• Journal of Auto-vehicle Safety Association
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• v.13 no.4
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• pp.7-13
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• 2021

This paper presents an vulnerable road user (VRU) classification and tracking algorithm using vision and LiDAR sensor fusion method for urban autonomous driving. The classification and tracking for vulnerable road users such as pedestrian, bicycle, and motorcycle are essential for autonomous driving in complex urban environments. In this paper, a real-time object image detection algorithm called Yolo and object tracking algorithm from LiDAR point cloud are fused in the high level. The proposed algorithm consists of four parts. First, the object bounding boxes on the pixel coordinate, which is obtained from YOLO, are transformed into the local coordinate of subject vehicle using the homography matrix. Second, a LiDAR point cloud is clustered based on Euclidean distance and the clusters are associated using GNN. In addition, the states of clusters including position, heading angle, velocity and acceleration information are estimated using geometric model free approach (GMFA) in real-time. Finally, the each LiDAR track is matched with a vision track using angle information of transformed vision track and assigned a classification id. The proposed fusion algorithm is evaluated via real vehicle test in the urban environment.

• Transportation Technology and Policy
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• v.10 no.5
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• pp.42-50
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• 2013

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.1
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• pp.240-257
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• 2022

Autonomous vehicles use various local sensors such as camera, radar, and lidar to perceive the surrounding environment. However, it is difficult to predict the movement of vulnerable road users using only local sensors that are subject to limits in cognitive range. This is true especially when these users are blocked from view by obstacles. Hence, this paper developed an algorithm for collision avoidance with VRU using V2X information. The main purpose of this collision avoidance system is to overcome the limitations of the local sensors. The algorithm first evaluates the risk of collision, based on the current driving condition and the V2X information of the VRU. Subsequently, the algorithm takes one of four evasive actions; steering, braking, steering after braking, and braking after steering. A simulation was performed under various conditions. The results of the simulation confirmed that the algorithm could significantly improve the performance of the collision avoidance system while securing vehicle stability during evasive maneuvers.

• Journal of Korea Multimedia Society
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• v.18 no.11
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• pp.1302-1312
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• 2015

Recent research has been devoted and focused on detecting pedestrian and vehicle in intelligent vehicles except for the vulnerable road user(VRUS). In this paper suggest a new projection method which has robustness for rotation invariant and reducing dimensionality for each cell from original image to detect two-wheeler. We applied new weighting values which are calculated by maximum curvature containing very important object shape features and uniform local binary pattern to remove the noise. This paper considered the Adaboost algorithm to make a strong classification from weak classification. Experiment results show that the new approach gives higher detection accuracy than of the conventional method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.2
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• pp.622-631
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• 2019

The purpose of this study is to establish and apply a public transport valuation system to form required policy for institutionalization. Over the past six years, Jeju has seen a steady increase in the number of cars owned by its population. Also, as the number of tourists has changed from group to individual tourists, the rate of rental car use has increased rapidly. As a result, road congestion in Jeju city is becoming as crowded as Seoul., Jeju Island is said to have created a foundation for faster, more convenient, and cheaper use of transportation through the reorganization of the public transportation system in August 2017. This is also reflected in the Public Transportation Value Assessment. Jeju residents were in favor of strengthening public transportation priority policy. In addition, public transport valuations are highly valued in the order of public transportation fares, public transportation stability, public transportation policies for the common people, public transportation policies for the vulnerable, public transportation policies for residents, environmentally-friendly policies, and public transportation to help ease traffic congestion. This is because public transportation has a wide range of values and should refine the factors that local governments use to evaluate policy. These methods need to be institutionalized and actively utilized through the establishment of a value assessment system for public transport.