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Journal articles on the topic 'Kinematic bicycle model'
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1
Zhao, Yan-Jiang, Ze-Hua Liu, Yong-De Zhang, and Zhi-Qing Liu. "Kinematic model and its parameter identification for cannula flexible needle insertion into soft tissue." Advances in Mechanical Engineering 11, no. 6 (June 2019): 168781401985218. http://dx.doi.org/10.1177/1687814019852185.
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In minimally invasive surgery, flexible needle insertion is a popular application which has been extensively researched. However, needle steering is challenging for a bevel tip cannula flexible needle due to the nonholonomic constraints and the rebounds of the needle shaft when the needle tip is reoriented. We proposed a novel kinematic model for the bevel tip cannula flexible needle based on bicycle and unicycle models, taking consideration of the deflection of the bevel tip and the rebounds of the needle shaft. Aiming at different types of paths, forward kinematics of the model was analyzed and calculated. Each parameter of the kinematic models was identified based on the experimental data using the least square method. Furthermore, the changing rules of parameters were explored under different angles of the bevel tip. The experimental results show that the errors of the proposed kinematic models are within 2 mm, which is greatly reduced compared to the traditional bicycle or unicycle model, and fulfill a general clinical surgery.
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Shyu, Jenq Huey, I. Tsung Lai, Ta Chang, Yun Cheng Wang, and Ta Wei Lin. "Research of the Joint Workspaces and Kinematic Efficiency of Man-Machine Systems of Bicycles." Key Engineering Materials 450 (November 2010): 13–18. http://dx.doi.org/10.4028/www.scientific.net/kem.450.13.
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Bicycle design largely contradicts human motion, necessitating consideration of both the bicycle structure and the kinematic efficiency in the dimensions of the rider’s limbs, as well as human factor engineering, i.e. comfortability. By focusing on the kinematic model of 5-bar linkage and joints workspace, this study examines the most appropriate bicycle design and the riding posture to ensure that muscles can produce the effective moment and increase driving efficiency of a crank necessary. For upright, racing and recumbent bicycle types, assumptions are made regarding mobility analysis and the system of man-machine systems of bicycles estimated as well. Simulation results can identify the major dimensions of bicycle designing for different riders efficiently by inputting physical measurements of the rider and the angle range of driving force, subsequently increasing the riding efficiency to decrease the load of lower limbs of riders and satisfying ergonomic requirements of bicycle riders.
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Matute, Jose A., Mauricio Marcano, Sergio Diaz, and Joshue Perez. "Experimental Validation of a Kinematic Bicycle Model Predictive Control with Lateral Acceleration Consideration." IFAC-PapersOnLine 52, no. 8 (2019): 289–94. http://dx.doi.org/10.1016/j.ifacol.2019.08.085.
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Fahlstedt, Madelen, Fady Abayazid, Matthew B. Panzer, Antonia Trotta, Wei Zhao, Mazdak Ghajari, Michael D. Gilchrist, et al. "Ranking and Rating Bicycle Helmet Safety Performance in Oblique Impacts Using Eight Different Brain Injury Models." Annals of Biomedical Engineering 49, no. 3 (January 21, 2021): 1097–109. http://dx.doi.org/10.1007/s10439-020-02703-w.
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AbstractBicycle helmets are shown to offer protection against head injuries. Rating methods and test standards are used to evaluate different helmet designs and safety performance. Both strain-based injury criteria obtained from finite element brain injury models and metrics derived from global kinematic responses can be used to evaluate helmet safety performance. Little is known about how different injury models or injury metrics would rank and rate different helmets. The objective of this study was to determine how eight brain models and eight metrics based on global kinematics rank and rate a large number of bicycle helmets (n=17) subjected to oblique impacts. The results showed that the ranking and rating are influenced by the choice of model and metric. Kendall’s tau varied between 0.50 and 0.95 when the ranking was based on maximum principal strain from brain models. One specific helmet was rated as 2-star when using one brain model but as 4-star by another model. This could cause confusion for consumers rather than inform them of the relative safety performance of a helmet. Therefore, we suggest that the biomechanics community should create a norm or recommendation for future ranking and rating methods.
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Fregly, Benjamin J., Felix E. Zajac, and Christine A. Dairaghi. "Bicycle Drive System Dynamics: Theory and Experimental Validation." Journal of Biomechanical Engineering 122, no. 4 (March 22, 2000): 446–52. http://dx.doi.org/10.1115/1.1286678.
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Bicycle pedaling has been studied from both a motor control and an equipment setup and design perspective. In both cases, although the dynamics of the bicycle drive system may have an influence on the results, a thorough understanding of the dynamics has not been developed. This study pursued three objectives related to developing such an understanding. The first was to identify the limitations of the inertial/frictional drive system model commonly used in the literature. The second was to investigate the advantages of an inertial/frictional/compliant model. The final objective was to use these models to develop a methodology for configuring a laboratory ergometer to emulate the drive system dynamics of road riding. Experimental data collected from the resulting road-riding emulator and from a standard ergometer confirmed that the inertial/frictional model is adequate for most studies of road-riding mechanics or pedaling coordination. However, the compliant model was needed to reproduce the phase shift in crank angle variations observed experimentally when emulating the high inertia of road riding. This finding may be significant for equipment setup and design studies where crank kinematic variations are important or for motor control studies where fine control issues are of interest. [S0148-0731(00)02004-5]
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Yavin, Y. "The derivation of a kinematic model from the dynamic model of the motion of a riderless bicycle." Computers & Mathematics with Applications 51, no. 6-7 (March 2006): 865–78. http://dx.doi.org/10.1016/j.camwa.2005.11.026.
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Darzian Rostami, Alireza, Anagha Katthe, Aryan Sohrabi, and Arash Jahangiri. "Predicting Critical Bicycle-Vehicle Conflicts at Signalized Intersections." Journal of Advanced Transportation 2020 (December 2, 2020): 1–16. http://dx.doi.org/10.1155/2020/8816616.
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Continuous development of urban infrastructure with a focus on sustainable transportation has led to a proliferation of vulnerable road users (VRUs), such as bicyclists and pedestrians, at intersections. Intersection safety evaluation has primarily relied on historical crash data. However, due to several limitations, including rarity, unpredictability, and irregularity of crash occurrences, quantitative and qualitative analyses of crashes may not be accurate. To transcend these limitations, intersection safety can be proactively evaluated by quantifying near-crashes using alternative measures known as surrogate safety measures (SSMs). This study focuses on developing models to predict critical near-crashes between vehicles and bicycles at intersections based on SSMs and kinematic data. Video data from ten signalized intersections in the city of San Diego were employed to train logistic regression (LR), support vector machine (SVM), and random forest (RF) models. A variation of time-to-collision called T2 and postencroachment time (PET) were used to specify monitoring periods and to identify critical near-crashes, respectively. Four scenarios were created using two thresholds of 5 and 3 s for both PET and T2. In each scenario, five monitoring period lengths were examined. The RF model was superior compared to other models in all different scenarios and across different monitoring period lengths. The results also showed a small trade-off between model performance and monitoring period length, identifying models with monitoring period lengths of 10 and 20 frames performed slightly better than those with lower or higher lengths. Sequential backward and forward feature selection methods were also applied that enhanced model performance. The best RF model had recall values of 85% or higher across all scenarios. Also, RF prediction models performed better when considering just the rear-end near-crashes with recalls of above 90%.
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Neptune, R. R., and M. L. Hull. "Evaluation of Performance Criteria for Simulation of Submaximal Steady-State Cycling Using a Forward Dynamic Model." Journal of Biomechanical Engineering 120, no. 3 (June 1, 1998): 334–41. http://dx.doi.org/10.1115/1.2797999.
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The objectives of this study were twofold. The first was to develop a forward dynamic model of cycling and an optimization framework to simulate pedaling during submaximal steady-state cycling conditions. The second was to use the model and framework to identify the kinetic, kinematic, and muscle timing quantities that should be included in a performance criterion to reproduce natural pedaling mechanics best during these pedaling conditions. To make this identification, kinetic and kinematic data were collected from 6 subjects who pedaled at 90 rpm and 225 W. Intersegmental joint moments were computed using an inverse dynamics technique and the muscle excitation onset and offset were taken from electromyographic (EMG) data collected previously (Neptune et al., 1997). Average cycles and their standard deviations for the various quantities were used to describe normal pedaling mechanics. The model of the bicycle-rider system was driven by 15 muscle actuators per leg. The optimization framework determined both the timing and magnitude of the muscle excitations to simulate pedaling at 90 rpm and 225 W. Using the model and optimization framework, seven performance criteria were evaluated. The criterion that included all of the kinematic and kinetic quantities combined with the EMG timing was the most successful in replicating the experimental data. The close agreement between the simulation results and the experimentally collected kinetic, kinematic, and EMG data gives confidence in the model to investigate individual muscle coordination during submaximal steady-state pedaling conditions from a theoretical perspective, which to date has only been performed experimentally.
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Gao, Wenrui, Zhonghao Bai, Feng Zhu, Clifford C. Chou, and Binhui Jiang. "A study on the cyclist head kinematic responses in electric-bicycle-to-car accidents using decision-tree model." Accident Analysis & Prevention 160 (September 2021): 106305. http://dx.doi.org/10.1016/j.aap.2021.106305.
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Carriere, Jay, Mohsen Khadem, Carlos Rossa, Nawaid Usmani, Ronald Sloboda, and Mahdi Tavakoli. "Event-Triggered 3D Needle Control Using a Reduced-Order Computationally Efficient Bicycle Model in a Constrained Optimization Framework." Journal of Medical Robotics Research 04, no. 01 (March 2019): 1842004. http://dx.doi.org/10.1142/s2424905x18420047.
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Long flexible needles used in percutaneous procedures such as biopsy and brachytherapy deflect during insertion, thus reducing needle tip placement accuracy. This paper presents a surgeon-in-the-loop system to automatically steer the needle during manual insertion and compensate for needle deflection using an event-triggered controller. A reduced-order kinematic bicycle model incorporating needle tip measurement data from ultrasound images is used to determine steering actions required to minimize needle deflection. To this end, an analytic solution to the reduced-order bicycle model, which is shown to be more computationally efficient than a discrete-step implementation of the same model, is derived and utilized for needle tip trajectory prediction. These needle tip trajectory predictions are used online to optimize the insertion depths (event-trigger points) for steering actions such that needle deflection is minimized. The use of the analytic model and the event-triggered controller also allows for limiting the number and extent of needle rotations (to reduce tissue trauma) in a constrained optimization framework. The system was tested experimentally in three different ex-vivo tissue phantoms with a surgeon-in-the-loop needle insertion device. The proposed needle steering controller was shown to keep the average needle deflection within 0.47 [Formula: see text] 0.21[Formula: see text]mm at the final insertion depth of 120[Formula: see text]mm.
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Bevly, David M., J. Christian Gerdes, and Bradford W. Parkinson. "A New Yaw Dynamic Model for Improved High Speed Control of a Farm Tractor." Journal of Dynamic Systems, Measurement, and Control 124, no. 4 (December 1, 2002): 659–67. http://dx.doi.org/10.1115/1.1515329.
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This paper presents the system identification of a new model for the farm tractor’s yaw dynamics in order to improve automatic control at higher speeds and understand controller limitations from neglecting these dynamics. As speed increases, higher order models are required to maintain accurate lateral control of the vehicle. Neglecting these dynamics can cause the controller to become unstable at the bandwidths required for accurate control at higher speeds. The yaw dynamic model, which is found to be dominated by a second order response, is identified for multiple speeds to determine the effect of velocity on the model. The second order yaw dynamics cannot be represented by the traditional bicycle model. An analytical derivation shows that the model characteristics can, however, be captured by a model consisting of a significant (non-negligible) relaxation length in the front tire. Experimental results are presented showing that the new yaw dynamic model can provide lateral control of the tractor to within 4 cm (1σ) at speeds up to 8 m/s. These results are shown to be an improvement, at high speeds, over controllers based on models (such as a kinematic model) previously used for control of farm equipment.
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Diachuk, Maksym, Said M. Easa, and Joel Bannis. "Path and Control Planning for Autonomous Vehicles in Restricted Space and Low Speed." Infrastructures 5, no. 5 (May 12, 2020): 42. http://dx.doi.org/10.3390/infrastructures5050042.
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This paper presents models of path and control planning for the parking, docking, and movement of autonomous vehicles at low speeds, considering space constraints. Given the low speed of motion, and in order to test and approve the proposed algorithms, vehicle kinematic models are used. Recent works on the development of parking algorithms for autonomous vehicles are reviewed. Bicycle kinematic models for vehicle motion are considered for three basic types of vehicles: passenger car, long wheelbase truck, and articulated vehicles with and without steered semitrailer axes. Mathematical descriptions of systems of differential equations in matrix form and expressions for determining the linearization elements of nonlinear motion equations that increase the speed of finding the optimal solution are presented. Options are proposed for describing the interaction of vehicle overall dimensions with the space boundaries, within which a maneuver should be performed. An original algorithm that considers numerous constraints is developed for determining vehicle permissible positions within the closed boundaries of the parking area, which are directly used in the iterative process of searching for the optimal plan solution using nonlinear model predictive control (NMPC). The process of using NMPC to find the best trajectories and control laws while moving in a semi-limited space of constant curvature (turnabouts, roundabouts) are described. Simulation tests were used to validate the proposed models for both constrained and unconstrained conditions and the output (state-space) and control parameters’ dependencies are shown. The proposed models represent an initial effort to model the movement of autonomous vehicles for parking and have the potential for other highway applications.
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Santini, Stefania, Nicola Albarella, Vincenzo Maria Arricale, Renato Brancati, and Aleksandr Sakhnevych. "On-Board Road Friction Estimation Technique for Autonomous Driving Vehicle-Following Maneuvers." Applied Sciences 11, no. 5 (March 3, 2021): 2197. http://dx.doi.org/10.3390/app11052197.
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In recent years, autonomous vehicles and advanced driver assistance systems have drawn a great deal of attention from both research and industry, because of their demonstrated benefit in reducing the rate of accidents or, at least, their severity. The main flaw of this system is related to the poor performances in adverse environmental conditions, due to the reduction of friction, which is mainly related to the state of the road. In this paper, a new model-based technique is proposed for real-time road friction estimation in different environmental conditions. The proposed technique is based on both bicycle model to evaluate the state of the vehicle and a tire Magic Formula model based on a slip-slope approach to evaluate the potential friction. The results, in terms of the maximum achievable grip value, have been involved in autonomous driving vehicle-following maneuvers, as well as the operating condition of the vehicle at which such grip value can be reached. The effectiveness of the proposed approach is disclosed via an extensive numerical analysis covering a wide range of environmental, traffic, and vehicle kinematic conditions. Results confirm the ability of the approach to properly automatically adapting the inter-vehicle space gap and to avoiding collisions also in adverse road conditions (e.g., ice, heavy rain).
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Salt Ducajú, Julián M., Julián J. Salt Llobregat, Ángel Cuenca, and Masayoshi Tomizuka. "Autonomous Ground Vehicle Lane-Keeping LPV Model-Based Control: Dual-Rate State Estimation and Comparison of Different Real-Time Control Strategies." Sensors 21, no. 4 (February 23, 2021): 1531. http://dx.doi.org/10.3390/s21041531.
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In this contribution, we suggest two proposals to achieve fast, real-time lane-keeping control for Autonomous Ground Vehicles (AGVs). The goal of lane-keeping is to orient and keep the vehicle within a given reference path using the front wheel steering angle as the control action for a specific longitudinal velocity. While nonlinear models can describe the lateral dynamics of the vehicle in an accurate manner, they might lead to difficulties when computing some control laws such as Model Predictive Control (MPC) in real time. Therefore, our first proposal is to use a Linear Parameter Varying (LPV) model to describe the AGV’s lateral dynamics, as a trade-off between computational complexity and model accuracy. Additionally, AGV sensors typically work at different measurement acquisition frequencies so that Kalman Filters (KFs) are usually needed for sensor fusion. Our second proposal is to use a Dual-Rate Extended Kalman Filter (DREFKF) to alleviate the cost of updating the internal state of the filter. To check the validity of our proposals, an LPV model-based control strategy is compared in simulations over a circuit path to another reduced computational complexity control strategy, the Inverse Kinematic Bicycle model (IKIBI), in the presence of process and measurement Gaussian noise. The LPV-MPC controller is shown to provide a more accurate lane-keeping behavior than an IKIBI control strategy. Finally, it is seen that Dual-Rate Extended Kalman Filters (DREKFs) constitute an interesting tool for providing fast vehicle state estimation in an AGV lane-keeping application.
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Pein, Wayne. "Bicyclist Performance on a Multiuse Trail." Transportation Research Record: Journal of the Transportation Research Board 1578, no. 1 (January 1997): 127–31. http://dx.doi.org/10.3141/1578-16.
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Bicyclist crossing time from a full stop was measured using video recording equipment at 16 diverse trail-roadway intersections (two to six lanes, stop or signal controlled, divided or undivided) of the Pinellas Trail in Pinellas County, Florida. A total of 442 bicyclists (single individuals or randomly selected individuals from a group) were timed. The cruising speed of 65 bicyclists was also determined. A linear regression model was fit to the time and crossing-distance data. A linear regression was also fit to eight 85th percentile crossing-time points that were calculated from grouped raw data. Using kinematic physics, in which bicycle acceleration and intersection crossing velocity are variables, a theoretical equation was derived to predict bicyclist crossing time for any distance. This derived equation is a linear function of distance, so the regression coefficients could then be used to estimate bicyclist crossing velocity and acceleration on the Pinellas Trail. These estimated values for bicyclist acceleration and intersection crossing velocity compare favorably with the scant available data from foreign and domestic sources. Thus, the crossing-time prediction equation can be a useful tool when designing intersections for bicyclists, with application in signal timing and crossing-sight distance calculations.
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Hull, Maury L., and Hiroko K. Gonzalez. "The Effect of Pedal Platform Height on Cycling Biomechanics." International Journal of Sport Biomechanics 6, no. 1 (February 1990): 1–17. http://dx.doi.org/10.1123/ijsb.6.1.1.
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Using a five-bar linkage model of the leg/bicycle system in conjunction with experimental kinematic and pedal force data, the inverse dynamics problem is solved to yield the intersegmental moments. Among the input data that affect the problem solution is the height of the pedal platform. This variable is isolated and its effects on the total joint moments are studied as it assumes values over a ±4-cm range. Platform height variation affects the total joint moment peak values by up to 13%. Relying on a cost function derived from the hip and knee moments, it is found that the platform height that minimizes the cost function is +2 cm. The sensitivity of the cost function to the platform height variable is low; over the variable range the cost function increases 2% above the minimum. These results hold for a pedaling rate of 90 rpm. As pedaling rate is varied above and below 90 rpm, the sensitivity of the cost function increases. The platform heights that minimize the cost function are the lower and upper limits for 60 and 120 rpm, respectively. Thus the platform height variable interacts with pedaling rate, requiring a compromise in platform height adjustment. The compromise height depends on the individual’s preferred pedaling rate range.
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Liu, Yan Bin, Qing Hua Ji, Xiao Chao Sun, and Jian Hai Han. "Kinematics and Trajectory Tracking Motion Plan of an Unmanned Bicycle." Advanced Materials Research 152-153 (October 2010): 341–45. http://dx.doi.org/10.4028/www.scientific.net/amr.152-153.341.
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Kinematics and ground plane trajectory tracking motion plan of an unmanned bicycle were researched in this paper. For the unmanned bicycle controlled by a steering torque, a pedaling toque and a tilting torque, rigorous kinematics model was set up and discussed, and when the ground plane trajectories and the bicycle tilting angular trajectory were given, by use of Back-stepping design means, the steering angular velocity, the rear wheel rotation angular velocity and the other motion parameters trajectories of the unmanned bicycle were planned and discussed, the simulation results showed that the kinematics model built was accurate and rigorous, all above motion parameter plans were reasonable.
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Condrea, OA, A. Chiru, RL Chiriac, and S. Vlase. "Mathematical model for studying cyclist kinematics in vehicle-bicycle frontal collisions." IOP Conference Series: Materials Science and Engineering 252 (October 2017): 012003. http://dx.doi.org/10.1088/1757-899x/252/1/012003.
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TAN, ZHENG, YINGFU GUO, GUIBING LI, and LINGBO YAN. "KINEMATICS AND INJURY MECHANISM OF CYCLIST LOWER LIMB IN VEHICLE-TO-BICYCLE COLLISIONS." Journal of Mechanics in Medicine and Biology 20, no. 06 (August 2020): 2050035. http://dx.doi.org/10.1142/s0219519420500359.
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Accident data show that lower limb is one of the most frequently injured body parts for cyclists in vehicle collisions. However, studies of cyclist lower limb injuries and protection are still sparse. Therefore, the purpose of this study is to investigate the kinematics and injury mechanism of cyclist lower limb in vehicle-to-bicycle collisions considering different impact boundary conditions. To achieve this, the finite element (FE) modeling approach and an FE human body lower limb model with detailed muscles were employed, and impact boundary conditions with different vehicle front-end shapes and cycling postures were considered. Predictions of lower limb kinematics, knee ligament elongation and bending moment of upper and lower leg were used for analysis. The simulation results show that cycling posture has a significant influence on cyclist lower limb kinematics and injury risk, lateral bending toward the direction of vehicle or vehicle moving combining with lateral shearing is the main mechanism for cyclist knee ligament injuries, and injuries to long bones of cyclist leg in vehicle impacts could form lateral bending at both directions. The findings suggest that the influence of cycling posture and distinct difference in injury mechanism between cyclist and pedestrian should be considered in the assessment of vehicle safety design for cyclist lower limb protection.
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Yuan, Min, Linpeng Hou, and Hui Jing. "Analysis of the Damage of Cyclists in Electric Bicycle - Sedan Angle Collision." International Journal of Ambient Computing and Intelligence 11, no. 1 (January 2020): 99–114. http://dx.doi.org/10.4018/ijaci.2020010106.
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In order to study the vulnerable factors of the traffic accidents—the cyclist's injury factor at the moment of the accident—the computer simulation analysis method is used to restore the information collected by a real accident combined with the scene. From the established multi-rigid kinematics model, the corresponding injury situation of a body structure of a traffic accident rider is obtained, which involves the collision speed, the collision angle, the acceleration of each part of the human body and the force. The data is compared with ECE R44, FMVSS 213 and Euro NCAP 2009 regulations to analyze and restore various factors of bicycle injury in the collision. The results show that when the car and the non-motor vehicle have a low-angle collision, the cyclist's injury is mainly caused by the collision with the ground after the parabola movement, and the damage position of the human body depends on the order of contact with the ground.
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Cantisani, Giuseppe, Laura Moretti, and Yessica De Andrade Barbosa. "Safety Problems in Urban Cycling Mobility: A Quantitative Risk Analysis at Urban Intersections." Safety 5, no. 1 (January 22, 2019): 6. http://dx.doi.org/10.3390/safety5010006.
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The attention to the most vulnerable road users has grown rapidly in recent decades. The experience gained reveals an important number of cyclist fatalities due to road crashes; most of which occur at intersections. In this study, dispersion of trajectories in urban intersections has been considered to identify the whole conflict area and the largest conflict areas between cars and bicycles, and the speeds have been used to calculate exposure time of cyclists and reaction time available to drivers to avoid collision. These data allow the summary approach to the problem, while a risk probability model has been developed to adopt an elementary approach analysis. A quantitative damage model has been proposed to classify each conflict point, and a probabilistic approach has been defined to consider the traffic volume and the elementary unit of exposure. The combination of damage and probability, permitted to assess the risk of crash, at the examined intersection. Three types of urban four-arm intersection, with and without bike paths, were considered. For each scheme, the authors assessed the risk of collision between the cyclist and the vehicle. The obtained results allowed the identification of the most hazardous maneuvers and highlighted that geometry and kinematics of traffic movements cannot be overlooked, when designing an urban road intersection. The strategy proposed by the authors could have a significant impact on the risk management of urban intersections. The obtained results and the proposed hazard estimation methodology could be used to design safer intersections.
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Huang, Chun-Feng, Bang-Hao Dai, and T. J. Yeh. "Determination of Motor Torque for Power-Assist Electric Bicycles Using Observer-Based Sensor Fusion." Journal of Dynamic Systems, Measurement, and Control 140, no. 7 (March 28, 2018). http://dx.doi.org/10.1115/1.4039280.
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This paper proposes a sensor fusion algorithm to determine the motor torque for power-assist electric bicycles. Instead of using torque sensors to directly measure the pedaling torque, outputs from a wheel encoder and a six-axis inertial measurement unit (IMU) are processed by the fusion algorithm to estimate the slope angle of the road and the longitudinal acceleration of the bicycle for conducting mass compensation, gravity compensation, and friction compensation. The compensations allow the ride of the electric bicycle on hills to be as effortless as the ride of a plain bicycle on the level ground regardless of the weight increase by the battery and the motor. The sensor fusion algorithm is basically an observer constructed on the kinematic model which describes the time-varying characteristics of the gravity vector observed from a frame moving with the bicycle. By exploiting the structure of the observer model, convergence of the estimation errors can be easily achieved by selecting two constant, subgain matrices in spite of the time-varying characteristics of the model. The validity of the sensor fusion is verified by both numerical simulations and experiments on a prototype bicycle.
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Abderezaei, Javid, Fargol Rezayaraghi, Brigit Kain, Andrea Menichetti, and Mehmet Kurt. "An Overview of the Effectiveness of Bicycle Helmet Designs in Impact Testing." Frontiers in Bioengineering and Biotechnology 9 (September 27, 2021). http://dx.doi.org/10.3389/fbioe.2021.718407.
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Cycling accidents are the leading cause of sports-related head injuries in the US. Conventional bicycle helmets typically consist of polycarbonate shell over Expanded Polystyrene (EPS) foam and are tested with drop tests to evaluate a helmet’s ability to reduce head kinematics. Within the last decade, novel helmet technologies have been proposed to mitigate brain injuries during bicycle accidents, which necessitates the evaluation of their effectiveness in impact testing as compared to conventional helmets. In this paper, we reviewed the literature to collect and analyze the kinematic data of drop test experiments carried out on helmets with different technologies. In order to provide a fair comparison across different types of tests, we clustered the datasets with respect to their normal impact velocities, impact angular momentum, and the type of neck apparatus. When we analyzed the data based on impact velocity and angular momentum clusters, we found that the bicycle helmets that used rotation damping based technology, namely MIPS, had significantly lower peak rotational acceleration (PRA) and Generalized Acceleration Model for Brain Injury Threshold (GAMBIT) as compared to the conventional EPS liner helmets (p < 0.01). SPIN helmets had a superior performance in PRA compared to conventional helmets (p < 0.05) in the impact angular momentum clustered group, but not in the impact-velocity clustered comparisons. We also analyzed other recently developed helmets that primarily use collapsible structures in their liners, such as WaveCel and Koroyd. In both of the impact velocity and angular momentum groups, helmets based on the WaveCel technology had significantly lower peak linear acceleration (PLA), PRA, and GAMBIT at low impact velocities as compared to the conventional helmets, respectively (p < 0.05). The protective gear with the airbag technology, namely Hövding, also performed significantly better compared to the conventional helmets in the analyzed kinematic-based injury metrics (p < 0.001), possibly due to its advantage in helmet size and stiffness. We also observed that the differences in the kinematic datasets strongly depend on the type of neck apparatus. Our findings highlight the importance and benefits of developing new technologies and impact testing standards for bicycle helmet designs for better prevention of traumatic brain injury (TBI).
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Mathieu, Johanna L., and J. Karl Hedrick. "Transformation of a Mismatched Nonlinear Dynamic System into Strict Feedback Form." Journal of Dynamic Systems, Measurement, and Control 133, no. 4 (April 11, 2011). http://dx.doi.org/10.1115/1.4003795.
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Dynamic surface control is a robust nonlinear control technique. It is generally applied to mismatched dynamic systems in strict feedback form. We have developed a new method of defining states and state-dependent disturbances to transform a mismatched dynamic system into strict feedback form. We apply this method to a multi-input multi-output (MIMO) extended-state kinematic model of a bicycle. We show how a dynamic surface controller can be used for position tracking of the bicycle. The performance of the dynamic surface controller is compared with that of a controller designed using feedback linearization. Transformation of the dynamic system into strict feedback form allows us to successfully apply dynamic surface control. Both the dynamic surface controller and the feedback linearization controller perform well in the absence of disturbances. The dynamic surface controller is more robust when disturbances are introduced; however, a large control effort is required to reject the disturbances. Our method of defining new states and state-dependent disturbances to transform mismatched nonlinear dynamic systems into strict feedback form could be used on other systems requiring robust nonlinear control.
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Kanchwala, Husain, Icaro Bezerra Viana, and Nabil Aouf. "Cooperative path-planning and tracking controller evaluation using vehicle models of varying complexities." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, July 28, 2020, 095440622094546. http://dx.doi.org/10.1177/0954406220945468.
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This paper discusses cooperative path-planning and tracking controller for autonomous vehicles using a distributed model predictive control approach. Mixed-integer quadratic programming approach is used for optimal trajectory generation using a linear model predictive control for path-tracking. Cooperative behaviour is introduced by broadcasting the planned trajectories of two connected automated vehicles. The controller generates steering and torque inputs. The steering and drive motor actuator constraints are incorporated in the control law. Computational simulations are performed to evaluate the controller for vehicle models of varying complexities. A 12-degrees-of-freedom vehicle model is developed and is subsequently linearised to be used as the plant model for the linearised model predictive control-based tracking controller. The model behaviour is compared against the kinematic, bicycle and the sophisticated high-fidelity multi-body dynamics CarSim model of the vehicle. Vehicle trajectories used for tracking are longitudinal and lateral positions, velocities and yaw rate. A cooperative obstacle avoidance manoeuvre is performed at different speeds using a co-simulation between the controller model in Simulink and the high-fidelity vehicle model in CarSim. The simulation results demonstrate the effectiveness of the proposed method.
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Hu, Shuaishuai, Xiaojiang Lv, Haiyang Zhang, Pengxiang Wang, and Pengyun Gu. "Head kinematics study of E-bicycle rider in car to E-bicycle side collisions." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, August 27, 2020, 095440702095007. http://dx.doi.org/10.1177/0954407020950073.
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In recent years, car to bicycle collisions take place more and more frequently, which have attracted the attention of some organizations and engineers. They are trying to make some rules for cars to realize better bicyclist protection, including defining new head impact location area and head impact velocity in pedestrian protection tests. However, car to E-bicycle collisions occur more than car to bicycle collisions in China. Therefore, vehicle to E-bicycle collisions should be researched to define appropriate head impact location area and head impact velocity in pedestrian protection tests for cars in Chinese market. In this article, the head kinematics of E-bicycle riders in car to E-bicycle side collisions are studied. First, through analyzing data from China In-Depth Accident Study Database (which conducts field investigation, analysis, and research on traffic accidents in China), some representative conditions and key parameters in car to E-bicycle collisions are extracted. Second, a condition of car to E-bicycle side collision from above analysis is simulated. Third, an experiment according to the above condition is performed and the finite element models in the above simulation are validated. Then, a series of conditions are simulated by using the validated models, and some factors affecting head impact locations and head impact velocities in car to E-bicycle side collisions are studied. Finally, some factors that affect the head kinematics of E-bicycle riders in car to E-bicycle collisions are identified and some results of head movement in these collisions are concluded, such as head impact locations and head impact velocities.
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Yap, Hwa Jen, Jenn Guey NG, Zanatul Aqillah ZAKARIA, Zahari Taha, Siow-Wee Chang, and Keem Siah Yap. "Design and development of 6-DOF system for Virtual Bicycle." Movement, Health & Exercise 5, no. 2 (October 18, 2016). http://dx.doi.org/10.15282/mohe.v5i2.100.
Full textAbstract:
There are many variations to the competition that takes place in Olympic track cycling. Hence, a bicycle simulator will bring a lot of benefits to the coaches and the athletes in a practical training. It is extremely low cost compared to a real Velodrome track which is required long construction time due to the unique geometry and size. In this project, a 6-degree-of-freedom (6-DOF) motion platform is designed and developed to simulate the Velodrome track cycling. The parallel manipulator was chosen to control the moving platform because of higher accuracy and greater weight to strength ratio compare to serial manipulator. The 6-DOF platform is controlled by linear actuators and micro-controller. An optical encoder was installed for closed-loop position feedback control. An inverse kinematics model was developed to obtain the movement of the platform, and it was validated with its CAD model. Besides, a design feasibility program was developed to calculate the optimum design dimension of the motion platform. All the positions (3-axes) and orientations (3-rotational axes) data are tracked for analysis purpose. A lab-scale prototype was successfully built for the analysis and validation purpose. A standard Velodrome track dimensions was chosen to be simulated. On the other hand, a gyro accelerometer was installed at the platform to acquire the actual motion of the platform. The data will be used to validate the control algorithms and accuracy of the motion platform. The experiment was conducted and the results are analyzed for further development.
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Bland, Megan L., Craig McNally, and Steven Rowson. "Differences in Impact Performance of Bicycle Helmets During Oblique Impacts." Journal of Biomechanical Engineering 140, no. 9 (May 24, 2018). http://dx.doi.org/10.1115/1.4040019.
Full textAbstract:
Cycling is a leading cause of sport-related head injuries in the U.S. Although bicycle helmets must comply with standards limiting head acceleration in severe impacts, helmets are not evaluated under more common, concussive-level impacts, and limited data are available indicating which helmets offer superior protection. Further, standards evaluate normal impacts, while real-world cyclist head impacts are oblique—involving normal and tangential velocities. The objective of this study was to investigate differences in protective capabilities of ten helmet models under common real-world accident conditions. Oblique impacts were evaluated through drop tests onto an angled anvil at common cyclist head impact velocities and locations. Linear and rotational accelerations were evaluated and related to concussion risk, which was then correlated with design parameters. Significant differences were observed in linear and rotational accelerations between models, producing concussion risks spanning >50% within single impact configurations. Risk differences were more attributable to linear acceleration, as rotational varied less between models. At the temporal location, shell thickness, vent configuration, and radius of curvature were found to influence helmet effective stiffness. This should be optimized to reduce impact kinematics. At the frontal, helmet rim location, liner thickness tapered off for some helmets, likely due to lack of standards testing at this location. This is a frequently impacted location for cyclists, suggesting that the standards testable area should be expanded to include the rim. These results can inform manufacturers, standards bodies, and consumers alike, aiding the development of improved bicycle helmet safety.