• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2003.09a
• /
• pp.636-639
• /
• 2003

In this paper, we present a robust method for detecting other vehicles from n forward-looking CCD camera in a moving vehicle. This system uses edge and shape information to detect other vehicles. The algorithm consists of three steps: lane detection, ehicle candidate generation, and vehicle verification. First after detecting a lane from the template matching method, we divide the road into three parts: left lane, front lane, and right lane. Second, we set the region of interest (ROI) using the lane position information and extract a vehicle candidate from the ROI. Third, we use local orientation coding (LOC) edge image of the vehicle candidate as input to a pretrained neural network for vehicle recognition. Experimental results from highway scenes show the robustness and effectiveness of this method.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.8
• /
• pp.3399-3419
• /
• 2020

In the Vehicular Ad-hoc Network (VANET), the data transmission of time-sensitive applications requires low latency, such as accident warnings, driving guidance, etc. However, frequent changes of topology in VANET will result in data transmission failures. In order to improve the efficiency of VANETs data transmission and increase the timeliness of data, this paper proposes a relay scheme based on Recurrent Neural Network (RNN) trajectory prediction, which can be used to select the optimal relay vehicle to transmit data. The proposed scheme learns vehicle trajectory in a distributed manner and calculates the predicted trajectory, and then the optimal vehicle can be selected to complete the data transmission, which ensures the timeliness of the data. Finally, we carry out a set of simulations to demonstrate the performance of the algorithm. Simulation results show that the proposed scheme enhances the timeliness of the data and the accuracy of the predicted driving trajectory.

• Journal of Institute of Control, Robotics and Systems
• /
• v.15 no.7
• /
• pp.753-759
• /
• 2009

As many systems depend on electronics in an intelligent vehicle, concern for fault tolerance is growing rapidly. For example, a car with its braking controlled by electronics and no mechanical linkage from brake pedal to calipers of front tires(brake-by-wire system) should be fault tolerant because a failure can come without any warning and its effect is devastating. In general, fault tolerance is usually designed by placing redundant components that duplicate the functions of the original module. In this way a fault can be isolated, and safe operation is guaranteed by replacing the faulty module with its redundant and normal module within a predefined interval. In order to make in-vehicle network fault tolerant, this paper presents the concept and design methodology of an IEEE 1451 based dual CAN module. In addition, feasibility of the dual CAN network was evaluated by implementing the dual CAN module.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2012.10a
• /
• pp.407-410
• /
• 2012

Recently, wireless network services are widely used, depending on the development of wireless network module technologies and the utilization gradually expanded, and thus is a trend that appears a lot of IT convergence industries. For this study, the OBD-II communication to Import your vehicle information, and other external devices in high-speed driving condition of the vehicle to verify the information system was developed to transfer data to an external server. From various sensors inside the vehicle using the OBD-II connector easily convert all users to read the information, then, Sent to the external server using the wireless network module, high-speed vehicle status check system was implemented. It was to test the performance of the system was developed using the actual circuit in a high-speed road racing vehicles. Transfer data generated from high-speed driving vehicles through the OBD-II scanner and check the status of a high-speed vehicle system was confirmed that this data is normally received. In the future, these new cars convergence of IT technology will grow as a new field of research.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.22 no.12
• /
• pp.1691-1697
• /
• 2018

There has been a steady study of unmanned vehicle. So far, continuous research has brought news of the commercialization of unmanned vehicle. In addition, it has been applied in a variety of fields with another industry. A lot of research has been done, too, to apply inert driving indoors. Using LoRa network, which is a network dedicated to IoT, unmanned vehicle control system that is applied to LoRa network from a small space, or from an office hospital to a factory, is installed to increase efficiency when the performs special tasks. This paper presents solutions to a variety of problems by using LoRa network, which is dedicated to IoT, to recognize an unmanned vehicle as a single object, to communicate with surrounding objects, and to receive information necessary for driving indoors from a cloud server.

• The Journal of Information Systems
• /
• v.29 no.2
• /
• pp.131-147
• /
• 2020

Purpose The purpose of this study is to develop intelligent vehicle parking distribution system based on LoRa network at the circumstance of traffic congestion during cultural festival in a local city. This paper proposes a parking dispatch and distribution system using a Q-learning algorithm to rapidly disperse traffics that increases suddenly because of in-bound traffics from the outside of a city in the real-time base as well as to increase parking probability in a parking lot which is widely located in a city. Design/methodology/approach The system get information on realtime-base from the sensor network of IoT (LoRa network). It will contribute to solve the sudden increase in traffic and parking bottlenecks during local cultural festival. We applied the simulation system with Queuing model to the Yudeung Festival in Jinju, Korea. We proposed a Q-learning algorithm that could change the learning policy by setting the acceptability value of each parking lot as a threshold from the Jinju highway IC (Interchange) to the 7 parking lots. LoRa Network platform supports to browse parking resource information to each vehicle in realtime. The system updates Q-table periodically using Q-learning algorithm as soon as get information from parking lots. The Queuing Theory with Poisson arrival distribution is used to get probability distribution function. The Dijkstra algorithm is used to find the shortest distance. Findings This paper suggest a simulation test to verify the efficiency of Q-learning algorithm at the circumstance of high traffic jam in a city during local festival. As a result of the simulation, the proposed algorithm performed well even when each parking lot was somewhat saturated. When an intelligent learning system such as an O-learning algorithm is applied, it is possible to more effectively distribute the vehicle to a lot with a high parking probability when the vehicle inflow from the outside rapidly increases at a specific time, such as a local city cultural festival.

• Journal of Institute of Control, Robotics and Systems
• /
• v.13 no.10
• /
• pp.933-939
• /
• 2007

Safety critical systems such as x-by-wire systems require in-vehicle network systems that can interconnect various sensors, actuators, and controllers. These networks need to have high data rate, deterministic operation, and fault tolerance. Recently, FlexRay protocol that is a time-triggered protocol has been introduced, and many automotive companies have been focusing on this protocol. This paper presents a design method of FlexRay network system and implementation of FlexRay-based motor control system.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 1999.10a
• /
• pp.142-147
• /
• 1999

This paper presents a new approach to the dynamic control technique for track vehicle system using neural network-fuzzy control method. The proposed control scheme uses a Gaussian function as a unit function in the neural network-fuzzy, and back propagation algorithm to train the fuzzy-neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is shown by simulation for trajectory tracking of the speed and azimuth of a track vehicle.

• Proceedings of the KSME Conference
• /
• 2004.04a
• /
• pp.864-869
• /
• 2004

In this paper, a blackbox approach is carried out to model the nonlinear dynamic bushing model. One-axis durability test is performed to describe the mechanical behavior of typical vehicle elastomeric components. The results of the tests are used to develop an empirical bushing model with an artificial neural network. The back propagation algorithm is used to obtain the weighting factor of the neural network. Since the output for a dynamic system depends on the histories of inputs and outputs, Narendra's algorithm of 'NARMAX' form is employed in the neural network bushing module. A numerical example is carried out to verify the developed bushing model.

• Journal of Institute of Control, Robotics and Systems
• /
• v.18 no.8
• /
• pp.706-712
• /
• 2012

This paper presents a sensor network and operation for multiple autonomous navigation platform and transport service. Multiple platform navigate with inside sensors and outside sensors while acquiring and process some useful information. Each platform communicates each other by navigational information through central main server. Efficient sensor network systems are considered for the scenario which some passengers call the service and the vehicle accomplish its transport service by transporting each caller to the destination by autonomous manners. In the scenario, all vehicles perform a role of sensor system to the central server and the server handles each information and integrate with faster procedure in the wireless 3G network.