Logistics activities are an important source of energy consumption and environmental issues. Research conclusions and practical experience show that promoting the development of container multimodal transport is an effective way to reduce the level of carbon footprint. The key to influencing the development of container multimodal transport lies in the cooperation of all participants and links (modes of transport, transport businesses). Evaluating the synergy degree is a key step in this development process. This paper takes the whole process of container multimodal transportation as the research perspective, analyzes the operation process, and treats the process as a production system composed of four subsystems: facilities and equipment, organizational management, business operations, and information interactions. Through in-depth interviews and an analysis of the academic literature and policy documents, we establish a synergy degree evaluation index system and measurement model of container multimodal transport based on synergy theory and case studies. The research results are consistent with the actual situation. From 2015 to 2018, the synergy of container multimodal transport system of China's G port developed slowly, but generally moved in a more orderly direction.Sustainability 2020, 12, 1487 2 of 26 of cargo transportation; by 2020, the volume of port railway collection and distribution and container multimodal transport will increase significantly. Multimodal container operation is an important economic activity and plays a vital role in transportation and low-carbon development.In actual operation, logistics companies tend to choose a single mode of transport when conditions permit. The reason is that the participants and links (modes of transport, transport businesses) are not coordinated, due to the following: (1) There is a lack of effective connection between infrastructures. For example, many ports have no dedicated railway lines, which greatly increases transportation costs.(2) There is no uniform standard for equipment. The size standards of road trucks are different from the standards of railway loading units, and the conversion is very troublesome, requiring loading and unloading, resulting in increased costs. (3) The devices are not completely intelligent. The development of special railway wagons, railway dual-use trailers, and river-sea combined carriers is lagging, and the connection efficiency is low. (4) There is a lack of multimodal transport integration service providers. Due to the lack of a large logistics network platform and effective deployment, small transportation companies are blind, and there is often repeated transportation and wasting of resources. (5) Information docking and sharing are difficult. There is no uniform information exchange standard and format between enterprises, and each enterprise is an information island. In addition, there is a lack of effective connection between multiple modes of transport, and the costs of short barges, reloading, loading and unloading...
This paper presents an improved model for improving headway-based bus route service reliability at bus stops using real-time preventive operation control, taking into account dynamic interaction among random passenger demand, stochastic driving conditions of route segments, and vehicle load capacity constraint. In this model, the real-time information of passenger demand and vehicle operation is involved to predict the imminent unacceptable headway deviation, in the case of which some in-time preventive control strategies are deployed according to the given control rules. As a case study, a single fixed bus route with high-frequency services was simulated and different scenarios of real-time preventive operation control were performed. Headway adherence and average passenger wait time were used to measure bus service reliability. The results show that the improved model is closer to the real bus route service, and using real-time information to predict potential service unreliability and trigger in-time preventive control can reduce bus bunching and avoid big gap.
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