scholarly journals Vision-Based Pavement Marking Detection and Condition Assessment—A Case Study

2021 ◽  
Vol 11 (7) ◽  
pp. 3152
Author(s):  
Shuyuan Xu ◽  
Jun Wang ◽  
Peng Wu ◽  
Wenchi Shou ◽  
Xiangyu Wang ◽  
...  
Keyword(s):  
Condition Assessment ◽  
Damage Estimation ◽  
Comprehensive Understanding ◽  
Maintenance Strategies ◽  
Traffic Demand ◽  
Pavement Markings ◽  
Road Users ◽  
Wear And Tear ◽  
Pavement Marking

Pavement markings constitute an effective way of conveying regulations and guidance to drivers. They constitute the most fundamental way to communicate with road users, thus, greatly contributing to ensuring safety and order on roads. However, due to the increasingly extensive traffic demand, pavement markings are subject to a series of deterioration issues (e.g., wear and tear). Markings in poor condition typically manifest as being blurred or even missing in certain places. The need for proper maintenance strategies on roadway markings, such as repainting, can only be determined based on a comprehensive understanding of their as-is worn condition. Given the fact that an efficient, automated and accurate approach to collect such condition information is lacking in practice, this study proposes a vision-based framework for pavement marking detection and condition assessment. A hybrid feature detector and a threshold-based method were used for line marking identification and classification. For each identified line marking, its worn/blurred severity level was then quantified in terms of worn percentage at a pixel level. The damage estimation results were compared to manual measurements for evaluation, indicating that the proposed method is capable of providing indicative knowledge about the as-is condition of pavement markings. This paper demonstrates the promising potential of computer vision in the infrastructure sector, in terms of implementing a wider range of managerial operations for roadway management.

scholarly journals Leveraging LiDAR Intensity to Evaluate Roadway Pavement Markings

2021 ◽  
Vol 1 (3) ◽  
pp. 720-736
Author(s):  
Justin A. Mahlberg ◽  
Yi-Ting Cheng ◽  
Darcy M. Bullock ◽  
Ayman Habib
Keyword(s):  
Linear Correlation ◽  
Autonomous Vehicles ◽  
The United States ◽  
Pavement Markings ◽  
Mapping System ◽  
Mobile Mapping System ◽  
Crucial Information ◽  
Pavement Marking ◽  
Human Inspection

The United States has over 8.8 million lane miles nationwide, which require regular maintenance and evaluations of sign retroreflectivity, pavement markings, and other pavement information. Pavement markings convey crucial information to drivers as well as connected and autonomous vehicles for lane delineations. Current means of evaluation are by human inspection or semi-automated dedicated vehicles, which often capture one to two pavement lines at a time. Mobile LiDAR is also frequently used by agencies to map signs and infrastructure as well as assess pavement conditions and drainage profiles. This paper presents a case study where over 70 miles of US-52 and US-41 in Indiana were assessed, utilizing both a mobile retroreflectometer and a LiDAR mobile mapping system. Comparing the intensity data from LiDAR data and the retroreflective readings, there was a linear correlation for right edge pavement markings with an R2 of 0.87 and for the center skip line a linear correlation with an R2 of 0.63. The p-values were 0.000 and 0.000, respectively. Although there are no published standards for using LiDAR to evaluate pavement marking retroreflectivity, these results suggest that mobile LiDAR is a viable tool for network level monitoring of retroreflectivity.

scholarly journals Prioritizing Roadway Pavement Marking Maintenance Using Lane Keep Assist Sensor Data

Sensors ◽  
2021 ◽  
Vol 21 (18) ◽  
pp. 6014
Author(s):  
Justin A. Mahlberg ◽  
Rahul Suryakant Sakhare ◽  
Howell Li ◽  
Jijo K. Mathew ◽  
Darcy M. Bullock ◽  
...  
Keyword(s):  
The United States ◽  
Sensor Data ◽  
Pavement Markings ◽  
Autonomous Operation ◽  
Maintenance Activities ◽  
Safety Features ◽  
Pavement Marking ◽  
Original Equipment Manufacturers ◽  
Human Inspection

There are over four million miles of roads in the United States, and the prioritization of locations to perform maintenance activities typically relies on human inspection or semi-automated dedicated vehicles. Pavement markings are used to delineate the boundaries of the lane the vehicle is driving within. These markings are also used by original equipment manufacturers (OEM) for implementing advanced safety features such as lane keep assist (LKA) and eventually autonomous operation. However, pavement markings deteriorate over time due to the fact of weather and wear from tires and snowplow operations. Furthermore, their performance varies depending upon lighting (day/night) as well as surface conditions (wet/dry). This paper presents a case study in Indiana where over 5000 miles of interstate were driven and LKA was used to classify pavement markings. Longitudinal comparisons between 2020 and 2021 showed that the percentage of lanes with both lines detected increased from 80.2% to 92.3%. This information can be used for various applications such as developing or updating standards for pavement marking materials (infrastructure), quantifying performance measures that can be used by automotive OEMs to warn drivers of potential problems with identifying pavement markings, and prioritizing agency pavement marking maintenance activities.

scholarly journals Using ADAS to Future-Proof Roads—Comparison of Fog Line Detection from an In-Vehicle Camera and Mobile Retroreflectometer

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1737
Author(s):  
Ane Dalsnes Storsæter ◽  
Kelly Pitera ◽  
Edward McCormack
Keyword(s):  
Warning System ◽  
Management Systems ◽  
Warning Systems ◽  
Lane Departure Warning ◽  
Automated Driving ◽  
Pavement Markings ◽  
Lighting Conditions ◽  
Lane Marking ◽  
Lane Departure ◽  
Pavement Marking

Pavement markings are used to convey positioning information to both humans and automated driving systems. As automated driving is increasingly being adopted to support safety, it is important to understand how successfully sensor systems can interpret these markings. In this effort, an in-vehicle lane departure warning system was compared to data collected simultaneously from an externally mounted mobile retroreflectometer. The test, performed over 200 km of driving on three different routes in variable lighting conditions and road classes found that, depending on conditions, the retroreflectometer could predict whether the car’s lane departure systems would detect markings in 92% to 98% of cases. The test demonstrated that automated driving systems can be used to monitor the state of pavement markings and can provide input on how to design and maintain road infrastructure to support automated driving features. Since data about the condition of lane marking from multiple lane departure warning systems (crowd-sourced data) can provide input into the pavement marking management systems operated by many road owners, these findings also indicate that these automated driving sensors have an important role in enhancing the maintenance of pavement markings.

scholarly journals Development and Evaluation of Geostatistical Methods for Estimating Weather Related Collisions: A Large-Scale Case Study

2021 ◽  
pp. 036119812110200
Author(s):  
Andy H. Wong ◽  
Tae J. Kwon
Keyword(s):  
Large Scale ◽  
Mean Squared Error ◽  
Hot Spot ◽  
High Ratio ◽  
Contributing Factors ◽  
Geostatistical Methods ◽  
Road Users ◽  
Statistical Measures ◽  
Weather Events

Winter driving conditions pose a real hazard to road users with increased chance of collisions during inclement weather events. As such, road authorities strive to service the hazardous roads or collision hot spots by increasing road safety, mobility, and accessibility. One measure of a hot spot would be winter collision statistics. Using the ratio of winter collisions (WC) to all collisions, roads that show a high ratio of WC should be given a high priority for further diagnosis and countermeasure selection. This study presents a unique methodological framework that is built on one of the least explored yet most powerful geostatistical techniques, namely, regression kriging (RK). Unlike other variants of kriging, RK uses auxiliary variables to gain a deeper understanding of contributing factors while also utilizing the spatial autocorrelation structure for predicting WC ratios. The applicability and validity of RK for a large-scale hot spot analysis is evaluated using the northeast quarter of the State of Iowa, spanning five winter seasons from 2013/14 to 2017/18. The findings of the case study assessed via three different statistical measures (mean squared error, root mean square error, and root mean squared standardized error) suggest that RK is very effective for modeling WC ratios, thereby further supporting its robustness and feasibility for a statewide implementation.

scholarly journals Developing Pavement Marking Management Systems: A Theoretical Model Framework Based on the Experiences of the US Transportation Agencies

2021 ◽  
Vol 6 (2) ◽  
pp. 18
Author(s):  
Alireza Sassani ◽  
Omar Smadi ◽  
Neal Hawkins
Keyword(s):  
Asset Management ◽  
Management Practices ◽  
Relevant Literature ◽  
Building Blocks ◽  
Management Systems ◽  
Model Framework ◽  
Pavement Markings ◽  
The Us ◽  
Pavement Marking ◽  
Transportation Agencies

Pavement markings are essential elements of transportation infrastructure with critical impacts on safety and mobility. They provide road users with the necessary information to adjust driving behavior or make calculated decisions about commuting. The visibility of pavement markings for drivers can be the boundary between a safe trip and a disastrous accident. Consequently, transportation agencies at the local or national levels allocate sizeable budgets to upkeep the pavement markings under their jurisdiction. Infrastructure asset management systems (IAMS) are often biased toward high-capital-cost assets such as pavements and bridges, not providing structured asset management (AM) plans for low-cost assets such as pavement markings. However, recent advances in transportation asset management (TAM) have promoted an integrated approach involving the pavement marking management system (PMMS). A PMMS brings all data items and processes under a comprehensive AM plan and enables managing pavement markings more efficiently. Pavement marking operations depend on location, conditions, and AM policies, highly diversifying the pavement marking management practices among agencies and making it difficult to create a holistic image of the system. Most of the available resources for pavement marking management focus on practices instead of strategies. Therefore, there is a lack of comprehensive guidelines and model frameworks for developing PMMS. This study utilizes the existing body of knowledge to build a guideline for developing and implementing PMMS. First, by adapting the core AM concepts to pavement marking management, a model framework for PMMS is created, and the building blocks and elements of the framework are introduced. Then, the caveats and practical points in PMMS implementation are discussed based on the US transportation agencies’ experiences and the relevant literature. This guideline is aspired to facilitate PMMS development for the agencies and pave the way for future pavement marking management tools and databases.

scholarly journals Lifetime Benefit Analysis of Intelligent Maintenance: Simulation Modeling Approach and Industrial Case Study

2021 ◽  
Vol 11 (8) ◽  
pp. 3487
Author(s):  
Helge Nordal ◽  
Idriss El-Thalji
Keyword(s):  
Simulation Model ◽  
Simulation Modeling ◽  
Study Data ◽  
Opportunistic Maintenance ◽  
Maintenance Strategies ◽  
Modeling Approach ◽  
Intelligent Maintenance ◽  
Diagnosis And Prognosis ◽  
Case Study Data

The introduction of Industry 4.0 is expected to revolutionize current maintenance practices by reaching new levels of predictive (detection, diagnosis, and prognosis processes) and prescriptive maintenance analytics. In general, the new maintenance paradigms (predictive and prescriptive) are often difficult to justify because of their multiple inherent trade-offs and hidden systems causalities. The prediction models, in the literature, can be considered as a “black box” that is missing the links between input data, analysis, and final predictions, which makes the industrial adaptability to such models almost impossible. It is also missing enable modeling deterioration based on loading, or considering technical specifications related to detection, diagnosis, and prognosis, which are all decisive for intelligent maintenance purposes. The purpose and scientific contribution of this paper is to present a novel simulation model that enables estimating the lifetime benefits of an industrial asset when an intelligent maintenance management system is utilized as mixed maintenance strategies and the predictive maintenance (PdM) is leveraged into opportunistic intervals. The multi-method simulation modeling approach combining agent-based modeling with system dynamics is applied with a purposefully selected case study to conceptualize and validate the simulation model. Three maintenance strategies (preventive, corrective, and intelligent) and five different scenarios (case study data, manipulated case study data, offshore and onshore reliability data handbook (OREDA) database, physics-based data, and hybrid) are modeled and simulated for a time period of 20 years (175,200 h). Intelligent maintenance is defined as PdM leveraged in opportunistic maintenance intervals. The results clearly demonstrate the possible lifetime benefits of implementing an intelligent maintenance system into the case study as it enhanced the operational availability by 0.268% and reduced corrective maintenance workload by 459 h or 11%. The multi-method simulation model leverages and shows the effect of the physics-based data (deterioration curves), loading profiles, and detection and prediction levels. It is concluded that implementing intelligent maintenance without an effective predictive horizon of the associated PdM and effective frequency of opportunistic maintenance intervals, does not guarantee the gain of its lifetime benefits. Moreover, the case study maintenance data shall be collected in a complete (no missing data) and more accurate manner (use hours instead of date only) and used to continuously upgrade the failure rates and maintenance times.

A practical approach for supporting decisions in bridge condition assessment and monitoring

2019 ◽  
Author(s):  
Dániel Honfi ◽  
John Leander ◽  
Ivar Björnsson ◽  
Oskar Larsson Ivanov
Keyword(s):  
Measurement Techniques ◽  
Condition Assessment ◽  
Illustrative Case ◽  
Public Authorities ◽  
Daily Work ◽  
Rational Decision Making ◽  
Bridge Condition Assessment ◽  
Assessment And Monitoring ◽  
Illustrative Case Study

<p>In this contribution a practical and rational decision-making approach is presented to be applied for common bridges typically managed by public authorities. The authors have developed a model with the intention to be applicable for practical cases for common bridges in the daily work of bride operators responsible for a large number of assets, yet still maintain the principles of more generic frameworks based on probabilistic decision-theory.</p><p>Three main attributes of the verification of sufficiency of structural performance are considered, namely: 1) the level of sophistication of modelling performance, 2) the degree of verification and acceptance criteria in terms of dealing with uncertainties and consequences, 3) the extent of information is obtained and incorporated in the verification.</p><p>The simplicity of the approach is demonstrated through an illustrative case study inspired by practical condition assessment decision problems. It is argued that in practical cases it may be desirable to utilize less advanced methods owing to constraints in resources or lack of reliable data (e.g. based on structural health monitoring or other on-site measurement techniques).</p>

scholarly journals Improving V2X-6G network capacity using a new UAV-based approach in a Cloud/ICN architecture, case Study: VANET network

2021 ◽  
Vol 297 ◽  
pp. 01019
Author(s):  
Abdeslam Houari ◽  
Tomader Mazri
Keyword(s):  
Mobile Networks ◽  
Network Capacity ◽  
Intelligent Environment ◽  
New Approach ◽  
The Road ◽  
Road Users ◽  
Aerial Vehicle ◽  
On The Road

6G of mobile networks plays a crucial role in improving the capacity and enhancing the quality of services of Vehicle-to-Everything (V2X) based networks evolving in an intelligent environment. VANET is a promising project in the intelligent transportation field using V2X communications. The emergence of several 5G and 6G technologies has raised several challenges for scientists and researchers to allow vehicles and road users to enjoy several services while ensuring their safety on the road. Among these technologies, the unmanned aerial vehicle (UAV), which can perform different tasks for road users and vehicle drivers such as data caching, packet relaying and processing. In this article, we present a new approach based on 6G Unmanned Aerial Vehicles (UAV) technology on a vehicular cloud architecture while exploiting the exchange support of information-centric networking (ICN) for the improvement of network capacity.

scholarly journals Safety Analysis of Pedestrians As Users of Road Traffic in the Slovak Republic

Auspicia ◽  
2020 ◽  
pp. 38-56
Author(s):  
Pavel Kohút ◽  
Ludmila Macurová ◽  
Miroslav Felcan
Keyword(s):  
Police Officers ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Slovak Republic ◽  
Risk Groups ◽  
Negative Consequences ◽  
Road Users ◽  
Pedestrian Accident ◽  
Principle Of Proportionality

ABSTRACT: The paper deals with the analysis of traffic accidents involving pedestrians in the Slovak Republic. The development of traffic accidents involving pedestrians is processed through statistical data for the period 2011 - 2019. The paper defines the risk groups of road users, identified areas with the highest traffic accidents, evaluated the negative consequences of traffic accidents and identified their possible causes. A separate chapter is a case study consisting of an analysis of a vehicle - pedestrian accident. Based on the performed analysis of traffic accidents involving pedestrians, safety measures are set to minimize the number of traffic accidents involving pedestrians and their negative consequences. The study is one of the outputs of the APVV-17-0217 project "Staffing of police officers and application of the principle of proportionality in criminal and administrative law.

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