scholarly journals Analysis of the lateral slope’s impact on the calculation of water-filled rut depth

PLoS ONE ◽  
2020 ◽  
Vol 15 (12) ◽  
pp. e0243952
Author(s):  
Jiao Yan ◽  
Hongwei Zhang ◽  
Bing Hui
Keyword(s):  
Moving Average ◽  
Driving Safety ◽  
Calculation Error ◽  
Accurate Calculation ◽  
Safe Driving ◽  
Cloud Data ◽  
Evaluation Indexes ◽  
Key Points ◽  
Matlab Programming ◽  
Transportation Agencies

Accurate calculation of the water-filled rut depth is critical for assessing hydroplaning potential. Nevertheless, due to the difficulty in collecting and calculating the water-filled rut depth, most transportation agencies do not use i, especially in the case of lateral slopes, although water-filled rut depth is a key parameter that impacts driving safety. Contributions of this paper are development of a methodology to reliably compute the water-filled rut depth and quantitatively evaluate the influence of lateral slope on the water-filled rut depth. The proposed method include: 1) acquisition of the high-resolution 3D point cloud data of rut, 2) smooth processing of rut profile through moving average method with Matlab programming, 3) water-filled rut depth computation at different lateral slopes with the assistance of key points based on rut sections. With the variation of water-filled rut depth (ΔWD), its change rate (δWD), and the calculation error between the rut depth and the water-filled rut depth (Δn) as evaluation indexes, the variation law of water-filled rut depth under different lateral slopes is analyzed when considering the severity level and rut shape of the rut profile. Results show that: 1) the increase in lateral slope leads to the reduction of water-filled rut depth; 2) the water-filled rut depth is affected by the rut shape, including rut side wall’s slope and the key points’ elevation. The accurate calculation of the water-filled rut depth can provide reliable suggestions for safe driving.

scholarly journals Variability of Gravel Pavement Roughness: An Analysis of the Impact on Vehicle Dynamic Response and Driving Comfort

2021 ◽  
Vol 11 (16) ◽  
pp. 7582
Author(s):  
Vidas Žuraulis ◽  
Henrikas Sivilevičius ◽  
Eldar Šabanovič ◽  
Valentin Ivanov ◽  
Viktor Skrickij
Keyword(s):  
High Speed ◽  
Ambient Air ◽  
Dynamic Responses ◽  
Driving Safety ◽  
Vehicle Dynamic ◽  
Safe Driving ◽  
Evaluation Indexes ◽  
Road Pavement ◽  
Driving Speed ◽  
The Impact

Gravel pavement has lower construction costs but poorer performance than asphalt surfaces on roads. It also emits dust and deforms under the impact of vehicle loads and ambient air factors; the resulting ripples and ruts constantly deepen, and therefore increase vehicle vibrations and fuel consumption, and reduce safe driving speed and comfort. In this study, existing pavement quality evaluation indexes are analysed, and a methodology for adapting them for roads with gravel pavement is proposed. We report the measured wave depth and length of gravel pavement profile using the straightedge method on a 160 m long road section at three stages of road utilization. The measured pavement elevation was processed according to ISO 8608, and the frequency response of a vehicle was investigated using simulations in MATLAB/Simulink. The international roughness index (IRI) analysis showed that a speed of 30–45 km/h instead of 80 km/h provided the objective results of the IRI calculation on the flexible pavement due to the decreasing velocity of a vehicle’s unsprung mass on a more deteriorated road pavement state. The influence of the corrugation phenomenon of gravel pavement was explored, identifying specific driving safety and comfort cases. Finally, an increase in the dynamic load coefficient (DLC) at a low speed of 30 km/h on the most deteriorated pavement and a high speed of 90 km/h on the middle-quality pavement demonstrated the demand for timely gravel pavement maintenance and the complicated prediction of a safe driving speed for drivers. The main relevant objectives of this study are the adaptation of a road roughness indicator to gravel pavement, including the evaluation of vehicle dynamic responses at different speeds and pavement deterioration states.

scholarly journals Variability of Gravel Pavement Roughness: Analysis of the Impact on Vehicle Response and Driving Comfort

2021 ◽  
Author(s):  
Vidas Žuraulis ◽  
Henrikas Sivilevičius ◽  
Eldar Šabanovič ◽  
Valentin Ivanov ◽  
Viktor Skrickij
Keyword(s):  
High Speed ◽  
Ambient Air ◽  
Driving Safety ◽  
Safe Driving ◽  
Pavement Maintenance ◽  
Evaluation Indexes ◽  
Road Pavement ◽  
Driving Speed ◽  
Roughness Analysis ◽  
The Impact

The gravel road pavement has a lower construction cost but poorer performance than the asphalt surface. It also emits dust and deforms under the impact of vehicle loads and ambient air factors. The resulting ripples and ruts are constantly deepening, increasing vehicle vibrations and fuel consumption, reducing safe driving speed and comfort. In this article, existing pavement quality evaluation indexes are analysed, and a methodology for their adaptation for roads with gravel pavement is proposed. This article reports the measured wave depth and length of the gravel pavement profile by the straightedge method of a 160 m long road section in three road exploitation stages. The measured pavement elevation was processed according to ISO 8608, and vehicle frequency response has been investigated using simulations in MATLAB/Simulink. The applied International Roughness Index (IRI) analysis showed that a speed of 30-45 km/h instead of 80 km/h provides the objective results of IRI calculation on the flexible pavement due to a decreasing velocity of vehicle's unsprung mass on a more deteriorated road pavement state. The influence of the corrugation phenomenon of gravel pavement has been explored, identifying specific driving safety and comfort cases. Finally, an increase in the Dynamic Load Coefficient (DLC) at a low speed of 30 km/h on the most deteriorated pavement and a high speed of 90 km/h on the middle-quality pavement demonstrates the demand for timely gravel pavement maintenance and the complicated prediction of a safe driving speed for drivers.

scholarly journals THE ROAD TO ACCEPTANCE OF DRIVER RETIREMENT FOR PATIENTS WITH DEMENTIA: PHYSICIANS’ AND PATIENTS’ PERSPECTIVES

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S117-S117
Author(s):  
Theresa L Scott ◽  
Jacki Liddle ◽  
Nancy A Pachana ◽  
Elizabeth Beattie ◽  
Geoffrey Mitchell
Keyword(s):  
Focus Groups ◽  
Best Practice ◽  
Current System ◽  
Driving Safety ◽  
Evidence Based ◽  
Driving Cessation ◽  
Safe Driving ◽  
The Road ◽  
Assessment Measures ◽  
Evidence Based Guidelines

Abstract People living with Alzheimer’s disease and related dementias (ADRD) must eventually stop driving. While some will voluntarily retire, many others will continue to drive until a crisis. In Australia, like many other countries, general physicians/practitioners (“GPs”) play a key role in monitoring driving safety and driver retirement with their patients with ADRD. Advising patients about driving cessation is one of the most challenging aspects of clinical dementia care, complicated by limited time in consultations, lack of patient awareness and insight, and objective screening and assessment measures. We examined how to support best practice in relation to management of driving cessation with patients with ADRD through focus groups with 29 GPs and contrasted their perspectives with those of 11 retired drivers with ADRD. Focus groups and interviews were transcribed and thematically analysed. Themes discovered highlighted the importance of providing education about the effects of dementia on safe driving and incorporating regular assessment of driving safety into the care continuum. Key strategies that GPs successfully employed included acknowledging loss and encouraging continued community engagement, providing referral pathways, and deferring to other GPs within the practice in challenging circumstances. In conclusion, there is demand for an overhaul of the current system of management and a need to establish nationally aligned, standardized and evidence-based guidelines, in particular relating to assessment of safe driving. In the meantime, we can learn from these GPs who have implemented particular strategies that mitigate some of the challenges and complex driving related issues that present in primary care.

Study on the Discrimination Method of Driving Safety States Based on BP Neural Network

2014 ◽  
Vol 556-562 ◽  
pp. 6111-6114
Author(s):  
Feng Ping Cao
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
Safety Assessment ◽  
Driving Safety ◽  
Assessment Index ◽  
Evaluation Indexes ◽  
The Neural Network ◽  
Discrimination Model ◽  
Assessment Index System ◽  
Discrimination Method

In order to estimating the state of driving safety and reducing accidents, a discrimination method of driving safety states based on BP neural network was presented in the paper. Firstly, the influencing factors on the vehicle driving safety were analyzed, and ten main factors that affected the driving safety of vehicles were confirmed, which constitute the safety assessment index system for vehicle driving. Then the discrimination model of driving safety states based on BP neural network was established, and inputs and outputs for the neurons were determined. At last, the input data for neurons were acquired on the basic of the main evaluation indexes of vehicle driving safety, and these data were used to train the neural network. The training result conform to expectations of the training requires.

scholarly journals Comparative Results of Regional and Residual Anomalies with the Upward Continuation, Moving Average, and Polynomial Methods for Magnetic Data

2020 ◽  
Vol 2 (2) ◽  
pp. 90-93
Author(s):  
Luvera Deva Intan Indrawati ◽  
Rina Dwi Indriana ◽  
Irham Nurwidyanto
Keyword(s):  
Moving Average ◽  
Continuation Method ◽  
Second Order ◽  
Magnetic Data ◽  
Third Order ◽  
First Order ◽  
Upward Continuation ◽  
Order Polynomial ◽  
Matlab Programming ◽  
Polynomial Methods

Geophysics programing of regional and residual anomaly separation on Magnetic data has been carried out with the results compared with the upward continuation method in the OasisMontaj software. Separation of anomalies with moving average and polynomial methods is processed using Matlab programming. The orders used in the polynomial method are first-order, second-order and third-order. Comparison is done by calculating the match value. The chosen matching method is autocorrelation. Correlation of residual magnetic anomalies resulting from upward continuation (Magpick) to moving averages, 1st-order polynomials, 2nd-order polynomials and 3rd-order polynomials. Correlation values obtained for the moving average method are 0.9604, first order polynomial 0.9072, 2nd order polynomial 0.9482 and third order polynomial 0.6057. The moving average and second order polynomial methods can be used as a substitute method if we do not use the upward continuation method.

scholarly journals ASSESSING THE VISIBILITY OF RAISED PAVEMENT MARKERS AND ALTERNATIVE FORMS OF DELINEATION

Transport ◽  
2020 ◽  
Vol 35 (1) ◽  
pp. 98-107
Author(s):  
John D. Bullough ◽  
Xiang Liu
Keyword(s):  
Visual Performance ◽  
Driving Safety ◽  
Viewing Distance ◽  
Geometric Conditions ◽  
Roadway Safety ◽  
Identification Threshold ◽  
Driving Task ◽  
Relative Potential ◽  
Nighttime Driving ◽  
Transportation Agencies

Raised Pavement Markers (RPMs) are used by a number of transportation agencies with the objective of improving roadway safety, especially in complex roadway geometries and along wet roads. Because of maintenance and cost issues, many transportation agencies are exploring alternatives to RPMs such as wet reflective pavement tape and barrier-mounted reflective delineators. In order to assess the relative potential of these devices to contribute to nighttime driving safety, the luminances of new and used RPM samples from different manufacturers and having different colors and of several alternative delineation devices were measured in the laboratory using a range of geometric conditions relevant to the driving task. From these data, Luminances under representative low-beam headlight illumination were determined and these quantities were used to estimate driver visual performance. Large variations in luminance yielded relatively small differences in visual performance for a viewing distance of 100 m, primarily because of the plateau characteristic of visual performance. Differences in threshold visibility distances were greater, with distances at identification threshold for the devices measured ranging approximately from 150 to 400 m. Used RPMs had luminances 20…30% lower than new RPMs but similar visibility characteristics as new devices. The analysis method in this study may be useful for practitioners seeking to characterize the visual effectiveness of RPMs and other roadway delineation devices and systems.

scholarly journals Advanced eNose-Driven Pedestrian Tracking Pipeline for Intelligent Car Driver Assisting System: Preliminary Results

Sensors ◽  
2022 ◽  
Vol 22 (2) ◽  
pp. 674
Author(s):  
Francesco Rundo ◽  
Ilaria Anfuso ◽  
Maria Grazia Amore ◽  
Alessandro Ortis ◽  
Angelo Messina ◽  
...  
Keyword(s):  
Air Quality ◽  
Network Architecture ◽  
Assessment System ◽  
Driving Safety ◽  
Physiological Status ◽  
Dynamic Features ◽  
Safe Driving ◽  
Preliminary Results ◽  
Sensing System ◽  
Driving Scenario

From a biological point of view, alcohol human attentional impairment occurs before reaching a Blood Alcohol Content (BAC index) of 0.08% (0.05% under the Italian legislation), thus generating a significant impact on driving safety if the drinker subject is driving a car. Car drivers must keep a safe driving dynamic, having an unaltered physiological status while processing the surrounding information coming from the driving scenario (e.g., traffic signs, other vehicles and pedestrians). Specifically, the identification and tracking of pedestrians in the driving scene is a widely investigated problem in the scientific community. The authors propose a full, deep pipeline for the identification, monitoring and tracking of the salient pedestrians, combined with an intelligent electronic alcohol sensing system to properly assess the physiological status of the driver. More in detail, the authors propose an intelligent sensing system that makes a common air quality sensor selective to alcohol. A downstream Deep 1D Temporal Residual Convolutional Neural Network architecture will be able to learn specific embedded alcohol-dynamic features in the collected sensing data coming from the GHT25S air-quality sensor of STMicroelectronics. A parallel deep attention-augmented architecture identifies and tracks the salient pedestrians in the driving scenario. A risk assessment system evaluates the sobriety of the driver in case of the presence of salient pedestrians in the driving scene. The collected preliminary results confirmed the effectiveness of the proposed approach.

scholarly journals A Hybrid Method for Short-Term Host Utilization Prediction in Cloud Computing

2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Jing Chen ◽  
Yinglong Wang
Keyword(s):  
Cloud Computing ◽  
Hybrid Method ◽  
Virtual Machines ◽  
Moving Average ◽  
Arima Model ◽  
Cost Effective ◽  
Short Term ◽  
Cloud Data Center ◽  
Cloud Data ◽  
Host Utilization

Dynamic resource scheduling is a critical activity to guarantee quality of service (QoS) in cloud computing. One challenging problem is how to predict future host utilization in real time. By predicting future host utilization, a cloud data center can place virtual machines to suitable hosts or migrate virtual machines in advance from overloaded or underloaded hosts to guarantee QoS or save energy. However, it is very difficult to accurately predict host utilization in a timely manner because host utilization varies very quickly and exhibits strong instability with many bursts. Although machine learning methods can accurately predict host utilization, it usually takes too much time to ensure rapid resource allocation and scheduling. In this paper, we propose a hybrid method, EEMD-RT-ARIMA, for short-term host utilization prediction based on ensemble empirical mode decomposition (EEMD), runs test (RT), and autoregressive integrated moving average (ARIMA). First, the EEMD method is used to decompose the nonstationary host utilization sequence into relatively stable intrinsic mode function (IMF) components and a residual component to improve prediction accuracy. Then, efficient IMF components are selected and then reconstructed into three new components to reduce the prediction time and error accumulation due to too many IMF components. Finally, the overall prediction results are obtained by superposing the prediction results of three new components, each of which is predicted by the ARIMA method. An experiment is conducted on real host utilization traces from a cloud platform. We compare our method with the ARIMA model and the EEMD-ARIMA method in terms of error, effectiveness, and time-cost analysis. The results show that our method is a cost-effective method and is more suitable for short-term host utilization prediction in cloud computing.

scholarly journals Investigating Automobile Passengers’ Comfort and Safety on Scenic Road Using Sideway Force Coefficient

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Ronghua Wang ◽  
Xingliang Liu ◽  
Feijie Han
Keyword(s):  
Numerical Simulation ◽  
Large Scale ◽  
Lateral Acceleration ◽  
Driving Safety ◽  
Horizontal Curve ◽  
Force Coefficient ◽  
Safe Driving ◽  
Minimum Radius ◽  
Curve Design ◽  
Naturalistic Driving

To satisfy passengers’ experiential demand in scenic roads, a study on passengers’ comfort in the aspect of horizontal curve design is stated in this study. A new indicator sideway force coefficient (SFC) describing passengers’ comfort is introduced, which differs from lateral acceleration. The mechanism of SFC is provided depending on the dynamic balance condition of the vehicle on horizontal curve and S F C c representing passengers’ comfort tolerance limitation is investigated. A large scale naturalistic driving experiments along a park road are conducted, and the S F C c value from naturalistic driving experiments is verified through numerical simulation of 15 horizontal curves from 5 scenic roads from the perspectives of both passengers’ comfort and driving safety. The statistical analysis on data collected in field tests indicates that age and gender have no effect on S F C c , and the value of S F C c is determined as 0.291. The corresponding minimum radius limits under 20–60 km/h and superelevation 6%, 8%, and 10% are proposed. The numerical simulation denotes, when satisfying the comfort demand of passengers (SFC less than 0.291), the lateral distance path is in a safe range, which could also satisfy the safe driving requirements. Thus, S F C c and minimum radius limits proposed in this study are proved to be credible and appropriate for the curve design of horizontal alignment in scenic roads.

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