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Freight logistics and shipment routing
Published in Dong-Ping Song, Container Logistics and Maritime Transport, 2021
According to the European Conference of Ministers of Transport, intermodal transport is defined as the movement of goods in a single loading unit through two or more successive modes of transport without handling the goods themselves in changing mode during transportation. Multimodal transport is defined as the transportation of freight by using at least two different modes of transport on the basis of a single contract from one place located in a country, in which the multimodal transport operator takes charge of the goods, to a place designated for delivery in a different country (UNCTAD 2003). Although the need for using a single loading unit for freight transportation is not highlighted in the definition of multimodal transport, this is often the case for multimodal transport.
Short sea shipping in Latin America
Published in Tiago A. Santos, C. Guedes Soares, Short Sea Shipping in the Age of Sustainable Development and Information Technology, 2020
A single transport contract characterizes the multimodal transport operation, in which two or more modes of transport are used from the origin to the destination. This task is performed under the sole responsibility of an OTM. This operator is a company contracted to carry out the multimodal transport of the cargo from origin to destination, either by own means or through third parties (Moura and Botter, 2017). In addition to the transport itself, multimodal cargo transport includes the services of collection, consolidation, cargo handling and storage, deconsolidation and delivery, in short, all the essential steps to complete the task. It is essential that the services provided are frequent and reliable to operate in potential markets. It is also imperative to minimize intermodal costs and have a team vision, control operations, integrated systems, an intermodal structure (own or outsourced), intermodal terminals and integrated decision-making.
Introduction
Published in Jason Monios, Rickard Bergqvist, Intermodal Freight Transport and Logistics, 2017
Jason Monios, Rickard Bergqvist
Multimodal transport refers to the use of more than one mode in a transport chain (e.g. road and water), while intermodal refers specifically to a transport movement in which the goods remain within the same loading unit. While wooden boxes had been utilised since the early days of rail, it was not until strong metal containers were developed that true intermodal transport emerged. The efficiencies and hence cost reductions of eliminating excessive handling by keeping the goods within the same unit were demonstrated in the first trials of a container vessel by Malcom McLean in 1956.1 The initial container revolution, therefore, took place in ports, as the stevedoring industry was transformed over a few decades from a labour-intensive operation to an increasingly automated activity. Vessels once spent weeks in port being unloaded manually by teams of workers; they can now be discharged of thousands of containers in a matter of hours by large cranes, with the boxes being repositioned in the stacks by automatic guided vehicles. This in turn means that ships can spend a much higher proportion of their time at sea, becoming far more profitable.
The coal origin-destination matrix analysis and multimodal transportation cost modelling in the Yangtze River region, China
Published in Systems Science & Control Engineering, 2018
A multimodal transport network consists of connection infrastructures, such as terminals or logistics platforms, where goods are loaded, unloaded, transshipped or processed in different ways. To analyse transport operations on the network, costs or weights must be attached to these geographical links of the transported goods as well as the connection points for handling the goods. However, most of these infrastructures can be used in different ways and at different costs. For example, boats of different sizes and operating costs can use the same waterway, and at a terminal, a truck’s load can be transshipped on a train or a ship bundled with some others on a boat or simply unloaded as it reached its destination. Normally, the costs of these alternative operations should be different. The geographic network should provide the detailed transport operations where the same infrastructure is used in different ways.
Modeling the competitiveness of a bike-sharing system using bicycle GPS and transit smartcard data
Published in Transportation Letters, 2022
Christian Kapuku, Seung-Young Kho, Dong-Kyu Kim, Shin-Hyung Cho
A well-integrated multimodal urban transport system is the key to sustainable urban mobility due to its great potential for overcoming urban issues related to high automobile demand, such as air pollution, high demand for parking space, and traffic congestion, as a result of the shift from automobile to multimodal transport trips. To achieve this sustainable mobility, however, planners and policymakers must provide multimodal transport systems that are more competitive than automobiles, both at the planning level, by supplying infrastructure and systems that optimally integrate several shared transport modes, such as buses, trains, taxis, bicycles, and walking (Mead, Johnson, and Rose 2016; Weliwitiya, Rose, and Johnson 2019), and at the operational level, using systems such as Intelligent Transport Systems (ITS), or Mobility as service (MaaS) to provide the best intermodal transport alternatives to travelers (Hietanen 2014; MaaS Global 2019; Ambrosino et al. 2016; Giesecke, Surakka, and Hakonen 2016). Therefore, how well different transport modes are integrated together to provide a better or comparable level of services than private vehicles are the key to a successful sustainable urban mobility. However, this integration has always been challenging, especially between motorized modes (e.g. buses, subways, trains, taxis) and non-motorized modes (e.g. walking and biking) (Mead, Johnson, and Rose 2016; Weliwitiya, Rose, and Johnson 2019). Public bike-sharing systems, for instance, are among the emerging active transport and shared mobility options that are being introduced in many cities. Despite the advantages of these systems, the shift from motorized modes to cycling has always been a challenge.
Development of computer vision informed container crane operator alarm methods
Published in Transportmetrica A: Transport Science, 2022
Ran Yan, Xuecheng Tian, Shuaian Wang, Chuansheng Peng
Multimodal transport plays a key role in global modern logistics, and it is facilitated by standard shipping containers which can be smoothly transferred among different transportation modes. When container ships arrive at the container terminal, containers are unloaded from the vessel one by one to trucks. This task is accomplished by crane operators, whose job is to load and unload containers to and from vessels by operating container cranes. The working environment of crane operators can be harsh due to the prolonged working period, repetitive working contents, and the restricted working area. Consequently, they are prone to fatigue and discomfort, and the probability of unloading a wrong container from a vessel is expected to increase with the progress of a work shift. To reduce the extra work and expected annual costs brought about by the issue, this study innovatively uses the color of shipping containers as an indicator of alerting crane operators for unloading a wrong container. We consider eight widely-used container colors, namely maroon, magenta, orange, light yellow, dark yellow, light blue, dark blue, and green, and the container color is predicted by a popular computer vision library called OpenCV. After obtaining the distribution of the prediction accuracy of the colors of concern, three methods are developed to address the container crane operator alarm problem. To be more specific, method 0 is a benchmark where no alarm is performed. Method 1 alerts the crane operator if the predicted container color is inconsistent with the color of the container that should be unloaded. Method 2 is based on a decision problem to decide whether to alert the crane operator with the aim to minimise the expected annual costs.