Title The Advanced Intelligent Operation and Management Pilot Project for Smart Bus (2/2) – Development of an Integrated Driver Digital Resume Management System for Onboard Devices
Dept Transportation Operations and Management Division
Year 113
Month 5
Price 520
Summary        To validate the feasibility of collecting operational information from fleet vehicles in the highway passenger transport industry through onboard devices (OBD, digital tachograph, ADAS, CAN Bus, 4G or 5G, etc.) for postpandemic digital governance and transformation, our institute initiated the “Advanced Intelligent Operation and Management Pilot Project for Smart Bus (Years 2021–2022).” This study is the second-year project and is in the expanded conceptual verification phase. The main focus is on developing an integrated blockchain onboard network and Advanced Driver Assistance System (ADAS) called the “Driver Digital Resume Management System.” The purpose of this system is to assist domestic passenger transport operators in strengthening data governance and digital transformation after the pandemic, creating a SMART public transportation development environment.
       The system involves the installation of a three-in-one active assistance device (ADAS), driver behavior analyzer, OBD/CAN onboard network, and vehicle networking communication module to collect driver ADAS alert data. The collected data is optimized through cloud database optimization and blockchain technology to prevent data tampering.The system helps operators correct drivers‘ undesirable driving behaviors, effectively improving road passenger safety. To validate the feasibility of the technology, the study conducted on-road tests on urban bus routes, national highway passenger routes, and mountainous roads. During the on-road testing period, a total of 4 buses and 4 drivers were dispatched, covering 5 routes, with a total of 5,033 trips, accumulating 2,900 hours of driving, and a data volume of 1.74 million records. The test results indicate that the system has achieved the expected goals. Based on the on-road test results, the study provides the following recommendations for parameters related to undesirable driving behaviors and driver grading calculation: (1) Adjust parameters for “frequent lane changes” and “multiple lane changes” according to road types; (2) Adjust parameters for “rapid acceleration and deceleration” based on road types and vehicle models.
       To assist operators, this study plans the overall architecture of the “Core Module for Public Transportation Digital Transformation,” to facilitate the subsequent development of various tools needed for digital transformation. This will
help operators quickly recover and revive after the pandemic.
Post date 2024/05/24
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