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Pavement management

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value of their infrastructure assets in their financial statements. GASB recommends that government agencies use a historical cost approach for capitalizing long-lived capital assets; however, if historical information is not available, guidance is provided for an alternate approach based on the current replacement cost of the assets. A method of representing the costs associated with the use of the assets must also be selected, and two methods are allowed by GASB. One approach is to depreciate the assets over time. The modified approach, on the other hand, provides an agency more flexibility in reporting the value of its assets based upon the use of a systematic, defensible approach that accounts for the preservation of the asset. Pavement management and pavement management systems provide agencies with the tools necessary to evaluate their pavement assets and meet the GASB34 requirements under the modified depreciation approach.
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significantly. Pavement management encompasses the many aspects and tasks needed to maintain a quality pavement inventory, and ensure that the overall condition of the road network can be sustained at desired levels. While pavement management covers the entire lifecycle of pavement from planning to maintenance in any transport infrastructure, road asset management and
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measures of existing pavement quality. Measurements can be made by persons on the ground, visually from a moving vehicle, or using automated sensors mounted to a vehicle. PMS software often helps the user create composite pavement quality rankings based on pavement quality measures on roads or road sections. Recommendations are usually biased towards
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Research has shown that it is far less expensive to keep a road in good condition than it is to repair it once it has deteriorated. This is why pavement management systems place the priority on preventive maintenance of roads in good condition, rather than reconstructing roads in poor condition. In
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A pavement management system (PMS) is a planning tool used to aid pavement management decisions. PMS software programs model future pavement deterioration due to traffic and weather, and recommend maintenance and repairs to the road's pavement based on the type and age of the pavement and various
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In the United States, the introduction of the Governmental Accounting Standards Board’s (GASB’s) Statement 34 is having a dramatic impact on the financial reporting requirements of state and local governments. Introduced in June 1999, this provision recommends that governmental agencies report the
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was among the first to adopt a (PMS) in 1979. Like others of its era, the first PMS was based in a mainframe computer and contained provisions for an extensive database. It can be used to determine long-term maintenance funding requirements and to examine the consequences on network condition if
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Pavement condition can be divided into structural and functional condition with various condition variables. Functional condition can be divided into roughness, texture and skid resistance while structural condition includes mechanical properties and pavement distresses. To measure such indices,
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Pavement management incorporates life cycle costs into a more systematic approach to minor and major road maintenance and reconstruction projects. The needs of the entire network as well as budget projections are considered before projects are executed, as the cost of data collection can change
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Ford, K., Arman, M., Labi, S., Sinha, K.C., Thompson, P.D., Shirole, A.M., and Li, Z. 2012. NCHRP Report 713 : Estimating life expectancies of highway assets. In Transportation Research Board, National Academy of Sciences, Washington, DC. Transportation Research Board, Washington
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terms of lifetime cost and long term pavement conditions, this will result in better system performance. Agencies that concentrate on restoring their bad roads often find that by the time they've repaired them all, the roads that were in good condition have deteriorated.
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Typically, pavement management requires road inventory to be created and tied to an Asset Location Referencing System (ALRS). Road inventory includes road location using both coordinate and linear referencing systems, road width, road length and pavement type.
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is caused by traffic and weather conditions. Also, material and construction choices affect the deterioration process. It has been shown that empirical models outperform the mechanical and hybrid models in condition prediction.
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including SirWay. The following management approach evolved over the last 30 years as part of the development of the PAVER management system (U.S. Army COE, Construction Engineering Research Laboratory, Micro PAVER 2004).
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Bennett, C. R., de Solminihac, H. and Chamorro, A. Data Collection Technologies for Road Management, Transport Note No. 30, Roads and Rural Transport Thematic Group, The World Bank, Washington D.C., 2007.
329:'Saha, P., & Ksaibati, K. (2015). 'A Risk-based Optimization Methodology for Managing County Paved Roads', In Transportation Research Board 94th Annual Meeting (No. 15-1916), 427: 177: 34: 459:
Sirvio, Konsta (2017) Advances in predictive maintenance planning of roads by empirical models. Aalto University publication series DOCTORAL DISSERTATIONS, 166/2017. (
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costly laser-based tools are used extensively while development of cost effective tools such as RGB-D sensors significantly reduces the cost of data collection.
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in which the maintenance works are assigned both spatially and temporally according to the desired criteria such as minimal costs to the society.
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Piryonesi, S. M.; El-Diraby, T. E. (2020) . "Data Analytics in Asset Management: Cost-Effective Prediction of the Pavement Condition Index".
155:, which can be based on mechanical or empirical models. Also, hybrid parameterized models are popular. More recently other methods based on 196:
Pavement Management - A Manual for Communities, U. S. Department of Transportation, Metropolitan Area Planning Council, Boston MA., 1986
428:"Using Data Analytics for Cost-Effective Prediction of Road Conditions: Case of The Pavement Condition Index:[summary report]" 29:
It is also applied to airport runways and ocean freight terminals. In effect, every highway superintendent does pavement management.
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Proceedings of the 2003 Mid-Continent Transportation Research Symposium, Ames, Iowa, August 2003. © 2003 by Iowa State University.
430:. United States. Federal Highway Administration. Office of Research, Development, and Technology. FHWA-HRT-18-065. Archived from 407:
Pavement Management for Airport, roads, and Parking Lots, 2nd Edition, M.Y. Shahin, Springer Science+Business Media, LLC, 2002
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Pavement Management for Airport, Roads, and Parking Lots, 2nd Edition, M.Y. Shahin, Springer Science+Business Media, LLC, 2002
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https://www.researchgate.net/publication/319998419_Advances_in_predictive_maintenance_planning_of_roads_by_empirical_models
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Hillsborough County Pavement Management Strategy, Hillsborough County Fl, Ch.1 - Introduction, pg1., R. Cox, P.E. 2006
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Assign importance ratings for road segments, based on traffic volumes, road functional class, and community demand.
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on 2019-02-02 – via National Transportation Library Repository & Open Science Access Portal.
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ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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or other paved facilities in order to optimize pavement conditions over the entire network.
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Schedule repairs of poor and fair pavements as remaining available funding allows.
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Inventory pavement conditions, identifying good, fair and poor pavements.
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is the process of planning the maintenance and repair of a network of
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The pavement management process has been incorporated into several
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Schedule maintenance of good roads to keep them in good condition.
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Process of planning the maintenance and repair of roadway networks
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Mahmoudzadeh, A.; Firoozi Yeganeh, S.; Golroo, A. (2015-12-11).
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The approach is a process that consists of the following steps:
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Typical tasks performed by pavement management systems include:
258:"Kinect, A Novel Cutting Edge Tool in Pavement Data Collection" 163:
have been proposed that outperform their former counterparts.
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Pavement condition prediction is often referred to pavement
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http://www.clrp.cornell.edu/nuggets_and_nibbles/index.htm
425: 217: 397:https://www.sirway.info/assets/pdf/Sirway-RMS.pdf 471: 342:Pavement Management System Summer Intern Program 44: 37:target more specifically road infrastructure. 387:, California Division, November 13, 2003) 277: 426:Piryonesi, S. M.; El-Diraby, T. (2018). 140: 131: 122: 472: 279:10.5194/isprsarchives-xl-1-w5-425-2015 86: 213: 211: 251: 249: 438: 331:http://docs.trb.org/prp/15-1916.pdf 83:insufficient funding is available. 13: 419: 232:10.1061/(ASCE)IS.1943-555X.0000512 208: 14: 496: 382:U.S. Department of Transportation 246: 220:Journal of Infrastructure Systems 171: 453: 410: 401: 390: 375: 350: 385:Federal Highway Administration 335: 323: 314: 303: 294: 199: 190: 1: 183: 176:Work planning is essentially 147:Pavement performance modeling 358:"Pavement Management Primer" 7: 93:pavement management systems 45:Pavement management systems 10: 501: 144: 178:road maintenance planning 35:road maintenance planning 165:Pavement deterioration 153:deterioration modeling 52:predictive maintenance 480:Pavement engineering 264:. XL-1–W5: 425–431. 141:Condition Prediction 132:Condition Assessment 123:Inventory Definition 112:Condition Prediction 109:Condition Assessment 103:Inventory Definition 270:2015ISPArXL15..425M 106:Pavement Inspection 87:Management approach 20:Pavement management 115:Condition Analysis 485:Road construction 310:GASB Welcome Page 492: 464: 457: 451: 450: 442: 436: 435: 423: 417: 414: 408: 405: 399: 394: 388: 379: 373: 372: 370: 368: 362: 354: 348: 339: 333: 327: 321: 318: 312: 307: 301: 298: 292: 291: 281: 253: 244: 243: 215: 206: 203: 197: 194: 161:machine learning 500: 499: 495: 494: 493: 491: 490: 489: 470: 469: 468: 467: 458: 454: 444: 443: 439: 424: 420: 415: 411: 406: 402: 395: 391: 380: 376: 366: 364: 360: 356: 355: 351: 340: 336: 328: 324: 319: 315: 308: 304: 299: 295: 254: 247: 216: 209: 204: 200: 195: 191: 186: 174: 149: 143: 134: 125: 89: 47: 17: 12: 11: 5: 498: 488: 487: 482: 466: 465: 452: 437: 418: 409: 400: 389: 374: 349: 334: 322: 313: 302: 293: 245: 207: 198: 188: 187: 185: 182: 173: 170: 145:Main article: 142: 139: 133: 130: 124: 121: 120: 119: 116: 113: 110: 107: 104: 88: 85: 72: 71: 68: 65: 62: 46: 43: 15: 9: 6: 4: 3: 2: 497: 486: 483: 481: 478: 477: 475: 462: 456: 448: 441: 433: 429: 422: 413: 404: 398: 393: 386: 383: 378: 359: 353: 347: 343: 338: 332: 326: 317: 311: 306: 297: 289: 285: 280: 275: 271: 267: 263: 259: 252: 250: 241: 237: 233: 229: 225: 221: 214: 212: 202: 193: 189: 181: 179: 172:Work Planning 169: 166: 162: 158: 157:Markov models 154: 148: 138: 129: 118:Work Planning 117: 114: 111: 108: 105: 102: 101: 100: 97: 94: 84: 81: 78:The State of 76: 69: 66: 63: 60: 59: 58: 55: 53: 42: 38: 36: 30: 27: 25: 21: 455: 445: 440: 432:the original 421: 412: 403: 392: 377: 365:. Retrieved 352: 341: 337: 325: 316: 305: 296: 261: 223: 219: 201: 192: 175: 150: 135: 126: 98: 90: 77: 73: 56: 48: 39: 31: 28: 19: 18: 474:Categories 184:References 80:California 288:2194-9034 240:213782055 24:roadways 367:May 11, 266:Bibcode 286:  238:  361:(PDF) 236:S2CID 226:(1). 369:2012 284:ISSN 159:and 274:doi 228:doi 476:: 447:DC 282:. 272:. 260:. 248:^ 234:. 224:26 222:. 210:^ 463:) 449:. 371:. 290:. 276:: 268:: 242:. 230::

Index

roadways
road maintenance planning
predictive maintenance
California
pavement management systems
Pavement performance modeling
deterioration modeling
Markov models
machine learning
Pavement deterioration
road maintenance planning


doi
10.1061/(ASCE)IS.1943-555X.0000512
S2CID
213782055


"Kinect, A Novel Cutting Edge Tool in Pavement Data Collection"
Bibcode
2015ISPArXL15..425M
doi
10.5194/isprsarchives-xl-1-w5-425-2015
ISSN
2194-9034
GASB Welcome Page
http://docs.trb.org/prp/15-1916.pdf
http://www.clrp.cornell.edu/nuggets_and_nibbles/index.htm
"Pavement Management Primer"

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