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Freight transportation, including just-in-time (JIT) supplier networks, accounts for a substantial part of the global carbon dioxide (CO $ _2 $ 2 ) emissions. The JIT truck routing problem (TRP-JIT) presented in the recent literature consists of several suppliers serving a single original equipment manufacturer (OEM). A logistics provider organises the milk-run routes. The shipments are available after their release dates at the suppliers and should be delivered on their due dates at the OEM with minimal total earliness-tardiness penalties (first objective). Unlike previous research on the TRP-JIT, we focus on its environmental impact: (1) We include the weight-distance (second objective), depending on the truck's curb weight, the load, and the transportation distance. (2) We adapt a state-of-the-art large neighbourhood search (LNS) from the literature considering both objectives. (3) The LNS is embedded in bi-criterial frameworks, i.e. ε-constraint and weighted sum methods. Thereby, we estimate Pareto frontiers with at least 60 solutions in less than 25 min for instances with 99 shipments. From a managerial perspective, increasing the difference between the release and due dates for a better JIT performance may worsen the environmental impact. Lighter trucks can reduce the environmental costs without affecting the JIT performance, whereas a smaller fleet negatively affects both objectives. [ABSTRACT FROM AUTHOR]

This study investigates the impacts of various factors on e-bike riders' injury severity in crashes with motor vehicles, based on the in-vehicle recording video crash data in China. Variables from human factors, vehicle characteristics, road conditions, and environmental attributes are extracted from the video, especially for drivers and riders' illegal and avoidance behaviour before the crash, and sun shade canopy use. Results of mixed logit models reveal that drivers' speeding, running red lights, slow-down and swerve behaviour, light trucks, heavy trucks, and buses have significantly varied impacts on riders' injury. Moreover, both drivers and riders' illegal behaviour leads to an increased injury, while their avoidance behaviour before crashes can protect riders. In addition, types of visual obstacles, accidents occurring at night, large vehicles' involvement, and the application of sunshade canopies by riders increased the probability of severe injury, while helmet use can protect riders in accidents with motor vehicles. [ABSTRACT FROM AUTHOR]

To tackle the energy-saving optimization issue of plug-in hybrid electric trucks traversing multiple traffic light intersections continuously, this paper presents a double-layer energy management strategy that utilizes the dynamic programming–twin delayed deep deterministic policy gradient (DP-TD3) algorithm to synergistically optimize the speed planning and energy management of plug-in hybrid electric trucks, thereby enhancing the vehicle's passability through traffic light intersections and fuel economy. In the upper layer, the dynamic programming (DP) algorithm is employed to create a speed-planning model. This model effectively converts the nonlinear constraints related to the position, phase, and timing information of each traffic signal on the road into time-varying constraints, thereby improving computational efficiency. In the lower layer, an energy management model is constructed using the twin delayed deep deterministic policy gradient (TD3) algorithm to achieve optimal allocation of demanded power through the interaction of the TD3 agent with the truck environment. The model's validity is confirmed through testing on a hardware-in-the-loop test machine, followed by simulation experiments. The results demonstrate that the DP-TD3 method proposed in this paper effectively enhances fuel economy, achieving an average fuel saving of 14.61% compared to the dynamic programming–charge depletion/charge sustenance (DP-CD/CS) method. [ABSTRACT FROM AUTHOR]

In order to improve the vehicle driving range of a pure electric light commercial vehicle, this paper proposes to reduce the electric power consumption per 100 kilometers by reducing power consumption and increasing coasting energy recovery power. Firstly, for ECO energy-saving mode, the paper proposes the energy-saving control technology based on different vehicle usage scenarios and working conditions, which significantly reduces the energy consumption of the vehicle in the whole scenario. Secondly, in the view of the coasting energy recovery deceleration of commercial vehicles with empty and full load varies greatly, the paper proposes the energy recovery control based on the vehicle mass to achieve the same coasting deceleration under different loads to recover more energy. Then, for the problem that coasting energy recovery is usually designed with low adhesion coefficient road surface, the paper proposes adaptive adjustment of coasting energy recovery based on road adhesion coefficient. Finally, the pure electric light truck is tested on real road. The results show that the ECO mode reduces the electricity consumption per 100 kilometers by 2.9%, and by 2.1% for scenarios of turning on the air conditioning and opening the car door. The energy recovery strategy based on the vehicle' s mass shows a 2.7% reduction in electricity consumption per 100 kilometers. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Harbin Institute of Technology. Social Sciences Edition / Haerbin Gongye Daxue Xuebao. Shehui Kexue Ban is the property of Harbin Institute of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Concerns are growing both within the Biden Administration and in Congress over a potential flood of low-priced electric vehicles (EVs) from China, directly or, more likely, via third countries such as Mexico. BYD, a leading Chinese producer, has announced in spring 2024 that it intends to establish production facilities in Mexico soon, with an initial capacity of 150,000 cars annually, although in August it reportedly deferred those plans until after the U.S. presidential election.1 While BYD has contended that such production would be for the local Mexican market and for export to the more than fifty countries with which Mexico has free trade agreements, observers believe that the U.S. market is the real prize given its enormous size, with more than 15.5 million auto and light trucks sold in 2023. This article begins with a brief discussion of the current situation and remedial legal and practical measures likely to be applied to trade in passenger vehicles under the United States-Mexico-Canada Agreement (USMCA) and relevant World Trade Organization (WTO) law. This is followed by the rationale for BYD and perhaps other Chinese auto producers to build factories in Mexico, the legal and practical options for BYD and other Chinese autos and SUVs assembled in Mexico to enter the U.S. market, and the trade remedy and national security actions available to the U.S. government to exclude those imports from entering the United States. Finally, this article examines the implications of the exclusion policies that appear likely to be followed by either Democratic or Republican administrations in the foreseeable future and offers some recommendations. [ABSTRACT FROM AUTHOR]

Fuel economy and improved vehicle safety are key to the modernisation of cars. With more vehicles on the road, efficient lighting is essential. LED vehicle lighting technology offers energy savings, improves fuel consumption, extends service life and reduces service costs, making it a popular choice for higherend vehicles. Improved brightness in low visibility reduces driver reaction times. This study investigates a lighting retrofit for an MP13 lift truck and its effect on alternator loads. The results show significant improvements in brightness, energy consumption and lifetime compared to conventional bulbs. Strategically placed LED lights improve safety and reduce engine load, especially when the platform is stationary. [ABSTRACT FROM AUTHOR]

Extensive vehicle fires threatening suspension bridges in the last decade have aroused an emerging demand to estimate the fire safety of hanger systems. One of the paramount tasks for evaluating the fire resistance of hangers is to calculate their temperatures. However, as plans always lag behind events, no competent temperature calculation methods are available now for engineers, whether vehicle fire models, thermal boundaries on hanger surfaces, or cross-sectional heat transfer formulations. This paper addresses these three issues and then proposes an integrated framework for assessing the thermal response of hanger systems subjected to vehicle fires. Vehicular fires were classified into five grades, adapted to cars, buses, light goods trucks, medium goods trucks, and tanker trucks, respectively. This hierarchy was validated using 16 full-scale vehicle fire tests in opening or tunnel conditions. An empirical formulation of thermal radiation developed for pool fires was adopted to envelope the heat flux applied by passenger vehicle fires on the hanger surface and was validated using five tests. Radiation from truck fires was constructed using a cuboid solid radiative flame. The spatial heat fluxes surrounding Grade-5 vehicle fires typified by tanker fires were computed using the computational fluid dynamics method validated by two large-scale outdoor trench fires. With these quantitative thermal boundaries on hanger exteriors, the transient temperature across the hanger section was derived using the lumped capacitance method, validated by finite-element models in various scenarios. As a multigrade temperature estimation methodology proposed for hangers subjected to vehicle fires, this method is easy to implement. It can serve in future structural fire design of critical suspension bridges with high exposure risks to vehicle fires. [ABSTRACT FROM AUTHOR]

As a core component of the powertrain system of Electric Logistics Vehicles (ELVs), the gearbox is crucial for ensuring the reliability and stability of ELV operations. Traditional fault diagnosis methods for gearboxes primarily rely on the analysis of vibration signals during operation. This paper presents research on diagnosing gear tooth wear faults in ELV powertrains using motor current signals. Firstly, an experimental test platform was constructed based on the structural principle of the powertrain of ELV models. Subsequently, a pure electric light truck powertrain gearbox with tooth wear was tested. Time–frequency domain analysis, amplitude analysis, ANOVA analysis, kurtosis analysis, and zero−crossing points analysis were used to analyze the U−phase current of the motor connected to the gearbox to study the characteristics of the phase current of the drive motor after tooth wear. The results indicate that while the time–frequency domain characteristics of the U−phase currents are not significantly altered by tooth wear faults, the amplitude, variance, and kurtosis of the current increase with the severity of the wear. Conversely, the number of zero−crossing points decreases. These findings provide valuable insights into new methodologies for diagnosing faults in ELV powertrain systems, potentially enhancing the efficiency and effectiveness of troubleshooting processes. [ABSTRACT FROM AUTHOR]

Copyright of Secuencia: Revista de Historia y Ciencias Sociales is the property of Instituto de Investigaciones - Dr. Jose M. Luis Mora and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Earthquake (1000-3274) is the property of Editorial Office of Earthquake Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The history of airbags for occupant protection in frontal crashes is reviewed from the perspective of a former Senior Executive at NHTSA from the early 1970's to the late 1980's. This paper summarizes the factors that led to regulatory delays as well as those that led to voluntary adoption of airbags by several manufacturers. The regulatory history and interactions with airbag suppliers and vehicle manufactures is recounted citing key steps in the evolution of frontal airbags. When the Advanced Notice of Proposed Rulemaking for Standard 208, "Occupant Protection" was issued on July 2, 1969 the Safety Agency anticipated that the industry response would provide automatic frontal crash protection from airbags that deployed to protect all front seat occupants from injury in severe frontal crashes. It was not until, September 1, 1998 that airbags were required in all cars and light trucks. The interim 29 years involved a series of stops and starts during which most of the original airbag suppliers lost interest and abandoned the airbag market. The issues associated with airbags and their place in Standard 208 were directly influenced by interventions from the President, the Congress, the Supreme Court, Secretaries of Transportation, NHTSA Administrators, the Presidents of US Auto Companies and Senior Executives of Insurance Companies. In 1966, there was support from the US auto industry for a single source of safety regulations that apply to new vehicles sold in the US. This is evidenced by the unanimous passage by the House of Representatives and Senate of the Law that created the Federal auto safety regulatory framework. The Law also required seatbelts in new cars and prohibited States from making separate safety rules. However, the large safety benefits offered by seatbelts were negated because they were rarely used. Consequently, finding ways of providing high levels of protection without requiring action by occupants became a goal of the new Safety Agency. The airbag offered the possibility of achieving that goal. From the initial airbag notice of proposed rulemaking on July 2, 1969, Safety Agency required 2 years to resolve objections before a final Standard 208 could be issued (on July 8,1971). The subsequent industry opposition to the Standard 208 employed Presidential influence and Court suits to cause a 5½ year delay until the Coleman Decision on December 6, 1976. Changes in regulatory approach of the Ford, Carter, and Reagan Administrations and associated Court suits caused another 7½ year delay until the Dole Decision on July 17, 1984. It required another 7 ½, until December 18, 1991, for market forces to reduce industry opposition to airbags and permit Congress to pass a law that mandated them. Another 6½ years of lead time was required before all cars and light trucks were required to meet the airbag standard. During the mid and late 1980's vehicle safety ratings, seatbelt use laws, and Vince and Larry PSA's had all acted to increase safety awareness and safety belt use. Consequently, added public demand for vehicle safety features slowly developed. Changes in economic incentives encouraged a number of vehicle lines to install driver airbags as standard equipment and the feature was being widely advertised by Chrysler. This combination of events made it possible for Congress to pass and President Bush 41 to sign legislation requiring airbags in cars and light trucks by September 1, 1998 – more than 29 years after the initial rulemaking notice in 1969. [ABSTRACT FROM AUTHOR]

The transport sector is the second leading emitter of greenhouse gas emissions (GHGEs) from fuel combustion activities on a global scale. Reducing emissions related to this sector requires detailed data about the emissions by vehicle type and traveled distance. Generally, these data are missing in developing countries, which makes difficult the establishment of effective policies for the reduction of these emissions. This paper presents a hybrid method to estimate these emissions using the IPCC 2006 guidelines. The method combines bottom-up and top-down approaches to estimate vehicular emissions using data about the vehicle type, vehicle kilometers traveled, and fuel consumption. This method is applied for the first time for the Palestinian territory. Data have been collected from the administration, official reports, and papers. The results show a significant increase in the total vehicles in Palestine, particularly diesel vehicles. Emissions from the on-road transport system were approximately 2,207,834 tons of CO2eq in 2019. Diesel vehicles were responsible for about 75% of these emissions. Private cars were the most significant contributor to these emissions, with a share exceeding 50% of the total emissions, followed by commercial vehicles and light trucks (20%), public taxis (9%), and buses (7%). These results show clearly that the GHGEs reduction policies in Palestine should focus on diesel and private vehicles by developing the public transport systems and replacing diesel and gasoline vehicles with more environmentally friendly vehicles, such as hybrid and electric cars. [ABSTRACT FROM AUTHOR]

Animal vehicle crash is a critical yet often under-emphasized safety concern of Louisiana. During 2014-2018, over 14,000 animal-related crashes cost Louisiana more than $520 million. To identify multiple key contributing factors and their association patterns, this study applied association rules mining in the dataset of animal-related roadway crashes that occurred during 2014-2018. Since high proportions of animal-related crashes involve complaint and no injury of vehicle occupants, separate analyses were performed for KAB (fatal, severe, and moderate injury) and CO (possible/complaint and no injury) crashes. Top rules ordered by higher lift values were interpreted and compared to implicate the quantified likelihood of crash patterns. KAB rules presented the likelihood of associations of characteristics such as unlighted dark conditions, interstate and parish roads, a wide range of speed limits, residential and open country locations, normal and rainy weather conditions, light trucks, young drivers, etc. The majority of CO crash patterns were associated with interstates, straight segments, normal driver conditions, clear weather, unlighted dark conditions, open country locations, a speed limit of 97 km/h or higher, etc. Findings in this study and their implications supported by prior studies are expected to be beneficial in strategic planning for identifying implementable countermeasures for animal-vehicle crashes. [ABSTRACT FROM AUTHOR]

Forward collision warning (FCW) and automatic emergency braking (AEB) have found to be effective on cars, SUVs, and large trucks. The objective of this study was to extend prior work and estimate the effects of FCW and AEB on pickups. Rear-end crashes where a pickup with optional FCW or AEB was the striking vehicle were identified in 25 U.S. states during 2017–2020. Quasi-induced exposure was performed with logistic regression to compare rear-end-striking crashes between vehicles with and without the systems relative to being struck in the rear. Rear-end-striking crash rates per registered vehicle year were also compared between equipped and non-equipped pickups with Poisson regression. The association of the systems with severity in the rear-end-striking crashes that occurred was examined with logistic regression. In the quasi-induced exposure analysis, AEB was associated with statistically significant 34% reductions in the risk of a rear-end-striking crash of any severity and with any injuries, and a 76% reduction in the risk of a rear-end-striking crash with serious or fatal injuries (p = 0.09). FCW was associated with statistically significant declines of 22% in the risk of a rear-end-striking crash with any injuries and 71% in the risk of a rear-end-striking crash with serious or fatal injuries, but FCW was not associated with a change in all rear-end-striking crashes. Results were similar in Poisson regression models for all but FCW's effect on all rear-end-striking crashes. The odds that rear-end-striking crashes involving pickups with FCW resulted in any injuries were 26% lower, and serious/fatal injuries were 75% lower, than those involving pickups without the system. AEB was associated with a nonsignificant reduction in the odds of serious/fatal injuries when a rear-end strike occurred and no change in the odds of any injuries. Consistent benefits for front crash prevention systems have been demonstrated for a wide range of vehicle types, now including a sample of pickups. Gaps in proposed U.S. regulations should be filled so that AEB is required equipment on all new vehicles. [ABSTRACT FROM AUTHOR]

The increasing market share of electric vehicles and the politically intended phase-out of the internal combustion engine require reliable and realistic predictions for future consumption and greenhouse gas emissions as a function of technological solutions. This also includes the consumption- and emission-intensive transport of goods. We consider both passenger vehicles and commercial vehicle traffic in our study and have investigated whether there are drive alternatives to the battery electric vehicle that enable uninterrupted trips with a long range, especially for regional delivery services and internationally active freight forwarders. To this end, we have analysed three system architectures and their expected technological progress until 2050: battery electric vehicles (BEV), fuel cell electric vehicles (FCEV), and internal combustion engine vehicles (ICEV) running on compressed natural gas (CNG). The latter case serves as a best-practice reference from a combustion technology perspective. The analysis is based on a validated and proven physical model and predicts that the BEV2050 will consume 3.5 times less energy and emit 15 times fewer greenhouse gases than the ICEV-CNG2020, whereas the FCEV2050 will consume 2.5 times less energy and emit 6.5 times fewer greenhouse gases than the ICEV-CNG2020 on the road (hilly terrain, transition season, and WLTP triple-mixed drive cycle). The advantages of the BEV result from the shorter drive train with lower total losses. Our results thus confirm the expected role of the BEV as the dominant drive technology in the future, and light vehicles with low-to-medium-range requirements will especially benefit from it. On the other hand, since the greenhouse gas emissions of the FCEV2050 are lower by a factor of 6.5 than those of the ICEV-CNG2020, it is reasonable to conclude that the FCEV can play a significant role in transport until 2050 when long distances have to be covered. Our model-based approach also allows us to determine the energy fractions of the acting physical forces and thus calculate the consumption shares: electric drive recuperation increases BEV and FCEV range by about 15% in 2020 and will increase it by about 20% in 2050, depending on drive technology and vehicle type. Air and rolling resistance contribute 20% each to the total consumption. The consumption of the accessories of modern vehicles with a share of about 10% of the total consumption cannot be neglected. [ABSTRACT FROM AUTHOR]

We present the first machine-learned multiple-input multiple-output aerodynamic feedback control under varying operating conditions. Closed-loop control is relevant to many fluid dynamic applications ranging from gust mitigation to drag reduction. Existing machine learning control investigations have been mainly applied under steady conditions. The current study leverages gradient-enriched machine learning control (Cornejo Maceda et al. in J Fluid Mech 917:A42, 2021) to identify optimal control laws under unsteady conditions. The approach is exemplified on a coupled oscillator system with unsteady coupling and demonstrated for a generic truck model undergoing a yawing maneuver. Key enablers of the experiment are a rich set of pneumatic actuators and pressure sensors. The results demonstrate the method's capabilities in identifying an efficient forcing for control under dynamically changing conditions. This automated and generalizable closed-loop control strategy complements and expands the machine learning control field and promises a new fast-track avenue to efficiently control a broader set of fluid flow problems. [ABSTRACT FROM AUTHOR]

More than 30% of cellphone-distracted fatal crashes occurred to drivers younger than 25-years-old in 2018, even though they constitute less than 12% of total licensed drivers in the U.S. Using joint correspondence analysis (JCA), this study analyzed six years (2014–2019) of cellphone-related fatal crashes involving young drivers based on the data from the Fatality Analysis Reporting System (FARS). This unsupervised learning algorithm can graphically display the co-occurrence of variable categories in a lower-dimensional space by effectively summarizing the knowledge of a complex crash dataset. The Boruta algorithm was applied to select the relevant features from the preliminary crash dataset. The empirical results of JCA manifest a few interesting fatal crash patterns. For example, young male drivers in light trucks were involved in deadly collisions while performing specific cellphone activities (other than talking and listening), cellphone-related fatal crashes occurred to young females with prior crash records, and so on. Apart from alcohol and drug involvement, this study identified young drivers' additional risk-taking maneuvers while engaged in cellphone usage, including: disregarding traffic signs and signals, speeding, and unrestrained driving. The associations could guide the safety officials and policymakers in developing appropriate engineering, education, and enforcement strategies when dealing with cellphone-distracted young drivers. [ABSTRACT FROM AUTHOR]

• A new method is proposed for non-contact identification of tire inflation pressure based on Tire-YOLO and tire deflection. • The Tire-YOLO is developed using YOLOv5 as the backbone network and introducing the Dark_DenseNet feature reuse and CIoU_Loss function, for detecting tire characters and extracting tire deformation features. • A statistical relationship between the actual and recommended pressures is established to obtain the statistical pressure, which is corrected based on visually identified tire deflection to an approximation of the actual pressure. • Field tests are conducted on the pressures of passenger cars, buses, light trucks, and heavy trucks to verify the proposed method. Errors in determining tire inflation pressure are within 10% of the actual pressure for all the studied cases. Tire inflation pressure has a significant impact on vehicle performance and safety. Existing tire pressure identification methods rely on sensors, which have limitations such as high maintenance costs and poor durability. This study proposes a non-contact method for tire pressure identification using Tire-YOLO and deflection. Firstly, a Tire-YOLO model is developed to identify tire specifications in images, which are used to obtain recommended pressure referring to the standards. Then, the statistical relationship between actual and recommended pressures is established to obtain statistical pressure. Next, the statistical pressure is corrected using the visually identified tire deflection, serving as an approximation of actual pressure. Finally, field tests are conducted on different tire types to verify the proposed method. The results indicate that the inflation pressures determined using this method are within 10% of actual pressures for all the cases. The proposed method provides a potential way for rapid identification of inflation pressure. [ABSTRACT FROM AUTHOR]

Vehicle suspension vibration is a prevalent form of oscillation, with approximately 22.5 % of automobile energy dissipated through suspension-induced vibration. This phenomenon suggests that recovering the energy dissipated by the suspension system holds significant potential. This paper introduces a novel piezoelectric energy harvesting shock absorber (EHSA) based on non-contact magnetic force for light truck applications. The vibration of the vehicle suspension system is transformed into the rotation of a ball screw, enabling the one-way high-speed output of the rotor through a one-way bearing and planetary gear mechanism. Based on the non-contact magnetic force, the piezoelectric patches generate frequent oscillations, and a novel energy harvesting circuit is designed that efficiently converts the output of multiple piezoelectric units into usable electricity. The damping and energy harvesting characteristics of the EHSA with different external and internal variables are explored. Under sinusoidal excitation of 40 mm amplitude and 0.4 Hz frequency, the EHSA achieves a maximum output power of 7.51 W, with an average output power of 1.89 W. Furthermore, under random action, the EHSA can successfully illuminate 824 LED lights, enabling the temperature and humidity sensor to function normally. These findings indicate that the proposed EHSA can effectively harness vehicle suspension vibration to power onboard self-powered appliances while offering a new design idea for integrating vibration energy harvesters into vehicles. • A piezoelectric energy harvesting shock absorber is proposed for light trucks. • The damping characteristics and energy harvesting characteristics are revealed. • The relative significance of different influencing factors are articulated. • During the random operation of the absorber, 824 LED lights can be successfully lit. [ABSTRACT FROM AUTHOR]

A test program to characterize the benefits and challenges of applying a European series production catalyzed gasoline particulate filter (GPF) to a U.S. Tier 2 turbocharged light duty truck (3.5 L Ecoboost Ford F150) in the underfloor location was initiated at the U.S. Environmental Protection Agency. The turbos and underfloor location keep the GPF relatively cool and minimize passive regeneration relative to other configurations. This study characterizes the relatively cool GPF in a lightly loaded state, approximately 0.1-0.4 g/L of soot loading, using four test cycles: 60 mph steady-state, 4-phase Federal Test Procedure city drive cycle (FTP), highway dirve cycle, and US06. Measurements include GPF temperature, soot loading, GPF pressure drop, brake thermal efficiency (BTE), CO2, particulate matter (PM) mass, elemental carbon (EC), filter-collected organic carbon (OC), CO, total hydrocarbons (THC), and NOx emissions. The lightly loaded underfloor GPF achieves an 85-99% reduction in PM mass, a 98.5-100.0% reduction in EC, and a 65-91% reduction in filter-collected OC, depending on test cycle. The smallest reductions in PM and EC occur in the US06 cycle due to mild GPF regeneration caused by GPF inlet temperature exceeding 500 °C. EC dominates filter-collected OC without a GPF, while OC dominates EC with a GPF. Composite cycle CO, THC, and NOx emissions are reduced by the washcoat on the GPF but the low temperature location of the GPF does not make best use of the catalyzed washcoat. Cycle average pressure drop across the GPF ranged from 1.25 kPa in the four-phase FTP to 4.64 kPa in the US06 but did not affect BTE or CO2 emissions in a measurable way in any test cycle. [ABSTRACT FROM AUTHOR]

• The injury severity of the reverse sideswipe crashes involving pickups and SUVs is analyzed. • Heterogeneous means and heteroscedastic variances inherent in random parameters are revealed. • Temporal volatility is observed across three different time periods. • Fluctuations in time of day imply the variations between daytime and nighttime. • Potential factors affecting the injury severity of reverse sideswipe crashes are investigated. Problem: Sideswipe collisions in the opposite direction often result in more severe injuries than the typical same-direction crashes, especially when light trucks are involved. This study investigates the time-of-day fluctuations and temporal volatility of potential factors that affect the injury severity of reverse sideswipe collisions. Methods: A series of random parameters logit models with heterogeneous means and heteroscedastic variances are developed and utilized to explore unobserved heterogeneity inherent in variables and preclude biased parameter estimation. The segmentation of estimated results is also examined through temporal instability tests. Results: Based on crash data in North Carolina, a number of contributing factors are identified that have profound associations with obvious and moderate injuries. Meanwhile, significant temporal volatility is observed in the marginal effects of several factors such as driver restraint, alcohol or drugs impact, Sport Utility Vehicle (SUV) at fault, and adverse road surface across three different periods. Fluctuations in the time of day indicate that restraint with belts is more effective in mitigating the obvious injury in the nighttime, and high-class roadway sustains a higher probability of resulting in more serious injury compared to the daytime. Practical Applications: The findings of this study could help further guide the implementation of safety countermeasures related to atypical sideswipe collisions. [ABSTRACT FROM AUTHOR]

• Light/medium truck drivers involved had higher FROI rates than heavy truck drivers involved in crashes. • Younger light/medium truck drivers were represented at a higher proportion in crash FROIs compared to younger heavy truck drivers. • The retail trade industry made up the largest percentage of light/medium truck local crash FROIs (47%); the transportation and warehousing industry was most frequently cited in heavy truck FROIs. • Light/medium truck crashes most frequently involved being rear-ended, running red lights, and turning in front of other vehicles. Objective: Multiple heavy truck driver injury studies exist, but there is a paucity of research on light and medium truck driver injuries. The objective of this study was to use first report of injury (FROI) data to: (a) compare demographic and injury characteristics; (b) assess workers' compensation (WC) claim disposition and lost work time status; and (c) describe injury scenarios by vehicle type for heavy truck and light/medium truck driver local crashes. Method: Kentucky Department of Workers' Claims FROI quantitative and free text data were analyzed for years 2010–2019. Of 800 total FROIs, 451 involved heavy trucks and 349 involved light or medium trucks. Results: There was a higher light/medium truck driver crash FROI rate compared to the heavy truck driver crash FROI rate. There was a higher proportion of younger light/medium truck driver crash FROIs compared to younger heavy truck driver crash FROIs. The retail trade industry made up the largest percentage of light/medium truck local crash FROIs (47%); the transportation and warehousing industry was most frequently cited in heavy truck FROIs (46%). The heavy truck types most frequently identified in FROIs were semi-trucks (13%) and dump trucks (11%). The most common light/medium truck type identified was delivery trucks (30%). Most commonly, heavy truck crash FROIs involved rollovers, driving off/overcorrecting on narrow roadways, and driving downhill/unable to downshift. Light/medium truck crash FROIs most frequently involved being rear-ended, running red lights, and turning in front of other vehicles. Conclusions: The utilization of WC FROI data highlighted top injury scenarios and specific vehicle types for targeting driver safety training among truck drivers, particularly light/medium truck drivers. Road safety policies regarding driver training, crash reviews, and in-vehicle monitoring systems are needed for truck drivers with previous crash injuries, especially for light and medium truck drivers. Practical applications: Enhanced safety training on speeding on narrow roadways, on nearing intersections, and on downshifting on hills is needed for semi-truck, dump truck, and coal truck drivers with previous crash injuries. Rear-end crash prevention training (e.g., gradual stopping and checking mirrors) is needed for drivers of furniture, automotive parts and accessories, and groceries and soft drink delivery trucks with previous crash injuries. [ABSTRACT FROM AUTHOR]

The research was conducted on a forest road on the territory of the State Forests in Poland, in the Brzeziny Forest District, where eight test sections with a total length of 422 m were created with different pavement system on a low-bearing soil substrate (clay, silt loam) as part of the road reconstruction in 2016. The bearing capacity of the pavement was evaluated based on the static strain modulus ME MN·m−2 by measuring with a statistic plate (VSS), the dynamic deformation modulus Evd MN·m−2 obtained from lightweight deflectometer measurements, and the elastic deflection of the pavement Us mm evaluated from Benkelaman beam measurements. It has been shown that pavements made of crushed aggregate and common gravel on timber roller substructure maintain good bearing capacity parameters, where the average values of secondary modulus of strain are above 130 MN·m−2, and in the case of pine rollers, this modulus has increased. Pavements on low-bearing soils reinforced with willow brushwood mattresses have low bearing capacity parameters, with averages of 26.09 ≤ MEII ≤ 53.93 and 22.1 ≤ Evd ≤ 39.1 MN·m−2, but the technical condition of the pavement makes it possible to continue carrying out forestry-related transportation. The research confirms the possibility of reinforcing soils with poor bearing capacity with wooden rollers, and in the case of willow mats for roads with light truck movements. [ABSTRACT FROM AUTHOR]