Transport Vehicles Research Articles

Comparison of current and proposed travel modes for students considering travelling and sustainable indicators

In the twenty-first century, global warming has become one of the severe challenges. Around one-fourth of the total carbon footprint is contributed by transport vehicles. It is crucial to provide alternative solutions to unsustainable transportation systems. This study compares the present travel modes of students of the Capital University of Science and Technology, Islamabad, with the proposed sustainable travel mode. A campus survey (N = 565) was conducted to understand travel choices, travel times, origin and destinations, and student preferences, considering university buses and private vehicles. A comparison was made between the travel time analysis of university bus users and non-bus users. A sustainability analysis has been conducted to evaluate the effects of the present travel modes on students and the proposed university bus transport system. Five main factors were compared: fuel consumption and associated fuel costs, carbon and vehicular emissions, traffic noise pollution, traffic congestion, and accident ratio. The results show that 38% of students commute by private cars and 18% by motorbikes. Around 25% of the students avoid university buses due to long travel times, and 30% prefer because their parents ask them. On average, university buses take 56.8 min, and non-bus transports take 38.8 min for one-way travel. If all students travel by university busses, they could be 86% more sustainable in fuel costs and carbon emissions than non-bus travel modes. These results give useful policy implications for providing sustainable travel alternatives to educational institutions.

A Passenger Detection and Action Recognition System for Public Transport Vehicles

In the past few years, advances of autonomous driving technologies have made significant progress. One successful deployment with great potential is for the self-driving public transportation. Consequently, the safety of passengers under unmanned operations is an important issue for the future development. In this paper, we propose a vision system for the detection, counting and action recognition of passengers on board a bus. To have a complete coverage of the passenger area, a pair of cameras mounted on the ceiling is adopted for image acquisition. A new cross-camera CNN structure is proposed for passenger pose recognition and action classification. To deal with the double counting problem caused by the overlap of multiple viewpoints, a region prediction algorithm is developed for matching validation. The experiments carried out on a minibus have demonstrated the feasibility of our proposed techniques.

A small-molecule carrier for the intracellular delivery of a membrane-impermeable protein with retained bioactivity.

Intracellular protein delivery has the potential to revolutionize cell-biological research and medicinal therapy, with broad applications in bioimaging, disease treatment, and genome editing. Herein, we demonstrate successful delivery of a functional protein, cytochrome c (CYC), by using a boron cluster anion as molecular carrier of the superchaotropic anion type (B12Br11OPr2-). CYC was delivered into lipid bilayer vesicles as well as living cells, with a cellular uptake ratio approaching 90%. Mechanistic studies showed that CYC was internalized into cells through a permeation pathway directly into the cytoplasm, bypassing endosomal entrapment. Upon carrier-assisted internalization, CYC retained its bioactivity, as reflected by an induced cell apoptosis rate of 25% at low dose (1 µM). This study furbishes a direct protein delivery method by a molecular carrier with high efficiency, confirming the potential of inorganic cluster ions as protein transport vehicles with an extensive range of future cell-biological or biomedical applications.

Traffic Congestion Scheduling for Underground Mine Ramps Based on an Improved Genetic Scheduling Algorithm

The dispatching of trackless transportation on the ramp of underground metal mines is closely related to the transportation efficiency of daily production equipment, personnel, and construction materials in the mine. The current dispatching of trackless transportation on the ramp of underground metal mines is discontinuous and imprecise, with unscientific vehicle arrangement leading to low efficiency and transportation congestion. This paper presents this study, which puts forward a kind of trackless transportation optimization method that can fully make use of the ramp in the roadway, and the slow slope fork point can be used for the trackless transportation vehicle passing section to improve the efficiency of trackless transportation on the ramp. This study adopts the principles of fuzzy logic and uses interval-based positioning instead of real-time positioning to effectively reduce the spatial complexity inherent in the algorithm. At the same time, this research presents a modified genetic algorithm that incorporates a time-loss fitness calculation. This innovation makes it possible to differentiate traffic priorities between different types of vehicles, thus bringing the scheduling scheme more in line with the economic objectives of the mining operations. Various parameters were determined and several sets of simulation experiments were carried out on the response speed and scheduling effect of the scheduling system, resulting in a 10 to 20 percent improvement for different vehicles in the efficiency of underground mining transport operations.

Modeling and Simulation of Hybrid Electric Vehicles for Sustainable Transportation: Insights into Fuel Savings and Emissions Reduction

Most motor vehicles have historically utilized Internal Combustion Engines powered by a fossil fuel. Despite the technological advancements in fuel-efficient engines, further improvements are required to reduce the effect of fuel costs and global warming. This study models and simulates Hybrid Electric Vehicles (HEVs) to evaluate their potential for fuel cost savings and emissions reduction compared to traditional vehicles. Using MATLAB® version R2023a Update 5 (9.14.0.2337262) Simulink version 10.7 (R2023a) and the Advanced Vehicle Simulator (ADVISOR) version 2003-00-r0116, the research examines Series and Parallel HEV configurations. The simulation explores various battery configurations, engine capacities, and power unit models to analyze their impact on energy utilization. The data, collected from the simulations, show significant fuel savings and emissions reduction with HEVs. The Parallel HEV configuration consistently saves fuel with fewer battery modules, while the Series HEV configuration performs better but requires more modules to maintain the system’s State of Charge.

Response of the upper ocean to northeast Pacific atmospheric rivers under climate change

Atmospheric rivers are important transport vehicles for Earth’s water cycle. Using a high-resolution, eddy-resolving Earth System Model, atmospheric river impacts on the upper ocean are investigated by analyzing historical and climate change simulations. For atmospheric rivers along the North American coastline, strong winds cause significant dynamic and thermodynamic upper ocean responses. They push ocean water towards the coast, measured by sea surface height, a process that is amplified under climate change. Mixed layers are deeper upstream of atmospheric rivers, and shallower downstream, however for climate change, shoaling downstream is subdued. Air-sea heat fluxes tend to promote ocean cooling upstream and warming downstream, although different regions have different climate change heat flux signals. Southern California heat flux changes due to warming are driven by evaporative processes and strengthen the ocean responses seen in historical simulations. The regions north are primarily dominated by sensible heat flux changes and counter the historical patterns.

Generalized multi-manufacturer multi-retailer production-delivery supply chain model and its minimum cost solution policy

Production of a product at multiple sources and its deliveries to multiple destinations are a common practice in business. Minimization of the integrated total cost of performing operations and transportation considering the relevant factors such as the minimum order quantity contract, capacities of transport vehicles, and times of transportation in this supply chain is essential, in supplying products to customers at reasonable lesser prices. However, such a supply chain has received little attention in terms of minimizing the integrated total cost taking into account these related factors explicitly. So, there lies a research scope on this topic to fulfill the growing need of minimizing the cost of production-deliveries of products to meet customers’ demands fruitfully. Here we develop such a generalized mathematical model to minimize the integrated total cost of carrying out operations at manufacturers and retailers, and transporting batches (sub-lots) of lots from sources to destinations considering the mentioned realistic constraints. The integrated production-delivery flow is synchronized by delivering lots with batches of equal and/or unequal sizes. First without considering transportation costs, we obtain optimal batches to minimize the total cost of the model. Each of these optimal batches is proportionally distributed at manufacturers as supplies and at retailers as demands. Then the minimum transportation cost solution from manufacturers to retailers is incorporated to the earlier solution to obtain the final result. We illustrate this solution policy with numerical example problems. Sensitivity analyses are performed to see the effect of increasing values of parameters on the minimum total cost.

Automatically Guided Vehicles (AGV) in Agriculture

In this paper, new types of autonomous systems used in agriculture were analysed. The paper shows new self-guiding systems such as AGVs with full autonomy in degrees operation. It explains internal transport and systems of autonomous vehicles in outdoor agriculture. New autonomous systems used outside such as appliance of special navigation systems and their purpose in agriculture are present in this work. Navigation systems with GPS signal and RTK technology, vehicle guidance camera and AI machine vision for manipulation are described. Light and laser technologies for fully autonomous robotic technologies such as LiDAR system in vehicle for detection of the presence of pests and diseases are presented in this paper. The paper emphasized advantages of using AGVs as result of their autonomy, clean power sources without harmful impact on the environment. Navigation in indoor spaces that uses LTE Direct protocol is explained, whereby the Wi-Fi ceiling antenna and wireless APP for horizontal movement of AGVs is shown. The ways of using UAVs for warehouse inventory through web applications with an advanced navigation system guided by AI are given in this work.

The Driving Profile of Autistic Drivers and Their Driving Experiences: A Systematic Review.

A developmental milestone that both contributes to and facilitates a successful transition into adulthood is the ability to drive. Yet only one in three autistic adolescents successfully obtain a driver's license by age 21 compared to over three-fourths of non-autistic adolescents. Of those who receive their license, there is inconsistency in driving attitudes, experiences and skills. The current study aimed to (1) provide a systematic review of the driving profile of autistic drivers and (2) structurally organize driving performance within a theoretical driving model - Michon's Hierarchical Model of Driving. Following PRISMA guidelines, four databases were systematically searched to identify published articles related to autistic drivers. To be included, all studies met the following inclusion criteria: included autistic sample or people representing or working with autistic individuals, peer-reviewed, published between 2000 and 2021 and contained empirical data reporting on an aspect related to driving or motor vehicle transportation. A systematic search yielded 37 articles that met inclusion criteria. Based on the differential results derived from this review, it appears that autistic drivers are not generally at greater risk of negative driving outcomes; instead, they face unique challenges based on the skills necessary to navigate specific driving contexts. However, due to the inconsistency across results, the actual driving performance in autistic drivers remains unclear. Future research should focus on quantifying these results using an evidenced-based, theoretical framework to identify consistent strengths and challenges in driving performance across autistic drivers.

Energy-saving cruise control method for heavy-duty transport vehicle based on pump-valve coordinated drive

In order to realize the dual-goal of the improvement in the cruise performance and fuel economy of the heavy-duty transport vehicle (HDTV) for the transfer of the prefabricated box-girder in the construction of high-speed railway, a pump-valve parallel coordinated drive scheme is designed on the basis of the hydrostatic drive system of the HDTV, which combines the load-sensing valve control system and hydrostatic pump control system. Furthermore, the pump-valve coordinated controller (PVC) is also proposed to ensure the cooperation of the two systems, which adopts power following control strategy to control engine speed, the pump and motor displacement respectively, thus achieving the rough adjustment of the cruise velocity. The linear quadratic regulator (LQR) based on the full-state closed-loop feedback is introduced in PVC to control the proportional direction-valve (EPDV) and compensate for the velocity errors, thus realizing the fine adjustment of cruise velocity. A semi-physical experimental test-platform for the HDTV is established to conduct contrast tests between the rule-based controller (RBC) and the proposed PVC under different operating conditions. The results indicate that the PVC effectively reduces the velocity error, the total error is decreased by 80.6% and that of the maximum error is 43.4% under empty-load conditions, and under heavy load conditions, the total error is lowered by 82.1% and that of the maximum error is 46.8%. Moreover, the PVC also brings down the fuel consumption rate of the HDTV, with a maximum reduction of 27.6% and a minimum of 11.4%.

Impact of logistics pooling on reduction of CO2 emissions in last-mile logistics

Purpose In previous years, there has been a peak in deliveries from all sectors. Consequently, the number of transport vehicles on urban roads has also increased. Unsurprisingly, this increase leads to many environmental problems, including increased carbon emissions. This paper attempts to examine this issue by addressing the impact of logistics pooling on the reduction of CO2 emissions in last-mile logistics. The aim is to see which of the logistics pooling options can minimize more CO2 emissions and in particular reach the threshold fixed by the Moroccan Agency of Logistics Development which is 30% until 2030.Design/methodology/approach The author conducted a simulation study. The sample was chosen from the economic pillar of the Moroccan Kingdom, namely Casablanca.Findings The results indicate that two pooling strategies lead to a higher level of environmental performance compared to the objective set up by the Moroccan Agency of Logistics Development (Direct Upstream and Downstream Transport: 44.39%/Multi-pick Upstream Transport and Multi-drop Downstream Transport: 30.93%). However, the first strategy remains the best one, as it not only minimizes emissions but also reflects the practices already implemented by several carriers and logistics service providers.Practical implications Successfully implementing these strategies in Casablanca could serve as a model for other cities facing similar challenges, demonstrating the viability and benefits of logistics pooling. Ultimately, the reduction in CO2 emissions aligns with global environmental goals, contributing to the fight against climate change and promoting a healthier urban environment for residents. By leveraging simulation technology, Casablanca can make significant strides toward more sustainable and efficient last-mile logistics, setting a precedent for green urban logistics practices.Originality/value Given Morocco’s significant geostrategic position, the urban logistics sector plays a crucial role in the development of Arab countries. The findings of this study can offer valuable insights for policymakers aiming to achieve sustainable economic growth. Additionally, to the author’s knowledge, this is the first study to focus on logistics pooling and carbon emissions in Arab nations. The paper further contributes by highlighting important directions for future research.

Acoustic camera applied on sound transmission identification in closed spaces

In the ongoing context of office partitioning, users are increasingly paying attention to acoustic insulation between rooms. The issues commonly related are translated by confidentiality problems and annoying use of sound-enabled videoconferencing. In practice, when an insulation defect is perceived, standardized acoustic insulation measurements are carried out to characterize the overall insulation performance. However, it is often challenging to precisely identify by ear the various paths of sound transmission: through the partition, by poorly caulked junctions, through the ceiling, through the facade, etc. Acoustic antenna solutions employed to identify the location and frequency content of sources have existed for several decades. But, in addition of being expensive and bulky, until now their use was reserved for detection of sources on transportation vehicles (trains, cars, planes, etc.) or industrial equipment (wind turbines, boiler rooms, etc.). In recent years, more accessible and practical antenna solutions known as "acoustic camera" have become available. In this sense, we have been handling an acoustic camera to assist on the detection of the sound transmission paths between two rooms. This work address what has been experienced, outlining results obtained through the (evolving) methodology for sound transmission identification with acoustic camera in closed spaces.

Forecasting the volume of urban freight traffic

The efficient development of transportation vehicles in conditions of stiff competition and global digitalization depends on the correct methodology and forecasting of freight transportation. A review of scientific literature showed that all studies are directed towards the railway mode of transportation. The research conducted in this work focuses on freight transportation by road transport in the city of Almaty, where trucks remain the sole means of delivering goods from one point to another at the local transportation level. The main goal of the research presented in this article is to analyze statistical indicators of transportation volumes and freight turnover by road transport and develop software aimed at forecasting the expected volume of freight transportation. In logistics planning and management, the moving average method is employed to predict truckload volumes and freight turnover for the next year. This method works by averaging data points to smooth out random fluctuations, thereby providing a more stable forecast. This phenomenon arises from replacing the original levels of the time series with arithmetic means calculated for certain time intervals. To facilitate transportation volume planning and substantiate the optimality of freight transportation, it is necessary to have up-to-date statistical data. These statistic data serve as the basis for constructing a dynamic representation of automobile traffic volumes and freight turnover in the city of Almaty. The growth rates of indicators are calculated to assess dynamics. The forecasting aspect of freight transportation volume is addressed by developing an algorithm based on the moving average method.

A New Approach for Improving Flame Retardancy of Automotive Interior Upholstery

This study presents the flame retardant (FR) performance of chemically treated automotive upholstery fabrics using two different impregnation methods of Resin Transfer Molding (RTM) and supercritical carbon dioxide (scCO2). Referring to the related standards, untreated seat fabric obtained from seat upholstery of a bus (neat fabric, NF) and treated fabric samples underwent burning rate (BR) and limiting oxygen index (LOI) tests to compare effect of treatment and impregnation methods on FR performance. Thermal analysis was also conducted on the samples considering onset degradation temperatures and char yields. The results showed that BR and LOI of all samples were in acceptable range and treatment provided enhancement in FR performance of NF. The treated sample using scCO2 method gave the highest LOI value of 32% and the lowest BR of 21 mm/min subtending to 18.5% increase in LOI and 30% reduction in BR compared to those of NF. The performance of treatment in RTM was worse than that of scCO2 and better than that of NF. The results confirm that both treatment and methods used in this study give promising results for safety against fire in transportation vehicles.

Designing and Implementing a Public Urban Transport Scheduling System Based on Artificial Intelligence for Smart Cities

Many countries encourage their populations to use public urban transport to decrease pollution and traffic congestion. However, this can generate overcrowded routes at certain times and low economic efficiency for public urban transport companies when buses carry few passengers. This article proposes a Public Urban Transport Scheduling System (PUTSS) algorithm for allocating a public urban transport fleet based on the number of passengers waiting for a bus and considering the efficiency of public urban transport companies. The PUTSS algorithm integrates artificial intelligence (AI) methods to identify the number of people waiting at each station through real-time image acquisition. The technique presented is Azure Computer Vision. In a case study, the accuracy of correctly identifying the number of persons in an image was computed using the Microsoft Azure Computer Vision service. The proposed PUTSS algorithm also uses Google Maps Service for congestion-level identification. Employing these modern tools in the algorithm makes improving public urban transport services possible. The algorithm is integrated into a software application developed in C#, simulating a real-world scenario involving two public urban transport vehicles. The global accuracy rate of 89.81% demonstrates the practical applicability of the software product.

Exploring intercity travel decision-making in a developing country: Insights from COVID-19 impacts in Iran

This study examines the impact of COVID-19 on intercity travel mode choices in Mazandaran province, Iran, addressing critical gaps in understanding how pandemics affect travel behavior in developing countries. The research focuses on how socio-economic factors, perceived health risks, and travel time influence individuals’ choice of transportation modes during the pandemic. Using a stated preference survey method with 669 participants, the study assessed how concerns about virus transmission and adherence to health protocols shape travel decisions. Discrete choice modeling was employed to predict travel mode shares between public transport and personal vehicles. The findings reveal that COVID-19 risk perception, socio-economic factors, and travel time significantly impact travel behavior. Specifically, heightened perceived risk of infection resulted in a 25% reduction in public transportation use, with individuals increasingly opting for personal vehicles. Additionally, strict adherence to health protocols, such as mask-wearing and vehicle cleaning, improved safety perception, leading to a 40% increase in confidence in public transport. The study also found that socio-economic factors like age, income, and education significantly shaped travel preferences. These insights provide valuable guidance for public health policymakers and transportation authorities to enhance the safety and management of intercity travel during ongoing and future pandemics.

A planning framework for intra-city electric bus road transportation systems

Gasoline-based vehicle transportation plays a crucial role in environmental pollution, which eventually leads to serious health issues in urban areas. The scope of large-scale deployment of personalized electric vehicles in the near future can lean toward such issues but can overburden local distribution grids (LDGs), and the entities are producing green energy. In this context, an electric bus road transportation system (EBRTS) can be seen as an effective and promising way, although it is capital-intensive. EBRTs can be successfully deployed by developing a well-tailored planning model that encompasses amicable solutions while considering the conflicting interests of electric utilities and investors/transporters.This paper proposes a planning model for intra-city EBRTS, especially for metropolitan cities, to extract tangible benefits in favour of electric utilities and private players. The proposed framework envisages a bus fleet charging model and financial model within the spatial, technical, and financial constraints yet preserves the interests of electric utilities and investors by providing tentative solutions with all information necessary from the investor’s perspective. The methodology is free from optimization as the realistic constraints inherently employ search space reduction. The simulation results on a real public transportation system reveal the proposed methodology’s simplicity, rationality, applicability, and flexibility.

DISSIMILAR HARDOX AND LOW-ALLOY STEEL IN EXCAVATOR STRUCTURES

In the structure of excavators and other transport vehicles, it is observed that there is an increasing necessity to weld elements from the Hardox steels. The paper verifies the possibility to obtain accurate DMW (dissimilar metal welds from totally different grades of Hardox 450 steel with S355J2 steel). The microstructure and mechanical tests of the obtained various welds were analysed. Argon-based shielding gases with micro nitrogen additions were used for MAG welding. Gas mixtures with micro nitrogen additions of up to even 2000 ppm and their use in welding are an absolute novelty. The purpose of the manuscript was to find the correct parameters of making dissimilar joints with such modern mixtures and to determine the most suitable mixture for welding Hardox steel and low-alloy steel for use in the automotive industry.

A CAV-Lead speed advice approach considering local spatiotemporal traffic state near bottlenecks

Bottlenecks of the freeway generated especially by traffic accidents or temporary work zones contribute to significant reductions in system throughput and hinder the efficient traffic operations. It is imperative to take proactive measures to improve traffic state. With the rapid advancements in intelligent transportation, connected and autonomous vehicles (CAVs) have attracted much attention by its speculated capabilities in improving traffic safety and well-organized operational coordination. Therefore, reasonably utilizing the advantages of CAVs is possible to reduce the impact induced by bottlenecks. In this research, we propose a novel algorithm called CAV-Lead to obtain the CAV’s regulated speed under mixed CAVs and human-driven vehicles (HVs) environment to improve the overall utilization of the freeway capacity near bottlenecks. Firstly, we illustrate the basic principle of the CAV-Lead algorithm that takes both microscopic and macroscopic traffic characteristics into account. Then, based on the local spatiotemporal traffic state, the CAV-Lead algorithm is proposed to determine each CAV’s speed under mixed flow. Furthermore, a real-time simulation control framework considering the random behavior of HVs is presented. Moreover, several simulation evaluations including comparisons with basic scenarios and similar research are conducted under various CAV market penetration rates (MPRs). The results demonstrate that the CAV-Lead could improve the traffic performance, especially for the high traffic demand with certain MPRs.

A Driving Warning System for Explosive Transport Vehicles Based on Object Detection Algorithm.

Due to the flammable and explosive nature of explosives, there are significant potential hazards and risks during transportation. During the operation of explosive transport vehicles, there are often situations where the vehicles around them approach or change lanes abnormally, resulting in insufficient avoidance and collision, leading to serious consequences such as explosions and fires. Therefore, in response to the above issues, this article has developed an explosive transport vehicle driving warning system based on object detection algorithms. Consumer-level cameras are flexibly arranged around the vehicle body to monitor surrounding vehicles. Using the YOLOv4 object detection algorithm to identify and distance surrounding vehicles, using a game theory-based cellular automaton model to simulate the actual operation of vehicles, simulating the driver's decision-making behavior when encountering other vehicles approaching or changing lanes abnormally during actual driving. The cellular automaton model was used to simulate two scenarios of explosive transport vehicles equipped with and without warning systems. The results show that when explosive transport vehicles encounter the above-mentioned dangerous situations, the warning system can timely issue warnings, remind drivers to make decisions, avoid risks, ensure the safety of vehicle operation, and verify the effectiveness of the warning system.