Connected and automated vehicles (CAVs) are emerging technologies expected to bring important environmental, social, and economic improvements in transportation systems. Given their implications in terms of air quality and sustainable and safer movement of goods, heavy‐duty trucks (HDTs), carrying the majority of U.S. freight, are considered an ideal domain for the application of CAV technology. An input–output (IO) model is developed based on the Eora database—a detailed IO database that consists of national IO tables, covering almost the entire global economy. Using the Eora‐based IO model, this study quantifies and assesses the environmental, economic, and social impacts of automated diesel and battery electric HDTs based on 20 macro‐level indicators. The life cycle sustainability performances of these HDTs are then compared to that of a conventional diesel HDT. The study finds an automated diesel HDT to cause 18% more fatalities than an automated electric HDT. The global warming potential (GWP) of automated diesel HDTs is estimated to be 4.7 thousand metric tons CO2‐eq. higher than that of automated electric HDTs. The health impact costs resulting from an automated diesel HDT are two times higher than that of an automated electric HDT. Overall, the results also show that automation brings important improvements to the selected sustainability indicators of HDTs such as global warming potential, life cycle cost, GDP, decrease in import, and increase in income. The findings also show that there are significant trade‐offs particularly between mineral and fossil resource losses and environmental gains, which are likely to complicate decision‐making processes regarding the further development and commercialization of the technology.

Life cycle sustainability assessment of autonomous heavy-duty trucks

As the demand for transport is growing, more and more attention is being paid to its quality aspects. These include, among other things, efficiency, safety, and a continuous effort to reduce external costs. That is why the transport policies of the EU countries and individual regions are increasingly addressing the issue of sustainable transport development. Multimodal transport, which is seen as a key element to effectively counterbalance the dominant role of vehicle transport in the economic progress of the European Community, plays an important role in these programmes. For consistency and continuity of freight flows, cooperation between neighbouring countries and regions is essential. The future of multimodal freight transport within the cross-border area of Poland, Czech Republic and Slovakia is not as evident as the transport policies imply. Therefore, the purpose of the paper is to identify a set of factors determining the development of multimodal transport within the cross-border area of TRITIA (The European Grouping of Territorial Cooperation of the four regional governments of Moravian-Silesian Region (CZ), Opole Voivodeship (PL), Silesian Voivodeship (PL) and Žilina Self-governing Region (SK)) and to develop four scenarios, the execution of which in the 2030 perspective depends on the implementation of cross-border infrastructure and organisational projects and the increasing level of cooperation in the field of multimodal transport. The article contains the methodology for developing scenarios of multimodal freight transport development. The research showed that initiating activities targeted at the development of multimodal transport within the cross-border area requires the involvement of all participants in the process, i.e., all countries (Poland, Czech Republic and Slovakia), along with many different stakeholders. The future development of multimodal transport as provided for in the scenarios is not linearly correlated with the increase in cooperation and the number of implemented infrastructure and organisational projects. It is vital for future research to define the role of stakeholders both in terms of cooperation and collaboration development.

Scenarios for the Development of Multimodal Transport in the TRITIA Cross-Border Area

Agent-based simulation (ABS) appears to be a suitable tool for research and application in the field of city logistics. In this paper, an attempt was made to classify the current literature on ABS in urban freight distribution following some homogeneity criteria. A set of six criteria was adopted and relevant papers were classified accordingly. It emerges that agent-based simulation models are suitable for use in simulating urban freight distribution, identifying a set of agents (at most, one agent per stakeholder) that operate to achieve their objectives, following rules, interacting, and learning from experience. However, this approach is still to be fully developed: the applications provided in the literature are only for test cases, refer to small study areas and a limited number of agents.

Agent-Based Simulation of urban goods distribution: a literature review

In supply chain management, fast and accurate decisions in supplier selection and order quantity allocation have a strong influence on the company's profitability and the total cost of finished products. In this paper, a novel and non-linear model is proposed for solving the supplier selection and order quantity allocation problem. The model is introduced for minimizing the total cost per time unit, considering ordering, purchasing, inventory, and transportation cost with freight rate discounts. Perfect rate and capacity constraints are also considered in the model. Since metaheuristic algorithms have been successfully applied in supplier selection, and due to the non-linearity of the proposed model, particle swarm optimization (PSO), genetic algorithm (GA), and differential evolution (DE), are implemented as optimizing solvers instead of analytical methods. The model is tested by solving a reference model using PSO, GA, and DE. The performance is evaluated by comparing the solution to the problem against other solutions reported in the literature. Experimental results prove the effectiveness of the proposed model, and demonstrate that metaheuristic algorithms can find lower-cost solutions in less time than analytical methods.

Inventory replenishment decision model for the supplier selection problem using metaheuristic algorithms

Possibilities of using Incoterms clauses in a country logistics performance assessment and benchmarking

The advanced internationalisation of markets and production processes continuously adds to the complexity of supply chains. At the same time improving the sustainability of the related international freight transport processes and optimising their efficiency is becoming a topic of central relevance. International freight transport models are an important tool to simulate impacts of measures taken to achieve such improvements of transport processes. Yet, the requirements towards international freight transport models are complex: they need to include various modes of transport, they need to cover different industries and their dynamics, they need to consider seasonality of supply and demand of goods, demographic parameters, economic developments, technological developments including their impact on production processes and structures, and many other aspects. Furthermore, international freight transport models need to include freight flows within countries as well as freight flows between the considered countries. This paper discusses the challenges which need to be confronted when developing international freight transport models which are able to correspond to the described complexity of international freight transport. Furthermore, it maps out the most important research gaps which need to be addressed by international freight transport modelling research in order to ensure that the challenges identified are captured within the models developed to improve international freight transport.

Ming Chen

Papers

Challenges and future research needs towards international freight transport modelling