Commercial Vehicle Operations Research Articles

Safety evaluation for regulation changes on commercial vehicle operation using multilevel Bayesian methods

Truck-involved crashes cause serious social and economic losses, and the crash severity is higher compared to ordinary vehicles. Driver fatigue is a major crash causation, especially have a larger impact on truck drivers. Therefore, mandating a truck rest-break is one of the road safety management strategies for reducing both truck-involved crash frequency and severity. This paper analyses the change in safety performance according to the revision of the truck rest-break time on highways. Because spatial heterogeneity and homogeneity should be considered to estimate safety effects precisely after executing crash countermeasures, this study estimates the safety effect after the revision of the Trucking Transport Business Act, by developing a model based on the Multilevel Full-Bayes before and after the study. The safety performance function was developed in different section units and distributions, and the crash modification factor was calculated for the most suitable model. As a result of the analysis, the performance of the Multilevel Bayesian Poisson-gamma model was the highest, and it was found that there was a crash reduction effect after the revision of the truck break time. The results of this study can be referred to when preparing measures for road safety regulations.

A Novel Application of Magnetorheological Seat Suspension with an Improved Tuning Control Strategy

During the operation of commercial vehicles, drivers are usually exposed to long-term vibrations and acquire several health problems. Moreover, the end-stop impacts caused by large-magnitude vibrations or shocks may affect driving performance and result in injuries. A study of magnetorheological (MR) seat suspension controlled by a novel tuning control strategy is conducted in this research to reduce vibrations and avoid end-stop impacts. First, the MR damper’s characteristics are tested, and a mathematical model of MR seat suspension is established. Then, an improved tuning control strategy is designed based on this model. The proposed strategy has three control stages that can be adjusted according to the suspension stroke to improve seat comfort or avoid end-stop impacts. Each part of the control strategy is designed separately, and the vibration attenuation performance of this seat suspension is evaluated with a simulation for three excitations, i.e., harmonic excitation, bump excitation, and random road excitation. Finally, an experiment is conducted to verify the conclusion of the simulation. The seat suspension with the proposed control shows good performances on vibration attenuation and end-stop impact reduction. Compared with a passive seat, the vibration level is reduced by around 27% and end-stop impact is avoided when semiactive suspension with the proposed strategy is used. It also shows the best overall performance among the three experimental algorithms. Both the simulation and the experiment results indicate that the vibration attenuation performance of the seat suspension can be greatly improved with the improved tuning control strategy.

A Comprehensive Approach for Detecting Brake Pad Defects Using Histogram and Wavelet Features with Nested Dichotomy Family Classifiers.

The brake system requires careful attention for continuous monitoring as a vital module. This study specifically focuses on monitoring the hydraulic brake system using vibration signals through experimentation. Vibration signals from the brake pad assembly of commercial vehicles were captured under both good and defective conditions. Relevant histograms and wavelet features were extracted from these signals. The selected features were then categorized using Nested dichotomy family classifiers. The accuracy of all the algorithms during categorization was evaluated. Among the algorithms tested, the class-balanced nested dichotomy algorithm with a wavelet filter achieved a maximum accuracy of 99.45%. This indicates a highly effective method for accurately categorizing the brake system based on vibration signals. By implementing such a monitoring system, the reliability of the hydraulic brake system can be ensured, which is crucial for the safe and efficient operation of commercial vehicles in the market.

A comprehensive assessment of vehicular performance and emission characteristics during real-time test-runs using selected bio-ethanol–gasoline blends

To reduce vehicular emissions, it is crucial to investigate the potential of low-carbon fuels in the operation of commercial vehicles. The current study aims to investigate vehicular performance while operating a typical Indian motorcycle using various ratios of bio-ethanol-blended gasoline (10%, 20%, 55%, and 85% by vol.). Three different test conditions, viz., steady-state engine testing, chassis dynamometer test measurement, and on-road vehicle performance tests, are conducted for a four-stroke motorcycle. The experimental results highlight that the E20 blend (20% ethanol and 80% gasoline by vol.) increased the power and torque output by 2% and 3.4%, respectively, compared to the base gasoline (E0). Further, the tailpipe emissions reduced significantly during assessment using E20 blends. However the performance was deteriorating, while using higher ratios of ethanol-blended gasoline. E55 blend decreased the power and torque by 22.3% and 27.8%, respectively, and an increased acceleration time of 3.1 seconds was observed in comparison to E0. A maximum increase of 38 % in total fuel consumption is observed with E85 and an increase of 34.3% in fuel filter pressure drop compared to E0. The reduced emissions and non-requirement of major modifications to a typical motorcycle's engine indicate that E20 could be an attractive fuel blend.

Challenges in Conducting Empirical Epidemiological Research with Truck and Bus Drivers in Diverse Settings in North America.

Over 6.5 million commercial vehicle drivers were operating a large truck or bus in the United States in 2020. This career often has high stress and long working hours, with few opportunities for physical activity. Previous research has linked these factors to adverse health conditions. Adverse health conditions affect not only the professional drivers’ wellbeing but potentially also commercial motor vehicle (CMV) operators’ safe driving ability and public safety for others sharing the roadway. The prevalence of health conditions with high impact on roadway safety in North American CMV drivers necessitates empirical epidemiological research to better understand and improve driver health. The paper presents four challenges in conducting epidemiological research with truck and bus drivers in North America and potential resolutions identified in past and current research. These challenges include (1) the correlation between driving performance, driving experience, and driver demographic factors; (2) the impact of medical treatment status on the relationship between health conditions and driver risk; (3) capturing accurate data in self-report data collection methods; and (4) reaching the CMV population for research. These challenges are common and influential in epidemiological research of this population, as drivers face severe health issues, health-related federal regulations, and the impact of vehicle operation on the safety of themselves and others using the roadways.

Effect of Mixed Traffic Platooning by Commercial Vehicle Types on Traffic Flow Characteristics of Highways

The existence of different types of Commercial Vehicles (CVs) in the shared roadway affects traffic flow characteristics differently from other vehicles. Owing to the uncertain placement and movement of these CVs in both longitudinal and lateral directions, the opportunities for lane changing and overtaking by other vehicles with lower maneuverability decrease, resulting in the formation of platoons. The study's primary aim is to assess the effect of mixed traffic platoons formed by three different classes of CVs on highway traffic speed, flow, and density under two different traffic regimes (regimes A and B). In this study, regime A represents the non-platooning condition, and regime B represents the platooning condition. Bi-directional traffic data was collected from the highway sections in India using an Infra-Red sensor-based device. The critical leading time headway is determined for the different CVs (platoon leaders) based on the mean absolute relative speed of platoons. The speed-flow-density plots are established using the macroscopic fundamental diagrams for the highway sections under regimes A and B to quantify the platooning impacts of CVs on the traffic characteristics. The study findings reveal that the speed at capacity, density at capacity, and traffic capacity decreased significantly due to CVs' influence on the general traffic mix during the mixed traffic platooning conditions. However, this effect was found to be relatively higher during the Heavy Commercial Vehicle operation as a platoon leader compared to Medium Commercial Vehicle and Light Commercial Vehicle as a platoon leader.

大型車の一般路自動走行のための経路計画手法

In order to solve the problem regarding the shortage of truck and bus drivers in recent years, manpower-saving and unmanned operation of commercial vehicles is currently being actively researched and developed. However, when traveling on narrow road widths and curves with large curvatures, such as urban roads, commercial vehicles have larger internal wheel truck differences and overhang swing than passenger cars. Therefore, the path tracking control focusing on CG position tracking applied to passenger cars cannot be applied directly to commercial vehicles. Therefore, the purpose of this study is to develop a path planning and motion control system for automated operation of commercial vehicles in urban areas. In designing the control system, a risk potential field was used to express the driver's sense of danger with respect to obstacles and road boundaries. A simulation is conducted on a course that recostructs a real intersection, and a parameter study is conducted. Finally, the simulation results of this method are compared with those of a general path-following method, and the results show that this method is effective for avoiding obstacles in intersection situations.

Automated Driving Control Method in Narrow Road for Commercial Vehicles Based on Risk Potential Optimization

In order to solve the truck driver shortage that has become a problem in recent years, manpower-saving and unmanned operation of commercial vehicles is currently being actively researched and developed. However, in narrow-road driving situations such as in urban areas and parking lots, commercial vehicles have larger internal wheel track differences and overhang lengths than passenger cars. Therefore, path tracking control focusing on CG position tracking applied to passenger cars cannot be applied directly to commercial vehicles. Therefore, the purpose of this study is to develop a path planning and motion control system for automatic driving of commercial vehicles on narrow roads in a restricted area. To construct the system, we used a risk potential field that expresses the driver's sense of risk. For tight curves, the system used Triclothoid to generate a route with a large turning radius, and modified the road information to cope with the curves. The effectiveness of the above methods was confirmed by simulations using IPG TruckMaker.

The Basics of Developing an Alternative Concept for Commercial and Military Vehicle Operation (Random Strategy)

The efficiency of commercial automobiles and wheeled military vehicles mainly depends on the choice of maintenance (M) and current repair (CR) concept. In the paper the difficulties of adapting the (M) and (CR) planning strategies to the structural characteristics of modern transport facilities are pointed out. The advantages of using the (M) and (CR) random strategy for transport facilities based on the stochastic nature of failures and malfunctions are substantiated. Considering the failures and malfunctions as random values and identifying the patterns of their distribution based on γ percentage resources, it is proposed to develop a list of regulated maintenance and repair work, periodicity and labor intensity based on a random strategy, which will increase the efficiency of preserving the technical resource of the rolling stock throughout the entire life cycle of the vehicle.

Economic assessment of the use of natural gas on commercial automobile transport when transporting bread in Omsk

The article presents the results of the analysis of scientific research on the use of compressed natural gas in road transport. The reasons limiting the widespread use of this type of motor fuel are considered. For the efficient operation of commercial vehicles running on compressed natural gas, it is important to take into account the relative position of the existing filling stations and the locations of the enterprises’ vehicles. When calculating the payback period and fuel costs of a truck for operation on compressed natural gas, the mileage to the refueling point is not taken into account, which reduces the economic efficiency of using CNG. In the present study, a mathematical model has been developed and tested for determining the operating costs of fuel depending on the mileage from the parking place of trucks to the place of refueling. Keywords: road transport, compressed natural gas, autogas filling compressor stations, fuel costs, mileage to the place of refueling

Development of in-use engine speed/torque heat maps across multiple heavy-duty commercial vehicle vocations

The U.S. Department of Energy (DOE) established the SuperTruck program with the goal of achieving brake thermal efficiency (BTE) greater than or equal to 55% as demonstrated in an operational heavy-duty (HD) diesel engine at a 65-miles-per-hour (mph) cruise point. Beyond the line-haul application, HD engines operate in a wide range of speed and torque conditions that are unlikely to yield the same efficiency under real-world operation. Thereby, the in-use engine heat maps described in this paper are a valuable tool to illustrate whether the engine-efficiency “sweet spot” matches the most frequent operating conditions. In this study, NREL developed engine heat maps to quantify the important operating points for various vocations using our Fleet DNA database of commercial fleet vehicle operations data. These heat maps clearly show that high-frequency operating points vary significantly according to vehicle vocation, while only a few of them match the sweet spot. Beyond the illustration, engine in-use heat maps can also be leveraged to build up reduced-order engine-efficiency models, needed by many rapid powertrain simulations. As case studies, nine reduced-order models – including line-haul truck, transfer truck, transit bus, transit bus with compressed natural gas (CNG) engine, drayage, refuse pickup, local delivery, utility truck, and school bus with CNG engine – using a trust-region reflective algorithm to fit the on-road data extracted based on the engine in-use heat maps.

Attitudes towards Safety Regulation and Job Satisfaction in Commercial Motor Vehicle Drivers

This paper presents a study about the relationship between attitudes toward safety regulations and job satisfaction among commercial motor vehicle operators in Chile. 318 truck drivers were recruited during 2012. Results show that the principal predictor of attitudes toward safety regulations is job satisfaction, after time driving in this occupation. These findings suggest that trust in work safety is relevant for a risky profession, as the studied.

Теоретические основы построения систем оперативного управления перевозочным процессом грузового транспорта при внедрении технологий 5G-V2X

The article considers some conceptual approaches to improving the management system of the functional capabilities of intelligent technical objects and vehicles on the highway. The authors propose using a scheme for constructing a system for managing the transportation process of freight transport with the introduction of the Smart Highway 5G-V2X technologies, taking into account the probabilistic nature of the system-forming factors. The transport infrastructure of ITS is presented on the basis of introducing the 5G-V2X technologies in order to improve the automation and traffic control systems in road transport. The authors substantiate using the promising areas of research aimed at improving functionality of the software and hardware systems in the autonomous movement of vehicles through the use of intelligent automated systems. There has been worked out the sequence of constructing the system of autonomous traffic operational management at the operation of commercial vehicles platooning into convoys, and the time intervals needed for data transfer regarding the transport flow.

\u201cWith tramadol, I ride like a Jaguar\u201d: a qualitative study of motivations for non-medical purpose tramadol use among commercial vehicle operators in Kumasi, Ghana

BackgroundThe misuse of tramadol has become a major aspect of the wider substance use challenge in recent years and is evolving into a health crisis at an alarming rate. However, literature on motivations for non-medical purpose tramadol use among commercial vehicle operators remains inadequate. The aim of this study was to document the motivations for non-medical purposes tramadol use in Kumasi. Such an understanding could inform policy direction to regulate non-medical purposes tramadol use in Ghana.MethodsWe conducted this exploratory qualitative study with 23 purposively selected commercial vehicle drivers (15) and assistants (8) in Kumasi, Ghana. Data for the study were collected through in-depth face-to-face interviews between June 2018 and March 2019. Using a thematic analytical approach, the interviews were coded and analysed.ResultsMultiple motivations for non-medical purposes tramadol use were found including those related to: (1) sexual; (2) psychological; (3) physical; and (4) economic factors. Participants also reported three main inter-linking categories of perceived tramadol adverse effects: (1) physical; (2) psychological; and (3) social effects. Although participants indicated no plans for stopping their non-medical use of tramadol any time soon, strong willingness was voiced for supporting officials in finding and dealing with non-medical purpose tramadol sellers.ConclusionNon-medical purposes tramadol use was associated with a confluence of factors, ranging from enhanced sexual performance to economic reasons. Based on the findings of the study and the dependence and addictive potentials of tramadol, there is the need for psychoeducational programmes for persons who misuse tramadol and enhancement of operational capacities of regulatory agencies.

Selling Fuel or Any Other Petroleum Product Without License Is a Crime In Nigeria

Black market hawkers or retailers of fuel, kerosene, gas and other petroleum products are found in every nook and cranny of towns in Nigeria though they tend to be found more in the oil producing states. They trade in jerrycans, drums, and tanks, and are steadily patronized by commercial vehicle operators popularly known as keke and okada, as well as the regular taxi drivers, some private motorists and other individuals who buy for household uses. This article establishes that selling of fuel or any other petroleum products, without license, is a criminal offence and since to every general rule there are exceptions, the article explained various circumstances that one may escape liability and punishment. The article further justifies the existence of such law given the importance of Petroleum and its allied resources to our economy.

A Model of Vignette for Motor Vehicles in the Czech Republic

This article examines the fees applied to vehicles of the maximum weight of 3.5 t based on time. It focuses on the analysis of the current application of time-based fees in individual countries of the EU. This analysis is carried out as a supporting tool serving the design models available in the Czech Republic. The goal of the contribution is designing a new model of time-based pricing of road motor vehicles in the territory of the Czech Republic. The contribution also includes the analysis of legal standards regulating the issue in the Czech Republic and in the EU countries; the analysis only deals with EU legal standards that directly address the area. The outcome of the contribution is a constructed model of a time-based fee, based on pre-defined assumptions, which were determined by needs ensuing from the current conditions that affect the operation of chargeable passenger cars and light commercial vehicles. In conclusion, a comparison of receipts from the current system of time-based fees with receipts resulting from the proposed model of time-based fees for the Czech Republic is made. The results shown in Table 6 show that the application of the newly defined time-based fee model in the Czech Republic leads to increased public budget revenues by 3.14%, ie by CZK 149.262 million in absolute terms.

Assessing Overnight Parking Infrastructure Policies for Commercial Vehicles in Cities Using Agent-Based Simulation

Urban freight transport is primarily fulfilled by commercial road vehicles. Within cities, overnight parking is a critical element influencing commercial vehicle operations, particularly for heavy vehicles with limited parking options. Providing adequate overnight parking spaces for commercial vehicles tends to be a challenge for urban planners. Inadequate parking supply can result in illegal parking and additional vehicle kilometers traveled, contributing to traffic congestion and air pollution. The lack of tools for evaluating the impacts of changing parking supply is an impediment in developing parking-related solutions that aim to minimize the negative externalities. In this study, we develop an overnight parking choice model for heavy commercial vehicles and integrate it with SimMobility, an agent-based urban simulation platform, demonstrating the potential of this tool for policy evaluation. Using simulations applied to a case study in Singapore, we compare two parking supply scenarios in terms of vehicle kilometers traveled due to changes in the first and last trips of vehicle tours, as well as resulting impacts in traffic flows.

Estimation Road Surface Temperature Variation Using Commercial Vehicle Ambient Sensor

Road surface temperature is more important than ambient temperature in term of road safety during winter season. The conventional method to collect road surface temperature is to install Road Weather Station(RWS). However RWS can only collect spot information and could be costly. To enhance these problem, this study used the commercial vehicle ambient temperature(VAT) sensors can collect the pattern of air temperature along the road effectively and rapidly. Also the thermal mapping equipment was used to collect the road surface temperature(RST). After that, our research analysed the similarity of the patterns of road surface and ambient temperatures using correlation analysis. The result showed that the patterns of temperature variation collected from VAT sensors are statistically comparable to patterns of road surface temperature variation collected from a thermal mapping. In addition, this research developed a way to segment roadway based on variation in road surface temperature. This segmentation is useful to road authorities for managing the road and providing information based on road segmentation. Although VAT sensors do not provide highly accurate temperature readings, they can identify patterns of surface road temperature on roadway sections. This study found out that the VAT can be estimated the patterns of RST and could be replace the road weather station or thermal mapping system. This information can be used so that individual drivers, commercial vehicle and fleet operators and road authorities acquire critical real-time information on road conditions. Further, using these sensors instead of fixed sensors or thermal mapping can significantly reduce road maintenance costs. Also the result could be applied to the automated driving system to provide the road surface condition in the future.

Screening for Obstructive Sleep Apnea in Commercial Drivers Using EKG-Derived Respiratory Power Index.

Obstructive sleep apnea (OSA) is common in commercial motor vehicle operators (CMVOs); however, polysomnography (PSG), the gold-standard diagnostic test, is expensive and inconvenient for screening. OSA is associated with changes in heart rate and voltage on electrocardiography (EKG). We evaluated the utility of EKG parameters in identifying CMVOs at greater risk for sleepiness-related crashes (apnea-hypopnea index [AHI] ≥ 30 events/h). In this prospective study of CMVOs, we performed EKGs with concurrent PSG, and calculated the respiratory power index (RPI) on EKG, a surrogate for AHI calculated from PSG. We evaluated the utility of two-stage predictive models using simple clinical measures (age, body mass index [BMI], neck circumference, Epworth Sleepiness Scale score, and the Multi-Variable Apnea Prediction [MVAP] score) in the first stage, followed by RPI in a subset as the second-stage. We assessed area under the receiver operating characteristic curve (AUC), sensitivity, and negative posttest probability (NPTP) for this two-stage approach and for RPI alone. The best-performing model used the MVAP, which combines BMI, age, and sex with three OSA symptoms, in the first stage, followed by RPI in the second. The model yielded an estimated (95% confidence interval) AUC of 0.883 (0.767-0.924), sensitivity of 0.917 (0.706-0.962), and NPTP of 0.034 (0.015-0.133). Predictive characteristics were similar using a model with only BMI as the first-stage screen. A two-stage model that combines BMI or the MVAP score in the first stage, with EKG in the second, had robust discriminatory power to identify severe OSA in CMVOs.

Applications of Internet of Things

This editorial introduces the special issue entitled “Applications of Internet of Things”, of ISPRS International Journal of Geo-Information. Topics covered in this issue include three main parts: (I) intelligent transportation systems (ITS), (II) location-based services (LBS), and (III) sensing techniques and applications. Three papers on ITS are as follows: (1) “Vehicle positioning and speed estimation based on cellular network signals for urban roads,” by Lai and Kuo; (2) “A method for traffic congestion clustering judgment based on grey relational analysis,” by Zhang et al.; and (3) “Smartphone-based pedestrian’s avoidance behavior recognition towards opportunistic road anomaly detection,” by Ishikawa and Fujinami. Three papers on LBS are as follows: (1) “A high-efficiency method of mobile positioning based on commercial vehicle operation data,” by Chen et al.; (2) “Efficient location privacy-preserving k-anonymity method based on the credible chain,” by Wang et al.; and (3) “Proximity-based asynchronous messaging platform for location-based Internet of things service,” by gon Jo et al. Two papers on sensing techniques and applications are as follows: (1) “Detection of electronic anklet wearers’ groupings throughout telematics monitoring,” by Machado et al.; and (2) “Camera coverage estimation based on multistage grid subdivision,” by Wang et al.