Stopping Maneuver Research Articles

Determination of the noise reduction potential at bus stops through the use of hybrid and electric buses

To investigate the noise reduction potential of electric buses at bus stops, extensive microphone measurements were conducted during the stopping process of IC powered, hybrid, and all-electric buses. A number of 18 microphones were placed along the roadway at heights of 1.2 m, 3 m, and 4.5 m. The distance between the mics in the direction of travel was 6 m in each case. In the course of the measurement, 3 bus types were measured. More than 200 measurements were performed in total. The stopping maneuvers consisted of decelerating from 30 km/h and 50 km/h, staying at a fixed position, opening and closing doors, and accelerating to 30 km/h and 50 km/h, respectively. The maneuvers were performed in both directions of travel.

Electric powered wheelchair control using user-independent classification methods based on surface electromyography signals.

Wheelchairs are one of the most popular assistive technology (AT) among individuals with motor impairments due to their comfort and mobility. People with finger problems may find it difficult to operate wheelchairs using the conventional joystick control method. Therefore, in this research study, a hand gesture-based control method is developed for operating an electric-powered wheelchair (EPW). This study selected a comfort-based hand position to determine the stop maneuver. An additional exploration was undertaken to investigate four gesture recognition methods: linear regression (LR), regularized linear regression (RLR), decision tree (DT), and multi-class support vector machine (MC-SVM). The first two methods, LR and RLR, have promising accuracy values of 94.85% and 95.88%, respectively, but each new user must be trained. To overcome this limitation, this study explored two user-independent classification methods: MC-SVM and DT. These methods effectively addressed the finger dependency issue and demonstrated remarkable success in recognizing gestures across different users. MC-SVM has about 99.05% of both precision and accuracy, and the DT has about 97.77% accuracy and precision. All six participants were successful in controlling the EPW without any collisions. According to the experimental results, the proposed approach has high accuracy and can address finger dependency issues.

Electrical non-invasive determination of aging progress and failure mechanisms of field aged automotive lead batteries

The increasing prevalence of electrically assisted functions in vehicles makes a reliable and safe power supply from the 12V lead battery more important to meet high safety requirements. In addition to traditional battery demands – Starting, Lighting, Ignition – new performance requirements related to a ‘safe stop maneuver’ have emerged. To ensure a consistent safety approach for the vehicle and its electrical system, it is crucial to understand the reliability of the battery, including its aging and failure behavior. Previous methods for determining reliability and failure rates based on subjective teardown analyses can result in different assessments, highlighting the need for an objective method for failure determination. This study presents a nondestructive electrical test method for 12V lead batteries from car workshops and roadside assistance that identifies aging progress and dominant aging mechanisms through equation-based analysis of measured data. The battery’s ability to maintain a specified voltage threshold during an alternative load profile, the ‘safe stop maneuver’ is used to evaluate its performance for future driving applications. Teardown analyses confirmed the aging mechanisms identified during electrical testing. With a sufficiently long observation period to account for seasonal effects, this test procedure can be used to establish an objectively determined sample for further statistical reliability analyses. The results of the procedure will be published in a follow-up study.

Numerical investigation of stopping maneuver for two by reversing propeller at different speeds

Numerical investigation of stopping maneuver for two by reversing propeller at different speeds

Learning-Based Shared Control Using Gaussian Processes for Obstacle Avoidance in Teleoperated Robots

Physically inspired models of the stochastic nature of the human-robot-environment interaction are generally difficult to derive from first principles, thus alternative data-driven approaches are an attractive option. In this article, Gaussian process regression is used to model a safe stop maneuver for a teleoperated robot. In the proposed approach, a limited number of discrete experimental training data points are acquired to fit (or learn) a Gaussian process model, which is then used to predict the evolution of the process over a desired continuous range (or domain). A confidence measure for those predictions is used as a tuning parameter in a shared control algorithm, and it is demonstrated that it can be used to assist a human operator by providing (low-level) obstacle avoidance when they utilize the robot to carry out safety-critical tasks that involve remote navigation using the robot. The algorithm is personalized in the sense that it can be tuned to match the specific driving style of the person that is teleoperating the robot over a specific terrain. Experimental results demonstrate that with the proposed shared controller enabled, the human operator is able to more easily maneuver the robot in environments with (potentially dangerous) static obstacles, thus keeping the robot safe and preserving the original state of the surroundings. The future evolution of this work will be to apply this shared controller to mobile robots that are being deployed to inspect hazardous nuclear environments, ensuring that they operate with increased safety.

Stopping by looking: A driver-pedestrian interaction study in a coupled simulator using head-mounted displays with eye-tracking

Automated vehicles (AVs) can perform low-level control tasks but are not always capable of proper decision-making. This paper presents a concept of eye-based maneuver control for AV-pedestrian interaction. Previously, it was unknown whether the AV should conduct a stopping maneuver when the driver looks at the pedestrian or looks away from the pedestrian. A two-agent experiment was conducted using two head-mounted displays with integrated eye-tracking. Seventeen pairs of participants (pedestrian and driver) each interacted in a road crossing scenario. The pedestrians' task was to hold a button when they felt safe to cross the road, and the drivers' task was to direct their gaze according to instructions. Participants completed three 16-trial blocks: (1) Baseline, in which the AV was pre-programmed to yield or not yield, (2) Look to Yield (LTY), in which the AV yielded when the driver looked at the pedestrian, and (3) Look Away to Yield (LATY), in which the AV yielded when the driver did not look at the pedestrian. The driver's eye movements in the LTY and LATY conditions were visualized using a virtual light beam. Crossing performance was assessed based on whether the pedestrian held the button when the AV yielded and released the button when the AV did not yield. Furthermore, the pedestrians' and drivers' acceptance of the mappings was measured through a questionnaire. The results showed that the LTY and LATY mappings yielded better crossing performance than Baseline. Furthermore, the LTY condition was best accepted by drivers and pedestrians. Eye-tracking analyses indicated that the LTY and LATY mappings attracted the pedestrian's attention, while pedestrians still distributed their attention between the AV and a second vehicle approaching from the other direction. In conclusion, LTY control may be a promising means of AV control at intersections before full automation is technologically feasible.

Minimizing the Effects of Urban Mobility-on-Demand Pick-Up and Drop-Off Stops: A Microscopic Simulation Approach

Short-term disruptions can have a long-lasting negative effect on traffic flow exceeding the duration of the disruption itself. This is especially the case when traffic demand approaches the network’s capacity. On-demand ride-sourcing services like ride-hailing and ride-pooling do not only have an impact on the overall kilometers driven in a network, but also conduct frequent stopping maneuvers to let passengers board and alight. As further growth of such services is expected, municipalities will need to find ways to organize and, if needed, regulate such activities. This paper proposes, evaluates, and discusses two possible methods that can be part of a holistic strategy to mitigate the impacts of frequent mobility-on-demand curbside stops in an urban environment. The first method adapts the positions of stops at an intersection according to real-time signal timings without adding another variable to the already quite complex traffic signal optimization. The second method discusses a temporary reduction of the number of allowed stopping maneuvers on saturated street sections or in other sensitive areas. Both methods are evaluated using microscopic traffic simulation and result in significant reductions of average vehicle delay as well as standard deviation thereof in all investigated traffic demand scenarios. These results indicate that the proposed methods can help to preserve a stable traffic state in situations close to the capacity limit, which is to the benefit of all stakeholders involved.

Electric Wheelchair Control Using Wrist Rotation Based on Analysis of Muscle Fatigue

The wheelchair is one of the most common assistive technologies for people with motor impairment, due to its environmentally friendly features in terms of mobility and comfort. However, the operational method for conventional wheelchair is still inconvenience for people with finger problems. Therefore, in the project, a novel control method to operate an electric wheelchair, using hand gestures ( wrist rotation) is developed. Sixty-five (65) participants were involved in this study. Five hand gestures were considered and studied for forward, backward, right, left, and stop maneuvers while considering human ergonomics factor. In this study, the stop maneuver was determined based on the most comfortable hand position to mitigate a fatigue experience, with two gesture classifying methods further investigated. The first method based on threshold has a promising accuracy of 96%, and 91% precision. This method however requires a calibration every time a new user is introduced. The second method, a Naïve Bayes approach, was observed to solve the problem, as it has about 99% of both the accuracy and the precision. The evaluation of this method was then conducted with six participants that operated the wheelchair to follow the trajectories from start to end. The results showed that the participants comfortably controlled the developed wheelchair system to the goal without any collision. Results from experiments indicate that the proposed approach has high accuracy and the potential to solve the problem related to finger dependencies and hand fatigue.

Numerical investigation of the ship propeller load under reversed propulsion condition

Stopping maneuver is an important research topic in ship maneuverability. The stopping ability of ship is not only related to the hydrodynamic characteristics of hull, rudder and propeller, but also related to the capacity of main engine. However, there are few researches on the capacity of main engine under reversed propulsion condition. In the paper, a numerical water tank is established to simulate the propeller loads using the computational fluid dynamics (CFD) software STAR CCM+. The numerical model is firstly validated by experimental data, and then is used to investigate the propeller loads on a full-scale model with different ship speed and propeller speed. By dimensionless, the relations between the advance coefficient and the load coefficients are shown as J - KT curves and J - KQ curves. Furtherly, the flow structures near the propeller and the pressure on the propeller with different J values are investigated. The simulations reveal that the flow velocities induced by the reversed propulsion of the propeller is similar to the wake flow by ship with J = -0.49. That is the reason for the minimum points of J - KT and J - KQ curve occurring in cases with J = -0.49. Subsequently, the capacity of the main engine and the output load of the propeller are considered comprehensively. The relations between the ship speeds and the maximum output loads on the propeller are discussed in details.

CFD numerical simulations of inertia stopping of a very large gas carrier using overset grid technology and body-force propeller

With the development of International shipping, waterways all over the world are becoming increasingly crowded. Research on inertia stopping ability of large ships is essential to voyage safety. At present, the inertial stopping of ship is mainly measured by ship model test, and there is little work to study the performance using CFD technology. STARCCM+based on the ship 6-DOF motion and overset grid technology and body-force method are used to numerically simulate the inertia stopping maneuver of a very large gas carrier. By controlling the rotation speed of the propeller, the ship is in a stable state of motion. Then set the speed to zero.The motion state and detailed flow field information of the ship model during motion can be got by solving viscous flow field. To verify the accuracy of numerical prediction results, ship model test is launched. Both the trajectory of the ship and the value of the characteristic parameter match very well.

An Interacting Multiple Model Approach for Target Intent Estimation at Urban Intersection for Application to Automated Driving Vehicle

Research shows that urban intersections are a hotspot for traffic accidents which cause major human injuries. Predicting turning, passing, and stop maneuvers against surrounding vehicles is considered to be fundamental for advanced driver assistance systems (ADAS), or automated driving systems in urban intersections. In order to estimate the target intent in such situations, an interacting multiple model (IMM)-based intersection-target-intent estimation algorithm is proposed. A driver model is developed to represent the driver’s maneuvering on the intersection using an IMM-based target intent classification algorithm. The performance of the intersection-target-intent estimation algorithm is examined through simulation studies. It is demonstrated that the intention of a target vehicle is successfully predicted based on observations at an individual intersection by proposed algorithms.

THE CRITICAL BEHAVIOR OF THE M. BICEPS FEMORIS FOR THE RISK OF INJURY — A SIMULATION STUDY

The behavior of the M. biceps femoris with regard to its enormous vulnerability to injuries in sport remains unclear. Despite prevention programs, the rate of injuries of the hamstring muscles has risen by more than 4% in recent years. To get more insights into its function, the aim of this study was to examine the effect of different muscle insertion characteristics and activation levels using a simulation. We created a multi-segmented muscle model for evaluating the critical behavior of M. biceps femoris during a one-legged stopping maneuver. We analyzed muscle function, movement of the knee angle after initial ground contact, the simulated muscle force and the stop torques in the knee joint. The insertion geometry has an elementary effect on knee joint function and contributes to knee extension. The muscle activity plays a decisive role in elementary muscle function regarding the knee joint and in this regard the internal load of the M. biceps femoris increased without showing any visible effects on the kinematics. The anthropometry and function of this muscle needs to be taken into account to assess its effects on injury risk.

CFD study of ship stopping maneuver by overset grid technique

The crowded waterways and worse maneuverability of large ships could cause more collision accidents. Therefore, it is necessary to study stopping ability of ships to ensure the navigational safety. In this paper, the CFD solver naoe-FOAM-SJTU associated with dynamic overset grid method is used to simulate several types of maneuvers of KVLCC1 ship model. Stopping maneuvers with reversing propeller, turning rudder with/without propeller are simulated to predict the ship stopping performance. Turning circle maneuver is also simulated to predict the advance and comparisons with stopping distance of other stopping maneuvers are discussed. Self-propulsion simulation is conducted firstly to validate the present CFD approach through comparisons with available experiments. Stopping maneuver simulations start from the steady state of self-propulsion, then different types of stopping maneuver is carried out by controlling the propeller and rudder. In addition, deep and shallow water conditions are both computed to illustrate the water depth effect on the stopping performance. The predicted trajectory and ship speed of different stopping maneuvers are presented and analyzed. Detail information of flow visualizations including pressure distribution and wake flow during stopping maneuver are discussed to explain the stopping behavior. It is concluded that the turning circle maneuver is the most preferable way to avoid the collision in open sea. However, if the ship needs to stop in port or waterways, then the reversing propeller (RP) is better due to the fact that it meets the relatively shorter lateral deviation.

Human tracking control system using Kinect sensors on wheelchair based on Arduino

Many people with disabilities who do not get the opportunity to work or the same rights as non-disabled people give encouragement to conduct research to help persons with disabilities. Currently there are several types of research and development on mind wave wheelchairs, but the developed wheelchair has limitations for blind users. Most of the wheelchairs require the user to see the surrounding area in order to move the wheelchair. Therefore, it is not optimal for disabled people who are also visually impaired. To help blind people with disabilities, a wheelchair system with human tracking control capabilities need to be developed. In this study, a prototype of a wheelchair system was developed using Kinect Xbox 360 sensor to read motion data which will then be processed on a mini PC before being sent to an Arduino pro micro based main control to drive the DC motor and track the wheelchair. The prototype has been tested by conducting start and stop maneuver. The results show that the wheelchair prototype has an average success rate for conducting a start maneuver of 87.50% and the average success rate for being able to stop after carrying out a maneuver of 85.83%. In the future the wheelchair is expected to be used by persons with multiple disabilities, namely those who are blind who cannot use an electric wheelchair with mind wave control to help with their daily mobility.

Joint Optimization of Signal Phasing and Timing and Vehicle Speed Guidance in a Connected and Autonomous Vehicle Environment

A joint traffic signal optimization algorithm is proposed which utilizes connected vehicle (CV) information to identify optimum signal timing and phasing plans while also providing speed guidance to individual vehicles to minimize total number of stopping maneuvers. The contribution of this paper is provision of speed guidance to both autonomous (AVs) and human-driven speed guidance-enabled vehicles (SGVs), recognizing that the latter may not fully comply with the speed guidance and would require some delay (i.e., reaction time) to implement it. The control algorithm is triggered at regular discrete time intervals during which CV information is used to identify the presence of non-CVs and incorporate them into signal timing decision-making. Optimal speeds are determined for any AVs or SGVs so that they can travel through the intersection at the expected departure time without stopping, considering both acceleration/deceleration and human reaction times. Simulation tests are performed under different CV, AV, and SGV penetration rates, while explicitly modeling the potential human errors and varying acceptance levels. The results suggest that average delay and number of stops decrease with higher CV penetration rate. Furthermore, the number of stops decreases as the ratio of both AVs and SGVs increases. While AVs are about 10% more efficient than SGVs, human-driven vehicles still provide a benefit even when they do not fully comply with speed guidance information. Sensitivity tests suggest that operation is not significantly affected by the range of human driver errors in speed compliance or range of reaction times.

Methods to reduce dimensionality and identify candidate solutions in multi-objective signal timing problems

Adjusting traffic signal timings is a practical way for agencies to manage urban traffic without the need for significant infrastructure investments. Signal timings are generally selected to minimize the total control delay vehicles experience at an intersection, particularly when the intersection is isolated or undersaturated. However, in practice, there are many other potential objectives that might be considered in signal timing design, including: total passenger delay, pedestrian delays, delay inequity among competing movements, total number of stopping maneuvers, among others. These objectives do not tend to share the same relationships with signal timing plans and some of these objectives may be in direct conflict. The research proposes the use of a new multi-objective optimization (MOO) visualization technique—the mosaic plot—to easily quantify and identify significant tradeoffs between competing objectives using the set of Pareto optimal solutions that are normally provided by MOO algorithms. Using this tool, methods are also proposed to identify and remove potentially redundant or unnecessary objectives that do not have any significant tradeoffs with others in an effort to reduce problem dimensionality. Since MOO procedures will still be needed if more than one objective remains and MOO algorithms generally provide a set of candidate solutions instead of a single final solution, two methods are proposed to rank the set of Pareto optimal solutions based on how well they balance between the competing objectives to provide a final recommendation. These methods rely on converting the objectives to dimensionless values based on the optimal value for each specific objectives, which allows for direct comparison between and weighting of each. The proposed methods are demonstrated using a simple numerical example of an undersaturated intersection where all objectives can be analytically obtained. However, they can be readily applied to other signal timing problems where objectives can be obtained using simulation outputs to help identify the signal timing plan that provides the most reasonable tradeoff between competing objectives.

Signal Timing Optimization with Connected Vehicle Technology: Platooning to Improve Computational Efficiency

This paper develops a real-time traffic signal optimization algorithm in the presence of connected and autonomous vehicles (CAVs). The proposed algorithm leverages information from connected vehicles (CVs) arriving at an intersection to identify naturally occurring platoons that consist of both CVs and non-CVs. Signal timings are then selected to optimize the sequence at which these platoons are allowed to discharge through the intersection to minimize total vehicle delay. Longitudinal trajectory guidance that explicitly accounts for vehicle acceleration and deceleration behavior is provided to the lead autonomous vehicle (AV) in any platoon to minimize the total number of stopping maneuvers performed by all vehicles. Simulation tests reveal that the proposed platoon-based algorithm provides superior computational savings (over 95%) compared with a previously developed algorithm that focuses on optimizing departure sequences of individual vehicles, with negligible changes in operational performance. The computational savings allow the platoon-based algorithm to accommodate intersections with four multi-lane approaches and left turns, whereas large computational costs limited the previous vehicle-based algorithm to only two single-lane approaches without conflicting left turns. Additional simulation tests of the platoon-based algorithm on these more realistic intersection configurations show that intersection performance increases as the penetration rate of CAVs in the vehicle fleet increases. However, the marginal benefits decrease rapidly after the fleet is composed of 40% CAVs.

Enhancement of force patterns classification based on Gaussian distributions

Description of the patterns of ground reaction force is a standard method in areas such as medicine, biomechanics and robotics. The fundamental parameter is the time course of the force, which is classified visually in particular in the field of clinical diagnostics. Here, the knowledge and experience of the diagnostician is relevant for its assessment. For an objective and valid discrimination of the ground reaction force pattern, a generic method, especially in the medical field, is absolutely necessary to describe the qualities of the time-course. The aim of the presented method was to combine the approaches of two existing procedures from the fields of machine learning and the Gauss approximation in order to take advantages of both methods for the classification of ground reaction force patterns. The current limitations of both methods could be eliminated by an overarching method.Twenty-nine male athletes from different sports were examined. Each participant was given the task of performing a one-legged stopping maneuver on a force plate from the maximum possible starting speed. The individual time course of the ground reaction force of each subject was registered and approximated on the basis of eight Gaussian distributions. The descriptive coefficients were then classified using Bayesian regulated neural networks. The different sports served as the distinguishing feature.Although the athletes were all given the same task, all sports referred to a different quality in the time course of ground reaction force. Meanwhile within each sport, the athletes were homogeneous. With an overall prediction (R = 0.938) all subjects/sports were classified correctly with 94.29% accuracy. The combination of the two methods: the mathematical description of the time course of ground reaction forces on the basis of Gaussian distributions and their classification by means of Bayesian regulated neural networks, seems an adequate and promising method to discriminate the ground reaction forces without any loss of information.

Modelling of Driver’s Stopping Maneuver Based on Expression as Hybrid Dynamical System under Three-Dimensional Virtual Reality Equipment

This paper presents a new framework to understand the modeling strategy of the human driving behavior based on the expression as Hybrid Dynamical System(HDS) model focusing on the driver’s stopping maneuver. The driving data are collected by using the three-dimensional driving simulator based on CAVE Automatic Virtual Environment(CAVE), which provides stereoscope immersive virtual environment. In our modeling, the control scenario of the human driver, that is, the mapping from the driver’s sensory information to the operation of the driver such as acceleration, braking and steering, is expressed by Piecewise Polynomial System (PWPS) model. Since the PWPS model includes both continuous behavior given by polynomials and discrete logical conditions, it can be regarded as a class of Hybrid Dynamical System(HDS). The key idea to solve the identification problem for the PWPS model is formulated as the Mixed Integer Linear Programming(MILP) by transforming the switching conditions into binary variables. From the obtained results, it is found that the driver appropriately switches the ‘control law’ according to the following scenario : At the beginning of the stopping maneuver (just after finding the stopping point), the driver decelerate the vehicle based on the acceleration information, and then switch th toe control law based on the distance to the stop line. These results enable us to capture not only the physical meaning of the driving skill(polynomials), but also the decision-making aspect(switching conditions) in the driver’s stopping maneuver.

Mechanism of Anterior Cruciate Ligament Injury in Female Soccer Players

Background: The risk of anterior cruciate ligament (ACL) injury is higher in female soccer players than in male soccer players. The most common reason for non-contact ACL injury has been found to be a cutting or stopping maneuver combined with deceleration and landing from a jump. In a previous study, there was no difference in the incidence of ACL injury between offensive and defensive players and in the risk of ACL injury between goalkeepers and other players. Recently studies reported that the most frequent injury situation was pressing in male players. However, the most common type of situation associated with ACL injury in female soccer players has not been clarified. Objectives: The purpose of the present study was to identify the most common type of situation associated with ACL injury in female soccer players. Methods: We handed out questionnaires to 80 female soccer players with a history of ACL injury (90 ACL injuries). The players were asked about the injury characteristics, injury circumstance, maneuver being performed when the injury occurred, and playing type associated with the injury. The players responded to the questionnaire under the guidance of the medical staff of each team. Results: The 80 female soccer players reported a total of 90 ACL injuries during soccer. Among 55 non-contact injuries, 29 (55%) occurred during a cutting maneuver and 22 (44%) occurred during pressing. On assessing the frequency distributions of playing type (pressing vs. others) and body contact (contact vs. no contact), we found that non-contact injuries at pressing were significantly more common than contact injuries at pressing (odds ratio: 3.03; 95% confidence interval, 1.11 - 8.25, P = 0.036) Conclusions: ACL injury often occurs as non-contact injury during pressing at the time of defense, regardless of the playing area, in female soccer players.