Truck Drivers Research Articles

Research on logistics that considers the working environment of truck drivers during the COVID-19 pandemic

Logistics concerns organisational planning, implementation and operations and plays an important role in the supply chain. During the COVID-19 pandemic, many supply chains broke down and goods became difficult to procure. The crisis underlined the importance of logistics. Professor Kuninori Suzuki, Nihon University, is a leader in the field of logistics who has authored well respected and highly read books that have been translated into different languages. He is currently conducting research on how the pandemic impacted the working environment of truck drivers. He is developing a logistics system that can deal with the shortage of truck drivers that keeps digital transformation (DX) in mind. By utilising AI to optimise operation scheduling, Suzuki wants to improve productivity in the loading and unloading of goods. He is also using AI to clarify the criteria for making decisions for return cargo and making recommendations on handling goods on a pallet-by-pallet basis. The goal is the development of a freight transport model that minimises the burden on truck drivers. A key focus for Suzuki is the food and beverage industry as this sector was most affected during quarantine, forcing significant changes on how food and drink is moved through supply chains. He utilises statistical processing and numerical analysis through computer simulations in his work. There is a focus on collaboration, including in-lab discussions with colleagues and feedback on the issues facing the companies with whom they are partnering. Suzuki set out to verify if the large-scale introduction of unmanned transport forklifts would reduce labour costs and improve the quality of unloading and loading.

Risk of crashes among self-employed truck drivers: Prevalence evaluation using fatigue data and machine learning prediction models

Introduction: Transportation companies have increasingly shifted their workforce from permanent to outsourced roles, a trend that has consequences for self-employed truck drivers. This transition leads to extended working hours, resulting in fatigue and an increased risk of crashes. The present study investigates the factors contributing to fatigue and impairment in truck driving performance while developing a machine learning-based model for predicting the risk of traffic crashes. Method: To achieve this, a comprehensive questionnaire was designed, covering various aspects of the participants’ sociodemographic characteristics, health, sleep, and working conditions. The questionnaire was administered to 363 self-employed truck drivers operating in the State of São Paulo, Brazil. Approximately 63% of the participants were smokers, while 17.56% reported drinking alcohol more than four times a week, and also admitted to being involved in at least one crash in the last three years. Fifty percent of the respondents reported consuming drugs (such as amphetamines, marijuana, or cocaine). Results: The surveyed individuals declared driving for approximately 14.62 h (SD = 1.97) before they felt fatigued, with an average of approximately 5.92 h of sleep in the last 24 h (SD = 0.96). Truck drivers unanimously agreed that waiting times for truck loading/unloading significantly impact the duration of their working day and rest time. The study employed eight machine learning algorithms to estimate the likelihood of truck drivers being involved in crashes, achieving accuracy rates ranging between 78% and 85%. Conclusions: These results validated the construction of accurate machine learning-derived models. Practical Applications: These findings can inform policies and practices aimed at enhancing the safety and well-being of self-employed truck drivers and the broader public.

The Antecedents of Perceived Value in Cargo Tires Retreading

Objective: Due to increasingly low freight prices and increasingly high operating costs, tire retreading presents itself as a viable and safe solution for costs reduction. It presents itself as a more sustainable alternative in terms of tire consumption. This paper discusses the consumption behavior of small fleet owners in relation to the purchase of cargo tire retreading services. Theoretical Framework: Our theoretical framework is organized into two axes: how tires and their retreading are carried out in Brazil considering small entrepreneurs, and how the multidimensionality of consumer behavior affects the relationship with the tire retreading service (based on the SERV-PERVAL proposal developed by Petrick (2002) and the “Affective Behavior” dimension of the model developed by Roberts, Varki and Brodie (2003), called Relationship Quality). Method: A model on the antecedents of the perception of value was proposed and refined (the questionnaire items were reorganized through exploratory and confirmatory factor analysis) based on a survey of 109 truck drivers. Results and Discussion: The antecedents of the perception of value of small fleet owners in relation to the cargo tire retreading service are the Sentimental constructs; Reputation; Loyalty; Convenience; Cost/Benefit. Originality/Value: Previous studies focused on the field of production engineering, use, performance and impacts on the environment, new tire purchasing behavior, association studies or government, not presenting in the literature studies in marketing or even business administration and its derived areas for tire retreading services. Research Implications: This study helps small tire retreaders to better understand their customers and enables better customer service that culminates in increased market share and profitability.

Analyzing Travel and Emission Characteristics of Hazardous Material Transportation Trucks Using BeiDou Satellite Navigation System Data

Road hazardous material transportation plays a critical role in road traffic management. Due to the dangerous nature of the cargo, hazardous material transportation trucks (HMTTs) have different route selection and driving characteristics compared to traditional freight trucks. These differences lead to unique travel and emission patterns, which in turn affect traffic management strategies and emission control measures. However, existing research predominantly focuses on safety aspects related to individual vehicle behavior, with limited exploration of the broader travel and emission characteristics of HMTTs. To bridge this gap, this study develops a comprehensive framework for analyzing the travel patterns and emissions of HMTTs. The methodology begins by applying a Gaussian mixture distribution model to identify vehicle stop points, eliminating biases associated with subjective settings. Origin–destination (OD) pairs are then determined through stop time clustering, followed by the extraction of travel characteristics using non-negative matrix factorization. Emissions are subsequently calculated based on the identified trip data. The relationship between emissions and land use characteristics is further analyzed using geographically weighted regression (GWR). Crucially, this study leverages data from the BeiDou Satellite Navigation System, focusing on HMTTs operating within Shanghai. The processed data reveal three distinct travel modes of HMTTs, categorized by spatiotemporal patterns: Daytime—Surrounding cities, Early morning—In-city, and Midnight—Scattered. Moreover, unlike other road vehicles, HMTT emissions are heavily influenced by industrial and company-related points of interest (POIs). These findings highlight the significant role of BeiDou Satellite Navigation System data in optimizing HMTT management strategies to reduce emissions and improve overall safety.

ANALISIS RISIKO TERHADAP PERILAKU YANG MEMBAHAYAKAN PADA PENGEMUDI DUMP TRUCK DALAM PENGANGKUTAN BATUBARA DI PT BAHANA BUMI MANDIRI KABUPATEN LAHAT PROVINSI SUMATERA SELATAN

PT Bahana Bumi Mandiri is an experienced logistics and contractor transportation provider company since 2016 located in South Sumatera. One of the accident prevention programs at PT Bahana Bumi Mandiri’s operations is to emphasize the importance of communication with dump truck drivers, and one form of implementing this programis to ensure that the unit is on the dump truck driver when operating. The aim of this research is to find out the risk of dangerous behavior of dump truck drivers when transporting coal and to find out efforts to improve or solve the risk and behavior that have been caused by dump truck drivers when transporting coal. The standard used at PT Bahana Bumi Mandiri is P2H (Daily Inspection and Checking). The implementation of safe driving at PT Bahana Bumi Mandiri is still relatively minimal so it is necessary to add safety driving to reduce potential dangers that could occur. However, it is necessary to know first the attitude of dump truck drivers by asking question in the form of a questionnaire so the data is processed so that the results can be known. If the need for safe driving in mines is not implemented more fully, it can increase the risk of accidents or incidents in the work emvironment.

The relationships between financial performance and driver compensation and safety outcomes in the trucking industry: a systematic review

ABSTRACT Heavy trucks largely contribute to road fatalities and injuries with most of the severely injured and killed being road users other than heavy truck occupants. Research has shown that the causes of truck crashes have economic roots, including high levels of competition creating economic pressure that could increase the likelihood of carriers reducing safety investments and adopting payment practices that encourage truck drivers to drive faster and longer than legally required. With a large body of research on safety policies and payment practices in the heavy trucking industry, there is a strong need to comprehensively understand the relationships between economic pressure in terms of truck company financial performance and driver compensation, and safety outcomes and the factors influencing the relationships. This paper presents a systematic review of the literature to address this important gap in the literature. The review identified 43 English-language articles published between 1988 and 2024. There is a general consensus in these articles that paying truck drivers based on the amount of work performed is associated with poorer safety outcomes than paying them based on the amount of time worked. In contrast, higher pay levels and payments for non-driving tasks positively influence safety outcomes. Regarding truck company financial performance, most of the studies reported a positive influence on safety outcomes. This review highlights the strengths and limitations of the methodologies of existing studies and proposes areas for future research.

Examining Long-Haul Truck Driver Needs and Preferences to Improve the Truck Stop Environment.

This study examined and compared the truck stop needs and preferences of long-haul truck drivers (LHTD) based on gender. LHTD were recruited from various provincial and federal trucking associations and trucking companies across Canada. A sample of 406 drivers completed an online survey that consisted of questions on demographics, health conditions and behaviours, and preferences for truck stop amenities. LHTD reported that parking, healthy and affordable foods, showers, washrooms, and exercise facilities with basic equipment are the most important amenities needed at truck stops. Compared to men, women were significantly more likely to desire a picnic area at truck stops; all other amenities were consistently desired by both genders. Improvements to the truck stop environment are needed to support the health and wellness of LHTD.

Trucks-to-trucks: a comparison of the raw forest products transportation industry and other forms of commercial trucking in the US South

ABSTRACT Forest products transportation in the US South is an essential component of the wood supply chain connecting raw materials with manufacturing facilities. Owners and operators of log trucks face many challenges to business success. This review analyzed variables associated with owning and operating commercial trucks in the United States to compare raw forest products transportation and general trucking applications. The variables for both log trucks and general trucking included fuel costs, fuel economy, insurance, driver characteristics and availability, driver wages, truck and trailer configurations, fleet characteristics, weight limits, and safety. Log trucks were approximately 5 years older than other commercial trucks and operated in smaller fleets of 5–10 trucks. The smaller size of log truck fleets often placed them at a disadvantage to larger carriers in insurance and fuel costs, with smaller fleets having less opportunity to buy fuel in bulk and paying 0.006–0.025 USD more per kilometer for insurance than larger fleets. Knowledge gaps include inadequate estimates of the number of log truck operators and limited information related to log truck transportation costs. Continued research into challenges faced by log truck owners is critical to better understand the industry and identify solutions to profitability challenges.

Risk of Raynaud's Phenomenon Among Workers in the Occupational Disease Surveillance System.

Raynaud's phenomenon (RP) is linked to occupational exposures such as vibration, cold temperature, and chemicals. However, large cohort studies examining RP by occupation and sex are scarce. To address this gap, this study aimed to assess risk of RP by both occupation and sex in a large cohort of workers in Ontario, Canada. Workers with accepted lost-time compensation claims were linked to physician billing records to identify diagnoses of RP between 2002 and 2020. A 3-year washout (disease-free) period was applied, and follow-up was limited to 5 years. Cox proportional hazard models were used to estimate hazard ratios (HR) and 95% confidence intervals (CI) for diagnoses of RP, adjusted for age at start of follow-up, birth year, and stratified by sex. A total of 7,131 RP cases were identified among 810,739 workers. Among men, higher risks were observed for truck drivers (HR = 1.23, 95% CI = 1.08-1.41), driver-salesmen (HR = 2.54, 95% CI = 1.21-5.34), those in mining and quarrying-related cutting, handling, and loading (HR = 2.57, 95% CI = 1.29-5.15), and construction trades laboring and elemental work (HR = 1.70, 95% CI = 1.24-2.34). Among women, higher risks were observed for those working in waitressing and related (HR = 1.70, 95% CI = 1.22-2.38), food and beverage preparation (HR = 1.34, 95% CI = 1.02-1.76), and electrical equipment fabricating and assembling (HR 1.96, 95% CI = 1.08-3.55). Study findings show elevated risks of RP among various occupations, with notable differences between men and women. These differences may be attributable to variations in potential exposures and susceptibility to RP. Findings underscore the need for large cohort studies to examine RP across various occupational groups and both sexes.

The transportation efficiency of cargo truck drivers from Thailand to Lao PDR

The purposes of this study are to study (1) opinions on the driving performance of cargo truck drivers and (2) the factors that affect the efficiency of driving cargo trucks from Thailand to the Lao PDR by crossing the first Thai-Lao Friendship Bridge. The study was conducted with a sample of truck drivers who transport goods across the Thailand border to Lao PDR at the Nong Khai Customs Area, Nong Khai Province. 384 respondents were acquired by selection according to their convenience. They then completed a questionnaire with confidence values between 0.70 – 0.90. The statistical data analysis for this study included mean and standard deviation, and structural equation analysis. The results showed that: (1) Truck drivers have various opinions on the personal factors of truck drivers; truck driver performance factors and truck driver transportation efficiency indicators are as follows: speed, economy, safety, comfort and punctuality factors, which are at very high levels and (2) The personal factors of a truck driver have a positive influence on truck driver performance while the truckers’ transportation efficiency and the truck drivers’ performance have positive influences on the efficiency of truck drivers' transportation by 54 percent.

What happened to the driver? Implications of electrification, digitalization, and automation on truck and taxi drivers

What happened to the driver? Implications of electrification, digitalization, and automation on truck and taxi drivers

Transportation and production collaborative scheduling optimization with multi-layer coding genetic algorithm for non-pipelined wells.

The marginal wells in low-permeability oil fields are characterized by small storage size, scattered distribution, intermittent production, etc. The construction of large-scale gathering pipelines has large investment. So the current production mode is featured by single well tank oil storage, oil tank truck transportation and manual tank truck scheduling. At present, oil well production and crude oil transportation scheduling mainly rely on manual formulation, which has poor coordination and seriously restricts the release of oil well production capacity and the reduction of transportation cost. A mixed-integer linear programming (MILP) model representation was proposed in our previous work. The scale of the built model variables is huge, and the model solution time is long. In this paper, a genetic algorithm based on multi-layer coding is proposed. The first layer of the design code is the driving path of the oil tanker, and the second layer is the crude oil loading and unloading amount and the cumulative time. The algorithm expands the search domain by flipping, exchanging and shifting the code. In the case analysis part, the exact algorithm and the genetic algorithm designed in this paper are used to solve cases of different scales (5, 10, 30 and 200 oil wells) respectively, and the correctness and effectiveness of the algorithm are verified. The results show that, compared with the exact algorithm, the genetic algorithm designed in this paper can quickly solve a feasible scheduling scheme under different oil well scales, especially in the case of large-scale (200 wells) oil well groups. The optimal one-time result in the calculation example (200 wells) takes 1062.3s to run, and the total driving distance of all tank trucks in the obtained feasible scheme is 11280km. This study can guide oilfields to quickly formulate dispatching plans and minimize travel distances in non-pipeline well tanker dispatching.

Mississippi Log Trucking Liability Insurance Premiums: A Hedonic Analysis

Abstract Rising liability insurance premiums have negatively impacted log trucking businesses in Mississippi and across the southeastern United States. A statewide mixed-mode log trucking business owner survey was used to study factors impacting liability insurance for Mississippi timber transportation. A hedonic regression model was developed to identify operational characteristics that significantly influenced insurance premiums. Marginal implicit prices were calculated to reveal an average per unit monetary contribution of each significant attribute while holding the others constant. The 3-year inflation-adjusted average for Mississippi companies was $12,466 per truck per year, with a minimum value of $4,000 per truck per year and a maximum of $24,404 per truck per year (all values in US$). On average, each year of owner experience provided a mean insurance premium discount of $72.42. Each additional 1,000 miles (1600 km) traveled by log trucks at the mean insurance premium was valued at $50.00; each safety violation was valued at $3,322; and an overweight violation was valued at $1,311. Implementation of safety practices and safety equipment did not significantly impact insurance premiums. Companies were not directly rewarded for using safety equipment and safety practices but were penalized through increased policy rates when cited for safety and overweight violations. Investing in safety practices (e.g., regular truck inspections, truck driver training, repair and maintenance programs, etc.) and safety equipment (truck scales, cameras, truck tracking, telematics, etc.) would reduce roadside inspection citations and crashes, which contribute to rising liability insurance premiums.

Generalized Additive Models to assess Truck Driver's Perceived LOS of Signalized Intersections

Generalized Additive Models to assess Truck Driver's Perceived LOS of Signalized Intersections

A Comprehensive Overview of Technologies Applied in Hydrogen Valleys

Hydrogen valleys are encompassed within a defined geographical region, with various technologies across the entire hydrogen value chain. The scope of this study is to analyze and assess the different hydrogen technologies for their application within the hydrogen valley context. Emphasizing on the coupling of renewable energy sources with electrolyzers to produce green hydrogen, this study is focused on the most prominent electrolysis technologies, including alkaline, proton exchange membrane, and solid oxide electrolysis. Moreover, challenges related to hydrogen storage are explored, alongside discussions on physical and chemical storage methods such as gaseous or liquid storage, methanol, ammonia, and liquid organic hydrogen carriers. This article also addresses the distribution of hydrogen within valley operations, especially regarding the current status on pipeline and truck transportation methods. Furthermore, the diverse applications of hydrogen in the mobility, industrial, and energy sectors are presented, showcasing its potential to integrate renewable energy into hard-to-abate sectors.

Shedding light on truck driver supply and demand: Heterogeneous state‐level recovery of trucking employment following the COVID‐19 employment shock

AbstractIs there a long‐term systemic shortage of truck drivers? We throw light on the underlying context—the demand for and supply of truck drivers—by investigating why states within the contiguous United States showed vastly different rates of recovery of state‐level truck transportation payrolls for May 2020–December 2021 following the negative employment shock brought about by COVID‐19 lockdowns in April 2020. We focus on heterogeneity in the industries that create demand for trucking services: state‐level natural resource extraction, warehousing, and container port activity. We create a state‐level archival data set of truck transportation establishment payrolls from the Quarterly Census of Employment and Wages, which we combine with other archival sources. We test our hypotheses via discontinuous growth curve models estimated using the mixed effects modeling framework. We find states that saw greater declines in natural resource extraction activity had much slower growth in trucking payrolls for May 2020–December 2021, whereas states that saw more warehousing activity growth or were home to large container ports saw faster growth in trucking payrolls. Our work extends theories regarding labor market dynamics in truck transportation and factor market rivalry, in addition to having important implications for managers and policy makers.

An Optimizing Sustainable Integrated Agricultural Model with Zero Waste and Carbon Neutrality by Bioethanol Truck Transportation with Blockchain Transaction

An Optimizing Sustainable Integrated Agricultural Model with Zero Waste and Carbon Neutrality by Bioethanol Truck Transportation with Blockchain Transaction

Accuracy analysis of cholesterol analyzer in detecting dyslipidemia in truck drivers.

Cardiovascular diseases (CVD) are a leading cause of mortality and morbidity worldwide. Rapid diagnostic tools are crucial for timely intervention, especially in high-risk groups such as truck drivers. In Brazil, the Mission® test uniquely offers test strips for simultaneous measurement of total cholesterol (TC), high-density lipoprotein (HDL), triglycerides (TG), and low-density lipoprotein (LDL). This study evaluates the accuracy of the Mission® analyzer compared to laboratory testing for HDL-C, TG, and TC in truck drivers. A blinded cross-sectional study was conducted among truck drivers aged 30-64 in Campo Grande, Mato Grosso do Sul, Brazil. Spearman correlation, linear regression, and the Bland-Altman analyses were employed to compare lipid profile results between the Mission® analyzer and laboratory methods. A total of 108 samples were analyzed. For HDL, the Mission® analyzer showed a sensitivity of 0.88, a specificity of 0.67, and an area under the curve (AUC) of 0.77 (95% CI: 0.68-0.86). For TG, sensitivity and specificity were 0.96 and 0.98, respectively, with an AUC of 0.97 (95% CI: 0.93-1.0). For TC, the AUC was 0.87 (95% CI: 0.79-0.95). Bland-Altman analysis revealed biases of -4.5 for HDL, 12.4 for TC, and -42.8 for TG between Mission® and laboratory results. The Mission® analyzer demonstrates good accuracy for rapid dyslipidemia diagnosis and Framingham Global Risk Score calculation. It is a valuable tool for initial screening and risk assessment, confirmation with laboratory testing is recommended for definitive diagnosis and treatment planning.

Optimal Weigh-in-Motion Planning for Multiple Stakeholders

Overloaded trucks contribute heavily to road damage and increased maintenance costs, and Weigh-In-Motion (WIM) systems are an effective tool for detecting them without disrupting traffic flow. However, overloaded truck drivers often adjust their routes to avoid WIM stations, complicating enforcement efforts for road management stakeholders. To address these challenges, this study integrates the strategic behaviors of multiple stakeholders with diverse objectives into optimal WIM planning by modeling interactions among the government, pavement management agencies, and drivers. The authorities are responsible for WIM installation, while drivers minimize their respective travel costs. The proposed approach considers both road maintenance costs incurred by authorities and travel costs for drivers, based on a traffic assignment model for each WIM installation strategy. Basic concepts from game theory are adopted to formalize the dynamic interactions among these stakeholders.

Comparative Assessments of At-Sea and Inland Low- and Medium-Pressure CO2 Transport

Developing cost-efficient systems for transporting CO2 is key to accelerating the deployment of carbon capture and storage. The present work explores the impact of reducing the pressure of tank-based inland and at-sea transport on their techno-economic performance. The study uses established techno-economic models for CO2 transport, adjusted with the most up-to-date knowledge on the costs of low-pressure containment and transport. In particular, the impact of cargo tank material and design on the transport costs show that low-pressure cargo tank systems can be 50% less expensive than medium-pressure systems if materials with similar price and strength can be used. This results in reductions in transport costs as high as 30% for long distances. This is partly driven by the currently suggested size limitation on medium-pressure shipping that limits its economies of scale. If this limitation is alleviated, the cost advantage of low-pressure shipping compared to medium-pressure is more limited (10–20%) although it remains advantageous. The same scaling effects on capacity were not found for truck and barge inland transport, thus yielding 1–10% cost reductions of low-pressure transport relative to medium-pressure transport. These results imply that future systems may combine medium-pressure inland and low-pressure at-sea transport and that efficient solutions connecting the two must be investigated.