Ensuring the accuracy of the estimated time of arrival (ETA) information for ships approaching ports and inland terminals is increasingly critical today. Waterway transportation plays a vital role in freight transportation and has a significant ecological impact. Improving the accuracy of ETA predictions can enhance the reliability of inland waterway shipping, increasing the acceptance of this eco-friendly mode of transportation. This study compares the industry-standard approach for predicting the ETA based on average travel times with a neural network (NN) trained using real-world historical data. This study generates and trains two NN models using historical ship position data. These models are then assessed and contrasted with the conventional method of calculating average travel times for two specific areas in the Netherlands and Germany. The results indicate by using specific input features, the quality of ETA predictions can improve by an average of 20.6% for short trips, 4.8% for medium-length trips, and 13.4% for long-haul journeys when compared to the average calculation.

The rising number of loading devices called swap bodies in road transport has created new opportunities for carriers and novel challenges for researchers in vehicle routing synchronization. Nevertheless, there are few vehicle routing models in literature that integrate swap bodies for combined road transport and there is no known best practice in the industry to handle these opportunities. In this paper we aim to examine to which extent Information Systems and Operations Research can help to provide solutions for this new planning problem and evaluate the potential of vehicle routing under consideration of swap bodies regarding a real world case of a major carrier. We develop a routing heuristic and prototype software to support routing considering loading options with swap bodies. The software is tested with real world data from the cooperating industry partner. We observe significant reductions in costs, total driven kilometers and operating times. Thus, we demonstrate the importance to integrate swap bodies in vehicle routing models for road transport. Furthermore, the developed software can be a basis for future work on exact planning models.