KOTI - Korea Transport institute

This study proposes a method to predict the change of traffic demand in the future in terms of both macro aspects and regional and demographic-hierarchical characteristics. In order to improve the utilization of traffic policy, based on this we have found and chosen alternatives for customized traffic policies in the future. The changes in economic and social conditions are taken into consideration for aging and single-person households. In addition, as the environment of traffic policy changes, the study has also considered the introduction of autonomous vehicles, improvement of fuel consumption, shared economy of autonomous vehicles, vitalizations of remote work from home, an increase in fuel prices, and the introduction of high-speed trains.
Taking into account all of the changing factors in the future, the study analyzed the changes in traffic demand by region, household, age, and income up to the year 2050.
Specifically, in order to increase the reliability of the model, the study did not only use household travel survey data from 2016, but was also updated with KTDB data. Furthermore, the study conducted an additional online travel survey on the potential subjects in future in order to improve the reliability of the factors for traffic policy change.
In particular, in this research we have established such travel behavior models as the car ownership model and the traffic generation model by travel purpose to analyze the change of future traffic characteristics.
As a result of predicting travel demand considering the factors of future change, we could not only know that there is a clear change in demand caused by the aging of the population and single-household change, but we also found a difference in travel demand and behaviour in the future according to city size. In addition, we demonstrated that vehicle trip frequencies and travel demand are affected differently by the changing factors in conditions of transport policies as well as by demographic group. This suggests that it is necessary to develop transport policies for farmers in consideration of micro-level and customized characteristics as well as macro ones.
Therefore, in this study we did not only set up policy directions responding to micro-level travel demand and behavior, but also established policy scenarios accordingly, predicting its change in travel demand. In addition, based on these scenarios, we suggested more specific policy alternatives including the time and agents of their implementation. We suggest following studies in order to specifically implement the policy actions since it is necessary to analyze and verify them.
As described in the study, it can be seen that future travel demand is highly variable, based on future factors such as changes in economic and social conditions, transport technology, and potential policies, The study also found that travel demand in the future was mostly affected by potential future that we cannot predict, as well as the probabilistic future that we can predict, and the prescriptive future that can be adjusted by will. Considering our research results, it can be seen that it is difficult to predict the future demand for transportation accurately at present. This is because future travel demand is variable according to changes in policy and environment. Therefore, an effort to improve the efficiency of transportation investment is currently needed through these efforts to accurately predict travel demand and also develop and employ alternative policy actions that responds to the expected demand.