Applying data mining techniques for technology prediction in new energy vehicle: a case study in China.

Technology prediction is an important technique to help new energy vehicle (NEV) firms keep market advantage and sustainable development. Under fierce competition in the new energy industry, there is an urgent necessity for innovative technology prediction method to effectively identify core and frontier technologies for NEV firms. Among the various methods of technology prediction, one of the most frequently used methods is to make technology prediction from patent data. This paper synthesizes the frequent pattern growth (FP-growth) algorithm and input-output analysis to construct a new technology prediction method based on the knowledge flow perspective, takes the data of NEV patent family in 1989-2018 the Derwent patent database as a sample, divides the data according to the 5-year standard, and uses the method to identify the core and frontier technologies in the NEV field during different periods. Furthermore, the multiple co-occurrence method applies to analyze the technology layout and evolution patterns in China's NEV field. The results show that the technology prediction method proposed in this paper can effectively identify core and frontier technologies to achieve NEV technology prediction.

Physical and Biological Performance Evaluation of Disinfection Systems for Transportation Vehicles against AI Virus.

To prevent the outbreak of infectious diseases that inflict huge economic and social losses, domestic livestock farms and related facilities have introduced automatic and semiautomatic disinfectant solution-spraying systems for vehicles. However, the facility standards and specifications vary by manufacturer, and no scientific performance evaluation has been conducted. The puropose of this study is to develop physical and biological evaluation methods. Physical and biological appraisals were conducted using two types of disinfection facilities (tunnel- and U-type) and two types of vehicles (passenger car, truck). Water-sensitive paper was used to evaluate the physical performance values for the disinfection facilities. In addition, to assess their biological performance, carriers containing low-pathogenic avian influenza virus were attached to vehicles, and the viral reduction was measured after the vehicles moved through the facility. The tunnel-type had rates of coverage in the range of 70-90% for the passenger car and 60-90% for the truck. At least 4-log virus reduction after spraying for 1-5 min was shown for both vehicles. For the U-type facility evaluation, the coverage rates were in the range of 60-90% for the passenger car and at least 90% for the truck. More than 4-log viral reduction was estimated within a spraying time of 5 min. To reduce viruses on the surface of vehicles by at least 4 log within a short period, the disinfectant solution should cover at least 71% of the pathogens. In conclusion, we were able to assess the physical and biological performance criteria for disinfection facilities aboard transportation vehicles.

Is a flick-through enough? A content analysis of Advanced Driver Assistance Systems (ADAS) user manuals.

Advanced Driver Assistance Systems (ADAS) are being developed and installed in increasing numbers. Some of the most popular ADAS include blind spot monitoring and cruise control which are fitted in the majority of new vehicles sold in high-income countries. With more drivers having access to these technologies, it is imperative to develop policy and strategies to guarantee the safe uptake of ADAS. One key issue is that ADAS education has been primarily centred on the user manual which are not widely utilised. Moreover, it is unclear if user manuals are an adequate source of education in terms of content and readability. To address this research gap, a content analysis was used to assess the differences in ADAS-related content and readability among the manuals of the highest selling vehicles in Australia. The qualitative findings showed that there are seven themes in the user manuals: differences between driving with and without ADAS, familiarisation requirements, operational limits of the ADAS, potential ADAS errors, behaviour adaptation warnings, confusion warnings, and malfunction warnings. The quantitative analysis found that some of the manuals require several years of education above the recommended for a universal audience (>8 years) to be understood. Additionally, there is a notable number of text diversions and infographics which could make comprehension of the user manual difficult. This investigation shows that there is a lack of standardisation of ADAS user manuals (in both content and delivery of information) which requires regulatory oversight. Driver ADAS education needs to be prioritised by policymakers and practitioners as smart technology continues to increase across the transport system. It seems that current strategies based on user manuals are insufficient to achieve successful adoption and safe use of these technologies.

Investigating factors affecting severity of large truck-involved crashes: Comparison of the SVM and random parameter logit model.

INTRODUCTION: Reducing the severity of crashes is a top priority for safety researchers due to its impact on saving human lives. Because of safety concerns posed by large trucks and the high rate of fatal large truck-involved crashes, an exploration into large truck-involved crashes could help determine factors that are influential in crash severity. The current study focuses on large truck-involved crashes to predict influencing factors on crash injury severity. METHOD: Two techniques have been utilized: Random Parameter Binary Logit (RPBL) and Support Vector Machine (SVM). Models have been developed to estimate: (1) multivehicle (MV) truck-involved crashes, in which large truck drivers are at fault, (2) MV track-involved crashes, in which large truck drivers are not at fault and (3) and single-vehicle (SV) large truck crashes. RESULTS: Fatigue and deviation to the left were found as the most important contributing factors that lead to fatal crashes when the large truck-driver is at fault. Outcomes show that there are differences among significant factors between RPBL and SVM. For instance, unsafe lane-changing was significant in all three categories in RPBL, but only SV large truck crashes in SVM. CONCLUSIONS: The outcomes showed the importance of the complementary approaches to incorporate both parametric RPBL and non-parametric SVM to identify the main contributing factors affecting the severity of large truck-involved crashes. Also, the results highlighted the importance of categorization based on the at-fault party. Practical Applications: Unrealistic schedules and expectations of trucking companies can cause excessive stress for the large truck drivers, which could leads to further neglect of their fatigue. Enacting and enforcing comprehensive regulations regarding large truck drivers' working schedules and direct and constant surveillance by authorities would significantly decrease large truck-involved crashes.

Characteristics of vehicles driven by teens and adults killed in crashes, 2013-2017.

INTRODUCTION: Teen drivers experience higher crash risk than their experienced adult counterparts. Legislative and community outreach methods have attempted to reduce this risk; results have been mixed. The increasing presence of vehicle safety features across the fleet has driven fatality numbers down in the past decades, but the disparity between young drivers and others remains. METHOD: We merged Fatality Analysis Reporting System (FARS) data on fatal crashes with vehicle characteristic data from the Highway Loss Data Institute (HLDI). The analysis compared the vehicle type, size, age, and the presence of select safety features in vehicles driven by teens (ages 15-17 years) and adult drivers (ages 35-50 years) who were killed in crashes from 2013 to 2017. Results were compared with a similar analysis conducted on data from 2007 to 2012. RESULTS: Teen drivers were more likely than their adult counterparts to be killed while driving older, smaller vehicles that were less likely to have the option to be equipped with side airbags. DISCUSSION: Teenage drivers remain more likely to be killed while driving older, smaller vehicles than adult drivers. Parents and guardians are mainly responsible for teen vehicle choice, and should keep vehicle size, weight, and safety features in mind when placing their teen in a vehicle. Practical Application: These findings can help guide safer vehicle choice for new teen drivers.

Risk factors associated with truck-involved fatal crash severity: Analyzing their impact for different groups of truck drivers.

INTRODUCTION: Fatal crashes that include at least one fatality of an occupant within 30 days of the crash cause large numbers of injured persons and property losses, especially when a truck is involved. METHOD: To better understand the underlying effects of truck-driver-related characteristics in fatal crashes, a five-year (from 2012 to 2016) dataset from the Fatality Analysis Reporting System (FARS) was used for analysis. Based on demographic attributes, driving violation behavior, crash histories, and conviction records of truck drivers, a latent class clustering analysis was applied to classify truck drivers into three groups, namely, ''middle-aged and elderly drivers with low risk of driving violations and high historical crash records," ''drivers with high risk of driving violations and high historical crash records," and ''middle-aged drivers with no driving violations and conviction records." Next, equivalent fatalities were used to scale fatal crash severities into three levels. Subsequently, a partial proportional odds (PPO) model for each driver group was developed to identify the risk factors associated with the crash severity. Results' Conclusions: The model estimation results showed that the risk factors, as well as their impacts on different driver groups, were different. Adverse weather conditions, rural areas, curved alignments, tractor-trailer units, heavier weights and various collision manners were significantly associated with the crash severities in all driver groups, whereas driving violation behaviors such as driving under the influence of alcohol or drugs, fatigue, or carelessness were significantly associated with the high-risk group only, and fewer risk factors and minor marginal effects were identified for the low-risk groups. Practical Applications: Corresponding countermeasures for specific truck driver groups are proposed. And drivers with high risk of driving violations and high historical crash records should be more concerned.

Injury-severity analysis of lane change crashes involving commercial motor vehicles on interstate highways.

INTRODUCTION: One of the challenging tasks for drivers is the ability to change lanes around large commercial motor vehicles. Lane changing is often characterized by speed, and crashes that occur due to unsafe lane changes can have serious consequences. Considering the economic importance of commercial trucks, ensuring the safety, security, and resilience of freight transportation is of paramount concern to the United States Department of Transportation and other stakeholders. METHOD: In this study, a mixed (random parameters) logit model was developed to better understand the relationship between crash factors and associated injury severities of commercial vehicle crashes involving lane change on interstate highways. The study was based on 2009-2016 crash data from Alabama. RESULTS: Preliminary data analysis showed that about 4% of the observed crashes were major injury crashes and drivers of commercial motor vehicles were at-fault in more than half of the crashes. Acknowledging potential crash data limitations, the model estimation results reveal that there is increased probability of major injury when lane change crashes occurred on dark unlit portions of interstates and involve older drivers, at-fault commercial vehicle drivers, and female drivers. The results further show that lane change crashes that occurred on interstates with higher number of travel lanes were less likely to have major injury outcomes. Practical Applications: These findings can help policy makers and state transportation agencies increase awareness on the hazards of changing lanes in the immediate vicinity and driving in the blind spots of large commercial motor vehicles. Additionally, law enforcement efforts may be intensified during times and locations of increased unsafe lane changing activities. These findings may also be useful in commercial vehicle driver training and driver licensing programs.

Data mining approach to model bus crash severity in Australia.

INTRODUCTION: Buses are different vehicles in terms of dimensions, maneuverability, and driver's vision. Although bus traveling is a safe mode to travel, the number of annual bus crashes cannot be neglected. Moreover, limited studies have been conducted on the bus involved in fatal crashes. Therefore, identification of the contributing factors in the bus involved fatal crashes can reduce the risk of fatality. METHOD: Data set of bus involved crashes in the State of Victoria, Australia was analyzed over the period of 2006-2019. Clustering of crash data was accomplished by dividing them into homogeneous categories, and by implementing association rules discovery on the clusters, the factors affecting fatality in bus involved crashes were extracted. RESULTS: Clustering results show bus crashes with all vehicles except motor vehicles and weekend crashes have a high rate of fatality. According to the association rule discovery findings, the factors that increase the risk of bus crashes with non-motor vehicles are: old bus driver, collision with pedestrians at signalized intersections, and the presence of vulnerable road users. Likewise, factors that increase the risk of fatality in bus involved crashes on weekends are: darkness of roads in high-speed zones, pedestrian presence at highways, bus crashes with passenger car by a female bus driver, and the occurrence of multi-vehicle crashes in high-speed zones. Practical Applications: The study provides a sequential pattern of factors, named rules that lead to fatality in bus involved crashes. By eliminating or improving one or all of the factors involved in rules, fatal bus crashes may be prevented. The recommendations to reduce fatality in bus crashes are: observing safe distances with the buses, using road safety campaigns to reduce pedestrians' distracted behavior, improving the lighting conditions, implementing speed bumps and rumble strips in high-speed zones, installing pedestrian detection systems on buses and setting special bus lanes in crowded areas.

Understanding the effects of vehicle platoons on crash type and severity.

Crash type is an informative indicator to infer driving behaviors and conditions that cause a crash. For example, rear-end and side-swipe crashes are typically caused by improper vehicle interaction such as sudden lane-changing or speed control while hit-object crashes are likely the result of a single driver's mistake. This study investigated the impact of vehicles travelling as a group (platoon) and its configuration (i.e., types of vehicles consisting of the platoon) on crash type and severity since the vehicles could affect each other when travelling in close proximity. This study applied Generalized Structure Equation Modeling (GSEM) to capture the complex relationships among the various crash factors such as traffic condition, driver characteristics, environmental conditions, and vehicle interaction to the crash attributes including type and severity. This study collected over 3 million individual vehicle data from 39 traffic count sites in California to estimate the vehicle interactions and driving behaviors. The microscopic traffic data are matched to 1417 crash reports. Results showed that vehicles traveling in platoons are associated with more rear-end and side-swipe crashes. Speed difference in the platoon had a positive effect on hit-object crashes if the platoon comprises vehicles of homogeneous type - either trucks or non-trucks. In addition, human factors such as age and gender were identified as significant influential factors in all type of crashes, however truck involvement particularly played an important role amongst side-swipe crashes. Crash severity was negatively affected by total flow, and rear-end crashes were more likely to be severe compared with hit-object crashes. Based on findings, this study suggests practical operational strategies to reduce traffic instability associated with platooned vehicle patterns. Understanding the high-risk factors for different crash types and severities would provide valuable insights for decision-makers and transportation engineers to develop targeted intervention strategies in consideration of road users and traffic conditions such as fleet mix and speed.

Comparison of the epidemiology and injury profile among injured patients involved in special purpose vehicle-related incidents in South Korea.

Injuries caused by mobile machinery or special purpose vehicles (SPVs) can lead to high socio-medical cost and fatality. In this descriptive study, we compared the epidemiology and injury profile of injured patients involved in SPVs-related incidents. We analyzed a nationwide database of SPV-related injured patients between January 2011 and December 2016. Injured patients were classified into three groups: pedestrian, motor vehicle occupant (MVO), and SPV operator groups. Of 1,419 cases, the highest number of SPV-related injured patients were found in the age group 40-59 years (671 cases, 47.3%) and at transport area (771 cases, 54.3%). The injury was most severe in the SPV operator group. The lower extremities were the most common fracture site, and intrathoracic injury was the most common visceral regions for SPV-related injured patients. SPV operator could lead to fatal intrathoracic injuries.

Factors affecting the accident size of motorcycle-involved crashes: a structural equation modeling approach.

Motorcycle users are one of the vulnerable road users in the event of a crash due to the low level of protection. In most of the studies related to the safety of motorcycle, the highest level of occupants' injury severity is frequently taken into account, which involves one aspect of the crash. To conduct a comprehensive study of crash severity, accident size can be utilized, which consists of different aspects of a crash. Therefore, to investigate the influential factors on the accident size of motorcycle-involved crashes, structural equation modeling was used in the present study. Results reveal that the crashes involving heavy vehicles, old-aged drivers, female drivers, day time, dry road surface, two-way roads, lack of shoulder and rural roads are associated with larger accident size. This study also showed the importance of considering the driver and road characteristics in safety programs for mitigating the crash severity.

A copula-based approach for jointly modeling crash severity and number of vehicles involved in express bus crashes on expressways considering temporal stability of data.

The consequences of crashes, including injury, loss of lives, and damage to properties, are further worsened when buses plying expressways are involved in the crash. Previous studies have separately analyzed crash severity in terms of monetary cost, injuries and loss of lives, and the size of crashes in terms of the number of vehicles involved. However, as both outcome variables are correlated, it is imperative to perform a combined analysis using an appropriate econometric model to achieve a better model fit. This study contributes to the literature by jointly exploring the factors influencing the severity and size of express bus-involved crashes that occur on expressways and characterizes the dependence between both outcome variables by employing a more plausible copula regression framework. Likelihood ratio tests were also conducted to investigate the temporal stability of the factors that affect both crash severity and size. Based on the goodness-of-fit statistics, the Frank copula model proved superior to the independent ordered probit model. The estimate of the underlying dependence between the outcome variables provided a better comprehension of the correlation between them. Temporal instability was detected for the individual parameters in the models and is attributed to the changing driving behavior due to the heightened road safety campaigns. The results suggest that traffic exposure measures are significantly associated with a higher propensity of observing increased bus crash severity and size. Insights into the factors influencing the size and severity of express bus crashes are discussed, and appropriate engineering, enforcement, and education-related countermeasures are proposed.

Influences of impact scenarios and vehicle front-end design on head injury risk of motorcyclist.

Motorcycle to vehicle collision is one of the most common accidents in the world and usually leads to serious or fatal head injuries to motorcyclists. This study aims to investigate the influences of impact scenarios and vehicle front-end design parameters on head injury risk of the motorcyclist. Five general vehicle types and different impact scenarios were selected for a parametric analysis. Impact scenarios were set according to ISO, 13232 regulation considering impact angles and impact speeds. Five vehicle types of Sedan, MPV (Multi-Purpose Vehicle), SUV (Sport Utility Vehicle), EV (Electric Vehicle) and 1-Box vehicle were included. HIC15 (Head Injury Criterion), head angular acceleration and CSDM (Cumulative Strain Damage Measure) were calculated to evaluate head injury risk of the motorcyclist. The results show that the critical impact speed for HIC15 and head angular acceleration was around 15 m/s, while the critical speed for CSDM was approximately 10 m/s. Impact angle of 45° show extremely high injury risk to the motorcyclist head. Bonnet leading edge height and its combination with other parameter present high influences on motorcyclist head injuries, and the increasing the bonnet leading edge height can potentially reduce head injury risk of motorcyclists. In summary, the present research results provide some theoretic bases for determining the test speed in motorcycle-vehicle crash regulation and design consideration for typical vehicle front end shape.

An energy loss-based vehicular injury severity model.

How crashes translate into physical injuries remains controversial. Previous studies recommended a predictor, Delta-V, to describe the crash consequences in terms of mass and impact speed of vehicles in crashes. This study adopts a new factor, energy loss-based vehicular injury severity (ELVIS), to explain the effects of the energy absorption of two vehicles in a collision. This calibrated variable, which is fitted with regression-based and machine learning models, is compared with the widely-used Delta-V predictor. A multivariate ordered logistic regression with multiple classes is then estimated. The results align with the observation that heavy vehicles are more likely to have inherent protection and rigid structures, especially in the side direction, and so suffer less impact.

Asociación del tipo de vehículo con el riesgo de provocar una colisión entre vehículos / Association between type of vehicle and the risk of provoking a collision between vehicles

OBJETIVO: Cuantificar la magnitud de la asociación entre el tipo de vehículo y la probabilidad de ser el responsable de una colisión entre dos o más vehículos. MÉTODO: A partir del registro de accidentes de tráfico con víctimas de la Dirección General de Tráfico (2014 y 2015) se diseñó un estudio de casos y controles emparejado. Los casos fueron los conductores infractores implicados en las 27.630 colisiones entre dos o más vehículos, en las que solo uno de los conductores implicados había cometido algún error de conducción o infracción. Cada caso se emparejó con los conductores no infractores de los vehículos implicados en el mismo accidente; en total se dispuso de 31.219 controles. Aparte de la comisión de infracciones y del tipo de vehículo implicado, se obtuvo información para otras características del conductor (edad, sexo, etc.) y del vehículo (antigüedad). Se calcularon odds ratios (OR) para cuantificar la asociación entre cada tipo de vehículo y la odds de ser el causante de la colisión, crudas y ajustadas (ORa) (regresión logística condicionada) por el resto de las variables recogidas. RESULTADOS: En comparación con los turismos, se obtuvo un menor riesgo de provocar la colisión para bicicletas (ORa: 0,30), ciclomotores (ORa: 0,52) y autobuses (ORa: 0,63), y un mayor riesgo para furgonetas (ORa: 1,19) y vehículos todoterreno (ORa: 1,33). CONCLUSIÓN: Los vehículos de dos ruedas y los autobuses tienen un menor riesgo de provocar colisiones que los turismos. Esta asociación es independiente de algunas características del conductor, así como de la antigüedad del vehículo

OBJECTIVE: To quantify the magnitude of the association between the type of vehicle and the probability of being responsible for a collision between two or more vehicles. METHOD: From the registry of road crashes with victims maintained by the Spanish Traffic General Directorate (2014 and 2015), a matched case-control study was designed. Cases were offending drivers involved in the 27,630 collisions between two or more vehicles in which only one of the drivers had committed a driving mistake or offence. Each case was matched with the non-offending drivers of the vehicles involved in the same crash: in all, 31,219 controls were included. Apart from the commission of offences and the type of vehicle involved, we got information about other characteristics of the driver (age, sex, etc.) and about the vehicle (age). Odds ratios (OR) were calculated in order to quantify the association between each type of vehicle and the odds of being responsible for the collision, crude and adjusted (by conditioned logistic regression) by the rest of collected variables. RESULTS: In comparison with private cars, bicycles had a lower risk of causing a collision (adjusted OR: .30), and also mopeds (aOR: .52) and buses (aOR: .63). Vans (aOR: 1.19) and four-wheel vehicles (aOR: 1.33) increased the risk. CONCLUSION: Two-wheeled vehicles and buses had a lower risk of causing collisions than private cars. This association is independent of some of the characteristics of the driver, as well as the age of the vehicle

Comprehensive safety assessment in mixed fleets with connected and automated vehicles: A crash severity and rate evaluation of conventional vehicles.

Connected and Automated Vehicle (CAV) technology, although in the development stage, is quickly expanding throughout the vehicle market. However, full market penetration will most likely require considerable planning as key stakeholders, manufacturers, consumers and governing agencies work together to determine optimal deployment strategies. Specifically, road safety is a critical challenge to the widespread deployment and adoption of this disruptive technology. During the transition period fleets will be composed of a combination of CAVs and conventional vehicles, and therefore it is imperative to investigate the repercussions of CAVs on traffic safety at different penetration rates. Since crash severity and frequency in conjunction reflect traffic safety, this study attempts to investigate the effect of CAVs on both crash severity and frequency through a microsimulation modelling exercise. VISSM microsimulation platform is used to simulate a case study of the M1 Geelong Ring Road network (Princes Freeway) in Victoria, Australia. Network performance is evaluated using performance metrics (Total System Travel Time, Delay) and kinematic variables (Speed, acceleration, jerk rate). Surrogate safety measures (time to collision, post encroachment time, etc.) are examined to inspect the safety in the network. The results indicate that the introduction of CAVs does not achieve the expected decrease in crash severity and rates involving manual vehicles, despite the improvement in network performance, given the demand and the set of parameters used in our operational CAV algorithm are intact. Additionally, the study identifies that the safety benefits of CAVs are not proportional to CAV penetration, and full-scale benefits of CAVs can only be achieved at 100 % CAV penetration. Further, considering network efficiency as a performance metric and total crash rate involving conventional vehicles as a safety metric, a Pareto frontier is extracted, for varying CAV operational behaviour. The results presented in this study provide insights into the impacts of CAVs on traffic safety valuable for insurance companies and other industry participants, enabling safety-related services and more enterprising business models.

Vehicle inspection policy and emission analysis in Kuwait.

Technical vehicle inspection centers are widespread in Kuwait. All vehicles should pass the test every 2 years if not older than 6 years or every 1 year for other vehicles. This study provided an insight into the data collected from test centers and the emission test utilized in Kuwait. Data were collected from test centers in the six Kuwaiti governorates. European standards were selected as limits for emission violations. Independent variables included the place of vehicle manufacture, vehicle's age, and odometer reading. A multinomial logit model was used to identify the significant predictors and determine the correlation between dependent and independent variables. Artificial neural network was employed to compare prediction estimates of neural network and multinomial logit. The findings showed that the place of vehicle's manufacture, vehicle's age, and odometer reading were significant regarding violating emission standards of carbon monoxide (CO). Asian vehicles, vehicles with more than 150,000 km mileage, and vehicles older than 15 years had a higher probability of failing the CO test compared to the place of manufacture. In contrast, the odometer reading was the only significant indicator for vehicles that have failed the hydrocarbons test, especially for vehicles with 150,000 km odometer reading. The findings of this study can reduce air-pollution, time, and money by targeting the most polluting vehicles; thus, more efficient test can be performed.

Electric Vehicle Charging Station Location towards Sustainable Cities.

Electric vehicles, a significant part of sustainable transport, are attracting increasing attention with the development of sustainable cities. However, as supporting facilities of electric vehicles, public charging stations are of great significance to the promotion of electric vehicles. This paper proposes an electric vehicle charging station location model to improve the resource utilization of electric vehicles for sustainable cities. In this model, reservation services, idle rates during off-peak periods, and waiting time during peak periods are considered. Finally, a case from Chengdu, China, is used to examine the effectiveness of the proposed model. Then, further analyses of reservation ratios and penetration rates are conducted. The results show that the introduction of a reservation service has a positive effect on reducing the total cost, which would provide further support for sustainable cities and have an even greater impact on healthier lives.

Investigating the injury severity of single-vehicle truck crashes in a developing country.

Trucking plays a vital role in economic development in every country, especially countries where it serves as the backbone of the economy. The fast growth of economy in Iran as a developing country has also been accompanied by an alarming situation in terms of fatalities in truck-involved crashes, among the drivers and passengers of the trucks as well as the other vehicles involved. Despite the sizable efforts to investigate the truck-involved crashes, very little is known about the safety of truck movements in developing countries, and about the single-truck crashes worldwide. Thus, this study aims to uncover significant factors associated with injury severities sustained by truck drivers in single-vehicle truck crashes in Iran. The explanatory factors tested in the models include the characteristics of drivers, vehicles, and roadways. A random threshold random parameters hierarchical ordered probit model is utilized to consider heterogeneity across observations. Several variables turned out to be significant in the model, including driver's education, advanced braking system deployment, presence of curves on roadways, and high speed-limit. Using those results, we propose safety countermeasures in three categories of 1) educational, 2) technological, and 3) road engineering to mitigate the severity of single-vehicle truck crashes.

In-vehicle noise exposure among military personnel depending on type of vehicle, riding compartment and road surface.

INTRODUCTION: Noise-induced hearing loss is one of the most common health problems among military service personnel. Exposure to noise in military vehicles constitutes a large proportion of total noise exposure. This pilot study aimed to evaluate in-vehicle noise levels depending on the type of vehicle, riding compartment and road surface. METHOD: Noise levels were measured in armoured personnel carriers and heavy all-terrain trucks, in the cab and rear passenger compartment, while driving on paved or off-road surfaces. The results were compared with national LLV and allowed noise exposure times were calculated per vehicle and surface. RESULTS: The equivalent noise levels in the cab of SISU XA-188 (p=0.001) and peak noise levels in MAN 4620 (p=0.0001) and DAF 4440 (p=0.0047) were higher on paved road, compared with off-road. The equivalent noise levels in the canvas covered rear compartment of MAN 4620 were significantly higher than in the cab on both paved (p=0.004) and off-road (p=0.0003). Peak noise levels in the cab of DAF 4440 exceeded the parameters measured in the canvas covered rear compartment on both paved (p=0.002) and off-road (p=0.0002). In most cases, peak noise levels were below the LLV (p=0.02-0.0001). The maximum noise exposure to passengers in the canvas covered rear compartment of MAN 4620 despite road surface was calculated 0.6 hours per working day. CONCLUSION: A high risk of noise-induced hearing loss among military personnel occurs during long distance transportation with vehicles showing noise levels higher than allowed LLV.