Hazard Avoidance Research Articles

Fear Arousal Drives the Renewal of Active Avoidance of Hazards in Construction Sites: Evidence from an Animal Behavior Experiment in Mice

Fear Arousal Drives the Renewal of Active Avoidance of Hazards in Construction Sites: Evidence from an Animal Behavior Experiment in Mice

Parental non-compliance to childhood safety practices: A cross-sectional study.

Background & objectives To assess the pattern of non-compliance to childhood safety practices among parents of children between one and five yr of age and to determine the reasons behind the same. Methods A descriptive, cross-sectional study was conducted on 120 children between one and five yr of age through a questionnaire-based interview of the primary carer. Poor compliance was defined as compliance to <85 per cent of the recommended practices. Results Of the total 48 injuries, 32 were serious (66.6%). Falls and burns/scalds were the two common types of injuries. Nearly three-fourths (72.5%) of families showed overall poor compliance. Poorest compliance was observed towards four safety practices namely, helmet wearing, restricting number of pillion riders to two on a two-wheeler, seatbelt wearing in a car and avoiding food items with a high risk of choking in children <3 yr. Parental perception of 'unnecessary' and 'lack of knowledge' were the main reasons behind non-compliance. Interpretation & conclusions Low compliance among families occurred with respect to safety on motor vehicles and avoidance of choking hazards. Change of parental perception and improved awareness is necessary for the prevention of unintentional childhood injuries.

Diagnostic methodology for vehicles equipped with antilock braking system and electronic stability control

Currently, several automotive companies are joining forces through the analysis and development of active safety systems for hazard avoidance and mitigation; from which according to the current regulations in the European Union the Anti-lock Braking System (ABS) and the Electronic Stability Control (ESC) outstand as mandatory for each new vehicle. The above has motivated the study of these two safety systems. Then, this research examines the ABS and ESC systems through a proposed diagnostic methodology, which identifies the main effect of these systems on the vehicle dynamics. To achieve this goal a software was developed, looking for processing the data acquired during the development of some specific vehicle maneuvers. The diagnostic results expose: (1) an indicator about the ABS/ESC systems performance; and (2) the impact of these systems on the vehicle dynamics; also, some of the results here obtained can also be taken as reference for the Brake Assistant System and the Anti-Roll Control analysis.

Calibration and validation of a multi-beam LiDAR onboard China Chang’e lunar probe for landing obstacle avoidance

For automatic exploration of specific areas with high scientific value on the moon and other planets, high-precision obstacle detection and hazard avoidance capabilities are required. Three-dimensional (3D) LiDAR can obtain a high-resolution 3D point cloud, offering significant advantages in landing obstacle avoidance. During the landing of the Chang’e lander, a laser 3D imaging sensor (L3DIS) is used to measure and generate accurate topographic maps of the candidate landing area in real-time to help find a safe landing zone. The L3DIS employs 16 beamlets split from a Gaussian laser beam and 16 channels of linear-array avalanche photodiodes within the same optical path and scans the object with a two-axis galvanometer in a field of view of 29°×33°. The calibration of the systematic errors and the performance of obstacle detection on this sensor are conducted in this paper. First, the instrument components and main error sources of the sensor are introduced, and the systematic errors are calibrated based on planar targets, indicating that the sensor’s accuracy is greater than 4 cm, and the corresponding obstacle detection accuracy is better than 12 cm. Second, the ground validation of obstacle detection is demonstrated, and the obtained point cloud is compared with that obtained by a terrestrial laser scanner, indicating that the sensor has good performance. Finally, the performance of onboard measurement and obstacle detection is analyzed, showing that the sensor can identify obvious craters and rocks, i.e., nine major craters with a maximum and minimum depth of 1.36 m and 0.16 m, respectively, and major rocks with a maximum and minimum height of 0.1 m and 0.05 m, respectively, and main landing area with slop less than 10° except for the edges of craters and rocks.

Individual route choice behavior in evacuation considering avoidance and phototropism: An experimental study

During an emergency evacuation in a building, participants' evacuation signs obedience behaviors have a significant impact on evacuation efficiency, while participants' possible phototropism and hazard avoidance behaviors occur during evacuation, which will affect evacuation efficiency. To investigate the effects of participants' phototropism and hazard avoidance behaviors on compliance with evacuation signs. One pre-experiment and four groups of evacuation experiments were conducted in the T-junction and Room of the building with a total of 170 participants. A fumes generator and searchlight to simulate light and fumes conditions under fire. Using the statistical analysis to explore the differences in the route choice behavior of evacuees under different conditions. The results show that: (1) In the natural state, participants showed significant phototropism and hazard avoidance. (2) Phototropism and hazard avoidance affect participants' obedience to evacuation signs. (3) In the room scene, participants demonstrated more obvious phototropism and hazard avoidance, even deviating from the evacuation sign's guidelines；(4) Participants showed some decision inertia during two consecutive decisions. Further combined with SHAP interpretable machine learning for analysis, it was found that (1) Scene conditions exist for phototropism and hazard avoidance in evacuees. (2) Fumes prevented participants' obedience to the evacuation sign, whereas light promoted participants' obedience to the sign. This indicates that evacuation signs need to be installed regarding the actual building structure. These findings can be used as theoretical references for building safety design, campus safety, and evacuation simulation tests.

Evaluating the effects of safety incentives on worker safety behavior control through image-based activity classification.

Construction worker safety remains a major concern even as task automation increases. Although safety incentives have been introduced to encourage safety compliance, it is still difficult to accurately measure the effectiveness of these measures. A simple count of accident rates and lower numbers do not necessarily mean that workers are properly complying with safety regulations. To address this problem, this study proposes an image-based approach to monitor moment-by-moment worker safety behavior and evaluate the effects of different safety incentive scenarios. By capturing workers' safety behaviors using a model integrated with OpenPose and spatiotemporal graph convolutional network, this study evaluated the effects of safety-incentive scenarios on workers' compliance with rules while on the job. The safety incentive scenarios in this study were designed as 1) varying the type (i.e., providing rewards and penalties) of incentives and 2) varying the frequency of feedback about ones' own compliance status during tasks. The effects of the scenarios were compared to the average compliance rates of three safety regulations (i.e., personal protective equipment self-monitoring hazard avoidance, and arranging the safety hook) for each scenario. The results show that 1) rewarding a good-compliance is more effective when there is no feedback on compliance status, and 2) penalizing non-compliance is more effective when there are three feedbacks during the tasks. This study provides a more accurate assessment of safety incentives and their effectiveness by focusing on safe behaviors to promote safety compliance among construction workers.

Evaluate Prototype Performance of Battery Pack Monitoring for PT XYZ E-Bus Maintenance

One of the primary issues with electric vehicles is battery longevity. This study uses Kodular as an application developer for mobile app monitoring. Furthermore, using the monitoring data, PT XYZ may increase the operational efficiency of electric buses, lengthen battery life, and lower the risk of damage and maintenance costs. The following parameters are used: power voltage, SoC, SoH, system insulation resistance, positive insulation, negative insulation, pack voltage, and current. Inspectors can perform maintenance, diagnose faults, and improve overall system performance by keeping track of these parameters. It also contributes to the prevention of equipment failure, the avoidance of safety hazards, and the reliable operation of electrical and electronic systems. The goal of this research is to examine the performance of prototype monitoring with battery pack measurement parameters on a mobile app using prototype monitoring of battery packs on electric bus maintenance at PT XYZ. In this trial, interval changes happened every 30 minutes from 20:10 to 21:40. This research was carried out four times. The output parameters are pack voltage (545.9 V), current (-67.7 A), power voltage (26676), SoC (81.4%), SoH (100%), system insulation resistance (1233 KΩ), positive insulation (2952 KΩ), and negative insulation (1233 KΩ).

Dynamic Validation of Calibration Accuracy and Structural Robustness of a Multi-Sensor Mobile Robot.

For mobile robots, the high-precision integrated calibration and structural robustness of multi-sensor systems are important prerequisites for ensuring healthy operations in the later stage. Currently, there is no well-established validation method for the calibration accuracy and structural robustness of multi-sensor systems, especially for dynamic traveling situations. This paper presents a novel validation method for the calibration accuracy and structural robustness of a multi-sensor mobile robot. The method employs a ground-object-air cooperation mechanism, termed the "ground surface simulation field (GSSF)-mobile robot -photoelectric transmitter station (PTS)". Firstly, a static high-precision GSSF is established with the true north datum as a unified reference. Secondly, a rotatable synchronous tracking system (PTS) is assembled to conduct real-time pose measurements for a mobile vehicle. The relationship between each sensor and the vehicle body is utilized to measure the dynamic pose of each sensor. Finally, the calibration accuracy and structural robustness of the sensors are dynamically evaluated. In this context, epipolar line alignment is employed to assess the accuracy of the evaluation of relative orientation calibration of binocular cameras. Point cloud projection and superposition are utilized to realize the evaluation of absolute calibration accuracy and structural robustness of individual sensors, including the navigation camera (Navcam), hazard avoidance camera (Hazcam), multispectral camera, time-of-flight depth camera (TOF), and light detection and ranging (LiDAR), with respect to the vehicle body. The experimental results demonstrate that the proposed method offers a reliable means of dynamic validation for the testing phase of a mobile robot.

Crowd navigation for dynamic hazard avoidance in evacuation using emotional reciprocal velocity obstacles

Crowd evacuation can be a challenging task, especially in emergency situations involving dynamically moving hazards. Effective obstacle avoidance is crucial for successful crowd evacuation, particularly in scenarios involving dynamic hazards such as natural or man-made disasters. In this paper, we propose a novel application of the emotional reciprocal velocity obstacles (ERVO) method for obstacle avoidance in dynamic hazard scenarios. ERVO is an established method that incorporates agent emotions and obstacle avoidance to produce more efficient and effective crowd navigation. Our approach improves on previous research by using ERVO to model the perceptive danger posed by dynamic hazards in real-time, which is crucial for rapid response in emergency situations. We conducted experiments to evaluate our approach and compared our results with other velocity obstacle methods. Our findings demonstrate that our approach is able to improve agent coordination, reduce congestion, and produce superior avoidance behavior. Our study shows that incorporating emotional reciprocity into obstacle avoidance can enhance crowd behavior in dynamic hazard scenarios.

Machine vision-based autonomous road hazard avoidance system for self-driving vehicles

The resolution of traffic congestion and personal safety issues holds paramount importance for human’s life. The ability of an autonomous driving system to navigate complex road conditions is crucial. Deep learning has greatly facilitated machine vision perception in autonomous driving. Aiming at the problem of small target detection in traditional YOLOv5s, this paper proposes an optimized target detection algorithm. The C3 module on the algorithm’s backbone is upgraded to the CBAMC3 module, introducing a novel GELU activation function and EfficiCIoU loss function, which accelerate convergence on position loss lbox, confidence loss lobj, and classification loss lcls, enhance image learning capabilities and address the issue of inaccurate detection of small targets by improving the algorithm. Testing with a vehicle-mounted camera on a predefined route effectively identifies road vehicles and analyzes depth position information. The avoidance model, combined with Pure Pursuit and MPC control algorithms, exhibits more stable variations in vehicle speed, front-wheel steering angle, lateral acceleration, etc., compared to the non-optimized version. The robustness of the driving system's visual avoidance functionality is enhanced, further ameliorating congestion issues and ensuring personal safety.

Congenital Anosmia and Facial Emotion Recognition

Major functions of the olfactory system include guiding ingestion and avoidance of environmental hazards. People with anosmia report reliance on others, for example to check the edibility of food, as their primary coping strategy. Facial expressions are a major source of non-verbal social information that can be used to guide approach and avoidance behaviour. Thus, it is of interest to explore whether a life-long absence of the sense of smell heightens sensitivity to others’ facial emotions, particularly those depicting threat. In the present, online study 28 people with congenital anosmia (mean age 43.46) and 24 people reporting no olfactory dysfunction (mean age 42.75) completed a facial emotion recognition task whereby emotionally neutral faces (6 different identities) morphed, over 40 stages, to express one of 5 basic emotions: anger, disgust, fear, happiness, or sadness. Results showed that, while the groups did not differ in their ability to identify the final, full-strength emotional expressions, nor in the accuracy of their first response, the congenital anosmia group successfully identified the emotions at significantly lower intensity (i.e. an earlier stage of the morph) than the control group. Exploratory analysis showed this main effect was primarily driven by an advantage in detecting anger and disgust. These findings indicate the absence of a functioning sense of smell during development leads to compensatory changes in visual, social cognition. Future work should explore the neural and behavioural basis for this advantage.

Imaging-based measurement of lunar dust velocity and particle size.

This paper introduces an optical-mechanical system designed for the dynamic detection and analysis of lunar dust, typically characterized as particles under 20micrometers on the lunar surface. The system's design is both compact and lightweight, aligning with the payload constraints of lunar exploration missions. It is capable of real-time tracking and recording the motion of lunar dust at various altitudes, a crucial capability for understanding the environmental dynamics of the lunar surface. By capturing images and applying sophisticated algorithms, the system accurately measures the velocity and size of dust particles. This approach significantly advances the quantitative analysis of lunar dust, especially during agitation events, filling a critical gap in our current understanding of lunar surface phenomena. The insights gained from this study are not only pivotal for developing theoretical models of lunar surface air flow disturbances and dust movement but also instrumental in designing effective dust mitigation and hazard avoidance strategies for future lunar missions, thereby enhancing both scientific knowledge and the engineering applications in lunar exploration.

Knowing me, knowing you-A study on top-down requirements for compensatory scanning in drivers with homonymous visual field loss.

It is currently still unknown why some drivers with visual field loss can compensate well for their visual impairment while others adopt ineffective strategies. This paper contributes to the methodological investigation of the associated top-down mechanisms and aims at validating a theoretical model on the requirements for successful compensation among drivers with homonymous visual field loss. A driving simulator study was conducted with eight participants with homonymous visual field loss and eight participants with normal vision. Participants drove through an urban surrounding and experienced a baseline scenario and scenarios with visual precursors indicating increased likelihoods of crossing hazards. Novel measures for the assessment of the mental model of their visual abilities, the mental model of the driving scene and the perceived attention demand were developed and used to investigate the top-down mechanisms behind attention allocation and hazard avoidance. Participants with an overestimation of their visual field size tended to prioritize their seeing side over their blind side both in subjective and objective measures. The mental model of the driving scene showed close relations to the subjective and actual attention allocation. While participants with homonymous visual field loss were less anticipatory in their usage of the visual precursors and showed poorer performances compared to participants with normal vision, the results indicate a stronger reliance on top-down mechanism for drivers with visual impairments. A subjective focus on the seeing side or on near peripheries more frequently led to bad performances in terms of collisions with crossing cyclists. The study yielded promising indicators for the potential of novel measures to elucidate top-down mechanisms in drivers with homonymous visual field loss. Furthermore, the results largely support the model of requirements for successful compensatory scanning. The findings highlight the importance of individualized interventions and driver assistance systems tailored to address these mechanisms.

High-Frequency Local Field Potential Oscillations for Pigeons in Effective Turning

Flexible turning behavior endows Homing Pigeons (Columba livia domestica) with high adaptability and intelligence in long-distance flight, foraging, hazard avoidance, and social interactions. The present study recorded the activity pattern of their local field potential (LFP) oscillations and explored the relationship between different bands of oscillations and turning behaviors in the formatio reticularis medialis mesencephali (FRM). The results showed that the C (13–60 Hz) and D (61–130 Hz) bands derived from FRM nuclei oscillated significantly in active turning, while the D and E (131–200 Hz) bands oscillated significantly in passive turning. Additionally, compared with lower-frequency stimulation (40 Hz and 60 Hz), 80 Hz stimulation can effectively activate the turning function of FRM nuclei. Electrical stimulation elicited stronger oscillations of neural activity, which strengthened the pigeons’ turning locomotion willingness, showing an enhanced neural activation effect. These findings suggest that different band oscillations play different roles in the turning behavior; in particular, higher-frequency oscillations (D and E bands) enhance the turning behavior. These findings will help us decode the complex relationship between bird brains and behaviors and are expected to facilitate the development of neuromodulation techniques for animal robotics.

Impact of presbyopia treatment pilocarpine hydrochloride 1.25% on night-driving performance

ABSTRACT Clinical relevance Patients prescribed pilocarpine ophthalmic solution are advised to be cautious when driving at night, but studies evaluating the effects of pilocarpine hydrochloride ophthalmic solution 1.25% (pilo), approved to treat presbyopia, on driving at night are lacking. Background This double-masked, crossover, phase 3b study evaluated night-driving performance with pilo or the placebo once daily. Methods Forty-three adults (40–55 years) with presbyopia impacting daily activities and mesopic, high-contrast, binocular distance-corrected near vision 6/12–6/30 were randomised to bilateral treatment with pilo followed by placebo or placebo followed by pilo (with a ≥7-day washout between interventions). Night-driving performance was evaluated at twilight at a closed-circuit course. Primary efficacy endpoint: overall composite night-driving performance Z score at the end of the 7–14-day intervention period, 1 hour post-instillation. Pilo was considered non-inferior if the lower limit of the 95% confidence interval (CI) for the least squares mean difference (LSMD, pilo minus placebo) was >–0.25. Other efficacy endpoints: individual components of the night-driving performance test (hazard avoidance rate; road sign recognition rate and distance; pedestrians recognition distance; overall driving and lane-keeping times) and night-driving experience questionnaire. Safety included treatment-emergent adverse events (TEAEs). Results The mean overall composite Z scores were −0.121 (pilo) and 0.118 (placebo). The LSMD (pilo minus placebo) was −0.224 (95% CI, −0.346, −0.103), with 3 of the 7 individual tasks being significantly better with the placebo. The questionnaire did not reveal significant differences between pilo and the placebo. There were no serious or severe TEAEs and no TEAE-related discontinuations. The most common ocular TEAEs were headache and visual impairment with pilo (both 27.9%), and dry eye (7.0%) with the placebo. Conclusion The overall performance of night driving was inferior with pilo, compared with placebo. The study findings are consistent with the current class labelling and provide evidence to inform regulators and assist clinicians considering prescribing pilo to adults who seek treatment of presbyopia symptoms and drive at night. ClinicalTrials.gov identifier: NCT04837482.

Investigating a Renewable-Resource-Targeting Mobile Aquaculture System Using Route Optimization Based on Optimal Foraging Theory

Aquaculture systems require careful consideration of location, which determines water conditions, pollution impacts, and hazardous conditions. Mobility may be able to address these factors while also supporting the targeting of renewable energy sources such as wind, wave, and solar power throughout the year. In this paper, a purpose-built mobile aquaculture ship is identified and modeled with a combination of renewable energy harvesting capabilities as a case study with the objective of assessing the potential benefits of targeting high renewable energy potentials to power aquaculture operations. A route optimization algorithm is created and tuned to simulate the mobility of the aquaculture platform and cost-basis comparisons are made to a stationary system. The small spatial variability in renewable energy potential when combining multiple resources significantly limits the benefits of a mobile, renewable-targeting aquaculture system. On the other hand, the consistent energy harvest from a blend of renewable energy types (13 kW installed wind capacity, 661 m2 installed solar, and 1 m characteristic width wave-energy converter) suggests that the potential benefits of a mobile platform for offshore aquaculture (mitigation of environmental and social concerns, any potential positive impact on yields, hazard avoidance, etc.) can likely be pursued without significant increases in energy harvester costs.

Collaborative Generation of Local Conflict Free Trajectories With Weather Hazards Avoidance

Collaborative Generation of Local Conflict Free Trajectories With Weather Hazards Avoidance

Data-Driven Hazard Avoidance Landing of Parafoil: A Deep Reinforcement Learning Approach

This paper examines a couple of realizations of autonomous landing hazard avoidance technology of parafoil: a reinforcement-learning-based approach and a rule-based approach, advocating the former. Furthermore, comparative advantages and behavioral analogies between the two approaches are presented. In the data-driven approach, a decision process observing only a series of nadir-pointing images is designed without explicit augmentation of vehicle dynamics for the homogeneity of observation data. An agent then learns the hazard avoidance steering law in an end-to-end fashion. On the contrary, the rule-based approach is facilitated via explicit notions of guidance-control hierarchy, vehicle dynamic states, and metric details of ground obstacles. The soft actor–critic method is applied to learn a policy that maps the down-looking images to parafoil brakes, whereas a vector field guidance law is employed in the rule-based approach, considering each hazard as a repulsive source. This paper then presents empirical equivalences in designing both approaches and their distinctions. Numerical experiments in multiple test cases validate the reinforcement learning method and present comparisons between the approaches regarding their resultant trajectories. The interesting behaviors of the resultant policy of the data-driven approach are emphasized.

Using Multilevel Hidden Markov Models to Understand Driver Hazard Avoidance during the Takeover Process in Conditionally Automated Vehicles

Ensuring a safe transition between the automation system and human operators is critical in conditionally automated vehicles. During the automation-to-human transition process, hazard avoidance plays an important role after human drivers regain the vehicle control. This study applies the multilevel Hidden Markov Model to understand the hazard avoidance processes in response to static road hazards as continuous processes. The three-state model—Approaching, Negotiating, and Recovering—had the best model fitness, compared to the four-state and five-state models. The trained model reaches an average of 66% accuracy rate on predicting hazard avoidance states on the testing data. The prediction performance reveals the possibility to use the hazard avoidance pattern to recognize driving behaviors. We further propose several improvements at the end to generalize our models into other scenarios, including the potential to model hazard avoidance as a basic driving skill across different levels of automation conditions.

Cavitating Venturi as a Mass Flow Controller in a Deep Throttling Liquid Rocket Engine

Abstract The most common solutions for rocket engines are the single operation point (thrust level) units. Oxidiser and fuel mass flow rates and the oxidiser-to-fuel mass flow rate ratio (OFR) are some of the determinants of the thrust level. Based on these, planetary ascent and descent; space rendezvous; orbital manoeuvring, including orientation and stabilisation in space; hovering, hazard avoidance during planetary landing; and ballistic missile trajectory control propulsion systems could use throttleable liquid engines. Several engine throttling methods, such as supply pressure variation and variable injector area, can be applied. Among others, a cavitating venturi propellant regulatory valve is one of the most promising throttling method. This type of valve can provide steady mass flow, despite the downstream pressure disturbance (i.e. from the combustion chamber), which sustains a stable engine thrust as the mass flow is kept. The article presents the valve sizing method, design and prototype test results of the cavitating venturi valve that has potential for utilisation in a deep throttling rocket engine. Mass flow stability and repeatability are presented for valve operating points in the 10%–110% nominal mass flow range. Valve design optimisation, based on CFD, to sustain cavitation for a higher downstream-to-upstream pressure ratio is shown.