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

Ane Dalsnes Storsæter; Kelly Pitera; Edward McCormack

doi:10.3390/s21051737

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

Sensors ◽

10.3390/s21051737 ◽

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.

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A Novel Real-Time Lighting-Invariant Lane Departure Warning System

Security and Privacy in Smart Sensor Networks - Advances in Information Security, Privacy, and Ethics ◽

10.4018/978-1-5225-5736-4.ch011 ◽

2018 ◽

pp. 231-252

Author(s):

Yassin Kortli ◽

Mehrez Marzougui ◽

Mohamed Atri

Keyword(s):

Real Time ◽

Traffic Accidents ◽

Essential Element ◽

Warning System ◽

Lane Detection ◽

Accuracy Evaluation ◽

Lane Departure Warning ◽

Lighting Conditions ◽

Lane Departure ◽

Driving Assistance

In recent years, in order to minimize traffic accidents, developing driving assistance systems for security has attracted much attention. Lane detection is an essential element of avoiding accidents and enhancing driving security. In this chapter, the authors implement a novel real-time lighting-invariant lane departure warning system. The proposed methodology works well in different lighting conditions, such as in poor conditions. The experimental results and accuracy evaluation indicates the efficiency of the system proposed for lane detection. The correct detection rate averages 97% and exceeds 95.6% in poor conditions. Furthermore, the entire process has only 29 ms per frame.

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Safety Evaluation of Alternative Audible Lane Departure Warning Treatments in Reducing Traffic Crashes: An Empirical Bayes Observational Before–After Study

Transportation Research Record Journal of the Transportation Research Board ◽

10.1177/0361198118776481 ◽

2018 ◽

Vol 2672 (21) ◽

pp. 30-40 ◽

Cited By ~ 8

Author(s):

Lingtao Wu ◽

Srinivas R. Geedipally ◽

Adam M. Pike

Keyword(s):

Empirical Bayes ◽

Safety Evaluation ◽

Highway Safety ◽

Warning Systems ◽

Lane Departure Warning ◽

Crash Data ◽

Pavement Markings ◽

Lane Departure ◽

Run Off ◽

Single Vehicle

Roadway departure crashes are a major contributor to traffic fatalities and injury. Rumble strips have been shown to be an effective countermeasure in reducing roadway departure crashes. However, some roadway situations, for instance, inadequate shoulder width or roadway surface depth, have limited the application of conventional milled or rolled in rumble strips. Alternative audible lane departure warning systems, including profile (audible) pavement markings and preformed rumble bars, are increasingly used to overcome the limitations that exist with the milled rumble strips. So far, the safety effectiveness of these alternative audible lane departure warning systems has not been extensively assessed. The main purpose of this paper is to examine the safety effect of installing profile pavement markings and preformed rumble bars. Specifically, this study developed crash modification factors for these treatments that quantify the effectiveness in reducing single-vehicle-run-off-road (SVROR) and opposite-direction (OD) crashes. Traffic, roadway, and crash data at the treated sites on 189 miles of rural two-lane highways in Texas were analyzed using an empirical Bayes (EB) before–after analysis method. Safety performance functions from the Highway Safety Manual and Texas Highway Safety Design Workbook were used in the EB analysis. The results revealed a 21.3% reduction in all SVROR and OD crashes, and 32.5% to 39.9% reduction in fatal and injury SVROR and OD crashes after installing profile pavement marking and preformed rumble bars.

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Effect of Pavement Marking Retroreflectivity on the Performance of Vision-Based Lane Departure Warning Systems

Journal of Intelligent Transportation Systems ◽

10.1080/15472450.2011.544587 ◽

2011 ◽

Vol 15 (1) ◽

pp. 42-51 ◽

Cited By ~ 6

Author(s):

Mohammed Hadi ◽

Prasoon Sinha

Keyword(s):

Warning Systems ◽

Lane Departure Warning ◽

Lane Departure ◽

Pavement Marking

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

Infrastructures ◽

10.3390/infrastructures6020018 ◽

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.

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