Freight Truck Research Articles

Variance in Truck load Carrying Capacity impacting Truck Fill Rate, Freight Cost and Carbon Emissions

Variance in Truck load Carrying Capacity impacting Truck Fill Rate, Freight Cost and Carbon Emissions

Variance in truck load carrying capacity impacting truck fill rate, freight cost and carbon emissions

Variance in truck load carrying capacity impacting truck fill rate, freight cost and carbon emissions

Нормативы скорости автомобиля в планировании перевозок с использованием электронных путевых листов

The development of digital technologies unveils prospects for paperless document management in road transport, which is confirmed by a pilot project on the use of an electronic shipping manifest and a bill of lading. It is important to use the shipping manifest not only as a digital document, but also as a specialized software tool for calculating planned and actual performance indicators of vehicles as part of the enterprise management information system. An algorithm is proposed for constructing the information system for managing transport activities using electronic waybills, which are used as software for calculating planned performance indicators of vehicles and summarizing the results of transportation. The established standards and legal documents regulating the transfer of document flow in the field of road freight transportation to electronic basis are given. The importance of reasonable standards of average technical speed and idle time of vehicles at loading and unloading points for scheduling the performance of freight trucks on routes is illustrated. The factors influencing the value of the average technical and operational speed of a vehicle during transportation are studied and systematized, recommendations on establishing of their regulatory standards are given, formulas for calculating quantitative values are provided. Based on the specified standard of average technical speed, the calculation of the radius of cargo delivery during the day in intercity communication is demonstrated.

Стэйкхолдерский подход в реализации системы утилизации вышедших из эксплуатации транспортных средств

The problem of the development of reverse logistics has become acute due to the increase in the number of age-related vehicles, which, along with the threat of their safe operation, pose an environmental threat. The key stakeholders are analyzed, their interests and emerging barriers are identified, their consideration formed the basis for formation of scientific and methodological objectives in creation of a unified state system of disposal and recycling, taking into account the possibilities of recycling of freight trucks along with passenger cars. The organizational scheme for creation of the system for disposal of decommissioned vehicles, including key stakeholders, is proposed. The proposal has been put forward to create the Association of Vehicle Processors as a coordinator of a complex infrastructure project of state significance. The information and management interactions between the enterprises of the vehicle recycling system and subjects of the transport system and government agencies are indicated. The key task of creating a data-base of recycling products as the information basis for formation of the recycling system and minimization of waste to be destroyed based on the ideology of reverse logistics is set, and it is assumed that this database will help to appoint the subject responsible for a vehicle at the end of its life cycle as an obligatory element of the system.

Utilization of dynamic wireless power transfer technology in multi-depot, multi-product delivery supply chain

Dynamic wireless charging technology (DWC) is considered an innovative contactless way to charge the battery of electric vehicles (EV) in the modern transportation system. By installing charging infrastructure beneath the road, this technology can overcome the obstacles of conventional charging topology, including high battery cost, restricted driving range, limited availability of charging stations, and long recharging downtime. This paper proposes a long-term mathematical model for locating-routing electric freight trucks (EFTs), which belongs to the Multi-Depot Multi-product delivery supply chain. In the proposed framework, the placement of DWC infrastructure and routing of EFTs has been accomplished by considering the battery capacity of trucks, charging facilities installation cost, electrical energy losses, and the voltage deviation in the power distribution system (PDS). Finally, two comparative case studies have been performed on the interconnected network IEEE 13 node test feeder and Nguyen–Dupius traffic network to validate the proposed approach. We also conduct a sensitivity analysis to understand the model’s system behavior and confirm it with insight.

Study on the control targets and measures for total diesel consumption from mobile sources in Beijing, China

Based on the current air pollution control and CO2 emission reduction policies, this study analyzed the energy structure, number of motor vehicles and nonroad mobile machinery, energy consumption and pollutant emissions in Beijing. Furthermore, the diesel consumption characteristics and challenges for emission reduction in key fields were investigated, such as medium- and heavy-duty diesel trucks, long-distance passenger and tourist diesel vehicles, and nonroad machinery, which are areas with difficult-to-reduce diesel consumption. Control targets and measures for total diesel consumption were also proposed. The results indicated that the higher diesel consumption per unit area in Beijing is related to the larger passenger car and freight truck populations. In recent decades, the number of diesel vehicles has increased, the vehicle type structure has been optimized, the proportion of vehicles with high emission standards has increased, and the absolute pollutant emissions have decreased. Among these, nitrogen oxides (NOx), fine particulate matter (PM2.5) and volatile organic compound (VOC) emissions of different models decreased by 39.5%, 75.3% and 42.8%, respectively, while carbon dioxide (CO2) emissions from diesel combustion decreased by 32%. Moreover, medium and large passenger vehicles, medium- and heavy-duty trucks and construction machinery are the main contributors to diesel consumption. These vehicle types are also difficult to control and reduce, and their replacement by new-energy vehicles is relatively limited. The main control measures for diesel consumption are as follows. First, a green transportation mode can be adopted for goods that can be converted from roads to railways. Second, fuel consumption reduction for nonroad mobile machinery can be realized by tightening fuel consumption limits, setting appropriate maximum retirement life, establishing low- or ultralow-emission zones, and establishing demonstration plots for electric vehicle (EV) substitution for mobile machinery. To improve the air quality and take the lead in carbon neutrality in the future, Beijing must further accelerate the energy structure adjustment and the development of new-energy vehicles in the transportation sector. Carbon neutralization is an important opportunity for diesel consumption reduction, and the synergistic control of atmospheric pollution and carbon emissions from diesel combustion must be strengthened.

Enhanced Road Network to Reduce the Effect of (External – External) Freight Trips on Traffic Flow

The transportation system is often described as the lifeblood of modern society. Roads constitute a fundamental part of this system for both passenger and freight transports, a well-functioning freight transportation system is an essential element in any successful economy. Hilla is one of the most densely populated cities in Iraq. The road network in Hilla city is under additional load due to (external - external) trips, especially freight trips by trucks passing through the city's main entrances to cross into neighboring districts and provinces. This is due to the city's strategic location, which connects Baghdad with the southern provinces, making it an important transit route. The objective of this research is to study a proposal for modifying and developing the road network in the city of Hilla by adding new roads to the current network in order to reduce the negative impact of freight trucks passing through the city, especially (external - external) trips, by using Trans CAD and ArcGIS software network analysis. The result of network analysis shows that the suggested roads will reduce the total (travel time and distance) for the same origin and destination points by 9%, and 30%, compared with the current distance and time, respectively, while improving the level of service from D to C at peak hours for freight vehicles. Doi: 10.28991/CEJ-2022-08-11-015 Full Text: PDF

Learning to Listen

Learning to Listen

Hydrogen fuel supply chains for vehicular emissions mitigation: A feasibility assessment for North American freight transport sector

Freight trucks powered by alternative low-emissions fuel sources such as electricity or hydrogen have gained significant attention as replacements for their fossil fuel-operated counterparts. Even though this shift to alternative fuels can reduce the operational emissions at the vehicle tailpipe, there can be significant emissions throughout their supply chains. A thorough review of the published literature highlights that a comprehensive investigation is lacking on the well-to-wheel life cycle impacts of hydrogen fuel used for freight transportation. Furthermore, a comparison between hydrogen-fueled and electric freight transport is unavailable in the published literature. This study comprehensively investigated the life cycle environmental and economic impacts of alternative fueled freight transport based on vehicle types and relevant supply chains. A life cycle impact database was developed for key electric and hydrogen fuel supply chain scenarios and was ranked based on the economic and environmental performance under different decision-maker perspectives. The life cycle emissions of delivering hydrogen fuel range from 2.2 to 12.6 kgCO2eq./kg of hydrogen whereas electric grid emissions range from 0.005 to 0.315 kgCO2eq./MJ. However, hydrogen systems that use electrolysis to produce hydrogen show better environmental performance over the complete vehicle life cycle compared to electric systems that are highly dependent on nonrenewable energy sources. The cost of ownership of a hydrogen and electric freight truck is approximately 2.15 and 0.54 CAD/km respectively. However, with investments from governments and private institutions to develop hydrogen refueling infrastructure, hydrogen-fueled freight vehicles have the potential for reducing GHG emissions in the road transportation sector.

Research on Differential Pricing and Train Operation Decisions for Railway Cargo Transportation Under Competitive Conditions

Railway freight operations aim not only to market themselves aggressively to capture the market in a competitive environment but also to achieve refined management. The operational decisions chosen by carriers can have a significant impact on the revenue across freight services. Nowadays, various forms of transported products, train make-up, and schedules are developed from the perspective of production convenience, with less consideration of shippers’ needs for the time utility, frequency, and tariffs of transportation services. This paper investigates a joint optimization approach to railroad operation planning that combines meeting the transport demand preferences of different shippers in a competitive environment. Considering the heterogeneity of shippers’ transportation demands and the competitive environment with freight trucking, a new bi-level programming model is proposed that incorporates pricing decisions and operational planning policies, such as car blocking, train routing, and make-up. An exact solution for this model is developed by adding valid inequalities to the mixed-integer formula and the experiment is conducted with data from bulk coal cargo transportation of the S Railway Bureau Group Corp. A simple transportation network is presented, and the calculation results of the pricing decisions that maximize the profit in each operation decision in this network are reported.

Simulated and Experimental Verification of Fuel-Efficient Truck Platooning With Model Predictive Control Under Grade and Traffic Disturbances

Abstract Truck platooning closely regulates gaps between heavy-duty freight trucks to exploit slipstream effects for reducing aerodynamic friction—and therefore reducing engine effort and fuel usage. Currently deployed applications of this have been classically actuated through error-correcting PID feedback loops with connectivity amongst trucks in a fleet to form a connected and adaptive cruise control law that attenuates disturbances between trucks to maintain tolerable gaps. Typically, performance of such systems is challenged by difficult, albeit not uncommon, transients when under traffic conditions and when under road grade variations. Because of this, such platooning control requires attentive and trained drivers to disengage the adaptive cruise control—which limits its potentials for reducing driver load. More advanced longitudinal motion planning under predictive optimal control can push for higher levels of autonomy under a larger range of scenarios, as well as improve fuel efficiency. Here, model predictive control for fuel-performant truck platooning is vetted in both simulation and experimentation for representative traffic and road grade routes. Several approaches are used exploiting physics-based models with and without the powertrain system, and neural network-encoded models. The fuel benefits of aerodynamic platooning are isolated from the more general eco-driving approach, which already provides fuel benefit to trucks by smartly selecting truck velocity. Results from simulation and validation in experimentation are presented—showing up to 6% benefit in fuel economy through eco-driving and an additional 3% achievable through platooning. Observed losses in fuel performance are explained by energy dissipation from braking.

Applications of Passive GPS Data to Characterize the Movement of Freight Trucks—A Case Study in the Calgary Region of Canada

The movement of trucks represents a significant portion of travel. Surveys have traditionally been used to measure truck movement, but this costly and limited data collection method typically involves in-person interviews and requiring high workload. This study explores different ways in which passive truck GPS data can be used to complement traditional data collection methods, for obtaining detailed information about the travel behaviors of freight trucks. First, we develop a heuristic-based model to identify truck stops. A new methodology is proposed to classify truck stops into a primary or secondary sto, which make identifying trip purposes possible. Primary stops are defined as the locations where the loading or unloading of the goods takes place. Secondary stops are those associated with all other purposes, including refueling, and driver breaks. Finally, we develop a destination choice model for modeling truck movements. This model applies a discrete choice modeling technique to distribute truck trips within the Calgary region, Canada. We test the utility function in the destination choice model to include of business establishment data, travel impedances, and other dummy variables that are likely to influence truck demand. The results show that a combination of trucks’ dwelling times and their entropy can be used to classify truck stops by purpose. This study also shows the potential of using passive GPS data to gain additional insights into truck movements characterization and truck trip distribution modeling.

Modeling Road Link-Level Truck Travel Times Using On- and Off-Network Characteristics

Travel times of freight trucks (or trucks) play a major role in trip planning, identification of efficient routes, and allocating resources for implementation of strategies. While research on travel time estimation models for passenger cars or traffic stream is documented in the literature, their applicability for trucks remains debatable. Truck travel is influenced by the road characteristics, surrounding land use, and demographics of an area. The focus of this research, therefore, is on estimating the truck travel times using the on-network (road) and off-network (land use and demographics) characteristics. Truck travel time data for 501 road links in North Carolina from 2019 were processed for four times of the day and two days of the week. Generalized estimating equations (GEE) were used with the average truck travel time per mile (ATTTPM) as the dependent variable. Spatial proximity (buffers of 0.25 mi, 0.50 mi, and 1 mi) and spatial weights (distance decay functions like 1/d, 1/d2, and 1/d3) were explored to check the best possible approach for capturing off-network characteristics. The office (business park and administrative areas), transportation (rest areas and parking facilities), heavy commercial, and light industrial land uses have an increasing influence on the ATTTPM. The linear model developed using data from a 0.25-mi buffer is best suited to estimate the ATTTPM. Off-peak hour delivery incentives or truck priority systems on road links near these land uses can be implemented to improve truck mobility. The methodology illustrated in this research is transferable and could be used for estimating truck travel times across a region.

Analyzing Freight Truck Platoon Accessibility with Route Deviations

Truck platooning is emerging as a sustainable means of transporting goods and commodities to destinations. Platooning optimizes road space and contributes to reducing freight truck emissions. However, there has been limited research on freight truck platoon accessibility to the destination that is often necessary to understand the impact of routes on which platoon is deployed. This study develops an analytical formulation for platoon accessibility by considering the possibility of the detour of trucks forming a platoon. Analyses with four prominent interstates in California, CA, USA, show that accessibility with truck platooning on select lengths of the I-5 continues to increase for about an initial 165 miles, attains a maximum there, and starts to drop after. The other three freeways, I-10, I-405, and I-710, show a continuous increase in accessibility for their lengths and the number of ramps considered. The findings can have significant implications in determining the selection of freeway routes that could be regarded as facilitators for a truck platoon.

Attacks on road-freight transporters: a threat to trade participation for landlocked countries in Southern Africa

South Africa hosts some of the busiest maritime ports which are gateway ports to several landlocked countries in the region. Road transportation is the main modality for moving goods between seaports and hinterland within South Africa and beyond to at least six landlocked countries in the region. However, the high rate of violent crime against freight trucks and vans has for many years been a major known risk to the road freight transport industry. Traditionally, these crimes have been motivated by monetary proceeds from sales of stolen goods from hijacked vehicles or the vehicles themselves. Recently, however, influenced by anti-immigrant sentiments, similar attacks have been specifically targeting foreign drivers and trucks resulting in death, injury, and damage to vehicles and cargo. Previously considered an internal problem for South Africa as a matter arising from domestic social and economic challenges in that country, the emergence of attacks on foreign drivers and trucks have raised concerns about the future of South Africa as an economic powerhouse, its role as a transit country for landlocked countries, and about its relationship with regional neighbors. For the landlocked countries in the region, any instability in South Africa can have a serious impact on the logistics that sustain businesses and international trade. This exploratory study gives an overview of the increasingly complex issue of violent attacks against foreign nationals in South Africa with a focus on attacks targeting the road freight transport sector and the implications on regional integration efforts.

Identifying intracity freight trip ends from heavy truck GPS trajectories

Intracity heavy truck freight trips are basic data in city freight system planning and management. In the big data era, massive heavy truck GPS trajectories can be acquired cost effectively in real-time. Identifying freight trip ends (origins and destinations) from heavy truck GPS trajectories is an outstanding problem. Although previous studies proposed a variety of trip end identification methods from different perspectives, these studies subjectively defined key threshold parameters and ignored the complex intracity heavy truck travel characteristics. Here, we propose a data-driven trip end identification method in which the speed threshold for identifying truck stops and the multilevel time thresholds for distinguishing temporary stops and freight trip ends are objectively defined. Moreover, an appropriate time threshold level is dynamically selected by considering the intracity activity patterns of heavy trucks. Furthermore, we use urban road networks and Point-of-Interest (POI) data to eliminate long-stay temporary stops to improve method accuracy. The validation results show that the accuracy of the method we propose is 88.79%. Our method incorporates the impact of the city freight context on truck trajectory characteristics, and its results can reflect the spatial distribution and chain patterns of intracity heavy truck freight trips, which have a wide range of practical applications.

Magnetic Coupler Robust Optimization Design for Electric Vehicle Wireless Charger Based on Improved Simulated Annealing Algorithm

Fleets of autonomous vehicles including shuttle buses, freight trucks, and road sweepers will be deployed in the Olympic Village during Beijing 2022 Winter Olympics. This requires intelligent charging infrastructure based on wireless power transfer technology to be equipped. To increase the misalignment tolerance of a high-power wireless charger, the robustness of the magnetic coupler should be optimized. This paper presents a new type of unipolar coupler, which is composed of three connected coils in series. The dimensional configuration of the coils is analyzed by the finite element method. The characteristic parameters of the coil are identified with their influence on the self-inductance and coupling coefficient. An expert model is built, whose feasibility can be verified in the aimed design domain. Combined with the expert model, an improved simulated annealing algorithm with a backtracking mechanism is proposed. The primary coil can reach the expected characteristics from any starting parameter combination through the proposed optimization algorithm. Under the same conditions in terms of external circuit parameters, ferrite usage, and aluminum shielding, the offset sensitivity of the magnetic coupler can be reduced from 58.79% to 18.89%. A prototype is established, validating the feasibility of the proposed coil structure with the optimized parameter algorithm.

Design of a two-echelon last-mile delivery model

Due to high congestion in cities and growing demand for last-mile delivery services, several companies have been implementing two-echelon distribution strategies over the past few years. Notably, the installation of urban transshipment points has gained increasing attention, used by logistics operators to transfer goods from large freight trucks to smaller and more agile vehicles for last-mile delivery. Nevertheless, the main challenge is how to decide the number and location of these facilities under the presence of demand uncertainty. In this paper, we develop a two-stage stochastic program to design two-echelon last-mile delivery networks under demand uncertainty. This approach decomposes the problem into strategic decisions (facility location) and operational decisions (daily distribution of goods). To address large-scale instances, we solve the model through the sample average approximation (SAA) technique and estimate the optimal routing costs (of the SAA counterpart) using a continuous approximation method. Using a real-world case study with more than 1300 customers from New York City, our results provide several managerial insights regarding the mix of transportation modes, facility location, and the impact of allowing the outsourcing of customer demand. We provide extensive validation of the two-stage stochastic program results through a simulation-based approach and the calculation of the value of the stochastic solutions. • We develop a two-stage stochastic program to design two-echelon last-mile delivery networks under demand uncertainty. • We use sample average approximation and continuum approximation of route cost to address large-scale instances. • For a real-world case study, we provide managerial insights regarding the mix of transportation modes, facility locations, and the benefits of outsourcing deliveries. • We extensively validate our results using a simulation-based approach and assess the value of accounting for stochasticity.

Identifying intercity freight trip ends of heavy trucks from GPS data

The intercity freight trips of heavy trucks are basic data for transportation system planning and management. In recent decades, extracting intercity freight trips from GPS data has gradually become the main alternative to traditional surveys. Identifying freight trip ends (origin and destination) is the first task in trip extraction. Although many trip end identification methods have been proposed in previous studies, most of these studies subjectively determined key parameters and ignored the complex characteristics of truck trajectory and freight activities. In this paper, we propose a data-driven trip end identification method based on massive GPS data of heavy trucks in China. First, we capture heavy truck trajectory characteristics under the influence of GPS drift to identify truck stops from GPS data. Second, we analyze the temporal characteristics of truck activities and use freight-related point-of-interest (POI) data and highway network GIS data to identify valid trip ends from truck stops. The results of method validation suggest that the accuracy of our proposed method is significantly improved in comparison with the benchmark methods. We further extract intercity freight trips from the identified trip ends and analyze the spatiotemporal characteristics of intercity freight trips in China.

Simulation study on carbon emission of China's freight system under the target of carbon peaking

The development of Chinese society needs the support of a perfect and efficient freight transport system. Nonetheless, China's freight system is facing a major challenge in reducing carbon emissions. Hence, firstly, this paper explores three major internal drivers of carbon emissions by analyzing the current situation in China's freight system: proportion of railway freight (PORF), railway electrification level (REL) and electric truck penetration (ETP). Secondly, the system dynamics (SDs) model is used to simulate the carbon emission system of freight transportation in China. Thirdly, this paper sets 13 scenarios of carbon peaking to explore the paths of carbon peaking before 2030 under the three levels of development of ETP oriented freight system. The results indicate that when PORF, REL, and ETP reach 23.96% of total freight volume, 83.7% of rail freight, and 11% of truck freight in 2030 respectively, China's freight system has the most optimistic scenario of carbon peaking. Meanwhile, the time of carbon peaking is 2024, and the peak value is 0.842 billion tons. When PORF, REL, and ETP reach 15.96% of total freight volume, 63.7% of rail freight, and 3% of truck freight in 2030 respectively, China's freight system has the worst scenario of carbon peaking. Meanwhile, the time of carbon peaking is 2029, and the peak value is 1.016 billion tons. Also, it is proved that improving PORF, REL, and ETP is an effective way to achieve green and sustainable development of China's freight industry.