Academic literature on the topic 'Road markings'
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Journal articles on the topic "Road markings"
Babić, Dario, Anđelko Ščukanec, Darko Babić, and Mario Fiolić. "Model for Predicting Road Markings Service Life." Baltic Journal of Road and Bridge Engineering 14, no. 3 (September 26, 2019): 341–59. http://dx.doi.org/10.7250/bjrbe.2019-14.447.
Full textStorsæter, Ane Dalsnes, Kelly Pitera, and Edward McCormack. "Camera-Based Lane Detection—Can Yellow Road Markings Facilitate Automated Driving in Snow?" Vehicles 3, no. 4 (October 13, 2021): 661–90. http://dx.doi.org/10.3390/vehicles3040040.
Full textStorsæter, Ane Dalsnes, Kelly Pitera, and Edward McCormack. "Camera-Based Lane Detection—Can Yellow Road Markings Facilitate Automated Driving in Snow?" Vehicles 3, no. 4 (October 13, 2021): 661–90. http://dx.doi.org/10.3390/vehicles3040040.
Full textSetyawan P., Arkham, Tamrin Mallawangeng, and Nurhadijah Yunianti. "Evaluasi Rambu Lalu Lintas Dan Marka Jalan Ruas Veteran Utara Dan Veteran Selatan." Jurnal Penelitian Teknik Sipil Konsolidasi 1, no. 3 (September 30, 2023): 226–31. http://dx.doi.org/10.56326/jptsk.v1i3.1605.
Full textKang, Seokchan, Jeongwon Lee, and Jiyeong Lee. "Developing a Method to Automatically Extract Road Boundary and Linear Road Markings from a Mobile Mapping System Point Cloud Using Oriented Bounding Box Collision-Detection Techniques." Remote Sensing 15, no. 19 (September 22, 2023): 4656. http://dx.doi.org/10.3390/rs15194656.
Full textWu, Wenxiu, Xiaoyong Zou, Jing Liu, Yonglin Hu, Zhong Lv, Ruijian Zheng, and Zhen Liu. "Research on the Anti-Fouling Properties of Double-Coated Road Markings." E3S Web of Conferences 512 (2024): 03037. http://dx.doi.org/10.1051/e3sconf/202451203037.
Full textPan, Y., B. Yang, S. Li, H. Yang, Z. Dong, and X. Yang. "AUTOMATIC ROAD MARKINGS EXTRACTION, CLASSIFICATION AND VECTORIZATION FROM MOBILE LASER SCANNING DATA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W13 (June 5, 2019): 1089–96. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w13-1089-2019.
Full textChou, Chia-Pei, Kin-Wai Leong, Ai-Chin Chen, and Yao-Xuan Lee. "Road marking retroreflectivity study via a visual algorithm." International Journal of Pavement Research and Technology 13, no. 6 (November 2020): 614–20. http://dx.doi.org/10.1007/s42947-020-6001-x.
Full textYe, Chengming, Hongfu Li, Ruilong Wei, Lixuan Wang, Tianbo Sui, Wensen Bai, and Pirasteh Saied. "Double Adaptive Intensity-Threshold Method for Uneven Lidar Data to Extract Road Markings." Photogrammetric Engineering & Remote Sensing 87, no. 9 (September 1, 2021): 639–48. http://dx.doi.org/10.14358/pers.20-00099.
Full textKEMSLEY, JYLLIAN. "road markings." Chemical & Engineering News 88, no. 36 (September 6, 2010): 67. http://dx.doi.org/10.1021/cen-v088n036.p067.
Full textDissertations / Theses on the topic "Road markings"
Du, Preez Emile. "Empirical investigation of life cycle cost of road studs on national roads." Thesis, Stellenbosch : Stellenbosch University, 2013. http://hdl.handle.net/10019.1/97394.
Full textENGLISH ABSTRACT: The study involved a detail empirical investigation into the different road studs in use on South Africa’s national road network and how they performed on the network under different road conditions in order to establish which road stud, under what conditions, offers best value for money in terms of life-cycle cost for the South African National Roads Agency Limited. These main questions were asked: What is the most cost-effective/value-for-money stud option for SANRAL to choose for each of the specified road categories? Under which conditions do the studs perform differently and what is the most likely mode of failure of specific studs linked to a specific road condition and road category? The South African and Australian road stud standards were reviewed to gain understanding of which criteria one has to consider when evaluating road studs and what information would be needed for the research. Similar studies on road studs were reviewed to compare the criteria that were looked at, namely Guidelines for the use of Raised Pavement Markers, developed by the Department of Transport in the United States, and Feasibility of using accelerated pavement testing to evaluate the long term performance of raised pavement markers, a research paper by the Florida Department of Transport. This research made use of a standardised questionnaire containing questions on various elements found to be key to the road stud performance. The study was done on approximately 4 659 km of roads in SANRAL’s Western region, consisting of the Western Cape and Northern Cape. From the literature review, it was identified that there is a need for the SABS standards to be updated to include the testing of structural properties of studs. SANRAL should look at the lack in specification requirements when asking for the installation of road studs. From the data available it was observed that the preferred studs were the Ferro Lynx followed by the STA+52 stud. They are predominantly used on the roads that were included in the survey. They perform well on the national roads. The data suggests that these two studs and the Rhino stud are the best-performing studs with the least dislodgement and loss in reflectivity. The STA+52 and Rhino stud, however, are fairly new on the market and more data for theirs full life cycle should be obtained for further monitoring The regression analysis indicated that 36 per cent of the variation in the reflectivity of the Ferro Lynx stud can be explained by the surface width of the road, the traffic volume measured as ELVS and the period installed. All the coefficients were significant with a 5 per cent significance. The prediction tables on the weighted data set, indicated that one should always consider width of road when choosing a road stud and that the reflectivity of studs deteriorates most on the narrower roads.
Pratyaksa, Prabha. "Safety evaluation of converging chevron pavement markings." Thesis, Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/47697.
Full textTao, Zui. "Autonomous road vehicles localization using satellites, lane markings and vision." Thesis, Compiègne, 2016. http://www.theses.fr/2016COMP2261/document.
Full textEstimating the pose (position and attitude) in real-time is a key function for road autonomous vehicles. This thesis aims at studying vehicle localization performance using low cost automotive sensors. Three kinds of sensors are considered : dead reckoning (DR) sensors that already exist in modern vehicles, mono-frequency GNSS (Global navigation satellite system) receivers with patch antennas and a frontlooking lane detection camera. Highly accurate maps enhanced with road features are also key components for autonomous vehicle navigation. In this work, a lane marking map with decimeter-level accuracy is considered. The localization problem is studied in a local East-North-Up (ENU) working frame. Indeed, the localization outputs are used in real-time as inputs to a path planner and a motion generator to make a valet vehicle able to drive autonomously at low speed with nobody on-board the car. The use of a lane detection camera makes possible to exploit lane marking information stored in the georeferenced map. A lane marking detection module detects the vehicle’s host lane and provides the lateral distance between the detected lane marking and the vehicle. The camera is also able to identify the type of the detected lane markings (e.g., solid or dashed). Since the camera gives relative measurements, the important step is to link the measures with the vehicle’s state. A refined camera observation model is proposed. It expresses the camera metric measurements as a function of the vehicle’s state vector and the parameters of the detected lane markings. However, the use of a camera alone has some limitations. For example, lane markings can be missing in some parts of the navigation area and the camera sometimes fails to detect the lane markings in particular at cross-roads. GNSS, which is mandatory for cold start initialization, can be used also continuously in the multi-sensor localization system as done often when GNSS compensates for the DR drift. GNSS positioning errors can’t be modeled as white noises in particular with low cost mono-frequency receivers working in a standalone way, due to the unknown delays when the satellites signals cross the atmosphere and real-time satellites orbits errors. GNSS can also be affected by strong biases which are mainly due to multipath effect. This thesis studies GNSS biases shaping models that are used in the localization solver by augmenting the state vector. An abrupt bias due to multipath is seen as an outlier that has to be rejected by the filter. Depending on the information flows between the GNSS receiver and the other components of the localization system, data-fusion architectures are commonly referred to as loosely coupled (GNSS fixes and velocities) and tightly coupled (raw pseudoranges and Dopplers for the satellites in view). This thesis investigates both approaches. In particular, a road-invariant approach is proposed to handle a refined modeling of the GNSS error in the loosely coupled approach since the camera can only improve the localization performance in the lateral direction of the road. Finally, this research discusses some map-matching issues for instance when the uncertainty domain of the vehicle state becomes large if the camera is blind. It is challenging in this case to distinguish between different lanes when the camera retrieves lane marking measurements.As many outdoor experiments have been carried out with equipped vehicles, every problem addressed in this thesis is evaluated with real data. The different studied approaches that perform the data fusion of DR, GNSS, camera and lane marking map are compared and several conclusions are drawn on the fusion architecture choice
Cao, Yong. "A design of experimental approach to study the road marking luminance contrast and variable message signs /." View online ; access limited to URI, 2004. http://0-wwwlib.umi.com.helin.uri.edu/dissertations/dlnow/3145413.
Full textSchnell, Thomas. "The development of a PC-based pavement-making visibility evaluation model." Ohio : Ohio University, 1994. http://www.ohiolink.edu/etd/view.cgi?ohiou1178732568.
Full textMohi, Amal A. "Performance Evaluation of Pavement Markings on Portland Cement Concrete Bridge Decks." University of Akron / OhioLINK, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=akron1238350586.
Full textCrescenzo, Giuseppe. "Visibility models for road markings: analysis of the influence of size and shape." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2018.
Find full textBurrow, M. P. N. "The development of an automated inspection system for the analysis of road markings." Thesis, University of Birmingham, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.324095.
Full textFrench, Kari A. "Evaluation of concrete median barrier delineation under poor visibility conditions." Morgantown, W. Va. : [West Virginia University Libraries], 2003. http://etd.wvu.edu/templates/showETD.cfm?recnum=3213.
Full textTitle from document title page. Document formatted into pages; contains viii, 86, 82 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 85-86).
Coves-Campos, Andrés. "Análisis de la Durabilidad de la Señalización Vial Horizontal Atendiendo a su Composición y Posicionamiento en la Calzada de Carreteras Secundarias en Climas Semiáridos Cálidos." Doctoral thesis, Universidad de Alicante, 2019. http://hdl.handle.net/10045/102947.
Full textBooks on the topic "Road markings"
Illumination, International Commission on. Visual aspects of road markings: Joint technical report CIE/PIARC. Vienna: Central Bureau of the CIE, 1988.
Find full textCarson, Jodi L. Applications of illuminated, active, in-pavement marker systems. Washington, D.C: Transportation Research Board, 2008.
Find full textThomas, Gary B. Durable, cost-effective pavement markings. Ames, Iowa: Center for Transportation Research and Education, Iowa State University, 2001.
Find full textNew York (State). Engineering Research and Development Bureau, ed. Evaluation of polyester pavement markings. Albany, N.Y: New York State Dept. of Transportation, Engineering Research and Development Bureau, 1992.
Find full textCuelho, Eli. A review of the performance and costs of contemporary pavement marking systems: Final report. Helena, Mont: Montana Dept. of Transportation, 2003.
Find full textMigletz, James. Long-term pavement marking practices: A synthesis of highway practice. Washington, DC: Transportation Research Board, 2002.
Find full textHolcombe, Wiley. System enhancement for an automated raised pavement marker placement machine. Georgia: Dept. of Transportation, State of Georgia, 2009.
Find full textAmerican Association of State Highway and Transportation Officials. and United States. Federal Highway Administration., eds. Pavement markings: Materials and application for extended service life. Washington, D.C: Transportation Research Board, National Research Council, 1988.
Find full textSmadi, Omar. Predicting the initial retroreflectivity of pavement markings from glass bead quality. Washington, D.C: Transportation Research Board, 2013.
Find full textLynde, McGregor. Evaluation of inlaid durable pavement markings in an Oregon snow zone: Final report. Salem, OR: Oregon Dept. of Transportation, Research Unit, 2006.
Find full textBook chapters on the topic "Road markings"
Burghardt, Tomasz E., and Anton Pashkevich. "Sustainable Road Markings." In Encyclopedia of Green Materials, 1–7. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-4921-9_142-1.
Full textPihlak, René, and Andri Riid. "Simultaneous Road Edge and Road Surface Markings Detection Using Convolutional Neural Networks." In Communications in Computer and Information Science, 109–21. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-57672-1_9.
Full textDrenth, Kars, Jun Yew Tan, Marc Drenth, and Ong Ju Kit. "LCMS-2 Measurements of the Quality of Road Markings." In Lecture Notes in Civil Engineering, 943–52. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-48679-2_88.
Full textLi, Cheng, Ivo Creusen, Lykele Hazelhoff, and Peter H. N. de With. "Detection and Recognition of Road Markings in Panoramic Images." In Computer Vision - ACCV 2014 Workshops, 448–58. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-16631-5_33.
Full textAdedeji, Jacob Adedayo, Samuel Olugbenga Abejide, Moliehi Monts’i, Mohamed Mostafa Hassan, and Wafaa H. H. Mostafa. "Reaction Behaviour of Drivers to Road Markings: Case Study of Main South Road Lesotho – N8 Road South Africa." In Sustainable Solutions for Railways and Transportation Engineering, 58–71. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-01911-2_6.
Full textLima, Orlando, Iran Rocha Segundo, Laura Nascimento Mazzoni, Elisabete Freitas, and Joaquim Carneiro. "Improving the road safety and the service life of road markings through self-cleaning ability." In Bituminous Mixtures and Pavements VIII, 673–80. London: CRC Press, 2024. http://dx.doi.org/10.1201/9781003402541-79.
Full textKim, JongBae. "Detection and Recognition of Road Markings for Advanced Driver Assistance System." In Lecture Notes in Electrical Engineering, 325–31. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-47895-0_39.
Full textVoisin, Vincent, Manuel Avila, Bruno Emile, Stephane Begot, and Jean-Christophe Bardet. "Road Markings Detection and Tracking Using Hough Transform and Kalman Filter." In Advanced Concepts for Intelligent Vision Systems, 76–83. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11558484_10.
Full textRiege, Daniel, Stephan Pareigis, and Tim Tiedemann. "Real-Time Aspects of Image Segmentation of Road Markings in Miniature Autonomy." In Real-time and Autonomous Systems 2022, 97–107. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-32700-1_11.
Full textPashkevich, Anton, Tomasz E. Burghardt, Ksenia Shubenkova, and Irina Makarova. "Analysis of Drivers’ Eye Movements to Observe Horizontal Road Markings Ahead of Intersections." In Vision Zero for Sustainable Road Safety in Baltic Sea Region, 1–10. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-22375-5_1.
Full textConference papers on the topic "Road markings"
Villa, C., R. Bremond, F. Eymond, and E. Saint-Jacques. "CHARACTERISATION OF LUMINESCENT ROAD MARKINGS." In CIE 2021 Conference. International Commission on Illumination, CIE, 2021. http://dx.doi.org/10.25039/x48.2021.op02.
Full textWu, Tao, and Ananth Ranganathan. "Vehicle localization using road markings." In 2013 IEEE Intelligent Vehicles Symposium (IV). IEEE, 2013. http://dx.doi.org/10.1109/ivs.2013.6629627.
Full textTidjani, Ali, Maxime Redondin, Laurent Bouillaut, and Dimitri Daucher. "Impact of Road Infrastructure Characteristics on Road Markings." In Proceedings of the 29th European Safety and Reliability Conference (ESREL). Singapore: Research Publishing Services, 2019. http://dx.doi.org/10.3850/978-981-11-2724-3_0166-cd.
Full textWang, Jike, Shanmu Wang, Yasha Iravantchi, Mingke Wang, Alanson Sample, Kang G. Shin, Xinbing Wang, Chenghu Zhou, and Dongyao Chen. "METRO: Magnetic Road Markings for All-weather, Smart Roads." In SenSys '23: 21st ACM Conference on Embedded Networked Sensor Systems. New York, NY, USA: ACM, 2023. http://dx.doi.org/10.1145/3625687.3625809.
Full textRehder, Eike, and Alexander Albrecht. "Submap-based SLAM for road markings." In 2015 IEEE Intelligent Vehicles Symposium (IV). IEEE, 2015. http://dx.doi.org/10.1109/ivs.2015.7225910.
Full textBouzar, S. "Traffic measurement: image processing using road markings." In Eighth International Conference on Road Traffic Monitoring and Control. IEE, 1996. http://dx.doi.org/10.1049/cp:19960300.
Full textHsu, Shau-Wei, Cheng-Hsien Chen, and Shao-Tang Hung. "VISIBILITY OF ROAD MARKINGS ON A LED-LIGHTED FOGGY ROAD." In CIE 2018. International Commission on Illumination, CIE, 2018. http://dx.doi.org/10.25039/x45.2018.po13.
Full textSafavi, Seyed Hamid, Mohammad Eslami, Aliasghar Sharifi Najafabadi, Amirhosein Hajihoseini, Mohammadreza Riahi, Maryam Rekabi, Sadaf Sarafan, et al. "Image dataset for Persian Road Surface Markings." In 2017 10th Iranian Conference on Machine Vision and Image Processing (MVIP). IEEE, 2017. http://dx.doi.org/10.1109/iranianmvip.2017.8342361.
Full textIshino, Yuichi, and Hitoshi Saji. "Extraction of road markings from aerial images." In SICE 2008 - 47th Annual Conference of the Society of Instrument and Control Engineers of Japan. IEEE, 2008. http://dx.doi.org/10.1109/sice.2008.4655024.
Full textDonghao Xu, Qiqi Zeng, Huijing Zhao, Chunzhao Guo, Kiyosumi Kidono, and Yoshiko Kojima. "Online stereovision calibration using on-road markings." In 2014 IEEE 17th International Conference on Intelligent Transportation Systems (ITSC). IEEE, 2014. http://dx.doi.org/10.1109/itsc.2014.6957699.
Full textReports on the topic "Road markings"
Coyner, Kelley, and Jason Bittner. Automated Vehicles and Infrastructure Enablers: Pavement Markings and Signs. SAE International, May 2022. http://dx.doi.org/10.4271/epr2022011.
Full textCoyner, Kelley, and Jason Bittner. Infrastructure Enablers and Automated Vehicles: Trucking. SAE International, July 2022. http://dx.doi.org/10.4271/epr2022017.
Full textPineda-Mendez, Raul A., Xueqian Shi, and Andrew P. Tarko. Speed Management on Freeways in Transition Zones Between Rural and Urban Conditions. Purdue University, 2023. http://dx.doi.org/10.5703/1288284317586.
Full textDahal, Sachindra, and Jeffery Roesler. Passive Sensing of Electromagnetic Signature of Roadway Material for Lateral Positioning of Vehicle. Illinois Center for Transportation, November 2021. http://dx.doi.org/10.36501/0197-9191/21-039.
Full textHealth hazard evaluation report: HETA-2008-0017-3095, evaluation of employees' chemical exposures while blending and repackaging glass beads for road markings, Weissker Manufacturing, Palestine, Texas. U.S. Department of Health and Human Services, Public Health Service, Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health, November 2009. http://dx.doi.org/10.26616/nioshheta200800173095.
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