@inproceedings{0abea32fab7e484c856ae3cfdf184fa5,
title = "An Integrated Bus Routing Control Platform for Autonomous Bus Driving based on Traffic-Demand Trade-off",
abstract = "Data conversion of the current system is essential for the commercialization of autonomous buses. The biggest advantage of autonomous buses is that they can follow flexible routes according to traffic demand. If a program automatically finds the optimal route depending on the time of day or traffic demand, then it will be very helpful for the commercialization of autonomous buses. Because it is most important to gather data such as the locations of bus stops, this paper proposes a method of creating a platform based on the bus stop data provided by Daegu City. Currently, Daegu City provides all locations and demand for bus stops. Visual Studio was used to classify the data according to Daegu's districts, and a platform to find the optimal route was created using the modified Dijkstra algorithm, which made it possible to simulate flexibly according to changes in data.",
keywords = "automation, autonomous driving, data structure, Dijkstra algorithm",
author = "Soeun Park and Daejin Park",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 4th IEEE Global Conference on Life Sciences and Technologies, LifeTech 2022 ; Conference date: 07-03-2022 Through 09-03-2022",
year = "2022",
doi = "10.1109/LifeTech53646.2022.9754830",
language = "English",
series = "LifeTech 2022 - 2022 IEEE 4th Global Conference on Life Sciences and Technologies",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "604--605",
booktitle = "LifeTech 2022 - 2022 IEEE 4th Global Conference on Life Sciences and Technologies",
address = "United States",
}