Truck Size Research Articles

Car or Cargo Bike? Determinants for the Use of a Small Vehicle Type in Urban Logistics: A Stated Preference Survey Among Commercial Transport Operators

To address the adverse effects of urban freight, downshifting to smaller vehicles, such as cargo bikes, has been indicated as a viable solution. Existing literature on freight mode choice rarely considers vehicles smaller than truck size. We aimed to fill this research gap by quantifying how vehicular, operational, trip-based, contextual, and individual determinants influenced the decision between cargo bikes and cars in urban logistics. To that end, a stated preference survey was conducted among 537 German organizations after they had been familiarized with cargo bikes through a 3-month vehicle trial period. Participants then took part in a survey in which they had to choose between the modes cargo bike, car, or neither of these two alternatives. The survey data were analyzed using a mixed logit model with 4,833 observations. The model estimations demonstrated that the values and signs of parameters were in accordance with both our expectations and the literature. The results indicated that cargo bikes were an attractive alternative to cars for delivery and service trips of short duration in fair weather. The probability of choosing a cargo bike over a car could be further increased by improving bike infrastructure or imposing parking limitations. The preference for cargo bike could be observed for respondents in dense urban centers and low-density parts of the country alike. Around 3 out of 10 respondents decided to buy their own cargo bike after the study, demonstrating the effectiveness of low-threshold testing programs in changing habits toward more sustainable mobility solutions.

The Economic Competitiveness of Hydrogen Fuel Cell-Powered Trucks: A Review of Total Cost of Ownership Estimates

This paper investigates the economic competitiveness of hydrogen-powered trucks. It reviews the growing number of papers that provide an estimate of the total cost of ownership (TCO) of hydrogen-powered trucks relative to their diesel equivalents. It examines the methodology applied, the variables considered, the data used for estimation, and the results obtained. All reviewed studies conclude that hydrogen-powered trucks are not currently cost-competitive, while they might become competitive after 2030. The conclusion holds across truck types and sizes, hydrogen pathways, mission profiles, and countries. However, we find that there is still a huge area of uncertainty regarding the purchase price of hydrogen-powered trucks and the cost of hydrogen, which hampers the reliability of the results obtained. Various areas of methodological improvements are suggested.

A short Literature Review on Sawlog and Pulpwood Transport Efficiency and Fuel Consumption

Timber transport is one of the main components of woody supply chain, which causes high costs and considerable emissions depending on truck size, type, transport distance, and payload. A cradle-to-gate life cycle assessment of Softwood plantations and regrowth hardwood native forests estimated that the most significant contributor to total greenhouse emissions per unit of wood production in softwood plantation was log haulage at 37%. For regrowth native hardwood forests, log transportation contributed 23% of greenhouse gas emissions. This research, built on existing literature, focused on how timber harvesting transportation costs and emissions to the environment can be reduced, specifically, the transport of the industrial timber logs from the Forest Stockpile to the processing facility or unloading points. The review summarized the data and highlighted that the efficiency and emissions data could be categorized into five themes: Higher Capacity Transportation (HCT), Road Networks & Surfaces, Logistics and Planning, Fleet Replacement, and Fuel efficiency technologies. Fuel efficiency improvements across these themes ranged from 3% to 43% within the reviewed case studies. Several studies researched the fuel efficiency of High Capacity Transport indicated that the fuel consumption in liters per ton kilometer was 8-11% lower in the 92-tonne combination HCT compared to a 72-tonne combination HCT due to the increased payload for High Capacity Transport. Road networks and the composition of the surfaces have been shown to have a strong correlation to emissions. Studies have shown a 16.7% increase in emissions from a network of predominantly highways to a higher proportion of Forrest and Gravel roads. Studies that included data on vehicle age found efficiency improvements of up to 26% when new vehicles’ fuel consumption was compared to older vehicles. Newer truck fleets incorporate newer technologies, with reports showing fuel consumption improvements of up to 43% with less than a two-year payback period.

Cost and Time Optimization in Fleet Management- Case Study of Sinnar Shirdi Highway

Abstract: The aim of the study is to show how fleet management can help in saving time and cost by comparing the current onsite equipment to optimised results. The detailed study of fleet of equipment and their related parameters and specifications is important because it helps to determine requirement of equipments for a particular activity. All the cost including labor, maintenance, operating costs, machine capacity were considered to find out the productivity as well as expenses. Based on the site visit and data collection various parameters such as productivity of excavator, production rate, cycle time and other parameters of activities such as earthmoving equipment, hauling of trucks as well as productivity of paver were also calculated. The parameters were obtained for various combinations of different truck sizes as shown in the MS- Excel sheet. For different truck sizes and different combinations we get different cost index.

IoT-Based Waste Management System in Formal and Informal Public Areas in Mecca.

Urban areas worldwide are in the race to become smarter, and the Kingdom of Saudi Arabia (KSA) is no exception. Many of these have envisaged a chance to establish devoted municipal access networks to assist all kinds of city administration and preserve services needing data connectivity. Organizations unanimously concentrate on sustainability issues with key features of general trends, particularly the combination of the 3Rs (reduce waste, reuse and recycle resources). This paper demonstrates how the incorporation of the Internet of Things (IoT) with data access networks, geographic information systems and combinatorial optimization can contribute to enhancing cities’ administration systems. A waste-gathering approach based on supplying smart bins is introduced by using an IoT prototype embedded with sensors, which can read and convey bin volume data over the Internet. However, from another perspective, the population and residents’ attitudes directly affect the control of the waste management system. The conventional waste collection system does not cover all areas in the city. It works based on a planned scheme that is implemented by the authorized organization focused on specific popular and formal areas. The conventional system cannot observe a real-time update of the bin status to recognize whether the waste level condition is ‘full,’ ‘not full,’ or ‘empty.’ This paper uses IoT in the container and trucks that secure the overflow and separation of waste. Waste source locations and population density influence the volume of waste generation, especially waste food, as it has the highest amount of waste generation. The open public area and the small space location problems are solved by proposing different truck sizes based on the waste type. Each container is used for one type of waste, such as food, plastic and others, and uses the optimization algorithm to calculate and find the optimal route toward the full waste container. In this work, the situations in KSA are evaluated, and relevant aspects are explored. Issues relating to the sustainability of organic waste management are conceptually analyzed. A genetic-based optimization algorithm for waste collection transportation enhances the performance of waste-gathering truck management. The selected routes based on the volume status and free spaces of the smart bins are the most effective through those obtainable towards the urgent smart bin targets. The proposed system outperforms other systems by reducing the number of locations and smart bins that have to be visited by 46% for all waste types, whereas the conventional and existing systems have to visit all locations every day, resulting in high cost and consumption time.

Trajectory Planning of Semi-Trailer Truck Vehicle Based on Algebraic General Trajectory Formula

The present group previously derived an algebraic general trajectory formula (GTF) for semi-trailer trucks based on six parameters relating to the truck size and truck turning situation. The present study proposes a trajectory planning method based on the GTF which ensures that several arbitrarily-chosen points on the truck pass sequentially through a set of user-defined target points along the required path. An illustrative example is provided to demonstrate the effectiveness of the proposed method. The results confirm that the trajectory planning method provides an effective, accurate, and simple methodology for planning the motion path of semi-trailer trucks.

Evolution of bridge live load models and truck weight limits: the case of Manitoba, Canada

Changes in the size and weight regulations for trucks have been used to improve their productivity, safety, and operational performance in Canada. In response to these changes, bridge design codes undergo modifications to envelop the potential range of trucks in operation. A five-decade timeline is presented to: (i) document how bridge codes and their live load models have evolved, with a focus on the Manitoba-specific HSS-25 truck; and (ii) discuss how responsive the bridge design codes have historically been to changes in truck size and weight regulations. While at times bridge codes are released in conjunction with expected regulation changes, there is often delay in the issuance of those codes. Assessments of the current truck fleet, which now includes long combination vehicles (LCVs), may be a consideration for future bridge live load models.

Method for Estimating Speed of the Out-of-Control Tractor-Semitrailer on Downhill Grades

Speed estimation for the out-of-control truck on a downhill grade is essential for passive safety features like truck escape ramps to promote traffic safety. This paper presents a method for estimating the speed of out-of-control trucks based on Newton’s Laws of Motion. First of all, we analyze gravity effort, aerodynamics, and rolling resistance through a free body diagram of an out-of-control truck on a downhill grade. Further, we select the speed as the dependent variable, with the following road and vehicle characteristics as independent variables: road surface type, grade, grade length, truck size, truck weight, and tire type. Finally, we estimate the speed and acceleration according to Newton’s Laws of Motion. The results show that the factors that significantly affect the out-of-control truck’s speed include tire type, road surface coefficient, grade, and grade length. TruckMaker simulation results demonstrate that the model is valid at a 99% confidence level.

Retrospective Longitudinal Study of the Impact of Truck Weight Regulatory Changes on Operating Gross Vehicle Weights

Three primary policy changes on truck size and weight occurred in Canada over the past five decades: the 1974 Western Canadian Highway Strengthening Program, the 1988 Roads and Transportation Association of Canada Memorandum of Understanding on Heavy Vehicle Weights and Dimensions, and ongoing special permitting of longer combination vehicles. These regulatory changes influenced the gross vehicle weight (GVW) of the predominant truck configurations operating on principal Canadian highways. Using a unique time-series of truck weight data, this retrospective longitudinal study contributes insights about the magnitude and timing of the impacts of truck weight regulatory changes on operating GVWs that address current knowledge gaps and persistent uncertainties in models used to predict and evaluate truck weight regulatory changes. The analysis reveals that carriers hauling heavy (i.e., weigh-out) commodities adapt immediately to increases in GVW limits if there is no need to purchase new vehicles. When a regulatory change coincides with the introduction of a new, more productive vehicle configuration, the uptake of the new vehicle lags behind the regulatory change by a few years. Finally, configurations exhibit different GVW distributions and responses to increased GVW limits depending on whether the configurations are well suited for hauling weigh-out or cube-out commodities. This differential response demonstrates how regulations facilitate fleet diversity within the trucking industry’s approach to the road freight transport task.

A theoretical framework to evaluate the traffic impact of urban freight consolidation centres

City logistics and goods movement using road freight is an outcome of the economic activities that sustain urban life. However, they produce negative externalities like traffic congestion and pollution. There are key areas within cities that are largely affected by logistics activities, such as commercial centres and retail districts. These locations attract many freight vehicles attempting to fulfil deliveries, often with limited parking supply. This results in long queues of delivery trucks waiting for parking spaces or illegal kerbside parking. Therefore, urban planners and decision-makers are motivated to initiate policies that can mitigate these impacts. Urban freight management policies like delivery time or truck size restrictions, and Urban Consolidation Centres (UCC) have been proposed as potential solutions. A UCC is a facility that allows deliveries to be consolidated before entering a busy commercial area. The focus of this study is to offer a theoretical framework for predicting the impact of a UCC on the number of freight trips attracted to a retail district in any city. A mathematical model is developed and used to analyse two possible policy cases concerning the location of a UCC: one where the UCC is located within the retail district, and another where the UCC is located outside the retail district. This model is subsequently applied to examine a retail district in Singapore using real-world data. The critical level of participation in a UCC scheme required for the retail district to experience fewer freight trips is characterised. The results show a diminishing marginal benefit associated with achieving greater consolidation by operating the UCC. This contribution offers a theoretical explanation for the traffic impacts of urban freight consolidation, and aids with the development an ex-ante evaluation of a UCC. The model may be readily applied to any city considering this initiative, by adjusting the model parameters for local conditions.

Quantifying the effect of landscape structure on transport costs for biorefinery of agricultural and forestry wastes in Malaysia

AbstractIn the context of climate change, sustainable biorefinery helps to mitigate carbon emissions. This paper examines how landscape structure metrics allow us to better understand the economics of agricultural and forestry wastes transportation. To verify that the landscape structure plays a significant role, we quantify the fragmentation of various lignocellulosic feedstock in Malaysia, as a typical tropical country. Fragmentation is compared with the variations of truck size, transport distance, and biomass nature. We use GRASS GIS to develop a series of transport cost maps, to quantify feedstocks, to run various biomass transport simulations, optimize locations of potential biorefineries, and to compute landscape structure metrics. We find that the cost of 1 million tonnes feedstock increases by more than 4 USD/tonne for every added unit of edge density (fragmentation index). It also increases by more than 6 USD/tonne for every added 100 km of average transportation. The average truck size has also a strong nonlinear relation to the cost with −84 USD/tonne when changing from 3‐ to 26‐tonne trucks. To our knowledge, this is the first paper to address simultaneously fragmentation with the other classical logistic factors in a tropical country like Malaysia. It has strong implications for policymakers: the importance of the landscape structure makes a seemingly abundant biomass not viable for biorefineries if too fragmented compared to a much less abundant one, but more concentrated. It also implies that in tropical countries where the landscape is typically very fragmented, multi‐crop feedstocks could be considered for sustainable biorefineries.

A generalised model for container drayage operations with heterogeneous fleet, multi-container sizes and two modes of operation

We propose a generalized model of drayage operations that incorporates the coupling and precedence principles, allows for live and separation operation modes, relaxes the assumptions about fleet composition and truck size, and operates in a realistic network. The results of the experiments reveal that the model efficiently and effectively allocates container transport requests and can find close to optimal solution in reasonable time for small and medium size problems. The results also suggest the existence of a threshold strongly related to the ratio of the fleet capacity over the number of requests where the fleet is utilised most effectively.

Internet of things-based urban waste management system for smart cities using a Cuckoo Search Algorithm

Waste management is one of the crucial issues in the creation of smart cities. Because of population growth, keeping urban areas clean is a challenge. The Internet of things (IoT) has played a vital role in urban computing because it facilitates the collection, integration, and processing of various types of information. Thus, the aim of this research is to develop an Internet of Things-Based Urban Waste Management System. IoT devices hav been used to monitor human activity and to support waste management. Information about a city was collected and processed in a cuckoo search-optimized long short-term recurrent neural network. The network facilitated the analysis of the waste type, truck size, and waste source. This information alerted the waste management centers so that the appropriate actions could be taken. The efficiency of this IoT-based waste management process was evaluated through an experimental analysis. The system was found to ensure that the bins were processed on a priority basis with minimum error (0.16) and maximum accuracy (98.4%) in the minimum amount of time (15 min).

The influence of gross vehicle weight (GVW) and transport distance on timber trucking performance indicators – Discrete event simulation case study in Central Finland

ABSTRACT Today, timber trucks of gross vehicle weight (GVW) up to 76 tonnes are allowed to operate on Finnish roads from roadside landings to mills. Reducing trucking costs and exhaust gas emissions have been the dominant reasons for the increased GVWs of timber trucks. A discrete-event simulation (DES) method was used to compare the impact of the truck and payload size, trucking distance, and timber assortment lengths on trucking performance indicators (e.g., productivity, energy efficiency, and costs of trucking) in the procurement area of a case logistic company operating in Central Finland. The studied truck sizes were 68, 76 and 84 t, of which the 76-t trucks dominate timber trucking in Finland. Over a transport distance of approx. 105 km with an average assortment length of 4.2 m, 76-t trucks had 9% higher and 12% lower productivity (m3/100 km), 1% lower and 4% higher fuel consumption (l/m3) and 4% lower and 6% higher trucking cost (€/m3) compared to 68- and 84-tonner options, respectively. The improvement in regards to previous indicators was clearly bigger for the 76-tonner than the 68-tonner if the trucked wood assortments were lengthened to 5.0 m. The differences in cost and fuel efficiency as well as annual trucking volumes were increased as a function of the trucking distance, when comparing the truck configurations with different GVWs and payloads. To conclude, the tendency of the size increase in GVWs in timber trucking in Finland can be justified in light of the study results.

A Localized Fire Model for Predicting the Surface Temperature of Box Girder Bridges Subjected to Tanker Truck Fire

The quantification of thermal action is important to the analysis of structural-fire performance of bridges. This study evaluates the parameters for the localized fire model adopted in SFPE Handbook for application to the fire scenario of a tanker truck burning beneath a bridge. Modification is applied first to the flame length and then to the distribution of gauge heat flux using the simulation results of various fire models established in Fire Dynamics Simulator considering parameters, including the sectional dimensions of bridge, bridge headroom, truck size and heat release rate. Spatially varied gauge heat flux or adiabatic surface temperature of the bridge can be predicted with this fire model. Implementation of this modified fire model in structural-fire analysis is illustrated with a sequentially coupled thermo-mechanical modelling of a post-tensioned segmental concrete box girder bridge exposed to tanker truck fire. The adiabatic surface temperature calculated from the modified fire model is applied as thermal boundary to the bridge. Simulation results show that, although the global structural responses are seldom influenced by fire, localized damage in concrete and tendon may result. The prestress in tendons near mid-span may be reduced even after the bridge is cooled down to ambient temperature, which may adversely affect its load-carrying capacity. The damage to concrete may also induce localized separation between adjacent segments, possibly affecting the durability of tendons.

动态无接触的货车尺寸测量方法

动态无接触的货车尺寸测量方法

On-board measurement of emissions from freight trucks in urban arterials: Effect of operating conditions, emission standards, and truck size

Diesel trucks contribute significantly to emissions leading to deterioration in urban air quality. Many recent studies have attempted to quantify real-world emissions from trucks in cities. However, studies on real-world emission from trucks in India are scarce. In this study, we measured real-world emissions of gaseous pollutants (CO, HC, and NO) from twenty trucks of different sizes and emission standards. The trucks were classified into three categories (light-duty diesel trucks (LDDTs), medium-duty diesel trucks (MDDTs), and heavy-duty diesel trucks (HDDTs)) based on their gross vehicle weight (GVW). The tested trucks conformed to Bharat Stage (BS) II, BS III, and BS IV emission standards. A vehicle specific power (VSP) based approach was adopted to model the relationship between vehicle activity and emissions. In addition, real-world emission factors of CO, HC, and NO for all the truck types were determined and compared based on their emission standard. Considerable reductions in emission factors were observed from lower to higher emission control standards for all the pollutants. The CO, HC and NO emission factors from the BS II standard LDDTs were 8.05 g/km, 0.86 g/km, and 8.04 g/km, respectively. The CO emission factor decreased by 29% and 65% respectively, for LDDTs and MDDTs with improved emission standards. The HC emissions (g/km) reduction from BS II to BS III for LDDTs and HDDTs were 49% and 8%, respectively. In the case of MDDTs, HC emission factor reduced by 16% from BS II to BS IV. On comparing with ARAI emission standards, we found that the emission factors of the trucks with GVW less than 3500 kg were higher for all the pollutants. In the case of trucks with GVW greater than 3500 kg, the CO emission factor for BS II and BS III complying trucks were higher than standard values while HC emission factors were lower than the standard values. Further, the emission factors of CO and NO from BS IV standard trucks were higher than the standard values. Moreover, emission factor values from our study were higher than that reported in the literature. Although India aims to adopt BS VI emission standards by 2020, phasing out older vehicles will be the key to mitigate emissions from diesel vehicles.

Estimating Incident Duration Considering the Unobserved Heterogeneity of Risk Factors for Trucks Transporting HAZMAT on Expressways

Traffic accidents involving vehicles transporting hazardous materials (HAZMAT) on expressways not only delay traffic flow but can also cause large-scale casualties and socio-economic losses. Therefore, rapid response to and prevention of these accidents is important to minimize such loss. To ensure more efficient accident response, this study applied a random parameter hazard-based Weibull modeling approach to measure the relationship between crash characteristics and accident duration for trucks transporting HAZMAT. The study focuses on finding the key factors that have an impact on the accident duration of these vehicles as well as a statistical method to estimate the accident duration. The analysis is based on raw crash data from 2007 to 2017, obtained from the Korea Expressway Corporation, of crashes that involved HAZMAT trucks. The study found that crashes occurring during peak times of the day; crashes occurring on segments at the mainline, ramp, and roadways with a guardrail; and the number of vehicles involved in a crash, result in random parameters. In addition, the weather, season, crash severity, truck size, crash location, type of accident report, roadside features (e.g., guardrails), and status after a crash, can be used to explain the accident duration. The random parameters hazard-based model is found to have a better fit than a fixed model since it is able to capture the unobserved heterogeneity in the hazard function.

Economic and environmental models for cold products with time varying demand

In response to the rising public concerns on environmental issues and the recently imposed governmental legislations and directives in this regard, companies nowadays ought to constantly adopt sustainable practices in their day-to-day operations. To that end, this paper seeks to optimize the replenishment strategy for a firm (e.g. retailer), who is facing a discrete time-varying demand for a temperature-sensitive (cold) product, while taking into account carbon emissions resulting from transportation and storage activities. In essence, the problem tackled herein is a variant of the classical dynamic lot-sizing problem (DLSP) for cold products with limited shelf life. To better resemble reality, we assume a stepwise cost function that is proportional to the number of fixed-capacity refrigerated trucks and cold stores used. We present three mathematical models, with the first being a cost minimization model, the second a carbon footprint minimization model, and the third a hybrid model that utilizes the carbon tax policy to jointly optimize both economic and environmental measures. We identify several structural properties of the optimal solution to the three models leading to the development of an exact solution algorithm based on the dynamic programming approach. The results of the computational experiments suggest that accounting for environmental aspects induces a change in the cost minimizing lot-sizing policy, resulting in a minor increase in the operational cost where the savings in the CO2 related costs outweigh this minor increase. The two-way sensitivity analysis, conducted under randomized values of the demand, truck sizes, and cold stores capacities, indicates that higher savings in cost and carbon reductions are realized for increasing values of the carbon tax rate. Furthermore, on average, more cost savings and lower carbon emissions are also achieved when the values of the shelf life, truck size, and cold store capacity are increased.

Optimising truckload operations in third-party logistics: A carbon footprint perspective in volatile supply chain

With government and customers driving third-party logistics seeking opportunities to improve operation efficiencies and mitigating carbon emissions in the supply chain, third-party logistics firms have been striving to improve their truckload utilization and vehicle routing operations, especially in emission-regulated countries and volatile business environment. Traditional literature has focused on either truckload utilization or vehicle routing operations but seldom integrating carbon emission mitigation in their daily trucking operations. This paper delineates the operation review of three third-party logistics firms in Hong Kong and develops an organisation-based carbon emission measurement metrics for logistics operations. The truckload utilization and routing performance are reviewed, followed by a correlation analysis on the truckload utilization against truck capacity, loading volume, fuel consumption, truck size, travelling distances and number of destinations. An integrated carbon-driven multi-criteria model is developed achieving carbon emission reduction initiatives, time and distance cost penalty, minimizing number of trucks, and improving truck utilization. The integrated mathematical model has been developed into a simulation system which has been tested with evaluated results. The mathematical model is enhanced for the set of cargo items and vehicle fleet with additional factors of arrival time slots and weight. The model assists traffic planners to reduce cargo planning time and optimize the truckload operations. Further development will be focused on adding the dimensions of pallet loading operations and exception rules for customer loading requirements.