IU Indianapolis ScholarWorks :: Browsing by Author "Chien, Stanley"

Browsing by Author "Chien, Stanley"

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ADVANCED GESTURE RECOGNIZING SURVEILANCE SYSTEMS USING MICROSOFT KINECTS
(Office of the Vice Chancellor for Research, 2012-04-13) Murray, Edward; Inman, Travis; Yang, Heng; Corbett, Benjamin; Robinson, Joshua; Chien, Stanley
This research explores the possibility of implementing an advanced ges-ture recognizing surveillance system (A.G.R.S.S.) with the capability of mon-itoring and targeting a person who performs a threatening gesture within a designated area. By networking multiple Microsoft Kinects (gesture based video game controllers) together, we hypothesize that people can be moni-tored, tracked, and targeted based on the gestures they perform. The suc-cessful development of an A.G.R.S.S. can provide significant support in spot-ting individuals who pose a threat which can have civilian and military im-plementations. Since each Kinect can provide a spatial representation for twenty joints on a person, we developed code that links the aforementioned information from each Kinect into a single program. With two Kinects run-ning, we did trials of our program to simulate a trade-off of information be-tween the two Kinects. We also used these trials to analyze the effectiveness of the gesture recognition software. We found that multiple Kinects can be linked together to monitor and target a person based on the gestures they perform. The outcome of the project is a program that uses two Kinects to observe (live video stream), target, follow, and capture a picture of a person who has simulated firing a hand gun. These results unequivocally answer the question that we set out to investigate. Therefore, we can conclude that an A.G.R.S.S. can be developed using multiple Microsoft Kinects. This research paves the way for a future A.G.R.S.S. that monitors larger areas, looks for more gestures, and implements biometrics to identify individuals of interest.
Analysis of Potential Co-Benefits for Bicyclist Crash Imminent Braking Systems
(IEEE, 2017-10) Good, David H.; Krutilla, Kerry; Chien, Stanley; Li, Lingxi; Chen, Yaobin; Electrical and Computer Engineering, School of Engineering and Technology
In the US, the number of traffic fatalities has had a long term downward trend as a result of advances in the crash worthiness of vehicles. However, these improvements in crash worthiness do little to protect other vulnerable road users such as pedestrians or bicyclists. Several manufacturers have developed a new generation of crash avoidance systems that attempt to recognize and mitigate imminent crashes with non-motorists. While the focus of these systems has been on pedestrians where they can make meaningful contributions to improved safety [1], recent designs of these systems have recognized mitigating bicyclist crashes as a potential co-benefit. This paper evaluates the performance of one system that is currently available for consumer purchase. Because the vehicle manufacturer does not claim effectiveness for their system under all crash geometries, we focus our attention on the crash scenario that has the highest social cost in the US: the cyclist and vehicle on parallel paths being struck from behind. Our analysis of co benefits examines the ability to reduce three measures: number of crashes, fatalities, and a comprehensive measure for social cost that incorporates morbidity and mortality. Test track simulations under realistic circumstances with a realistic surrogate bicyclist target are conducted. Empirical models are developed for system performance and potential benefits for injury and fatality reduction. These models identify three key variables in the analysis: vehicle speed, cyclist speed and cyclist age as key determinants of potential co-benefits. We find that the evaluated system offers only limited benefits for any but the oldest bicycle riders for our tested scenario.
Certainty and Critical Speed for Decision Making in Tests of Pedestrian Automatic Emergency Braking Systems
(IEEE, 2016-09) Rosado, Alberto López; Chien, Stanley; Li, Lingxi; Yi, Qiang; Chen, Yaobin; Sherony, Rini; Department of Electrical and Computer Engineering, School of Engineering and Technology
This paper starts with depicting the test series carried out by the Transportation Active Safety Institute, with two cars equipped with pedestrian automatic emergency braking (AEB) systems. Then, an AEB analytical model that allows the prediction of the crash speed, stopping distance, and stopping time with a high degree of accuracy is presented. The model has been validated with the test results and can be used for real-time application due to its simplicity. The concept of the active safety margin is introduced and expressed in terms of deceleration, time, and distance in the model. This margin is a criterion that can be used either in the design phase of pedestrian AEB for real-time decision making or as a characteristic indicator in test procedures. Finally, the decision making is completed with the analysis of the behavior of the pedestrian lateral movement and the calculation of the certainty of finding the pedestrian into the crash zone. This model of certainty completes the analysis of decision making and leads to the introduction of the new concept of “critical speed for decision making.” All major variables influencing the performance of pedestrian AEB have been modeled. A proposal of certainty scale in this kind of tests and a set of recommendations are given to improve the efficiency and accuracy of evaluation of pedestrian AEB systems.
Collision-Free Path Planning for Automated Vehicles Risk Assessment via Predictive Occupancy Map
(IEEE, 2020-11) Shen, Dan; Chen, Yaobin; Li, Lingxi; Chien, Stanley; Electrical and Computer Engineering, School of Engineering and Technology
Vehicle collision avoidance system (CAS) is a control system that can guide the vehicle into a collision-free safe region in the presence of other objects on road. Common CAS functions, such as forward-collision warning and automatic emergency braking, have recently been developed and equipped on production vehicles. However, these CASs focus on mitigating or avoiding potential crashes with the preceding cars and objects. They are not effective for crash scenarios with vehicles from the rear-end or lateral directions. This paper proposes a novel collision avoidance system that will provide the vehicle with all-around (360-degree) collision avoidance capability. A risk evaluation model is developed to calculate potential risk levels by considering surrounding vehicles (according to their relative positions, velocities, and accelerations) and using a predictive occupancy map (POM). By using the POM, the safest path with the minimum risk values is chosen from 12 acceleration-based trajectory directions. The global optimal trajectory is then planned using the optimal rapidly exploring random tree (RRT*) algorithm. The planned vehicle motion profile is generated as the reference for future control. Simulation results show that the developed POM-based CAS demonstrates effective operations to mitigate the potential crashes in both lateral and rear-end crash scenarios.
Contrast Between Road and Roadside Material For Road Edge Detection In Vehicle Road Departure Mitigation System
(National Highway Traffic Safety Administration, 2019) Yi, Qiang; Chien, Stanley; Chen, Yaobin; Sherony, Rini; Electrical and Computer Engineering, School of Engineering and Technology
Vehicle roadway departure crashes results in a large number of fatalities in the U.S. Road departure mitigation (RDM) systems rely on the road edge and road boundary identification. Cameras are widely used in RDMS for identifying road edges. The contrast between road and road boundary objects is one of the key image features used by the camera to detect road edges. This paper analyzes and compares the contrasts between various road surfaces. and road edges.
Data Collection and Processing Methods for the Evaluation of Vehicle Road Departure Detection Systems
(IEEE, 2018) Shen, Dan; Yi, Qiang; Li, Lingxi; Chien, Stanley; Chen, Yaobin; Sherony, Rini; Mechanical and Energy Engineering, School of Engineering and Technology
Road departure detection systems (RDDSs) for avoiding/mitigating road departure crashes have been developed and included on some production vehicles in recent years. In order to support and provide a standardized and objective performance evaluation of RDDSs, this paper describes the development of the data acquisition and data post-processing systems for testing RDDSs. Seven parameters are used to describe road departure test scenarios. The overall structure and specific components of data collection system and data post-processing system for evaluating vehicle RDDSs is devised and presented. Experimental results showed sensing system and data post-processing system could capture all needed signals and display vehicle motion profile from the testing vehicle accurately. Test track testing under different scenarios demonstrates the effective operations of the proposed data collection system.
Determine characteristics requirement for the surrogate road edge objects for road departure mitigation testing
(2019) Chien, Stanley; Yi, Qiang; Lin, Jun; Saha, Abir; Li, Lin; Chen, Yaobin; Chen, Chi-Chih; Sherony, Rini; Electrical and Computer Engineering, School of Engineering and Technology
Road departure mitigation system (RDMS), a vehicle active safety feature, uses road edge objects to determine potential road departure. In the U.S., 45%, 16%, and 15% of car-mile (traffic flow * miles) roads have grass, metal guardrail, and concrete divider as road edge, respectively. It is difficult to test RDMS with real roadside objects. Lightweight and crashable surrogate roadside objects that have representative radar, LIDAR and camera characteristics of real objects have been developed for testing. This paper describes the identification of automotive radar, LIDAR, and visual characteristics of metal guardrail, concrete divider, and grass. These characteristics will be referenced for designing and fabricating the representative surrogate objects for RDMS testing. Colors and types of the roadside objects were identified from 24,735 randomly sampled locations in the US using Google street view images. The radar and LIDAR parameters were measured using 24GHz/77GHz radar and 350-2500nm IR spectrometer.
Development of a Force Sensing Instrument Assisted Soft Tissue Mobilization Device
(ASME, 2016-11) Alotaibi, Ahmed M.; Anwar, Sohel; Loghmani, M. Terry; Chien, Stanley; Mechanical Engineering, School of Engineering and Technology
Instrument assisted soft tissue mobilization (IASTM) is a form of massage using rigid manufactured or cast devices. The delivered force, which is a critical parameter in massage during IASTM, has not been measured or standardized for most clinical practices. In addition to the force, the angle of treatment and frequency play an important role during IASTM. As a result, there is a strong need to characterize the delivered force to a patient, angle of treatment, and stroke frequency. This paper proposes a novel mechatronic design for a specific instrument from Graston Technique® (Model GT-3), which is a frequently used tool to clinically deliver localize pressure to the soft tissue. The design uses a 3D load cell, which can measure all three force components force simultaneously. The overall design is implemented with an IMUduino microcontroller chip which can also measure tool orientation angles and provide computed stroke frequency. The prototype of the mechatronic IASTM tool was validated for force measurements using an electronic plate scale that provided the baseline force values to compare with the applied force magnitudes measured by the device. The load cell measurements and the scale readings were found to be in agreement within the expected degree of accuracy. The stroke frequency was computed using the force data and determining the peaks during force application. The orientation angles were obtained from the built-in sensors in the microchip.
Development of a Portable Knee Rehabilitation Device That Uses Mechanical Loading
(ASME, 2013-12) Fitzwater, Daric; Dodge, Todd; Chien, Stanley; Yokota, Hiroki; Anwar, Sohel; Mechanical Engineering, School of Engineering and Technology
Joint loading is a recently developed mechanical modality, which potentially provides a therapeutic regimen to activate bone formation and prevent degradation of joint tissues. To our knowledge, however, few joint loading devices are available for clinical or point-of-care applications. Using a voice-coil actuator, we developed an electromechanical loading system appropriate for human studies and preclinical trials that should prove both safe and effective. Two specific tasks for this loading system were development of loading conditions (magnitude and frequency) suitable for humans, and provision of a convenient and portable joint loading apparatus. Desktop devices have been previously designed to evaluate the effects of various loading conditions using small and large animals. However, a portable knee loading device is more desirable from a usability point of view. In this paper, we present such a device that is designed to be portable, providing a compact, user-friendly loader. The portable device was employed to evaluate its capabilities using a human knee model. The portable device was characterized for force-pulse width modulation duty cycle and loading frequency properties. The results demonstrate that the device is capable of producing the necessary magnitude of forces at appropriate frequencies to promote the stimulation of bone growth and which can be used in clinical studies for further evaluations.
Development of an Artificial Finger-Like Knee Loading Device to Promote Bone Health
(Scientific Research Publishing, 2017-11) Korupolu, Sandeep; Chien, Stanley; Yokota, Hiroki; Anwar, Sohel; Mechanical and Energy Engineering, School of Engineering and Technology
This study presents the development of an innovative artificial finger-like device that provides position specific mechanical loads at the end of the long bone and induces mechanotransduction in bone. Bone cells such as osteoblasts are the mechanosensitive cells that regulate bone remodelling. When they receive gentle, periodic mechanical loads, new bone formation is promoted. The proposed device is an under-actuated multi-fingered artificial hand with 4 fingers, each having two phalanges. These fingers are connected by mechanical linkages and operated by a worm gearing mechanism. With the help of 3D printing technology, a prototype device was built mostly using plastic materials. The experimental validation results show that the device is capable of generating necessary forces at the desired frequencies, which are suitable for the stimulation of bone cells and the promotion of bone formation. It is recommended that the device be tested in a clinical study for confirming its safety and efficacy with patients.

Browsing by Author "Chien, Stanley"

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