Smart Transportation

Abstract

As mobile technologies become more widely adopted, many countries are gradually transforming their transport policies into smart transportation innovation policies. This study explores an evaluation model for such smart transportation innovation policies. First, we studied texts related to smart transportation innovation policies of various countries, published in numerous journal articles, magazines and newspapers, and online media. We identified six major dimensions and 32 criteria within the policies, the six major dimensions being Connected and Automated Vehicles (CAVs), smart traffic safety, transportation management systems, intelligent-based transportation technology, transportation resource integration and sharing, and traffic data collection. We combined two research methods, Analytic Hierarchy Process (AHP) and Decision-Making Trial and Evaluation Laboratory (DEMATEL), to analyze the weighted values, correlation, and degree of influence between the different dimensions and criteria of smart transportation innovation policies. Through the results of the research, we were able to formulate a smart transportation innovation policy that prioritizes short-term and long-term development. We designed two questionnaires with AHP and DEMATEL, which were given to 15 experts from the government, academia, industry, and foundations, with backgrounds in traffic, transportation, geography, environmental engineering, artificial intelligent (AI), Internet of Things (IoT), etc. The results showed that among the six major dimensions of smart transportation innovation policies, smart traffic safety is considered the most important in the short term, while traffic data collection is considered the most important in the long term, followed by CAV, then transportation resource integration and sharing. Therefore, this study can serve as an important reference for an evaluation model of smart transportation innovation policies.