MULTRA provides a forum for high quality, cutting-edge research in transportation science and technology. MULTRA covers all modes - road, rail, air, maritime - and the integration of multimodal transport. Papers concerning multimodal integration or emerging transportation technologies are particularly welcome, as is work focusing on Intelligent Transportation Systems, Smart Transportation, or Big Data, as applied to transport planning, network modelling or traffic safety. MULTRA is an interdisciplinary journal and embraces work from a wide range of disciplines, including, but not limited to, transportation, logistics, economics, operations research, and urban planning. MULTRA publishes papers in two categories: Theory and Methodology: Papers in this category employ mathematical modeling, optimization theory, etc., to develop new concepts and technologies, rather than the refinement of established theories. Empirical Research: Papers in this category can either employ quantitative techniques from statistics, AI, machine learning etc., or qualitative research methods such as one-on-one interviews, focus groups, case study research etc., to obtain new insights into specific aspects of transportation science. Regardless of the category, MULTRA papers are expected to clearly articulate their expected impact on the practice of transportation science.