Individual Driving Behaviour in Wildfire Smoke

Abstract

This work presents the results of a virtual reality (VR) experiment aiming at investigating how individual driving behaviour is affected by the presence of wildfire smoke. The experiment included a driving simulation task to study the chosen driving speed at different smoke densities and the lateral position of the driven car on the road cross section. During the VR experiment, participants were presented with a simulated wildfire evacuation scenario including the presence of smoke through a head mounted display and were given a task to evacuate via car using a steering wheel and pedals on a single carriageway road with two lanes. A total of 46 participants took part in the experiments and their driven trajectories along with their instantaneous speed were collected in 5 different visibility conditions. Driving speed decreased with increasing smoke density. No difference in choice of speed was found in relation to the smoke density in the previously driven road segment (in thicker or thinner smoke). No difference in lateral position (closer to or further from the centreline of the road) at different smoke densities was found. Suggested correlations between driving speed and wildfire smoke density are provided in this paper, referring to either a fractional reduction of the speed in smoke-free conditions or an absolute choice of speed at a given visibility condition. These correlations are useful to provide more accurate estimation of evacuation times with traffic evacuation modelling tools in case of wildfire and wildland-urban interface fire scenarios.

Fire smoke dispersion inside and outside of a warehouse building in moderate and strong wind conditions

“…Furthermore, due to the significant reduction of visibility in the street over its whole width, and at a length of over 200 m, the street would have to be closed for the road traffic. Otherwise, the smoke obscuration in this area would affect the driving abilities [67] and significantly increase the risk of traffic accidents [68].…”

The verification of wildland–urban interface fire evacuation models

“…Traffic during wildfire evacuation can encounter smoke which can obscure the drivers' views and make it unsafe to drive at the usual speeds for that specific road type. This causes the adopted speeds to decrease with decreasing visibility conditions, in addition to the potential speed reduction already adopted for increasing traffic densities (Wetterberg et al 2021;Intini et al 2022).…”

“…The decision can be based on the shortest, fastest, or a specified route to a destination, and their availability. Other conditions may also affect this decision, such as the presence of smoke (Wetterberg et al 2021 ) or the choice of familiar routes by evacuees (Akbarzadeh and Wilmot 2015 ).…”

“…Route choice in traffic refers to the evacuee’s decision on which route to take to reach a destination (Wong et al 2020 ). This decision is tested separately from destination choice and can depend on the time or distance to traverse the route (faster or shorter) but can also be affected by other conditions such as route familiarity (Colonna et al 2016 ), or the smoke/fire conditions blocking or impeding a route (Wetterberg et al 2021 ). In other words, the traffic modeller should be able to consider the case in which the shortest route does not correspond to the fastest route (due to congestion).…”

Roxborough Park Community Wildfire Evacuation Drill: Data Collection and Model Benchmarking

“…Such a community might be required to evacuate to a place of relative safety in response to the conditions faced. The time for the community to reach safety is crucial as it determines whether residents avoid worsening (and possibly untenable) conditions [ 11 , 32 ]. The time for a community to reach a place of safety is an emergent property of its response, the infrastructure available, the information available, and the fire conditions experienced.…”