• Proceedings of the Korea Information Processing Society Conference
• /
• 2020.05a
• /
• pp.497-499
• /
• 2020

자율주행 차량이 많아지고 차량의 ECU가 고도화되면서 정확한 차량의 데이터를 획득하고 분석하여 활용하는 것이 중요해지고 있다. 현재에는 내연 기관 차량의 ECU 데이터를 얻기 위해서 OBDII 포트(규격)에 기반한 CAN동선을 주로 이용하고 있다. 하지만 OBDII 규격을 통해서 연비와 같은 중요한 차량 정보를 얻는 경우, 변환식 (MAF 센서(흡입 공기량 센서)와 공기/연료 비율을 이용)의 오차 범위가 커서 데이터의 정확도가 낮다. 본 연구에서는 머신 러닝 기법 중에 하나인 회귀 기법을 통해서 기존의 계산보디 더 정확한 연비를 구할 수 있는 모델을 개발하였다. 이러한 모델 개발을 통하여 차량의 RAW 데이터를 기반으로 필요한 차량 데이터를 정확하게 구할 수 있게 되었으며 20회가 넘는 실 도로주행을 통해서 본 모델의 정확도를 검증하였다.

• KIPS Transactions on Software and Data Engineering
• /
• v.10 no.2
• /
• pp.57-64
• /
• 2021

This study presents a method for realtime fuel consumption prediction using real data collected from OBDII. With the advent of the era of self-driving cars, electronic control units(ECU) are getting more complex, and various studies are being attempted to extract and analyze more accurate data from vehicles. But since ECU is getting more complex, it is getting harder to get the data from ECU. To solve this problem, the firmware was developed for acquiring accurate vehicle data in this study, which extracted 53,580 actual driving data sets from vehicles from January to February 2019. Using these data, the ensemble stacking technique was used to increase the accuracy of the realtime fuel consumption prediction model. In this study, Ridge, Lasso, XGBoost, and LightGBM were used as base models, and Ridge was used for meta model, and the predicted performance was MAE 0.011, RMSE 0.017.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2010.10a
• /
• pp.66-69
• /
• 2010

Lately, vehicle combined vehicle and IT(Information Technology) for vehicle's safety and convenience. so, vehicles is equipped with many ECU(Electronic control unit). the ECU's transmit data about each electronic control unit with OBD(On-Board Diagnostics) Network and data about each multimedia with MOST(Media Oriented System Transport) Network. In this paper, Supplementing disadvantage of existing blackbox, Using MOST of in-vehicle multimedia network and OBD-II of in-vehicle control network, blackbox system obtain the vehicle's driving state data. so, blackbox system judge vehicle's driving state and provide vehicle's driving state information to driver. Blackbox system implement the features mentioned above. as a result, blackbox is going to be more accurate blackbox system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2010.10a
• /
• pp.76-79
• /
• 2010

lately, vehicle blackbox increasing importance and usability Is needed accuracy and variety of information. because, blackbox help to analyze the exact cause of the accident and use as objective evidence in vehicle-related crime. In the paper, to overcome the limitations of the existing black box, use various sensors and vehicle information blackbox store current state of the vehicle with OBD-II protocol using vehicle state information and store exact current location and direction information of the vehicle with Gyro sensor and GPS and use global time of GPS for synchronization of information. In addition, blackbox back the information up with wifi. because, when blackbox damaged, dirvers were able to verify the information.