The purpose of this study is to identify the characteristics of freight mode choices made by shippers and carriers with the introduction of a new freight transport system. We set an area in which actual freight transport takes place as the analysis scope and performed a survey of the shippers and carriers that transport containers to identify their stated preference (SP) regarding the new freight mode. The SP survey was carried out through an experimental design and this study considered the three factors of transport time, transport cost, and service level. This study compared and analyzed the models by distance using an individual behavior model. The results of estimating the model showed that the explanatory power of the model classified by distance and the individual parameters have statistical significance. The hit ratio was also high, which confirms that the model was estimated properly. In addition, the range of elasticity and the value of travel time analyzed using the model were evaluated to be appropriate compared to previous studies. The findings of the elasticity analysis show that strategies for reducing the transport cost are effective to increase the demand for the new transport mode. The value of travel time of freight transport was found to be higher than the current value generally applied in Korea. Considering that the value of travel time currently used is based on road freight transport, further research is required to apply a new value of travel time that reflects the characteristics of the new transport mode in the future.

One of the preliminary requirements for freight transportation modeling is to understand the factors that affect the freight volume. In this study, we attempt to investigate the relationship between various factors and freight volumes using a structural equation model. From a review of the existing literature, we formulate our research hypotheses and identify the factors. We propose a research model describing the relationship between the factors and freight volume. Finally, we estimate a structural equation model using the survey data of 97 private steel companies in Korea. From the developed models, we find that all the three characteristics (i.e., location, agglomeration, and other) have positive effects on steel freight volume. Location and other characteristics have a more significant effect than agglomeration characteristics because these characteristics have a direct effect, whereas agglomeration characteristics have an indirect effect.

Finished vehicles are loaded onto and discharged from roll-on/roll-off (Ro-Ro) vessels by drivers who choose routes from experience. Automated handling requires continuous routes between storage-yard parking positions and on-deck stowage positions in both directions. This study represents the storage yard, the quay connection and the vessel decks as a single directed network built from OpenStreetMap (OSM) data. The route cost adds fixed penalties for turns, level transitions and ramp use to the travel time, which is reported separately. Because these penalties dominate the route cost, a lower bound on the level-transition penalties is incorporated into the A* heuristic, and routes are computed by bidirectional A* with an average potential and a sum-based stopping rule. On the Gwangyang Port testbed, the method returned the optimal route for all 15,000 origin–destination pairs and reduced the search effort by about one quarter relative to Dijkstra’s algorithm. Unidirectional A* with the same bound achieved a similar reduction, indicating that the gain derives from the heuristic rather than from the bidirectional structure. Compared with shortest-distance routes, the cost-based routes contained markedly fewer left turns at almost no additional travel time and remained stable over a wide range of penalty values.