The growing population density in the urban areas induce traffic problems despite the continuous development in artificial intelligence, big data analysis, and unmanned transportation.
In order to resolve the traffic problems, there is a need to identify an efficient public transportation servic...
The growing population density in the urban areas induce traffic problems despite the continuous development in artificial intelligence, big data analysis, and unmanned transportation.
In order to resolve the traffic problems, there is a need to identify an efficient public transportation service scheme based from the perspective of public transportation users to reduce the use of private vehicles and arrange relevant user information and fare system to mobilize the public transportation system.
Appropriate mode of transportation differs from city to city as their spatial area and traffic environment varies. Hence, it is necessary to plan and build applicable transportation system depending on the volume of the traffic demand. Furthermore, the government needs to develop a plan to introduce new transportation mode suitable for the high-tech era for continuous development, and develop a fare and settlement system for an efficient operation.
The purpose of this study is to identify measures on how to facilitate the efficient use of public transportation system by connecting and integrating the existing and new mode of transportation.
In line with the Fourth Industrial Revolution, Mobility-as-a-Service (MaaS) was introduced as a model for a new mode of transportation to create a new ecosystem of personal mobility with ICT (Information Communication Technology). MaaS provides mobility according to the diversity of the transportation system to meet individual transportation needs, which includes public bicycle, car sharing and self-driving cars, along with the existing public transportation modes such as buses, taxis, subways, and railroads.
A virtual analysis network similar to the actual environment was created to analyze the new integrated transportation system as a service based on the public transportation data. The objective of MaaS is to improve convenience and quality of service to users, and to provide various analysis data such as optimum travel path, transfer frequency, fare system, and travel time between mode of transportation using the current traffic data (traffic situation, public transport system, etc.).
In this study, the traffic demand model of Sejong City was established based on the household travel survey. Travel behavior, socio-economic indicators, and the network was analyzed, and the current data was compared with the forecasted traffic demand.
After integrating public vehicle and car-sharing system in the existing mode of public transportation in the established traffic demand model network, an optimal route analysis was conducted considering the transfer system. Different scenarios according to various fare system, routes and mode conditions was also analyzed. The most suitable route, which reduces the most in terms of travel time and fare during traffic, was selected, and it is then compared to other community website's optimal route.
It is expected that the efficiency of public transportation in terms of speed, convenience, and frequency will lead to the reduction of private vehicles in the roads. Likewise, providing transportation information, such as optimum fare, optimal route, and optimal time, to users through various methods will improve the efficiency of the transportation operation.
The growing population density in the urban areas induce traffic problems despite the continuous development in artificial intelligence, big data analysis, and unmanned transportation.
In order to resolve the traffic problems, there is a need to identify an efficient public transportation service scheme based from the perspective of public transportation users to reduce the use of private vehicles and arrange relevant user information and fare system to mobilize the public transportation system.
Appropriate mode of transportation differs from city to city as their spatial area and traffic environment varies. Hence, it is necessary to plan and build applicable transportation system depending on the volume of the traffic demand. Furthermore, the government needs to develop a plan to introduce new transportation mode suitable for the high-tech era for continuous development, and develop a fare and settlement system for an efficient operation.
The purpose of this study is to identify measures on how to facilitate the efficient use of public transportation system by connecting and integrating the existing and new mode of transportation.
In line with the Fourth Industrial Revolution, Mobility-as-a-Service (MaaS) was introduced as a model for a new mode of transportation to create a new ecosystem of personal mobility with ICT (Information Communication Technology). MaaS provides mobility according to the diversity of the transportation system to meet individual transportation needs, which includes public bicycle, car sharing and self-driving cars, along with the existing public transportation modes such as buses, taxis, subways, and railroads.
A virtual analysis network similar to the actual environment was created to analyze the new integrated transportation system as a service based on the public transportation data. The objective of MaaS is to improve convenience and quality of service to users, and to provide various analysis data such as optimum travel path, transfer frequency, fare system, and travel time between mode of transportation using the current traffic data (traffic situation, public transport system, etc.).
In this study, the traffic demand model of Sejong City was established based on the household travel survey. Travel behavior, socio-economic indicators, and the network was analyzed, and the current data was compared with the forecasted traffic demand.
After integrating public vehicle and car-sharing system in the existing mode of public transportation in the established traffic demand model network, an optimal route analysis was conducted considering the transfer system. Different scenarios according to various fare system, routes and mode conditions was also analyzed. The most suitable route, which reduces the most in terms of travel time and fare during traffic, was selected, and it is then compared to other community website's optimal route.
It is expected that the efficiency of public transportation in terms of speed, convenience, and frequency will lead to the reduction of private vehicles in the roads. Likewise, providing transportation information, such as optimum fare, optimal route, and optimal time, to users through various methods will improve the efficiency of the transportation operation.
※ AI-Helper는 부적절한 답변을 할 수 있습니다.