• Journal of Korea Multimedia Society
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• v.24 no.7
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• pp.860-867
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• 2021

Lane detection is important technology for implementing ADAS or autonomous driving. Although edge detection has been typically used for the lane detection however, false detections occur frequently. To improve this problem, a deep learning based lane detection algorithm is proposed in this paper. This algorithm is mounted on an ARM-based embedded system to implement a LDW(lane departure warning). Since the embedded environment lacks computing power, the VGG-11, a lightweight model based on VGG-13, has been proposed. In order to evaluate the performance of the LDW, the test was conducted according to the test scenario of NHTSA.

• Transactions of the Korean Society of Automotive Engineers
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• v.20 no.6
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• pp.39-45
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• 2012

More than 80 percent of traffic accidents related with lane departure believed to be the result of crossing the lane due to either negligence or drowsiness of the driver. Lane-departure related accident in the highway usually involve high fatality. Even though LDWS is believed to prevent accident 25% and reduce fatalities by 15% respectively, its effectiveness in performance is yet to be confirmed in many aspects. In this study, the vehicle lateral locations relative to warning zone envelop (earliest and latest warning zone) defined in ISO standard, ECE and NHTSA regulations are compared with respect to various factors including delays, vehicle speed and vehicle heading angle with respect to the lane. Since LDWS is designed to be activated at the speed over 60 km/h, vehicle speed range for the study is set to be from 60 to 100 km/h. The vehicle heading angle (yaw angle) is set to be up to 5 degree away from the lane (abrupt lane change) considering standard for lane change test using double lane-change test specification. The TLC is calculated using factors like vehicle speed, yaw angle and reaction time. In addition, the effect of vehicle type has been considered to assess LDWS safety.

• Transactions of the Korean Society of Automotive Engineers
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• v.24 no.6
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• pp.627-634
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• 2016

In this paper, an augmented video generation method to evaluate the performance of lane departure warning system is proposed. In our system, the input is a video which have road scene with general clean lane, and the content of output video is the same but the lane is synthesized with contamination image. In order to synthesize the contamination lane image, two approaches were used. One is example-based image synthesis, and the other is background-based image synthesis. Example-based image synthesis is generated in the assumption of the situation that contamination is applied to the lane, and background-based image synthesis is for the situation that the lane is erased due to aging. In this paper, a new contamination pattern generation method using Gaussian function is also proposed in order to produce contamination with various shape and size. The contamination lane video can be generated by shifting synthesized image as lane movement amount obtained empirically. Our experiment showed that the similarity between the generated contamination lane image and real lane image is over 90 %. Futhermore, we can verify the reliability of the video generated from the proposed method through the analysis of the change of lane recognition rate. In other words, the recognition rate based on the video generated from the proposed method is very similar to that of the real contamination lane video.

• Journal of Advanced Navigation Technology
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• v.18 no.1
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• pp.14-21
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• 2014

In this paper, we devise a new ontology-based context-aware system to recognize the smart car information, in which driver's intent is utilized by information of car, driver, environment as well as driving state, driver state. So proposed system can handle dynamically risk changes by adding real-time situational awareness information. We utilize the camera image recognition technology for context-aware intelligent vehicle driving information, and implement information acquisition scheme OBD-II protocol to acquire vehicle's information. Experiments confirm that the proposed advanced driver safety assist system outperforms the conventional system, which only utilizes the information of vehicle, driver, and environmental information, to support the service of a high-speed driving, lane-departure service and emergency braking situation awareness.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.1
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• pp.14-26
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• 2019

For bus drivers' safe driving, a policy that analyzes the causes of the drivers' traffic accidents and then assists their safe driving is required. Therefore, the Ministry of Land, Infrastructure and Transport set up its plan to gradually expand the equipping of commercial vehicles with FCWS (Forward Collision Warning System) and LDWS(Lane Departure Warning System), from the driver-supporting ADAS(Advanced Driver Assistance Systems). However, there is not much basic research on the analysis of bus drivers' traffic accidents in Korea. As such, the time is appropriate to research what is the most necessary ADAS for bus drivers going forward to prevent bus accidents. The purpose of this research is to analyze how serious the accidents were in the different bus routes and whether the accidents were repetitive, and to give recommendations on how to support ADAS for buses, as an improvement. A model of ordered logit was used to analyze how serious the accidents were and as a result, vehicle to pedestrian accidents which directly affected individuals were statistically significant in all of the models, and violations of regulations, such as speeding, traffic signal violation and violation of safeguards for passengers, were indicated in common in several models. Therefore, the pedestrian-sensor system and automatic emergency control device for pedestrian should be installed to reduce bus accidents directly affecting persons in the future, and education for drivers and ADAS are to be offered to reduce the violations of regulations.