Applied Sciences

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22 pages, 31076 KiB

Open AccessArticle

Resilience Assessment of a Twin-Tube Motorway Tunnel in the Event of a Traffic Accident or Fire in a Tube

by Ciro Caliendo, Isidoro Russo and Gianluca Genovese

Appl. Sci. 2022, 12(1), 513; https://doi.org/10.3390/app12010513 - 05 Jan 2022

Cited by 7 | Viewed by 2457

We have developed a traffic simulation model to quantitatively assess the resilience of a twin-tube motorway tunnel in the event of traffic accident or fire occurring within a tube. The motorway section containing the tunnel was investigated for different possible scenarios including its [...] Read more.

We have developed a traffic simulation model to quantitatively assess the resilience of a twin-tube motorway tunnel in the event of traffic accident or fire occurring within a tube. The motorway section containing the tunnel was investigated for different possible scenarios including its partial or complete closure. The functionality of the road infrastructure, in the case of an accident in one of the two tubes (each tube presents two lanes with unidirectional traffic under ordinary conditions), was assumed to be recovered both by using the remaining undisrupted lane of the tube interested by the disruptive event (only one lane is closed) and reorganizing the traffic flow by utilizing the adjacent tube for bi-directional traffic (both lanes are closed). The effects of an alternative itinerary individualized in the corresponding open road network were also examined. The level of functionality of the system during the period in which the tube is partially or completely closed was computed as the ratio between the average travel time required to reach a given destination from a specific origin before and after the occurrence of the disruptive event. The resilience metrics were assumed to be resilience loss, recovery speed, and resilience index. The best scenario was found to be the partial closure of the tube in contrast to the complete one. However, in order to contain the negative effects on the functionality of the motorway section due to the complete closure of the tube, it is worth highlighting how the traffic by-pass before the entrance portal of the closed tube should be open in a very short time by the tunnel management team to allow for the quick use of the adjacent tube for bi-directional traffic. An additional improvement, with reference exclusively to passenger cars traveling through the adjacent unblocked tube, might be obtained by activating the variable message signs, located at a sufficient distance from the motorway junction before the entrance portal of the closed tube, in order to suggest an alternative route to heavy good vehicles (HGVs) only. Whereas, when the alternative itinerary is used by all vehicles traveling towards the blocked tube (i.e., both passenger cars and HGVs), this redirectioning of the motorway traffic flow was found to be characterized by an excessive travel time, with it therefore not being advisable. The results obtained might be useful as a decision-making support tool aimed at improving the resilience of twin-tube tunnels. Full article

(This article belongs to the Special Issue Risk Assessment in Traffic and Transportation)

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12 pages, 1313 KiB

Open AccessArticle

Risk Prediction for Winter Road Accidents on Expressways

by Daeseong Kim, Sangyun Jung and Sanghoo Yoon

Appl. Sci. 2021, 11(20), 9534; https://doi.org/10.3390/app11209534 - 14 Oct 2021

Cited by 8 | Viewed by 1830

Abstract

Road accidents caused by weather conditions in winter lead to higher mortality rates than in other seasons. The main causes of road accidents include human carelessness, vehicle defects, road conditions, and weather factors. If the risk of road accidents with changes in road [...] Read more.

Road accidents caused by weather conditions in winter lead to higher mortality rates than in other seasons. The main causes of road accidents include human carelessness, vehicle defects, road conditions, and weather factors. If the risk of road accidents with changes in road weather conditions can be quantitatively evaluated, it will contribute to reducing the road accident fatalities. The road accident data used in this study were obtained for the period 2017 to 2019. Spatial interpolation estimated the weather information; geographic information system (GIS) and Shuttle Radar Topography Mission (SRTM) data identified road geometry and accident area altitude; synthetic minority oversampling technique (SMOTE) addressed the data imbalance problem between road accidents due to weather conditions and from other causes, and finally, machine learning was performed on the data using various models such as random forest, XGBoost, neural network, and logistic regression. The training- to test data ratio was 7:3. Random forest model exhibited the best classification performance for road accident status according to weather risks. Thus, by applying weather data and road geometry to machine learning models, the risk of road accidents due to weather conditions in the winter season can be predicted and provided as a service. Full article

(This article belongs to the Special Issue Risk Assessment in Traffic and Transportation)

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16 pages, 3575 KiB

Open AccessArticle

Detection Model on Fatigue Driving Behaviors Based on the Operating Parameters of Freight Vehicles

by Jianfeng Xi, Shiqing Wang, Tongqiang Ding, Jian Tian, Hui Shao and Xinning Miao

Appl. Sci. 2021, 11(15), 7132; https://doi.org/10.3390/app11157132 - 02 Aug 2021

Cited by 7 | Viewed by 1599

Abstract

Whether in developing or developed countries, traffic accidents caused by freight vehicles are responsible for more than 10% of deaths of all traffic accidents. Fatigue driving is one of the main causes of freight vehicle accidents. Existing fatigue driving studies mostly use vehicle [...] Read more.

Whether in developing or developed countries, traffic accidents caused by freight vehicles are responsible for more than 10% of deaths of all traffic accidents. Fatigue driving is one of the main causes of freight vehicle accidents. Existing fatigue driving studies mostly use vehicle operating data from experiments or simulation data, exposing certain drawbacks in the validity and reliability of the models used. This study collected a large quantity of real driving data to extract sample data under different fatigue degrees. The parameters of vehicle operating data were selected based on significant driver fatigue degrees. The

k

-nearest neighbor algorithm was used to establish the detection model of fatigue driving behaviors, taking into account influence of the number of training samples and other parameters in the accuracy of fatigue driving behavior detection. With the collected operating data of 50 freight vehicles in the past month, the fatigue driving behavior detection models based on the

k

-nearest neighbor algorithm and the commonly used BP neural network proposed in this paper were tested, respectively. The analysis results showed that the accuracy of both models are 75.9%, but the fatigue driving detection model based on the

k

-nearest neighbor algorithm is more reliable. Full article

(This article belongs to the Special Issue Risk Assessment in Traffic and Transportation)

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18 pages, 2727 KiB

Open AccessArticle

Traffic Accident Risk Assessment Framework for Qassim, Saudi Arabia: Evaluating the Impact of Speed Cameras

by Meshal Almoshaogeh, Radfan Abdulrehman, Husnain Haider, Fawaz Alharbi, Arshad Jamal, Saif Alarifi and Md. Shafiquzzaman

Appl. Sci. 2021, 11(15), 6682; https://doi.org/10.3390/app11156682 - 21 Jul 2021

Cited by 27 | Viewed by 3932

Abstract

Saudi Arabia is one of the countries with the highest number of road accidents and associated fatalities in the world. Speeding has been identified as an important cause of increased traffic accidents, which also aggravate their severity. Road safety improvement strategies are primarily [...] Read more.

Saudi Arabia is one of the countries with the highest number of road accidents and associated fatalities in the world. Speeding has been identified as an important cause of increased traffic accidents, which also aggravate their severity. Road safety improvement strategies are primarily based on the accurate identification of accident hotspots. Installing speed cameras at a network level is an expensive road safety measure, and its spatiotemporal effectiveness should be assessed. In this study, a traffic accident risk assessment framework has been developed and implemented on the 84 km long Buraydah Ring Road in the Qassim region of Saudi Arabia. The selected highway was divided into 42 (×2 km long) segments using the ArcGIS software. A risk scoring scheme was developed to incorporate both the frequency and severity of road accidents. Speed cameras installation at various segments showed a 70% decline in total accident counts, 53% in accidents with property damage, 84% decline in accidents causing injury, and complete absence of accidents with fatalities. The 48% segments were identified as hotspots with risk level ≥ medium, while the speed cameras installation completely eliminated the hotspots from the study area. The proposed framework can be implemented on major high-speed highways, accommodating high traffic volumes, for hotspot identification and evaluation of various road safety measures in Saudi Arabia and elsewhere. Full article

(This article belongs to the Special Issue Risk Assessment in Traffic and Transportation)

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15 pages, 4133 KiB

Open AccessArticle

Effect Evaluation of Forward Collision Warning System Using IoT Log and Virtual Driving Simulation Data

by Hyungkyu Kim, Byungkon Kim and Doyoung Jung

Appl. Sci. 2021, 11(13), 6045; https://doi.org/10.3390/app11136045 - 29 Jun 2021

Cited by 2 | Viewed by 1832

Abstract

Advanced driver-assistance systems (ADAS) are primarily known for their positive impact in improving the safety of drivers. Previous studies primarily analyzed the positive effects of ADAS with short-term experiments and accident data without considering the long-term changes in drivers’ safety perception. The human [...] Read more.

Advanced driver-assistance systems (ADAS) are primarily known for their positive impact in improving the safety of drivers. Previous studies primarily analyzed the positive effects of ADAS with short-term experiments and accident data without considering the long-term changes in drivers’ safety perception. The human factor is the most dominant among factors that cause traffic accidents, and safety effect evaluation should be performed considering changes in human errors. To this end, this study classified the safety effect of ADAS-forward collision warning (FCW) on taxi drivers in Seoul into behavioral control and attitude change to perform analysis on respective factors. With regard to behavioral control, virtual driving simulation was used to analyze the reaction time of drivers and deceleration rate, and for attitude change, autoregressive integrated moving average (ARIMA) time series analysis was employed to predict the long-term perception change of drivers. The analysis results indicated that, in terms of behavioral control, ADAS-FCW reduces the cognitive reaction time of drivers in risk situations on the road, similar to the findings in previous studies. However, in terms of attitude change, ADAS-FCW has the adverse long-term effect of increasing violations in maintaining safety distance in the case of nighttime-drivers under 60 years old. As can be seen from these results, new technologies in the road safety arena can have a short-term effect of improving safety with behavioral control but may have a negative impact in the long term. The results of this study are expected to provide a theoretical basis for reference in the safety evaluation of ADAS and traffic safety facilities. Full article

(This article belongs to the Special Issue Risk Assessment in Traffic and Transportation)

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15 pages, 4561 KiB

Open AccessArticle

Do Heavy Vehicles Always Have a Negative Effect on Traffic Flow?

by Chang-Gyun Roh, Hyeonmyeong Jeon and Bongsoo Son

Appl. Sci. 2021, 11(12), 5520; https://doi.org/10.3390/app11125520 - 15 Jun 2021

Cited by 4 | Viewed by 2389

Abstract

The purpose of this study is to analyze the effect of heavy vehicles on traffic flow on a two-lane highway. To achieve this goal, data was obtained from piezosensors on the Seoul–Chuncheon Expressway. Analysis of the data showed that, as everyone knows, the [...] Read more.

The purpose of this study is to analyze the effect of heavy vehicles on traffic flow on a two-lane highway. To achieve this goal, data was obtained from piezosensors on the Seoul–Chuncheon Expressway. Analysis of the data showed that, as everyone knows, the average speed of traffic flows decreases as the proportion of heavy vehicles increases. However, not only the speed decreased, but the speed deviation between vehicles decreased. In other words, it was found that within the traffic group that formed the same platoon, individual vehicles were forced to form similar speeds, resulting in a homogeneous rate. This means that heavy vehicles can be included in the traffic stream, reducing the chances of a vehicle-to-vehicle conflict. This kind of influence can be said to explain that heavy vehicles do not necessarily have a negative effect on traffic flow. In this way, we expect to be able to study ways to manage traffic flow by using the effects of low-speed vehicles. Full article

(This article belongs to the Special Issue Risk Assessment in Traffic and Transportation)

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21 pages, 3590 KiB

Open AccessArticle

The Impact of Obstacle’s Risk in Pedestrian Agent’s Local Path-Planning

by Thanh-Trung Trinh and Masaomi Kimura

Appl. Sci. 2021, 11(12), 5442; https://doi.org/10.3390/app11125442 - 11 Jun 2021

Cited by 2 | Viewed by 2017

Abstract

While the risk from the obstacle could significantly alter the navigation path of a pedestrian, this problem is often disregarded by many studies in pedestrian simulation, or is hindered by a simplistic simulation approach. To address this problem, we proposed a novel simulation [...] Read more.

While the risk from the obstacle could significantly alter the navigation path of a pedestrian, this problem is often disregarded by many studies in pedestrian simulation, or is hindered by a simplistic simulation approach. To address this problem, we proposed a novel simulation model for the local path-planning process of the pedestrian agent, adopting reinforcement learning to replicate the navigation path. We also addressed the problem of assessing the obstacle’s risk by determining its probability of collision with the obstacle, combining with the danger from the obstacle. This process is subsequently incorporated with our prediction model to provide an accurate navigation path similar to the human thinking process. Our proposed model’s implementation demonstrates a more favorable result than other simulation models, especially in the case of the obstacle’s appearance. The pedestrian agent is capable of assessing the risk from the obstacle in different situations and adapting the navigation path correspondingly. Full article

(This article belongs to the Special Issue Risk Assessment in Traffic and Transportation)

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26 pages, 7606 KiB

Open AccessArticle

A Numerical Study for Assessing the Risk Reduction Using an Emergency Vehicle Equipped with a Micronized Water System for Contrasting the Fire Growth Phase in Road Tunnels

by Ciro Caliendo, Gianluca Genovese and Isidoro Russo

Appl. Sci. 2021, 11(11), 5248; https://doi.org/10.3390/app11115248 - 05 Jun 2021

Cited by 9 | Viewed by 2077

Abstract

We performed Computational Fluid Dynamics (CFD) modeling, and simulated a people evacuation process from a tunnel in the event of a fire, for evaluating the potentialities of using, as a temporary safety measure, an emergency vehicle equipped with a micronized water system for [...] Read more.

We performed Computational Fluid Dynamics (CFD) modeling, and simulated a people evacuation process from a tunnel in the event of a fire, for evaluating the potentialities of using, as a temporary safety measure, an emergency vehicle equipped with a micronized water system for contrasting the fire growth phase. The structure investigated is a one-way road tunnel with only natural ventilation, and with a length less than 1000 m. The tunnel is assumed at present to be affected by refurbishment works for making it comply with the minimum safety requirements of the European Directive 2004/54/EC. In particular, it is considered that it has not yet been provided with hydrants, and with the sidewalks and the emergency exit which are still under construction. This means that users are forced to use the road carriageway for escaping from the tunnel if a fire occurs. The CFD findings have shown that the use of the micronized water system might lead to a significant improvement in the environmental conditions along the escape route since the tenability limits of temperature, radiant heat flux, CO and CO₂ concentration were found to be better satisfied. Additionally, the visibility distance was shown to increase, even though it was found to be higher than the acceptable threshold value only in a few cases. However, the quantitative risk analysis based on a probabilistic approach, which was combined with a method currently used in Europe for assessing the risk due to the transit of only dangerous goods, shows that the final cumulative F-N curves related to the micronized water system always lie below those without the mentioned system, and in addition, they are always contained within the limits of the ALARP region. It is to be stressed that our paper might represent a reference in showing the effectiveness of the micronized water system as a temporary safety measure. However, it is desirable that the Tunnel Management Agencies accelerate the refurbishment works for making road tunnels definitively safer for users in a short period of time. Full article

(This article belongs to the Special Issue Risk Assessment in Traffic and Transportation)

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14 pages, 4484 KiB

Open AccessArticle

Use of Pupil Area and Fixation Maps to Evaluate Visual Behavior of Drivers inside Tunnels at Different Luminance Levels—A Pilot Study

by Li Qin, Qi-Lei Cao, Arturo S. Leon, Ying-Na Weng and Xu-Hua Shi

Appl. Sci. 2021, 11(11), 5014; https://doi.org/10.3390/app11115014 - 28 May 2021

Cited by 5 | Viewed by 2282

Abstract

This study reports the results of a pilot study on spatiotemporal characteristics of drivers’ visual behavior while driving in three different luminance levels in a tunnel. The study was carried out in a relatively long tunnel during the daytime. Six experienced drivers were [...] Read more.

This study reports the results of a pilot study on spatiotemporal characteristics of drivers’ visual behavior while driving in three different luminance levels in a tunnel. The study was carried out in a relatively long tunnel during the daytime. Six experienced drivers were recruited to participate in the driving experiment. Experimental data of pupil area and fixation point position (at the tunnel’s interior zone: 1566 m long) were collected by non-intrusive eye-tracking equipment at three luminance levels (2 cd/m², 2.5 cd/m², and 3 cd/m²). Fixation maps (color-coded maps presenting distributed data) were created based on fixation point position data to quantify changes in visual behavior. The results demonstrated that luminance levels had a significant effect on pupil areas and fixation zones. Fixation area and average pupil area had a significant negative correlation with luminance levels during the daytime. In addition, drivers concentrated more on the front road pavement, the top wall surface, and the cars’ control wheels. The results revealed that the pupil area had a linear relationship with the luminance level. The limitations of this research are pointed out and the future research directions are also prospected. Full article

(This article belongs to the Special Issue Risk Assessment in Traffic and Transportation)

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21 pages, 2634 KiB

Open AccessArticle

Risk Analysis of One-Way Road Tunnel Tube Used for Bi-Directional Traffic under Fire Scenarios

by Ciro Caliendo, Isidoro Russo and Gianluca Genovese

Appl. Sci. 2021, 11(7), 3198; https://doi.org/10.3390/app11073198 - 02 Apr 2021

Cited by 8 | Viewed by 2221

Abstract

We have set up a Computational Fluid Dynamics (CFD) modeling, and performed a user evacuation model, for evaluating the risk level in one-way road tunnel tube when used for bi-directional traffic in particular circumstances. The simulations were carried out by considering both peak-hour [...] Read more.

We have set up a Computational Fluid Dynamics (CFD) modeling, and performed a user evacuation model, for evaluating the risk level in one-way road tunnel tube when used for bi-directional traffic in particular circumstances. The simulations were carried out by considering both peak-hour traffic volumes during the day and off-peak hours overnight. The investigated one-way tube is ventilated by natural ventilation only, and has a length of less than 1000 m. With reference to the worst environmental conditions, which are downstream of the fire due to the direction of natural ventilation, the consequences on escaping users, caused by different types of burning vehicles located in various longitudinal positions along the tube, are shown. The results prove the positive effects on environmental conditions (in terms of temperature, visibility distance, CO and CO₂ concentration) along the user evacuation path when the tube is used for bi-directional traffic at night rather than daytime. Only for the case of 100 MW fire and in the proximity of the exit portal, the last escaping user might be affected by a visibility distance and CO concentration exceeding the threshold values. In this special case, countermeasures for reducing smoke concentration or emergency services at the portals should be provided. However, the quantitative risk analysis, based on a probabilistic approach, showed that the F-N curve of the tube when used for bi-directional traffic with reference to the night always lies below that of the daytime, and the reduction in the risk level is between 80 and 100% for the night traffic compared to daytime one. It is to be focused on the fact that our modeling may represent a reference in investigating the effects of hourly traffic volumes on the risk level in tunnels and may help decisionmakers in understanding when to temporarily close a tube for maintenance, repair, or rehabilitation activities and use the adjacent tube for bi-directional traffic. Full article

(This article belongs to the Special Issue Risk Assessment in Traffic and Transportation)

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15 pages, 1096 KiB

Open AccessArticle

Modeling of Railway Stations Based on Queuing Networks

by Igor Bychkov, Alexander Kazakov, Anna Lempert and Maxim Zharkov

Appl. Sci. 2021, 11(5), 2425; https://doi.org/10.3390/app11052425 - 09 Mar 2021

Cited by 16 | Viewed by 3592

Abstract

Among the micro-logistic transport systems, railway stations should be highlighted, such as one of the most important transport infrastructure elements. The efficiency of the transport industry as a whole depends on the quality of their operation. Such systems have a complex multi-level structure, [...] Read more.

Among the micro-logistic transport systems, railway stations should be highlighted, such as one of the most important transport infrastructure elements. The efficiency of the transport industry as a whole depends on the quality of their operation. Such systems have a complex multi-level structure, and the incoming traffic flow often has a stochastic character. It is known that the most effective approach to study the operation of such systems is mathematical modeling. Earlier, we proposed an approach to transport hub modeling using multiphase queuing systems with a batch Markovian arrival process (BMAP) as an incoming flow. In this paper, we develop the method by applying more complex models based on queuing networks that allow us to describe in detail the route of requests within an object with a non-linear hierarchical structure. This allows us to increase the adequacy of modeling and explore a new class of objects—freight railway stations and marshalling yards. Here we present mathematical models of two railway stations, one of which is a freight railway station located in Russia, and the other is a marshalling yard in the USA. The models have the form of queuing networks with BMAP flow. They are implemented as simulation software, and a numerical experiment is carried out. Based on the numerical results, some “bottlenecks” in the structure of the studied stations are determined. Moreover, the risk of switching to an irregular mode of operation is assessed. The proposed method is suitable for describing a wide range of cargo and passenger transport systems, including river ports, seaports, airports, and multimodal transport hubs. It allows a primary analysis of the hub operation and does not need large statistical information for parametric identification. Full article

(This article belongs to the Special Issue Risk Assessment in Traffic and Transportation)

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19 pages, 625 KiB

Open AccessArticle

Dynamic Railway Derailment Risk Analysis with Text-Data-Based Bayesian Network

by Liu Yang, Keping Li, Guozheng Song and Faisal Khan

Appl. Sci. 2021, 11(3), 994; https://doi.org/10.3390/app11030994 - 22 Jan 2021

Cited by 7 | Viewed by 2039

Abstract

In recent years, transportation system safety analysis has become increasingly challenging and highly demanding. Unstructured data contain sufficient information from which inherent interactions can be extracted. Determining how to process and fuse a large amount of unstructured data is a challenging task. In [...] Read more.

In recent years, transportation system safety analysis has become increasingly challenging and highly demanding. Unstructured data contain sufficient information from which inherent interactions can be extracted. Determining how to process and fuse a large amount of unstructured data is a challenging task. In this paper, we propose a text-based Bayesian network (TBN) method to establish a Bayesian network (BN) based on text records, where the BN’s arcs are obtained from barrier relationships identified by a graphical model and its prior probabilities stem from fault trees. The comparative experimental results illustrate that the text-based method in TBN is efficient. The precision, recall and F-measure of TBN are 8.64%, 10.70% and 9.84% higher, respectively, than the most frequent (MF) result. Moreover, compared to the traditional BN, whose prior probabilities are frequently acquired from experts, the prior probabilities of the proposed text-based BN (TBN) have a high confidence. The experimental results of a train derailment accident case study show that with changes in the train derailment probabilities and the safety potentials of the barriers, the TBN generates quantitative results and reveals the critical risks of derailment accidents. Additionally, this work demonstrates relevant nonlinear relationships to improve the assessment results. Therefore, based on text-based data, this study reveals that barrier safety analysis has the potential to identify high-risk barriers, which can guide managers to enhance these barriers. Full article

(This article belongs to the Special Issue Risk Assessment in Traffic and Transportation)

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16 pages, 1945 KiB

Open AccessArticle

Risk Analysis of Road Tunnels: A Computational Fluid Dynamic Model for Assessing the Effects of Natural Ventilation

by Ciro Caliendo, Gianluca Genovese and Isidoro Russo

Appl. Sci. 2021, 11(1), 32; https://doi.org/10.3390/app11010032 - 23 Dec 2020

Cited by 12 | Viewed by 2485

Abstract

We have developed an appropriate Computational Fluid Dynamics (CFD) model for assessing the exposure to risk of tunnel users during their evacuation process in the event of fire. The effects on escaping users, which can be caused by fire from different types of [...] Read more.

We have developed an appropriate Computational Fluid Dynamics (CFD) model for assessing the exposure to risk of tunnel users during their evacuation process in the event of fire. The effects on escaping users, which can be caused by fire from different types of vehicles located in various longitudinal positions within a one-way tunnel with natural ventilation only and length less than 1 km are shown. Simulated fires, in terms of maximum Heat Release Rate (HRR) are: 8, 30, 50, and 100 MW for two cars, a bus, and two types of Heavy Goods Vehicles (HGVs), respectively. With reference to environmental conditions (i.e., temperatures, radiant heat fluxes, visibility distances, and CO and CO₂ concentrations) along the evacuation path, the results prove that these are always within the limits acceptable for user safety. The exposure to toxic gases and heat also confirms that the tunnel users can safely evacuate. The evacuation time was found to be higher when fire was related to the bus, which is due to a major pre-movement time required for leaving the vehicle. The findings show that mechanical ventilation is not necessary in the case of the tunnel investigated. It is to be emphasized that our modeling might represent a reference in investigating the effects of natural ventilation in tunnels. Full article

(This article belongs to the Special Issue Risk Assessment in Traffic and Transportation)

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