduce or even prevent the occurrence of crashes along the evacuation routes.