Truck scheduling for ground to air connectivity

A critical link in the overnight package business is the on-time arrival of trucks at airport terminals. Truck delays can delay the package sorting and transfer process, which can in turn delay aircraft departures from the local terminal, as well as aircraft departures from hub terminals that depend on timely aircraft arrivals. This paper models the airport terminal as a queueing process with random bulk arrivals. Predictions are provided for expectation, and standard deviation, of arrived work. From these predictions performance measures are developed for sort end time and sort starvation. Particular attention is given to scheduling the start time for the sorting process, to balance a trade-off between maximizing sort productivity and minimizing the end time of the sort. The methods are being implemented as a web-based scheduling tool.     

Exploring the relationship between truck load capacity and traffic accidents in the European Union

Applying econometric techniques to EU28 panel data and controlling for explanatory variables such as road types, we find that increased truck load capacity does not necessarily aggravate road traffic safety. Specifically, heavy trucks do not seem to be linked with greater numbers of traffic fatalities/accidents, medium trucks appear to be the worst performers in terms of fatalities, and light trucks seem to be the worst for accidents. In summary, our results clarify the complex relationship between truck load capacity and road safety, pointing to the existence of a negative correlation for accidents per capita and an inverse U-shaped curve for fatalities per capita.     

Assessment of out-of-state truck activity in California

The continued growth of interstate freight trucking brings with it the potential for inaccuracies in official government statistics on trucks’ road use and pollutant emission contributions. State government agency emission estimates for states within the US commonly rely on in-state truck and fuel use records. Consequently, these records can incompletely reflect overall truck activity and emissions by neglecting the trucks that are registered and/or are fueled out of state. An in-person interview survey of 433 heavy-duty truck drivers was conducted at select points of entry into California to better understand the contribution of out-of-state trucks, their fuel use, and their emissions in California. The results indicate that non-California-registered trucks and non-California-diesel fuel make up approximately 30% of Class 8 heavy-duty truck mileage on California roads. Non-California-registered-truck mileage is disproportionately concentrated in four California air basins that have significant air quality issues.     

Scheduling commercial vehicle queues at a Canada-US border crossing

Using the context of queue operations at a major Canada-US commercial border crossing for truck-borne trade flows, we report on a computer simulation study to predict the likely impacts of smoothing those flows. We quantify the operational and resource efficiencies of smoothing for trans-border trucking companies and their trans-border supply chain partners as well as for government authorities with regulatory jurisdiction at border crossings. Our study’s major conclusion is that smoothing can achieve queue performance levels that, in the absence of smoothing, would require significant investment in truck processing capacity at border crossings.     

Modeling the mixed storage strategy for quay crane double cycling in container terminals

A mixed storage strategy was proposed to improve the efficiency of yard operations and horizontal transportation to corporate with quay crane double cycling. The effects of the mixed storage strategy on terminal operations, including truck travel distance, yard crane operations and the number of required trucks, were analyzed. An approach based on cycle-time models, the queuing theory was proposed to evaluate the performances from long-term run. Results show using the mixed storage strategy, the truck travel distance can be decreased and the number of required trucks and yard crane’s operation time can be reduced by 16% and 26% respectively.     

Reducing truck emissions at container terminals in a low carbon economy: Proposal of a queueing-based bi-objective model for optimizing truck arrival pattern

This study proposes a methodology to optimize truck arrival patterns to reduce emissions from idling truck engines at marine container terminals. A bi-objective model is developed minimizing both truck waiting times and truck arrival pattern change. The truck waiting time is estimated via a queueing network. Based on the waiting time, truck idling emissions are estimated. The proposed methodology is evaluated with a case study, where truck arrival rates vary over time. We propose a Genetic Algorithm based heuristic to solve the resulting problem. Result shows that, a small shift of truck arrivals can significantly reduce truck emissions, especially at the gate.     

The relative importance of factors that influence the break-even distance of intermodal freight transport systems

The break-even distance of an intermodal freight system is a crucial piece of information for shippers as they decide whether to choose a specific freight transport system. It is also important for policy makers who want to demonstrate to shippers that the intermodal system is substantially more beneficial over a certain distance and encourage shippers to use it. However, the break-even distance is highly dependent on market situations. In other words, it is not possible to estimate the definitive break-even distance that is generally applicable. To date, the literature has addressed factors, including costs and distances, that impact the break-even distance without considering the relative importance of each of these factors. This study attempts to address this gap in knowledge by evaluating the relative importance of geometric and cost factors. The former includes drayage distances (i.e., pre- and post-haulage by trucks), truck-only distance, rail distance, the shape of the market area, and the terminal location, while the latter includes the drayage truck rate, the long-distance truck rate, the rail rate, and the terminal handling rate. Finally, by developing a Monte Carlo-based simulation model, the relative importance can be evaluated. The key finding is that the geometric factors and terminal handling costs are not more significant than the transport costs (i.e., rail costs and long-distance trucking costs) in general. Specifically, to shorten the break-even distance, either reducing the rail rate or increasing the truck rate is the most effective strategy. A 1% change in these factors is almost seven times, three times, and twice as effective as a 1% change in the handling costs at terminals, rail distance, and drayage cost, respectively. Furthermore, neither the oval-shaped market area nor a terminal relocation attracts customers to intermodal systems in general. When two options are combined, the synergic effect is significant.     

A heuristic algorithm for yard truck scheduling and storage allocation problems

The yard truck scheduling and the storage allocation are two important decision problems affecting the efficiency of container terminal operations. This paper proposes a novel approach that integrates these two problems into a whole. The objective is to minimize the weighted sum of total delay of requests and the total travel time of yard trucks. Due to the intractability of the proposed problem, a hybrid insertion algorithm is designed for effective problem solutions. Computational experiments are conducted to examine the key factors of the problem and the performance of the proposed heuristic algorithm.     

Truck movement across the Canada–US border: The effects of 9/11 and other factors

The objective of this study is to isolate the effects of the terrorist attacks of 9/11 and the subsequent stringent border security regime on the levels of truck movement across the Canada–US border. A time series analysis, within an econometric system that rendered stationarity and used the seemingly unrelated regression (SUR) estimator, was performed to model these movements. The analysis represents a natural experiment on the variability of cross-border truck movements in the aftermath of 9/11. Annual truck crossing data over the period 1972–2011, disaggregated by the country of registration (US and Canada) and Canadian jurisdictions (provinces) were used in the analysis. The results indicate that in general, 9/11 have had a negative effect on the cross-border movement of Canadian and US trucks, but the impacts were more pronounced in the case of the US trucks. Other interesting results include an increase in the number of US trucks during the period that followed the last US financial crisis. The results also illustrate the importance of GDP in explaining the observed truck movements across the Canada–US border.     

Scheduling trucks in cross-docking systems: A robust meta-heuristics approach

In a cross-docking system, trucks must be scheduled to minimize the total flow time of the system. This problem is NP-hard, and this study proposes two hybrid meta-heuristics—hybrid simulated annealing and hybrid variable neighborhood search—to solve it by achieving the best sequence of truck pairs. The Taguchi method serves to reveal the best robustness of these algorithms. To demonstrate the effectiveness of the proposed methods, especially for large-sized problems, this study solves various test problems, and the computational results clearly reveal that the proposed methods outperform previous approaches.     

A time-period choice model for road freight transport in Flanders based on stated preference data

This paper presents one of the first models explaining the choice of time-period in road freight transport. Policies that would shift some fraction of the trucks from peak to earlier and later periods will contribute to the reduction of congestion. Therefore there is an increasing interest in modelling the time-period sensitivity of road freight transport to changes in travel time and cost by period. The model developed here is based on a stated preference survey amongst receivers of goods in Flanders and was implemented in the strategic freight transport model of the Flemish authorities.     

Dispatching trucks for drayage operations

We propose a novel model for dispatching trucks given the constraints and sources of uncertainty that arise in drayage operations. The proposed model is designed to minimize the expected cost and is generally applicable to cases including different distributions of random parameters. Numerical examples illustrate this robustness of the model, as well as the potential for reducing the drayage cost by increasing the available storage capacity and permitted number of terminal truck entries. Mathematical results derived within this paper (e.g. expected dwell time) can be used more generally in analyzing transfers in transportation networks under stochastic conditions.     

The geography of freight-related accidents in the era of E-commerce: Evidence from the Los Angeles metropolitan area

Due to the burgeoning demand for freight movement in the era of e-commerce, freight related road safety threats have been growing in both urban and suburban areas, despite the improved general traffic safety over the past decades. The empirical evidence on how freight trucks related crashes are distributed across neighborhoods and correlated to spatially varying factors is, however, highly limited. This article uses data from the Los Angeles region in 2018 to analyze the spatial patterns of freight trucks related traffic crashes and examines the major factors that contribute to those patterns using spatial econometric models. Maps show that freight trucks related crashes are highly associated with major freight generators but less clustered than the overall traffic crashes. Results from the spatial Durbin model indicate that access to freight generators, economic attributes, land uses, road infrastructure, and road network variables all contribute to the spatial distribution of freight trucks related crashes. The findings could help transport planners understand the dynamics of freight trucks related traffic safety and develop operational measures for mitigating the impacts of growing goods movement on local communities.     

The integrated yard truck and yard crane scheduling problem: Benders’ decomposition-based methods

This paper proposes a novel integrated model for yard truck and yard crane scheduling problems for loading operations in container terminal. The problem is formulated as a mixed-integer programming model. Due to the computational intractability, two efficient solution methods, based on Benders’ decomposition, are developed for problem solution; namely, the general Benders’ cut-based method and the combinatorial Benders’ cut-based method. Computational experiments are conducted to evaluate the effectiveness of the proposed solution methods.     

Studying border crossing choice behavior of trucks moving between Ontario,Canada and the United States

The effectiveness of trade between Canada and US relies heavily on land borders. This study uses GPS data to explore the movement of trucks across four major border crossings in southwestern and southeastern parts of the Canadian province of Ontario. Multinomial logit models are estimated to examine the route choice decisions of trucks using the four crossings. While observed crossing time has a significant and negative influence on the observed choices, its impact is generally inelastic. More importantly, the geographic location of truck trip origins and destinations appear to play a more significant role in choosing the border crossing, suggesting that geography is at play when it comes to the choice of a land border. Finally, the results suggest that long-haul trips tend to favor the Ambassador Bridge crossing that connects Windsor, Ontario to Detroit, Michigan.     

Government plans for lorry road-user charging in the UK: a critique and an alternative

The British government was planning to introduce a system of road-user charging for lorries in 2008. In July 2005, it decided to abandon these plans and incorporate the development of a charging scheme for trucks into a future road pricing system for all categories of traffic. This paper examines the objectives of the proposed lorry road-user charging scheme in the UK and argues that the government's plans for LRUC would have been inappropriate. An alternative method of road-user charging for lorries is proposed which would meet the main objectives of LRUC at much lower cost, disruption and risk and act as an interim measure until it is possible, technically and politically, to introduce general road pricing in the UK.     

Development of air pollutant emission factors under real-world truck driving cycle

The truck driving cycle was developed in Thailand using actual speed-time profile from trucks in suburban area. Driving data were separated into micro trips and the representative driving cycle was selected by matching micro trips statistics and target statistics. The Performance Value (PV) was considered for selecting the representative driving cycle. This selected driving cycle was then used as input data for estimating emission factors of 4 air pollutants and 3 greenhouse gases by the International Vehicle Emission (IVE) model. Results were then compared with emission factors developed using the European Transient Cycle (ETC). Additionally, a comparison was made between emission factors calculated in this study and direct measurements of emissions from truck driven on chassis dynamometer under the European driving cycle. Comparison results revealed that CO, NO_x and CO₂ emission factor were about 2.05, 2.24 and 1.78 times lower than those obtained from direct measurements. PM emission factor was about 0.89 times higher than measured data. This study confirms the need to considered actual fleets and characteristics of vehicular sources when calculating their emission rates for further use in development of emission inventory.     

Multilevel modelling of commercial vehicle inter-arrival duration using GPS data

This study uses truck GPS data to study inter-arrival duration, defined as the time between arrivals at a destination of two successive vehicles operated by the same carrier. Destinations were separated into market segments: (1) frequently-visited destinations, (2) regularly-scheduled destinations, and (3) unscheduled destinations, based on visit frequency and regularity. Inter-arrival duration was modelled using multilevel ordered probit and multilevel multinomial logit models. Market segmentation improved modelling results, and multilevel models performed better than single level models. Results showed a wide variation in shipping behavior of commercial establishments and that many firms do not follow consistent shipping schedules.     

Development and application of a dynamic model for road port access and its impacts on port-city relationship indicators

Seaports are major intermodal structures in the global supply chain, where multiple stakeholders search for profitable and resilient maritime lines. Shipowners reduce the distance between the northern and southern hemispheres by connecting hub ports. Hosting a global hub port implies competitive advantages to the municipality. However, operational bottlenecks loosen the port-city relationship. One of the main conflicts in this relation is the land port access, a hard-to-be-mapped, random operation. The traffic flow rise noticed in developed countries' ports and, more recently, in emerging markets, causes congestion and air pollutant emissions in terminal surroundings. Current models for road port access are static, single-window non-synchronized truck appointment systems. As a contribution, this case study develops a dynamic model of road port access. Also, it verifies the effectiveness of its application in the port-city relationship indicators in an emerging market global hub port, the Port of Santos, faced with ports of developed countries, prospecting optimal conditions to its implementation in an environment with significant institutional obstacles.     

The impact of truck arrival information on container terminal rehandling

This paper uses simulation to evaluate the use of truck arrival information to reduce container rehandles during the import container retrieval process by improving terminal operations. A variety of scenarios with different levels of truck information and various container bay configurations are modeled to explore how the information quality and bay configuration affect the magnitude of benefit. The results demonstrate that a complete arrival sequence is not required to substantially reduce rehandles, significant benefit can be obtained under small amounts of information, the benefits grow with the bay size, and that updating information in real time significantly lowers information requirements.