Truck Vehicle Research Articles

RECYCLING OF WASTE TIRES FOR BIO CRUDE FUEL PRODUCTION THROUGH A PYROLYSIS SYSTEM

Recycling of solid waste is one of the most valuable method which is used in worldwide for integral solid waste management. Waste tires are considered to be a source of energy and valuable chemical products. In this study waste tire samples of mixed types (passenger, truck, and heavy vehicles etc.) were decomposed thermally in a fixed bed reactor made up of stainless steel placed inside an electrical heater. Thermal pyrolysis on tire waste samples with (1-2) cm of particle size was carried out at temperatures of 330 ᵒC, 430ᵒC, 530ᵒC, and 630 ᵒC under Argon flow rate of 0.5 L/min and retention time of 15 min to study the effect of temperature on the distribution of pyrolysis products yield. Three main products were obtained by tire pyrolysis pyro oil, gas, and solid residue. Chemical compositions of pyrolysis oil product were characterized by Gas chromatography mass and Fourier transform infrared spectroscopy analyses, it is a complex mixture of alkane, alkene, cycloalkane, cycloalkane, alcohol, ester, and aromatic compounds which are preferable in fuel. If found that a limonene compound occupies the largest proportion of the oil product which is considered as a more valuable compounds.

Prediction of neck injury using multiple linear regression and bumper damage: Case study for low-speed rear-end collisions

The most frequent type of traffic accident is a low-speed rear-end collision, which can damage parts of the vehicle, including the bumper, and cause neck injury to the occupants. Even in minor damage accidents, such as scratches on bumper covers, 26.3% of occupants received treatment for bodily injuries whose main symptom was neck injuries through auto insurance. This study was conducted to evaluate the potential for neck injuries in low-speed accidents. Fifty-nine low-speed rear-end impact tests were conducted, and the motion of the struck vehicle and the neck injury criterion (NIC) of the occupant according to the test conditions were predicted using multiple linear regression derived via supervised machine learning. It was confirmed that the NIC can be predicted using vehicle motion values that can be obtained through an event data recorder. The coefficients of determination of the regression equations were 0.67–0.83. Lastly, we investigated whether neck injuries can be predicted through bumper cover damage that can be checked immediately after a vehicle accident. In the case of the vehicle damage type 1/2/3 category applied to auto insurance by the Korean government, an occupant would have a very low possibility of neck injury or symptoms. No symptoms or injuries were reported in the volunteer tests conducted for this study.

Environmental Problems Caused by Motor Vehicles in and Around the City of Sumgait

The purpose is to study the impact of motor vehicles passing through the city on human health and the environment and to develop an action plan to prevent negative processes in the city of Sumgait. Materials and methods. The negative impact of motor vehicles on the environment was studied using GIS technologies, historical and geographical, mathematical-statistical, comparative, observation, systematic analysis and other methods. Results and discussion. The article calculates the length of existing roads in Sumgait, the number of motor vehicles (cars, trucks and buses) passing through the city during the year, the amount of waste each of them emits to the surrounding areas, especially to the atmosphere. In addition, their impact on soil and vegetation, as well as on human health, has been studied. The results were analysed and compared with the established sanitary standards for their exceedance. Statistical characteristics of the level of pollution have been calculated. The analysis of the data obtained from the measurements led to conclusions about the insufficient effectiveness of structures that reduce the level of pollution only at distances of 100 and 150 m from the sources. Conclusion. In the considered areas, it is necessary to take measures to protect the population from road traffic pollution. In these measures, special attention was paid to creating favourable conditions for people to live in a cleaner environment.

Research of Determining Low-Reliability Elements of Multiple-Flows Compressed Air Braking System Based on Goal-Oriented (GO) Methodology

The multi-flows pneumatic braking system is one of the modern braking systems equipped with truck vehicles which is a very complex system consisting of many elements connected in series or parallel. The reliability of the braking system has a significant influence on safety and the ability to manoeuvre. The study of identifying low-reliability elements in the brake system is of great significance to improve the efficiency of maintenance and repair. This article shows the research results that determine low-reliability elements of the multi-flows pneumatic brake system based on GO methodology, and allow to examine each element's reliability and the complex system. The reliability assessment model is built based on GO theory and statistics data collected at the used units about the frequency of damage, ability, and time to repair and restore the assemblies in the brake system. By using this model, the reliability of the assemblies and the whole system can be determined at any point in time relative to the actual operating time of the brake system. The article's research results can be applied for surveying other components’ reliability and complex systems such as steering or suspension systems.

Log truck crashes before and after weight limit increases in North Carolina and Virginia, USA

ABSTRACT Increasing timber transportation safety is essential to the timber harvesting and forest products industries. Log truck weight limits in the US South are lower than in other US regions. North Carolina and Virginia increased their gross vehicle weight limits for log trucks from 38,102 kg to 40,823 kg in 2012 and 2015, respectively. Log truck crash reports were collected from state authorities in North Carolina and Virginia for crashes occurring between 2009 and 2019. Log truck crash rates, contributing factors, crash locations, and vehicle condition were analyzed to identify opportunities to improve safety and evaluate the relationship between log truck crashes and changes in weight limits. Between 2009 and 2019, log truck crashes per million tonnes of timber harvested increased by 134% and 29% in North Carolina and Virginia, respectively. Crash rates were rising before the increases in weight limits and continued to rise afterward. Exceeding safe speed, improper turn, and failure to yield the right-of-way were common contributors to crashes in both states. Timber transportation safety may be improved through driver education, better fleet maintenance, and increased use of crash reduction technologies.

Developing an aluminum honeycomb barrier to represent a striking SUV in a side impact crash test

Objective The Insurance Institute for Highway Safety (IIHS) introduced its side impact ratings test in 2003. Despite manufacturers' improvements to airbags and vehicle structures, 45% of 2018 side crash fatalities on U.S. roadways were in good-rated vehicles, suggesting that more crashworthiness improvements are necessary. Crash trends indicate that the most promising avenue to address the remaining real-world injuries is a higher severity vehicle-to-vehicle test using a barrier to represent a striking sport-utility vehicle (SUV). Laboratory tests comparing striking SUVs with the current IIHS moving deformable barrier (MDB) showed discrepancies in damage patterns and injury measures. The current study outlines the characteristics of a multi-stiffness aluminum honeycomb barrier to represent a modern SUV-striking vehicle in side impact crash tests. Methods Barrier size and shape were determined from a series of measurements taken from 21 modern SUVs. Barrier honeycomb stiffness characteristics were derived by comparing the damage profile of six different barrier prototypes against a baseline profile obtained from a high-severity SUV crash into a midsize car. Tests were conducted at 60 km/h with a 1,900 kg MDB. The best honeycomb design was tested against four additional vehicles to ensure it was representative of striking SUVs of different sizes and types. Results The final barrier has a 1,700-mm width by 600-mm height and 500-mm depth multi-stiffness design, with less stiffness on the top and more stiffness in the lower outside sections compared with the original IIHS barrier. For three struck vehicles, the redesigned barrier matched all performance criteria set by the striking-SUV tests. For two additional struck vehicles, there were some differences in intrusion patterns but overall, these matched the test trends of the striking SUVs. The new barrier in a higher severity test mode resulted in a range of performance for these good-rated vehicles. Conclusion A multi-stiffness aluminum honeycomb barrier was developed to represent the characteristics of striking SUVs in 60 km/h perpendicular side impact crash tests focusing on the occupant compartment. The redesigned barrier differentiates between currently good-rated vehicles, which will promote structural and restraint system improvements to the fleet relevant to the remaining real-world injuries.

Sliding Mode-Based Slip Control of Compact Electric Vehicle Truck for Varying Load and Yaw Rate

Vehicle stability is a critical problem, especially for compact electric vehicle (EV) trucks, owing to the impact of the cargo weight and cornering characteristics. In this study, this problem was approached by mathematically formulating the change in the understeer characteristics of an EV truck as variable mass understeer gradient (VMUG) according to the vehicle cargo weight to design the reference yaw rate without the need to consider cornering stiffness. Comparison was made with the conventional methods by applying the VMUG-based slip control while simulating the yaw rate and side-slip tracking performance of the compact EV model for normal loading and overloading conditions. The simulation results demonstrate the superior performance of the proposed method compared to the existing methods. The proposed method has the potential for application for stability enhancement in non-electric and general-purpose vehicles as well.

Failure Analysis of a Fractured Leaf Spring as the Suspension System Applied on the Dump Truck

A spring is a component which is designed to have relatively low stiffness compared to normal rigid rods, thereby making it possible to accept certain forces that are charged. A leaf spring is an important suspension component for heavy vehicles, as a failure of the leaf spring can cause severe if not fatal accidents. This study aims to investigate the factors that cause leaf spring failure in the form of a 125 PS dump truck vehicle suspension system. The method employed incorporated experimental and finite element analyses. The experimental work included visual observations, observation using a scanning electron microscope (SEM), hardness testing, and microstructure testing. Leaf spring modelling was conducted using Autodesk Inventor 2017 software, and the finite element analysis (FEA) was performed using Siemens ™ FEMAP V12.0.1 application software to calculate the maximum stress and strain that occurred near the crack tip of the leaf spring. The results from the analysis indicated that the cause of the fracture that occurred in leaf spring No. 3 was due to a defect discovered on the surface of the leaf spring. Based on the observations of the fracture surface, it is revealed that the cause of failure was due to the cyclic load experienced by the components during operation which caused crack propagation beginning from micro-cracks until reaching a significant dimension to cause a final fracture. In addition, the overload imposed on the leaf springs also caused maximum stress on the springs to increase, thus accelerating the failure of the leaf springs. Further results also showed that the value of the stress intensity factor, KI = 29.15 MPa.m1/2 was greater than the value of fracture toughness, KIC = 23 MPa.m1/2 of the spring material.

Field effectiveness of general motors advanced driver assistance and headlighting systems

This study examined the field effectiveness of General Motors advanced driver assistance and headlighting systems. A total of 8,311,707 Model Year 2013–2019 vehicles were matched to police-reported crashes from 12 states. The quasi-induced exposure method was used to compare system-relevant and system-irrelevant (control) crash counts for equipped and unequipped vehicles. Logistic regression was used to adjust for ten covariates. Results indicated fusion/radar Automatic Emergency Braking, camera Automatic Emergency Braking, and Forward Collision Alert systems reduced rear-end striking crashes by 45%, 38%, and 20%, respectively. When restricting data to crashes in which someone in the General Motors striking vehicle was injured, these reductions were elevated to 59%, 54%, and 31%, respectively, providing evidence of additional crash mitigation benefits. Similarly, the Lane Keep Assist with Lane Departure Warning and Lane Departure Warning (alone) systems provided 12% and 10% reductions in lane departure crashes, respectively, with corresponding benefits in the injury analysis increasing to 19% and 18%, respectively. The Lane Change Alert with Side Blind Zone Alert system reduced lane change crashes by 16%. Reverse Automatic Braking, Rear Cross Traffic Alert, Rear Park Assist, and Rear Vision Camera (where each of these systems generally included all of the preceding systems) produced, respectively, an 82%, 55%, 36%, and 24% reduction in backing crashes. For Front Pedestrian Braking, a non-significant 14% reduction was observed for the limited set of available pedestrian crash cases. Intellibeam (auto high beam headlighting), High-Intensity Discharge headlights, and the combination of these two systems provided 26%, 11%, and 32% reductions (relative to halogen headlights) in a combined set of (unlighted) nighttime animal, pedestrian, and bicyclist crashes, respectively. These results provide widespread evidence of the substantial crash avoidance and injury reduction opportunities afforded by the production systems evaluated, as well as identify untapped system opportunities for moving toward a zero crashes vision.

Examining the Effect of Pedestrian Crashes on Vulnerable Populations in North Carolina.

Over the last several years, pedestrian fatalities have increased in North Carolina; however, fatalities represent a small proportion of the total number of nonfatally injured pedestrians. Therefore, we linked statewide motor vehicle crash (MVC) and emergency department (ED) visit data to better understand the circumstances and characteristics of pedestrians treated in North Carolina emergency departments (EDs) for injuries related to crashes. We linked information for pedestrians and bicyclists from 2017 North Carolina police-reported MVCs to population-based ED visit data using hierarchical deterministic methods. We linked 45% of pedestrian crash records to ED visit records (N = 1383 incident ED visits). The rate of pedestrians treated in North Carolina EDs for their injuries was 13.6 ED visits per 100,000 person years. For pedestrian injuries treated in North Carolina EDs, rates (per 100,000 person years in parentheses) were higher among men (15.5) and Black pedestrians (22.7) than women (10.6) and White pedestrians (8.2). Sociodemographic characteristics associated with serious injuries included age, sex, race/ethnicity, and expected source of payment for the ED visit. Crash characteristics associated with serious injuries included posted speed limit, ambient light, number of lanes, and striking vehicle type. The study involved the use of secondary data, not collected specifically for pedestrian injury surveillance. Pedestrian injuries and fatalities place a considerable burden on the population of North Carolina, especially among persons of color and older adults. Injury prevention programs are actively addressing this problem, but more needs to be done.

The impact of 7-hour and 11-hour rest breaks between shifts on heavy vehicle truck drivers’ sleep, alertness and naturalistic driving performance

BackgroundAn inadequate rest break between shifts may contribute to driver sleepiness. This study assessed whether extending the major rest break between shifts from 7-hours (Australian industry standard) to 11-hours, improved drivers’ sleep, alertness and naturalistic driving performance. Methods17 heavy vehicle drivers (16 male) were recruited to complete two conditions. Each condition comprised two 13-hour shifts, separated by either a 7- or 11-hour rest break. The initial 13-hour shift was the drivers’ regular work. The rest break and following 13-hour shift were simulated. The simulated shift included 5-hours of naturalistic driving with measures of subjective sleepiness, physiological alertness (ocular and electroencephalogram) and performance (steering and lane departures). Results13 drivers provided useable data. Total sleep during the rest break was greater in the 11-hour than the 7-hour condition (median hours [25th to 75th percentile] 6.59 [6.23, 7.23] vs. 5.07 [4.46, 5.38], p = 0.008). During the simulated shift subjective sleepiness was marginally better for the 11-hour condition (mean Karolinska Sleepiness Scale [95th CI] = 4.52 [3.98, 5.07] vs. 5.12 [4.56, 5.68], p = 0.009). During the drive, ocular and vehicle metrics were improved for the 11-hour condition (p<0.05). Contrary to expectations, mean lane departures p/hour were increased during the 11-hour condition (1.34 [−0.38,3.07] vs. 0.63 [−0.2,1.47], p = 0.027). ConclusionsExtending the major rest between shifts substantially increases sleep duration and has a modest positive impact on driver alertness and performance. Future work should replicate the study in a larger sample size to improve generalisability and assess the impact of consecutive 7-hour major rest breaks.

Framework for energy storage selection to design the next generation of electrified military vehicles

In this paper, a methodology is proposed that aims at selecting the most suitable energy storage system (ESS) for a targeted application. Specifically, the focus is on electrified military vehicles for the wide range of load requirements, driving missions and operating conditions call for such a cohesive framework. The method uses the Enhanced-Ragone plot (ERp) as a guiding tool to map the performance of different lithium-ion batteries, as a function of C-rate and temperature, and supercapacitors, on the specific power and specific energy log-log plane. A frequency-based segmentation strategy is employed to assign the requested power to the powertrain actuators. Both full-electric battery-powered and hybrid electric vehicle (including an internal combustion engine, battery and supercapacitors) configurations are considered. Using the ERp, ESSs that are able to match the C-rate corresponding to the power-to-energy ratio calculated from the load are selected. Moreover, weight, volume, number of cells and pack energy of the selected ESSs are also returned from the design framework. The algorithm is tested over three vehicle powertrains which strongly differ in load requirements - Tesla Model S, Tesla Semi truck and high-mobility multipurpose wheeled vehicle.

Associations Between Workplace Factors and Depression and Anxiety in Australian Heavy Vehicle Truck Drivers.

A number of health issues have been identified as prevalent within the Australian heavy vehicle driving population. Mental illnesses, such as depression and anxiety, are among those disorders that have been regularly reported, however, the contributing factors are yet to be elucidated. This study aimed to assess the associations between workplace factors such as years of employment, social interaction and shift length, with depressive and anxious symptomology in a cohort of 60 Australian heavy vehicle drivers. Significant positive associations were identified between depression and alcohol use (P = 0.044), coffee consumption (P = 0.037), number of accidents during career (P = < 0.004), and number of hours driving per shift (P ≤ 0.001). Anxiety was found to be positively associated with a number of hours driving per week (P ≤ 0.001), and the number of accidents or near misses during a driving career (P = 0.039). Several workplace factors were identified as being correlated to depression or anxiety within this cohort, suggesting potential changes to rostering systems and education regarding alcohol use may benefit the mental health of this driver population.

Do Driver Characteristics and Crash Conditions Modify the Effectiveness of Automatic Emergency Braking?

&lt;div class="section abstract"&gt;&lt;div class="htmlview paragraph"&gt;Studies of automatic emergency braking (AEB) find that AEB-equipped vehicles are around half as likely to crash. This study examines whether driver characteristics and road and weather conditions modify this preventive effect of AEB.&lt;/div&gt;&lt;div class="htmlview paragraph"&gt;Toyota production data were merged with police reported crash files from eight U.S. states for crash years 2015 up to 2019 by 17-digit vehicle identification number (VIN). Using a case-control design, this study investigated the relationship of AEB presence with being a case vehicle in a system-relevant crash (the striking vehicle in front-to-rear crash; n=30,056) versus an AEB non-relevant control vehicle (the struck vehicle in a front-to-rear crash; n=62,820). The analysis was stratified by driver characteristics and by weather and road conditions. Logistic regression modeled the relationship, controlling for exposure (vehicle-days) and possible confounding factors. The resulting odds ratios for AEB equipment from the separate models were compared to determine if the effect of AEB presence was modified by the characteristic or condition of interest.&lt;/div&gt;&lt;div class="htmlview paragraph"&gt;Overall, AEB-equipped vehicles were 43% (p&amp;lt;0.001) less likely to be the striking (case) vehicle compared to non-equipped vehicles. However, the preventive effect of AEB was significantly lower among older drivers (over 65 years) compared to younger drivers; 29% less likely to be a striking vehicle (OR=0.71) versus 46% (OR=0.54), respectively. The effect of AEB was also lower in adverse weather conditions (rain, fog, snow) (OR=0.66) and on wet or snowy roads (OR=0.65), though these differences were not significant compared to clear weather and dry roads. The AEB effect was also lower among risk-taking drivers (alcohol-involved, speeding, or unrestrained) compared to non-risk-taking (OR=0.72 versus OR=0.59, respectively).&lt;/div&gt;&lt;div class="htmlview paragraph"&gt;AEB prevents crashes, regardless of driver characteristics and environmental conditions. This study suggests, however, that the size of the effect is smaller among older and risk-taking drivers, and in adverse weather and road conditions.&lt;/div&gt;&lt;/div&gt;

Effectiveness of Advanced Driver Assistance Systems in Preventing System-Relevant Crashes

&lt;div class="section abstract"&gt;&lt;div class="htmlview paragraph"&gt;This retrospective cohort study uses survival analysis to estimate the effectiveness of Toyota ADAS in helping prevent system-relevant crashes. Toyota production data were merged with police reported crash files from eight U.S. states for crash years 2015 up to 2019 by 17-digit vehicle identification number (VIN). System-relevant crash scenarios included: striking vehicle in front-to-rear, single vehicle run-off-the-road, same-direction sideswipe, head-on, and pedestrian struck. The study vehicle cohort included 11 Toyota/Lexus models, model years 2015 through 2018, sold in the eight study states. ADAS technologies studied included automatic emergency braking (AEB), lane departure warning (LDW), lane keeping assistance (LKA), blind spot monitoring (BSM) and pedestrian automatic emergency braking (PedAEB). Among the study cohort of 2,394,913 vehicles, police reported 308,490 crashes. The crude crash rate ratio (CRR) was 0.61 for AEB-equipped versus non-equipped vehicles. However, the CRR does not adjust for differences in ADAS-equipped versus non- equipped vehicles. To adjust for group differences (confounding factors), Cox proportional-hazards (CPH) regression modeled the relative risk (hazard ratio, HR) of being in a system-relevant crash for vehicles with versus without the ADAS. CPH modeling found that AEB-equipped vehicles were 43% less likely (HR=0.57) to be the striking vehicle in a front-to-rear crash compared to non-equipped vehicles. The analysis was also stratified to look at the effect in intersection versus non-intersection crashes. BSM-equipped vehicles were 4% less likely (HR=0.96) to be involved in a same-direction sideswipe, though the differences were not significant (p=0.252). LKA-equipped vehicles were 9% less likely (HR=0.91) to run off the road. LDW and LKA did not have a significant effect on risk of same-direction sideswipe or head-on crash. PedAEB-equipped vehicles were less likely to hit a pedestrian (HR=0.84), but the hazard ratios were marginally significant (p=0.114). This study contributes new evidence of the effectiveness of ADAS in helping prevent system-targeted crashes.&lt;/div&gt;&lt;/div&gt;

Exhaust system of commercial vehicle: a review

In Automobiles like Truck, Bus, Car, and other commercial vehicles, various exhaust emission norms like Euro IV and Euro VI are considered for a non-polluted environment. This paper focuses on increasing engine and vehicle performance of commercial vehicle by reducing back-pressure and noise due to after treatment systems, considering exhaust emission norms. Back-pressure in exhaust systems is calculated with advanced Computational Fluid Dynamics (CFD) technologies like ANSYS Fluent, GT Power. Backpressure in the exhaust pipe is reduced by varying length, diameter, number of bends, exhaust mass flow rate and bending angle of exhaust pipe. Narrow band noise in vehicles is predicted by Large Eddy Simulation (LES). Selective Catalytic Reduction (SCR) converts harmful NOx to harmless N2. SCR non-linearities are calculated by CFD code CONVERGE and TRIZ method. SCR urea deposit is minimized by proper nozzle position of urea spray. Diesel and gasoline particulate filter is used to filter particulate matter in diesel and gasoline engine respectively. This research focuses on the optimization of commercial vehicle exhaust systems.

ANALYSIS OF THE EFFECT OF SLAB THICKNESS ON CRACK WIDTH IN RIGID PAVEMENT SLABS

Cracks that occur in rigid pavements include longitudinal cracks, transverse cracks, and corner cracks. The relatively large crack width not only spoils the aesthetics of the concrete structural elements but can also lead to structural failure. This study aims to determine the crack width of a rigid pavement concrete slab located above the subgrade which is considered a beam on an elastic foundation, so that a minimum rigid pavement concrete slab thickness can be recommended. The specimen will be observed at various thicknesses to obtain the optimum thickness. The load used is a centralized monotonous load, which represents the load of the truck vehicle. The research limitation is using a test object in the form of a concrete plate measuring 2000x600 mm which is placed on the ground with CBR=6 %. The quality of reinforced concrete slabs is fc'=40 MPa and fy=440.31 MPa. The thickness of the concrete slab varies between 100 mm, 150 mm, and 200 mm. The slab placed on the ground is then given a central loading in the form of a centralized monotonic load. The loading range starts from a load of 2–180 kN with a load interval of 2 kN. The experimental results show that the rigid pavement slab has a bending failure so that the crack pattern that occurs begins with the first crack on the underside of the slab. The crack pattern in terms of slab thickness variation has a similar pattern. The initial crack width on the slab is 0.04 mm. The thicker the slab smaller the crack width at the same load. Based on the maximum allowable crack width=0.3 mm. For loads between (80–100) kN (Road Class I, II, and III), a minimum thickness of rigid pavement slabs (70–80) mm is recommended. For loads between (130–140) kN, the minimum thickness of the rigid pavement slab (105–115) mm is recommended

Genomics for conservation: a case study of behavioral genes in the Tasmanian devil

The increased availability of genomic resources for many species has expanded perspectives on problems in conservation by helping to design management strategies for threatened species. Tasmanian devils (Sarcophilus harrisii) are an iconic and endangered marsupial with an intensively managed breeding program aimed at preventing extinction in the wild caused by devil facial tumour disease. Between 2015 and 2017, 85 devils from this program were released to three sites in Tasmania to support wild populations. Of these, 26 were known to have been killed by vehicles shortly after release. A previous analysis indicated that increased generations in captivity was a positive predictor of vehicle strike, with possible behavioural change hypothesised. Here we use 39 resequenced devil genomes to characterise diversity at 35 behaviour-associated genes, which contained 826 single nucleotide polymorphisms (24 were non-synonymous). We tested for a predictor of survival by examining three genes (AVPR1B, OXT and SLC6A4) in 62 released devils with known fates (survived, N = 39; died, N = 23), and genome-wide associations via reduced-representation sequencing (1727 single nucleotide polymorphisms [SNPs]), in 55 devils with known fates (survived, N = 38; died, N = 17). Overall, there was little evidence of an association between genetic profile and probability of being struck by a vehicle. Despite previous evidence of low genetic diversity in devils, the 35 behaviour-associated genes contained variation that may influence their functions. Our dataset can be used for future research into devil behavioural ecology, and adds to the increasing body of research applying genomics to conservation problems.

Effects of Hunting on a Puma Population in Colorado

Effects of Hunting on a Puma Population in Colorado

Evaluation of Intelligent Transport Systems Used in Urban Agglomerations and Intercity Roads by Professional Truck Drivers

Using intelligent transport systems in cities is gaining popularity. The fundamental aim of their existence is to improve safety and traffic flow and prevent congestion in city centres. All people moving around the city, such as public transport passengers, as well as truck and emergency vehicle drivers and drivers of passenger vehicles, are users of intelligent transport systems. Research which was carried out for the article entirely concerns functioning and utility of intelligent transport systems from truck drivers’ experience. The main aim of the research was to evaluate services and tools within intelligent transport systems in European cities which are visited by Polish truck drivers. Our research indicates that most drivers (almost 98%) stated that they find intelligent transport systems useful and 92.5% of interviewed pointed that intelligent transport systems help with their everyday work duties. Of all the tools in the survey drivers agreed that variable content signs, accommodative traffic lights, and extra road illumination have most influence in road safety. Identifying the most useful and helpful tools of intelligent transport systems will allow to define their preferred development directions from truck drivers’ point of view.