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Adaptive brake warning system for automobiles

Adaptive brake warning system for automobiles

引用

International Conference on ITS Telecommunications (ITST)

作者： P. Thammakaroon P. Tangamchit Department of Control System and Instrumentation Engineering King Mongkut''s University of Technology Thailand

We present an adaptive brake warning system in order to help a driver keep a safe distance from the cars in front to avoid rear-end collisions. The safe distance continuously varies according to the carpsilas velocity, driving events, and road conditions. Three sensors, an ECU reader, a camera, and a laser range finder, are used to collect the vehicular velocity, the density of cars on the road and the following distance respectively. These data are sent to a main computer to calculate the level of critical situation where the driver needs to apply brake ranging from 0 to 4 where level 0 is the safest and level 4 means the most dangerous. Two decision algorithms: adaptive threshold and fuzzy inference system are compared. The results from real driving situations indicated that both methods can achieve an accuracy of 76.98% and 65.46% respectively.

关键词： Adaptive systems Alarm systems Automobiles Roads Cameras Vehicles Collision avoidance Programmable control Adaptive control Accidents

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Evaluation of a 500-N deadweight force standard machine at NIMT

Evaluation of a 500-N deadweight force standard machine at N...

引用

The Society of Instrument and control Engineers Annual Conference 2015

作者： Kittipong Chaemthet Ake Chaisawadi Department of Control System and Instrumentation Engineering King Mongkut's University of Technology Thonburi

A 500-N deadweight force standard machine(DWM) has been developed for calibrating force proving instrument of small force ranges at National Institute of Metrology, Thailand(NIMT). The DWM is able to generate calibration forces ranging from 2 N to 500 N with the relative expanded uncertainty of 5×10-5. This machine can be divided into six calibration ranges, which are 10 N, 20 N, 50 N, 100 N, 200 N and 500 N. To verify performance of the machine, this paper shows the evaluation of relative uncertainty in the range of 50 N to 500 N. The force transducer was calibrated by the machine according to ISO376:2011[1]. The calibration result of force transducers has shown repeatability and reproducibility. The relative deviation of the calibration errors were less than 5×10-5 at the 50 % to 100 % of the capacity of force transducer.

关键词： Deadweight force standard machine,DWM,uncertainty,force-proving instrument,ISO 376:2011

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Road traffic estimation with signal matching in mobile phone using large-size database

Road traffic estimation with signal matching in mobile phone...

引用

2009 12th International IEEE Conference on Intelligent Transportation systems, ITSC '09

作者： Promnoi, Sunisa Tangamchit, Poj Pattara-Atikom, Wasan Department of Control System and Instrumentation Engineering King Mongkut's University of Technology Thonburi Bangkok Thailand National Electronics and Computer Technology Center 112 Phahol Yothin Rd Klong Luang Pathumthani 12120 Thailand

ISBN: (纸本)9781424455218

This paper presents a road traffic estimation method using a GSM mobile phone as a probe. The technique relies on localization by signal strength matching. Our emphasis is on the unusual-large size of the database. We built a module that automatically collects location-signal with one second refresh rate and carried it along a test route to collect database. To handle big database, we additionally present a noise reduction algorithm, which eliminates bad data and compacts the database. For the localization algorithm, the fast nearest neighbor strategy is applied in the database matching to reduce computation time. The position estimations which formerly implemented noise reduction are compared with the ordinary results. Furthermore, we compared the computation time of the fast nearest neighbor algorithm to the normal method. The results show that the mobile phone positioning based on signal strength pattern matching can locate its location down to 63 meter accuracy. © 2009 IEEE.

关键词： Database systems

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A real-time automatic inspection system for pattavia pineapples

A real-time automatic inspection system for pattavia pineapp...

引用

作者： Kaewapichai, Watcharin Kaewtrakulpong, Pakorn Prateepasen, Asa Department of Instrumentation and Control System Engineering King Mongkut's University of Technology Thonburi 91 Prachautid Bangmod Toongkru Bangkok 10140 Thailand Production Engineering Department Faculty of Engineering King Mongkut's University of Technology Thonburi 91 Prachautid Bangmod Toongkru Bangkok 10140 Thailand

This paper presents a machine vision method to inspect the maturity of pineapples that ripe naturally. Unlike previous methods, the proposed technique can be categorized as a real-time non destructive testing (Real-Time NDT) approach. It consists of two phases, learning and recognition phases. In the learning phase, the system constructs a library of reference pineapple-skin-color models. In the recognition phase, the same process is performed to build a pineapple-skin-color model of the testing subject. The model is then compared with each of the reference in the library by a method called region-segmented histogram intersection. The subject is then labeled with the grade of the best match. The system achieved a high performance and speed (3 frames/sec.) in our experiment. The system also includes weighing machine on belt transmission for weight prediction.

关键词： Fruits

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Deep Learning-Driven Navigation for Autonomous Golf Carts: Implementing YOLOP for Roadside Tracking

Deep Learning-Driven Navigation for Autonomous Golf Carts: I...

引用

International Conference on control, Automation and systems ( ICCAS)

作者： Benjamas Panomruttanarug Jirapasson Ponpimonangkul Paiporn Muangthai Natthakan Piyawanich Department of Department of Control System and Instrumentation Engineering King Mongkut University Technology Thonburi Bangkok Thailand

ISBN: (数字)9788993215380

ISBN: (纸本)9798331517939

This paper presents a vision-based navigation system for an autonomous golf cart, utilizing a custom drive-by-wire system and a single webcam strategically mounted on the left-hand side for real-time roadside tracking. Employing the You Only Look Once for Panoptic Driving Perception (YOLOP) model, optimized with TensorRT and trained on the Berkeley Deep Drive 100K dataset, the system effectively processes images to delineate drivable paths under various lighting conditions. Experiments conducted on both straight and curved paths at King Mongkut’s University of Technology Thonburi demonstrated the system’s capability to accurately track and adjust to lane deviations using a Proportional-Derivative control mechanism, ensuring precise vehicle steering and robust performance. The findings underscore the potential of integrating advanced image processing and deep learning models to enhance autonomous navigation in urban settings, suggesting avenues for further improvements in multi-sensor fusion and algorithm optimization.

关键词： YOLO Navigation Webcams Urban areas Lighting Real-time systems Robustness PD control Vehicle dynamics Optimization

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Comparing Network RTK and Own RTK Base Station for Lateral Tracking in GNSS-Based Navigation: An Autonomous Golf Cart Study

Comparing Network RTK and Own RTK Base Station for Lateral T...

引用

International Conference on control, Automation and systems ( ICCAS)

作者： Surayuth Duenkwang Chutimon Ketkarn Sorravee Wanichphol Benjamas Panomruttanarug Department of Department of Control System and Instrumentation Engineering King Mongkut university Technology Thonburi Bangkok Thailand

This study investigates the impact of utilizing a network RTK and our own RTK base station on the lateral tracking performance of a GNSS-based navigation system. The experiment employs an adaptive PID controller and compares the performance of both methods on an autonomous golf cart. The tracking path, composed of straight and curve segments, is manually generated based on the network RTK. The adaptive PID controller, with the gains tuned based on the slope of the path, is used to perform the tracking based on the real-time positioning observed from the network RTK as well as our own RTK base station. The results demonstrate that both network RTK and our own RTK base station achieve acceptable tracking performance, with lateral errors remaining within acceptable limits. Our own RTK base station exhibits slightly lower lateral errors compared to the network RTK, indicating improved tracking accuracy. However, setting up and maintaining our own RTK base station requires a more complex process and additional costs for an extra GNSS receiver. Hence, the choice between the two methods involves a trade-off between enhanced performance and the associated complexities.

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Predictive brake warning at night using taillight characteristic

Predictive brake warning at night using taillight characteri...

引用

IEEE International Symposium on Industrial Electronics (ISIE)

作者： Peachanika Thammakaroon Poj Tangamchit Department of Control System and Instrumentation Engineering King Mongkut''s University of Technology Thonburi Thailand

We present a technique used for frontal collision warning in an intelligent vehicle. The system uses an image processing algorithm to detect taillights (red brake lights) of vehicles driving at night time. The area of red lights, the size of the largest brake lights, and the vehicle's speed are used to compute the rear-end collision risk, which can be used as an indicator to danger that potentially leads to frontal collision. Therefore, the driver can be warned, and he can perform brake action on time. The algorithm uses a threshold to detect red color on an RGB image. The thresholds are obtained from statistical collection of 50 sample images. From our experiment on real driving situation, the collision risk can predict the actual brakes with 90% accuracy. The result also indicates that the area of red lights detected has a close relationship with the brake applied.

关键词： Costs Image processing Cameras Data mining Intelligent vehicles Vehicle detection Vehicle driving Layout Humans Road accidents

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Cooperative behavior-based control of decentralized mobile robots on an overhead box carrying task

Cooperative behavior-based control of decentralized mobile r...

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International Conference on Electrical engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON

作者： Mahitthidetch Udomkun Poj Tangamchit Department of Control System and Instrumentation Engineering King Mongkut's University of Technology Bangkok Thailand

We demonstrated that the regular behavior-based architecture can be used to control decentralized multiple robots on a tightly-coupled task. With carefully designed behaviors, the robots can work cooperatively and effectively. We divided the behaviors into two types: individual behaviors and group behaviors. Group behaviors, embedded as layers in the behavior-based architecture, act as a mechanism to induced coordination and synchronization among robots. The tightly-coupled task that we use as our testbed is the cooperative overhead transportation of a box, in which two robots have to carry a box over their tops. Little movement error will result in a fall of the box. The result illustrated the validity of the proposed method. The robots can move the box to a goal without falling down with a success rate of 80%.

关键词： Robots Robot kinematics Mobile robots Robot sensing systems Synchronization Transportation Distributed control

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Improvement of warning lag time in forward collision warning systems based on multifunctional warnings

Improvement of warning lag time in forward collision warning...

引用

IEEE International Conference on Vehicular Electronics and Safety (ICVES)

作者： Peachanika Thammakaroon Poj Tangamchit Department of Control System and Instrumentation Engineering King Mongkut's University of Technology Bangkok Thailand

We present an improvement of forward collision warning (FCW) by adding more layers of warning functionality based on five stages of crash timeline. Generally, FCW operates at stage 3, the critical moment before crash. The added functionality is the location-based warning (LW) which warns the driver when driving toward a dangerous spot with high speed. LW operates at stage 2, an open condition to crash which comes from bad driving habit. We propose the use of warning lag time as a performance indicator, which is appropriate for real driving experiment. The warning lag time is defined as the time period between the issue of warning and the execution of brake by a normal driver. We performed real driving experiments with normal drivers and compare their brake actions with warnings from our system. The system with FCW alone achieved an average time lag of 1.47 sec., while the system with both FCW+LW can warn the driver faster with average time lag of 1.32 sec. The accuracy of both systems was about the same at 79%.

关键词： Vehicles Alarm systems Accidents Sensors Vehicle crash testing Safety Computer crashes

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Fuzzy inference-based reinforcement learning of dynamic recurrent neural networks

Fuzzy inference-based reinforcement learning of dynamic recu...

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SICE Annual Conference

作者： Hyo-Byung Jun Dong-Wook Lee Dae-Joon Kim Kwee-Bo Sim Robotics and Intelligent Control System Lab Department of Control and Instrumentation Engineering Chung-Ang University Seoul South Korea

ISBN: (纸本)0780342089

This paper presents the fuzzy inference-based reinforcement learning algorithm of dynamic recurrent neural network, similar to the psychological learning scheme of the higher animals. The proposed method follows the way linguistic and conceptional expressions have an effect on human's behavior by reasoning reinforcement based on fuzzy rules. The intervals of fuzzy membership functions are found optimally by genetic algorithms. By using the recurrent neural network composed of dynamic neurons as action-generation network, not only the current state but also the past state is considered to make an action in dynamical environment. We show the validity of the proposed learning algorithm by applying it to the inverted pendulum control problem.

关键词： Learning Recurrent neural networks Fuzzy neural networks Heuristic algorithms Inference algorithms Psychology Animals Fuzzy reasoning Genetic algorithms Neurons

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