Truck Movements Research Articles

Revealing the impacts of COVID-19 pandemic on intercity truck transport: New insights from big data analytics

Intercity truck transport emerged as a crucial lifeline for maintaining city operations during COVID-19 pandemic. Understanding pandemic-imposed impacts on intercity truck transport can inform policymakers in crafting more effective strategies for future crises and disruptions. However, to our best knowledge, previous research predominantly focused on freight movements under normal circumstances. Due to the data limitation, the pandemic-related studies commonly relied on freight survey and focused on specific industries, which cannot capture the full spectrum of factors influencing freight trip generation (FTG) during the pandemic. Here, a novel dataset capturing large-scale individual truck movements during the COVID-19 pandemic is provided. By leveraging the mobility dataset, pandemic-induced changes in truck transport demand structure are quantified using spatial statistical methods. Furthermore, an interpretable machine learning framework for intercity freight demand estimation is developed, revealing the complex interplay of factors that influence and shape the behavior shifts of intercity truck transport systems due to the pandemic outbreak. The findings suggest significant changes in various factors influencing intercity truck movements across local and broader regions, emphasizing city-specific challenges amidst pandemic. The developed FTG model could serve as a tool to predict freight demand between cities for future crises and to support policymaking in the practice of freight management.

Optimized Rear Drive Torque Allocation Strategy for Dual-Motor Mining Dump Trucks

This paper takes the dual-motor pure electric mining dump truck as the research object and designs a dual-motor rear-drive torque optimization allocation strategy in view of the problems such as the large load variation of the dump truck and the facts that the motor output torque cannot accurately express the driver’s dynamic intention and that the overall output efficiency of the dual motor is low. The strategy first divides the demand torque of the whole vehicle into two parts, the base torque and the compensation torque, which are determined by the accelerator pedal opening and the motor speed, and the compensation torque is fuzzy-controlled by taking the vehicle speed, the rate of change of the accelerator pedal opening, and the state of the battery charge as inputs. Subsequently, the dual-motor drive torque allocation is optimized using a particle swarm algorithm, with the objective of minimizing power loss in the dual motors. Furthermore, the energy-saving effect of the torque optimization allocation strategy proposed in this paper is compared with that of the traditional torque average allocation strategy under three working conditions: the driving conditions of Chinese dump trucks, the unloaded uphill movement of mining dump trucks, and the fully loaded downhill movement of mining dump trucks. The results show that the average efficiency of the dual-motor drive using the torque optimization allocation strategy is improved by 2.32%, 4.23%, and 2.24%, respectively, and battery energy savings are improved by 0.5%, 0.47%, and 0.24%, respectively.

Freight consolidation through carrier collaboration - A cooperative game

Reducing inefficient truck movements, this research investigates the potential of freight consolidation through carrier collaboration. Considering the financial benefits of consolidation as well as the additional cost arising from collaboration, we introduce a cooperative game in which several carriers can collaborate by pooling transportation capacities. Although the core of this game can be empty, we provide three conditions under which core non-emptiness is preserved. Numerical experiments indicate, moreover, that core non-emptiness is also likely outside these conditions.

Feasibility of zero emission freight zones: scenario analysis and risk assessment

To further incentivize the adoption of zero-emission trucks (ZETs), Chinese cities would need more proactive policies like zero-emission freight zones (ZEFZs). However, the design of the policy should avoid the disruption of goods supply, increase of logistic costs, and ensure inclusive transition of small carriers and financial sustainability for city governments. To this end, this study employs Beijing as a case: Based on ZEFZ case studies, policy document and literature review, and data analysis of freight demand distribution and truck movements in Beijing, this study constructs four scenarios with different spatial coverages, restricted truck segments, and roll-out years of ZEFZs. The impacts of different ZEFZ scenarios on emissions reduction potentials, goods supply and vehicle fleet replacement, and public and private expenditure are evaluated. The most cost-efficient and easy-to-implement scenario is recommended as the initial phase of the ZEFZ scheme, with risk assessment and risk mitigation measures.

Scheduling shared passenger and freight transport for an underground logistics system

With the introduction of freight transportation into the passenger transit network, underground city logistics are regarded as a desirable alternative to address the challenges due to truck movements in urban freight transport. Furthermore, some metro lines suffer from low-capacity utilization because of the unbalanced demand, which provides the potential to expand the extra capacity for freight transportation. Therefore, this study integrates the train unit scheduling problem with combined transportation of passengers and freight during off-peak hours. The objective is to fully utilize the remaining capacity by not only integrating passenger and freight flows but also allowing a flexible composition such that the capacity can better meet the demand. The composition of a trip is defined as its state. A three-dimensional space–time–state network is constructed to capture the composition transitions and passenger/freight trajectories. The problem is formulated as an integer linear programming model to minimize the weighted sum of train unit operational, passenger travel, and freight travel costs. Utilizing the problem-specific characteristics, a constrained-gap-based branch-and-bound approach is developed to efficiently solve the model. The worst bound for each objective is guaranteed by introducing two gaps in the passenger- and freight-related objectives. The nodes with estimated lower bounds exceeding the designated gaps are pruned. A beam search procedure is also included to further reduce the computational complexity. The developed algorithm is tested on real-life instances from the Beijing Metro Network. The results provide insights into the benefits and applicable scenarios for integrating passenger and freight transportation. Moreover, we demonstrate that the number of train units should be carefully determined considering the tradeoff between passenger service quality and freight demand volume.

Analysis of Urban Freight Flows and Retail Goods Movement Using GPS Trajectory and Land Use Data

In recent years, GPS data on truck movements have become much more available, leading researchers and practitioners to leverage these sources to generate a wealth of data and information related to truck OD flows. In this study large amount of truck GPS data used to investigate characteristics of freight transportation in particularly OD land uses and freight vehicle classes. Aiming to realize the freight flows characteristics of the Chicago Metropolitan Agency Planning (CMAP) region. The data are used primarily to gain insight into the nature of urban goods movement and the distribution of retail goods. The main objective in this respect is analyzing urban freight flows and retail goods movement. The data-driven analysis generates a number of interesting findings regarding the nature and volume of trips by light-duty, medium-duty, and heavy-duty truck that serve various types of retail and industrial functions are generated. The design of this study especially its land use data fusion aspect is expected to benefit both practitioners and researchers as they plan future data collection, model calibration and urban freight studies.

Selection and justification of routes of garbage cars with a hybrid power unit on the basis of the "Ural" vehicle chassis

In this paper, we study the possibility of creating a hybrid power plant based on th e chassis of the Ural car equipped with a bin for collecting municipal solid waste (MSW). The operation of municipal equipment, in particular, garbage trucks, has its own specifics, which is associated with the need for their work, often in confined spaces. The hybrid scheme of such vehicles allows the use of an environmentally friendly silent mode of electric traction in urban working conditions. When developing a traction drive and attachment systems for vehicles operating as municipal special equipment, it is necessary to take into account the features of their operation and movement routes. The aim of the work is to analyze the existing routes for the movement of garbage trucks in the city of Chelyabinsk to identify the most loaded and develop on its basis a test route for the created garbage truck with a hybrid power plant based on the chassis of the "Ural" vehicle. Keywords garbage truck, hybrid power plant, traffic routes, experimental data, statistical research

Terrain Factors Induced Slope Instability in CNG 37 – Ghat section, Panthalur, The Nilgiris

— Landslides are short-lived phenomena but can cause extraordinary changes in the landscape, destroying life and property. Mitigation and management of natural disasters are important issues. Recognising this, the United Nations in the year 2004 made gout “Learning from today’s disaster for tomorrow’s hazards”(UNISDR website). The Nadugani Hill is situated in SE of Panthalur taluk, Nilgiris District. The ghat section is 6.5 km in length. The region has moderate climatic conditions. The average rainfall in this ghat section is 3500mm. In this ghat section, two major activities, like tea plantation and heavy truck movement, lead to slope instability during heavy monsoon season. The study mainly aimed to use terrain factors and identify land susceptibility zonation. In this context, a detailed investigation was carried out using geomorphology, parent rock weathering, structural mapping, runoff and anthropogenic activities. The ghat section is covered by a thick Reserve Forest, a tea plantation and a smaller area enclosed by settlement. Hornblende biotitic gneiss and patches of charnockite in some places cover the study area. The gneissic rocks are highly fissile in nature. NE - SW fault controls the drainage systems, contributing to landslides. The structural data delineated from IRS-RS2, L-IV data and the lineaments are oriented in NE - SW. Morphology is one of the prime factors that cause which is landslides. Satellite imageries identify structural and fracture valleys in this study area. The thematic maps were converted into a digital format using ARC Map (10.2v) software. GIS-based Decision Support System provides advanced models of a system to identify land susceptibility zonation. Based on the analysis, the study area has been categorized into low, moderate, high and very high classes.

Effect of shell spacing on mechanical behavior of multi-span soil-steel composite structure

This study analyses the effect of lateral shells on central shell at a different spacing in a multi-span soil-steel composite structure subjected to quasi-static moving loads. The displacements and internal forces of the central shell during consecutive truck passages over the structure are investigated by finite element (FE) analysis. Field measurements from a site in Niemcza, Poland, are used to calibrate input parameters. Next, the simulations for different spacing between the shells are investigated. The backfill soil is modeled as elastic-perfectly plastic, while the shells and sheet piles are linear elastic. The non-linear contact zone between the shell and the soil backfill is assumed to reflect an elastic-plastic constitutive model. The analysis reveals that both vertical and horizontal displacements increase significantly when the ratio of shell spacing to span length is less than 0.5. Maximum stress occurs when the shells are placed adjacent to each other, i.e., without spacing. The stress is almost doubled in this position compared to the reference case—a single-span structure. The shifting of extreme deflections and stress is observed in the direction of truck movement. Nevertheless, the influence of lateral shells on the central shell's performance under moving loads is nearly negligible when the spacing-to-span ratio exceeds 0.5.

Structure and dynamics of urban freight truck movements: A complex network theory perspective

Knowledge of the core structure and inherent dynamics of urban freight transport systems is important for the development of policies, aimed at improving the livability and sustainability of cities. The past decade has witnessed a great deal of efforts into analyzing the geographic structure of urban freight transport systems. However, in-depth studies on the system core structure and underlying dynamics are still absent. This study contributes to the field by analyzing large scale freight truck trip data from Chinese cities, using complex network analysis. We empirically reconstruct and characterize the urban freight truck mobility networks and reveal the underlying spatial interaction patterns. We develop a spatial network growth model which explains how hub-and-spoke core structure of urban freight transport systems are formed. The developed model captures the essential interaction dynamics of freight locations, and explains the effects of spatial distance, economic size and business pattern replication. Inspired by the model, we provide policy implications for land-use planning, transportation planning and sustainable urban development.

Uncovering and modeling the hierarchical organization of urban heavy truck flows

Knowledge of the hierarchical organization of urban heavy truck flows is important for understanding the structure of urban freight system and underlying interactions dynamics, providing insights to assess and develop freight policies. The complexity and dynamic nature of urban freight system pose significant challenges in comprehensively capturing structured arrangement of heavy truck movements. In this paper, we uncover the hierarchical organization of urban heavy truck flows by using complex network theory. We use large-scale heavy truck GPS data and urban freight location point-of-interest (POI) data to construct urban heavy truck mobility networks, and detect their community structure. The empirical results suggest different sets of locations are closely linked to each other to form multiple clusters. By integrating the categories of locations, we reveal the cluster-specific industry concentration and industry-specific location roles, informing evidence-based policy formulation. To capture the interaction dynamics of locations, we develop a spatial network growth model that considers the spatial agglomeration of industrial clusters and interaction pattern of locations. The model provides a mathematical tool to simulate the formation process of real-world networks for logistics planning and management.

Estimating intercity heavy truck mobility flows using the deep gravity framework

Accurate estimation of intercity heavy truck mobility flows is of vital importance to urban planning, transportation management and logistics operations. The inaccessibility of big data related to intercity transport systems and the heterogeneity of trucking activities pose challenges for the reliable estimation. Recently, the advance of Artificial Intelligence (AI) provides a potential solution to this problem. However, most previous studies focused on the estimation of inter-regional passenger mobility. In-depth studies of estimating intercity heavy truck mobility flows by using deep learning techniques are still scarce. To fill in the gaps, we construct a deep neural network based on the Deep Gravity framework, an advanced predictive model for human mobility. We collect a wide range of data related to heavy truck movements, freight locations, road networks and land uses to train the model, and validate its high performance by comparing to traditional gravity model. Furthermore, we use an explainable AI technique to interpret how the city features contribute to the determination of intercity heavy truck movements, and the results can provide valuable policy implications for logistics operations, businesses and urban planning.

Inter-terminal transportation for an offshore port integrating an inland container depot

Offshore ports, which are located on islands or away from the hinterland, are usually connected with the hinterland via bridges for truck transportation. With the rapid growth of port throughput, the bridges are likely to become a bottleneck restricting the development of port business. Inland container depots (ICD) have been introduced as satellite terminals to address congestion issues on bridges by allowing a proportion of drayage trucks to pick up and drop off containers at the ICD instead of going to the container terminals of the offshore ports. Containers are transported between the ICD and container terminals by inter-terminal transportation (ITT) trucks owned by port authorities. The ICD is expected to mitigate the bridge congestion by transferring the travel demands of drayage trucks in peak hours to the travel demands of ITT trucks in off-peak hours. We propose a methodology for analyzing the influence of ICDs on port efficiency. An integer linear programming model is developed to optimize the movements of containers, drayage trucks and ITT trucks in an offshore port area with the objective of minimizing the costs of drayage trucks and ITT trucks and the penalty for late delivery of containers. Two model transformation approaches are proposed to reduce the solution space of the model for improving the computational efficiency of the algorithm. The influence of ICDs on port efficiency is evaluated through a real-world case study using the proposed methodology. The results provide insights for port authorities to make strategic decisions.

THE STRATEGIC HGVS PLANNING PRACTICES FOR SUSTAINABLE GREEN LOGISTICS IMPLEMENTATION

The Malaysian government is introducing a number of initiatives to try and reduce the effects of global warming. One of these is the road haulage industry, which contributes significantly as one of Malaysia's largest industries to the nation's effort to reduce its transportation emissions to 45% by 2030. However, the empty movement of trucks and improper transport planning by the management caused some delivery trucks to come back to the headquarters empty and did not fully utilise the space of the vehicles. Therefore, the researchers aimed to propose heavy goods vehicle (HGV) planning practice to solve the problems. This is a mixed-mode research paper in which data was gathered through interviews and estimated calculations. The data has been analysed by comparing the result of the simple estimation calculation with the operational cost and carbon emission. Based on the results, most of them agreed that by using the right strategy, operational costs and carbon emissions can be reduced. The researchers had introduced a few recommendations to enhance the firm’s transport planning practices that could contribute to the field of green logistics as well as the road haulage industry in Malaysia.

Identification of Hazardous Materials Truck Stops and Their Spatio-Temporal Distribution by Using GPS Trajectories

Existing studies on hazardous materials trucks mainly focus on route selection and risk assessment during truck movements, neglecting the potential threat to the areas which surround truck stops. In this paper, we propose a novel algorithm to identify the truck stops from GPS data based on the temporal and spatial attributes, and classify the categories of hazardous materials truck stops according to the Chinese National Economy Industry Classification System. GIS spatial analysis method is then employed to establish the temporal and spatial distribution of different categories of stops. Taking the trajectory data of hazardous materials trucks in Chengdu, China, as the sample dataset, the study shows that the trucks are mainly used in service, manufacturing, and wholesale and retail industries, and more than 80% of the stops are located outside the urban core area. Concerning stay time, nearly 60% of trucks stay in the identified areas for less than 2 h and only 20% of trucks for more than 9 h. The peak periods for the arrival of the trucks at most stops are 9–12 a.m. and 2–10 p.m., and stops on weekdays have less influence on their spatial distribution. Such results can provide decision-making support to government departments in their designation of operation sites, regulatory facilities, and transportation corridors, and transportation companies can arrange transportation routes and travel time according to the management measures thus taken.

Optimizing Coal Hauling Operations: A Strategic Plan for Increased Productivity at PT Borneo

The purpose of this research is to determine the key operational variables that impact productivity in PT BORNEO and identify optimal targets to improve productivity. A mixed methodology of qualitative and quantitative approaches, supported by process observation, was used to collect data. The study primarily uses existing quantitative data, but interviews may be conducted to capture constraints in the implementation plan process. GPS data also collected via an API to obtain information about truck movements, which can be divided into various activities to identify cycle time and analyze system performance. The study found that reducing loading time and minimizing random stoppages can significantly improve productivity, with average loading time being the most important factor. Stoppage before rest time and stoppage in loaded condition and at major prayer time had little impact on overall productivity. Future research could investigate the impact of other variables such as equipment maintenance and driver training on productivity.

Kajian Pergerakan Truk Transport TBS Sebagai Bagian Dari Rantai Pasok Bahan Pabrik Kelapa Sawit

The transportation of oil palm fresh fruit bunches (FFB) is a crucial stage in the palm oil production system. Productivity and efficiency due to the movement of haul trucks also affect the smooth supply chain of FFB as a material for palm oil mills (PMKS). This paper presents the results of a study that aims to compare the productivity and efficiency of truck movement in the process of evacuating fruit from the yield collection point (TPH) to the PMKS, between direct and transit systems. The efficiency or level of truck utility will affect the supply of FFB for PMKS. In trucks and systems that are less efficient, the FFB supply chain for mills stagnates, which can result in reduced volume and quality of CPO output. The research method is to measure the time of each stage of the FFB evacuation, record the data on the weight of the load, measure the distance traveled, calculate the truck cycle time, productivity level, and the efficiency of the truck movement, then analyze the statistics with the T test. The results showed that there was a difference in performance between transit evacuation system with direct evacuation system to PMKS. In the transit system, truck cycle time = 3.5 hours, truck work efficiency = 44.3%, and truck productivity = 15.4 tons/day. While in direct system, the cycle time = 5.07 hours, work efficiency = 63.3%, and productivity = 12.07 tons/day. Recommendations from the research for improving the FFB supply chain are 1) doubling the supply of FFB from small transport in the transit system, 2) optimizing truck mobility by setting work locations

Assessment of the Impact of Selected Parameters of Tractor-Semitrailer Set on the Braking Safety Indicators

With the continuous development of road transport of goods, the issue of safety risks related to the movement of trucks and road trains remains an essential element of the overall road safety system. One of the persistent problems is the braking of such kits, especially in emergencies on the road. The work aims to show how typical changes in operating conditions can affect the basic indicators illustrating the safety of braking (effectiveness indicators, stability symptoms). A simulation method was applied for the analysis, which used a relatively simple (quasi-static) model of the tractor-semitrailer set’s rectilinear motion and models of the braking system and the longitudinal forces in the tyre-road surface contact. Calculations were made for the selected truck-trailer set in nominal condition and for several deviations from the nominal state, such as loading the trailer (load value, location of the semi-trailer’s centre of gravity), reduced surface adhesion, and selected faults of the semitrailer braking system. The results were compared for several qualitative and quantitative criteria for the evaluation of braking safety. Attention was drawn to the problem of the forces in the coupling (which determine the possibility of jack-knifing phenomena), the order of axle locking, and the braking distance. The presented results show that the change of operating conditions as above compared to the nominal condition visibly deteriorates the effectiveness of the braking process. The greatest threat, both related to the braking efficiency and the increase in the force in the coupling, is associated with the lack of braking of the semitrailer axle or a significant reduction in its load. The weight and location of the load’s centre of gravity considerably impact braking safety. In addition to the negative impact on the braking distance or increase in the horizontal force in the coupling, it changes the order of locking the axle. ABS reduces the risk associated with braking safety but does not eliminate it. At the same time, it has been shown that using relatively simple calculation tools makes it possible to indicate the risks related to the braking safety of such articulated vehicles.

MATHEMATICAL MODEL OF THE MOVEMENT OF A LOW-TONNAGE TRUCK WITH A MECHANICAL ENERGY RECOVERY UNIT

To date, an important role in many areas of economic activity is played by road freight transport. First of all, it depends on how quickly and reliably the goods will be delivered from one place to another. With an extensive list of various goods that need to be transported, there is no less a large selection of vehicles to perform these tasks.
 Due to the fact that heavy trucks are currently prohibited from entering most cities, low-tonnage trucks, including vans and trucks of the transport category “N1”, have become in demand. Their main purpose is the transportation of small shipments within the city or over relatively short distances.
 Low-tonnage trucks should have not only high dynamic characteristics, but also low fuel consumption. Numerous studies have shown that the most promising direction of increasing dynamic characteristics and reducing fuel consumption are mechanical energy recovery devices that accumulate the energy of the rotating masses of the car during braking and transfer it to the same rotating masses at the moment the car starts moving. Analysis of the movement of light trucks using a mechanical energy recovery device can reveal changes in the dynamics of light trucks and fuel consumption.
 Purpose. Investigation of changes in dynamic characteristics and fuel consumption of a low-tonnage truck with a mechanical energy recovery unit using a model in the MATLAB Simulink environment.
 Methodology. Methods of mathematical modeling and analysis were used in the article.
 Results. The parameters showing the efficiency of operation of a low-tonnage truck with a mechanical energy recovery unit are obtained.
 Practical implications. The results obtained can be applied when designing a car to identify the optimal parameters of the vehicle’s power plant, which are used together with mechanical energy recovery devices.

Method for applying vehicle driving cycles to assess the durability of electromechanical transmissions of trucks

The article discusses the relevance of the problem of calculating the elements of electromechanical transmissions of trucks for strength and durability. The main methods used for the formation of load conditions on electromechanical transmissions of trucks are given. The driving cycles of trucks used to obtain loads when calculating the durability of the elements of electromechanical transmissions are given. The universal driving cycles of vehicles obtained on the basis of the collection of statistical data on the movement of trucks are considered. A simulation model of the movement of a truck used to determine the loads on the electromechanical transmission while overcoming driving cycles of trucks is presented. The durability of the gears of the electromechanical transmission of a truck is analyzed on the basis of load cyclograms obtained during simulation modeling of movement. Numerical results of the safety factors of one of the gear stages are obtained. Conclusions are drawn about the optimality of the use of existing driving cycles of trucks in strength calculations. Conclusions are worded about the need to synthesize driving cycles of trucks based on the collection of statistical data on the movement of truck vehicles on the territory of the region under consideration.