Case Studies
Mar 24, 2022

Examining Crossing Conflicts by Vehicle Type at Unsignalized T-Intersections Using Accepted Gaps: A Perspective from Emerging Countries

Publication: Journal of Transportation Engineering, Part A: Systems
Volume 148, Issue 6

Abstract

The present study focuses on examining the potential of accepted gaps to assess traffic safety at unsignalized T-intersections by estimating the likelihood of a crash. Four unsignalized T-intersections with varying geometry from four different cities in India were selected. Postencroachment time (PET), a surrogate safety measure, was included in the present study to validate the results obtained through the accepted gap. The critical gap was devised as a potential parameter to evaluate traffic safety based on accepted gaps. Various probability distributions were checked for defining accepted gap and PET datasets. Generalized extreme value (GEV) was found to be the best-fitted distribution defining both: accepted gap and PET datasets. Thereafter, GEV distribution was used to estimate the likelihood of crash using accepted gap and PET datasets. The statistical check showed no significant difference in the crash probability obtained using the accepted gap and PET. Thus, the study was further extended, and risk characterization was performed using accepted gap data. The risk is characterized into different levels using the K-means clustering technique. The results attained were validated with 3 years’ crash data obtained from Surat police authorities. The developed risk thresholds provided a close approximation with the crash data. Thus, it can be concluded that accepted gaps can be considered as a potential surrogate safety measure for analyzing the risk and severity of crossing conflicts at unsignalized intersections.

Get full access to this article

View all available purchase options and get full access to this article.

Data Availability Statement

Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.

Acknowledgments

The authors would like to thank Surat police authorities for providing the crash data. The authors would also like to thank Council of Scientific and Industrial Reseach-Central Road Research Institute (CSIR-CRRI) for sharing the video data of Faridabad intersection collected for the research project “Development of Indian Highway Capacity Manual (Indo-HCM).” The authors sincerely acknowledge The Maharaja Sayajirao (MS) University of Baroda for sharing the data related to Vadodara intersection.

References

Amundsen, F. H., and C. Hyden. 1977. Proceedings of first workshop on traffic conflicts. Oslo, Norway: TTI.
Arasan, V. T., and S. S. Arkatkar. 2010. “Microsimulation study of effect of volume and road width on PCU of vehicles under heterogeneous traffic.” J. Transp. Eng. 136 (12): 1110–1119. https://doi.org/10.1061/(ASCE)TE.1943-5436.0000176.
Archer, J. 2005. Indicators for traffic safety assessment and prediction and their application in micro-simulation modelling: A study of urban and suburban intersections. Stockholm, Sweden: KTH Royal Institute of Technology.
Arkatkar, S., S. Velmurugan, R. Puvvala, B. Ponnu, and S. Narula. 2016. “Methodology for simulating heterogeneous traffic on expressways in developing countries: A case study in India.” Transp. Lett. 8 (2): 61–76. https://doi.org/10.1179/1942787515Y.0000000008.
Arkatkar, S. S., and V. T. Arasan. 2010. “Effect of gradient and its length on performance of vehicles under heterogeneous traffic conditions.” J. Transp. Eng. 136 (12): 1120–1136. https://doi.org/10.1061/(ASCE)TE.1943-5436.0000177.
Arun, A., M. M. Haque, A. Bhaskar, S. Washington, and T. Sayed. 2021. “A systematic mapping review of surrogate safety assessment using traffic conflict techniques.” Accid. Anal. Prev. 153 (Apr): 106016. https://doi.org/10.1016/j.aap.2021.106016.
Ashalatha, R., and S. Chandra. 2011. “Critical gap through clearing behavior of drivers at unsignalised intersections.” KSCE J. Civ. Eng. 15 (8): 1427–1434. https://doi.org/10.1007/s12205-011-1392-5.
Azevedo, C. L., and H. Farah. 2015. “Using extreme value theory for the prediction of head-on collisions during passing maneuvres.” In Proc., 2015 IEEE 18th Int. Conf. on Intelligent Transportation Systems, 268–273. New York: IEEE.
Babu, S. S., and P. Vedagiri. 2018. “Proactive safety evaluation of a multilane unsignalized intersection using surrogate measures.” Transp. Lett. 10 (2): 104–112. https://doi.org/10.1080/19427867.2016.1230172.
Chaudhari, A., N. Gore, S. Arkatkar, G. Joshi, and S. Pulugurtha. 2019. “Gap acceptance based safety evaluation of urban midblock crossings under mixed traffic environment.” In Proc., 98th Annual Meeting of Transportation Research Board. Washington, DC: Transportation Research Board.
Chaudhari, A., N. Gore, S. Arkatkar, G. Joshi, and S. Pulugurtha. 2020. “Pedestrian crossing warrants for urban midblock crossings under mixed traffic environment.” J. Transp. Eng. Part A. Syst. 146 (5): 04020031. https://doi.org/10.1061/JTEPBS.0000338.
Chaudhari, A., N. Gore, S. Arkatkar, G. Joshi, and S. Pulugurtha. 2021. “Exploring pedestrian surrogate safety measures by road geometry at midblock crosswalks: A perspective under mixed traffic conditions.” IATSS Res. 45 (1): 87–101. https://doi.org/10.1016/j.iatssr.2020.06.001.
Chin, H., and S. Quek. 1997. “Measurement of traffic conflicts.” Saf. Sci. 26 (3): 169–185. https://doi.org/10.1016/S0925-7535(97)00041-6.
Čokorilo, O., M. De Luca, and G. D. Acqua. 2016. “Aircraft safety analysis using clustering algorithms.” J. Risk Res. 17 (10): 1325–1340. https://doi.org/10.1080/13669877.2013.879493.
Cooper, P. J. 1984. “Experience with traffic conflicts in Canada with emphasis on ‘post encroachment time’ techniques.” In International calibration study of traffic conflict techniques, 75–96. Berlin: Springer.
Creaser, J. I., M. E. Rakauskas, N. J. Ward, J. C. Laberge, and M. Donath. 2007. “Concept evaluation of intersection decision support (IDS) system interfaces to support drivers’ gap acceptance decisions at rural stop-controlled intersections.” Transp. Res. Part F Traffic Psychol. Behav. 10 (3): 208–228. https://doi.org/10.1016/j.trf.2006.10.004.
CSIR (Council of Scientific and Industrial Reseach). 2017. Indian highway capacity manual. New Delhi, India: CSIR.
Farah, H., and C. Lima. 2017. “Safety analysis of passing maneuvers using extreme value theory.” IATSS Res. 41 (1): 12–21. https://doi.org/10.1016/j.iatssr.2016.07.001.
Gelau, C., J. Sirek, and K. Dahmen-Zimmer. 2011. “Effects of time pressure on left-turn decisions of elderly drivers in a fixed-base driving simulator.” Transp. Res. Part F Traffic Psychol. Behav. 14 (1): 76–86. https://doi.org/10.1016/j.trf.2010.10.002.
Gettman, D., and L. Head. 2003. “Surrogate safety measures from traffic simulation models.” Transp. Res. Rec. 1840 (1): 104–115. https://doi.org/10.3141/1840-12.
Glauz, W. D., and D. J. Migletz. 1980. Application of traffic conflict analysis at intersections. Washington, DC: Transportation Research Board.
Goyani, J., A. B. Paul, N. Gore, S. Arkatkar, and G. Joshi. 2021. “Investigation of crossing conflicts by vehicle type at unsignalized T-intersections under varying roadway and traffic conditions in India.” J. Transp. Eng. Part A. Syst. 147 (2): 05020011. https://doi.org/10.1061/JTEPBS.0000479.
Goyani, J., N. Pawar, N. Gore, M. Jain, and S. Arkatkar. 2019. “Investigation of traffic conflicts at unsignalized intersection for reckoning crash probability under mixed traffic conditions.” J. East. Asia Soc. Transp. Stud. 13 (Dec): 2091–2110. https://doi.org/10.11175/easts.13.2091.
Guo, F., S. G. Klauer, J. M. Hankey, and T. A. Dingus. 2010. “Near crashes as crash surrogate for naturalistic driving studies.” Transp. Res. Rec. 2147 (1): 66–74. https://doi.org/10.3141/2147-09.
Gupta, M., N. M. Pawar, and N. R. Velaga. 2021. “Impact of lockdown and change in mobility patterns on road fatalities during COVID-19 pandemic.” Transp. Lett. 13 (5–6): 447–460. https://doi.org/10.1080/19427867.2021.1892937.
Hyden, C. 1987. The development of a method for traffic safety evaluation: The Swedish traffic conflicts technique. Lund, Sweden: Lund Institute of Technology.
IRC (Indian Roads Congress). 2012. Road accident recording forms A-1 and A-4 (second revision). IRC 53-2012. New Delhi, India: IRC.
Kala, R. 2016. “Advanced driver assistance systems.” In On-road intelligent vehicles, 59–82. Amsterdam, Netherlands: Elsevier.
Killi, D. V., and P. Vedagiri. 2014. “Proactive evaluation of traffic safety at an unsignalized intersection using micro-simulation.” J. Traffic Logist. Eng. 2 (2): 140–145. https://doi.org/10.12720/jtle.2.2.140-145.
Killi, D. V., and P. Vedagiri. 2015. “Traffic safety evaluation of uncontrolled intersections using surrogate safety measures under mixed traffic conditions.” Transp. Res. Rec. 2512 (1): 81–89. https://doi.org/10.3141/2512-10.
Mahmud, S. M. S., L. Ferreira, M. S. Hoque, and A. Tavassoli. 2017. “Application of proximal surrogate indicators for safety evaluation: A review of recent developments and research needs.” IATSS Res. 41 (4): 153–163. https://doi.org/10.1016/j.iatssr.2017.02.001.
Mahmud, S. M. S., L. Ferreira, M. S. Hoque, and A. Tavassoli. 2020. “Using a surrogate safety approach to prioritize hazardous segments in a rural highway in a developing country.” IATSS Res. 44 (2): 132–141. https://doi.org/10.1016/j.iatssr.2019.11.002.
McDowell, M., J. Wennell, P. Storr, and J. Darzentas. 1983. Gap acceptance and traffic conflict simulation as a measure of risk. Crowthorne, UK: Transport and Road Research Laboratory.
Migletz, D. J., W. D. Glauz, and K. M. Bauer. 1985. Relationships between traffic conflicts and accidents. Washington, DC: US DOT, Federal Highway Administration.
Ministry of Road Transport and Highways. 2019. Road transport yearbook (2016-17). New Delhi, India: Ministry of Road Transport and Highways.
Ministry of Road Transport and Highways. 2020. Road accidents in India-2019. New Delhi, India: Ministry of Road Transport and Highways.
Ministry of Road Transport and Highways. 2021. “Road accidents in India.” Accessed May 23, 2021. https://morth.nic.in/road-accident-in-india.
Mishra, A., A. Chepuri, S. S. Arkatkar, and A. Maji. 2017. “Safety evaluation of un-signalized intersection using hybrid.” In Proc., 97th Annual Meeting of Transportation Research Board. Washington, DC: Transportation Research Board.
Mohan, M., and S. Chandra. 2018a. “Critical gap estimation at two-way stop-controlled intersections based on occupancy time data.” Transportmetrica A Transp. Sci. 14 (4): 316–329. https://doi.org/10.1080/23249935.2017.1385657.
Mohan, M., and S. Chandra. 2018b. “Three methods of PCU estimation at unsignalized intersections.” Transp. Lett. 10 (2): 68–74. https://doi.org/10.1080/19427867.2016.1190883.
Mohan, M., and S. Chandra. 2019. “Capacity estimation of unsignalized intersections under heterogeneous traffic conditions.” Can. J. Civ. Eng. 47 (6): 651–662. https://doi.org/10.1139/cjce-2018-0796.
Mohan, M., and S. Chandra. 2021. “Investigating the influence of conflicting flow’s composition on critical gap under heterogeneous traffic conditions.” Int. J. Transp. Sci. Technol. 10 (4): 393–401. https://doi.org/10.1016/j.ijtst.2021.01.004.
Mondal, S., and A. Gupta. 2019. “Discharge characteristics analysis of queued-up vehicles at signal-controlled intersections under heterogeneous traffic conditions.” Int. J. Civ. Eng. 17 (5): 619–628. https://doi.org/10.1007/s40999-018-0343-7.
Mondal, S., and A. Gupta. 2021. “Non-linear evaluation model to analyze saturation flow under weak-lane-disciplined mixed traffic stream.” Transp. Res. Rec. 2675 (8): 422–431. https://doi.org/10.1177/0361198121998370.
Patil, G. R., and D. S. Pawar. 2014. “Temporal and spatial gap acceptance for minor road at uncontrolled intersections in India.” Transp. Res. Rec. 2461 (1): 129–136. https://doi.org/10.3141/2461-16.
Paul, M., V. Charan, V. Soni, and I. Ghosh. 2018. “Calibration methodology of microsimulation model for unsignalized intersection under.” In Urbanization challenges in emerging economies: Energy and water infrastructure; transportation infrastructure; and planning and financing, 618–627. Reston, VA: ASCE.
Paul, M., and I. Ghosh. 2018. “Speed-based proximal indicator for right-turn crashes at unsignalized intersections in India.” J. Transp. Eng. Part A. Syst. 144 (6): 04018024. https://doi.org/10.1061/JTEPBS.0000139.
Paul, M., and I. Ghosh. 2020. “Post encroachment time threshold identification for right-turn related crashes at unsignalized intersections on intercity highways under mixed traffic.” Int. J. Inj. Control Saf. Promot. 27 (2): 121–135. https://doi.org/10.1080/17457300.2019.1669666.
Pawar, D. S., and G. R. Patil. 2017. “Minor-street vehicle dilemma while maneuvering at unsignalized intersections.” J. Transp. Eng. Part A. Syst. 143 (8): 04017039. https://doi.org/10.1061/JTEPBS.0000066.
Pawar, N., N. Gore, and S. Arkatkar. 2019. “Influence of driving environment on safety at un-signalized T-intersection under mixed traffic conditions.” In Innovative research in transportation infrastructure, 23–31. Singapore: Springer.
Pawar, N. M., R. K. Khanuja, P. Choudhary, and N. R. Velaga. 2020. “Modelling braking behaviour and accident probability of drivers under increasing time pressure conditions.” Accid. Anal. Prev. 136 (Mar): 105401. https://doi.org/10.1016/j.aap.2019.105401.
Pawar, N. M., and N. R. Velaga. 2020. “Modelling the influence of time pressure on reaction time of drivers.” Transp. Res. Part F Traffic Psychol. Behav. 72 (Jul): 1–22. https://doi.org/10.1016/j.trf.2020.04.017.
Pawar, N. M., and N. R. Velaga. 2021. “Effect of time pressure on steering control of the drivers in a car-following situation.” Transp. Res. Part F Traffic Psychol. Behav. 80 (Jul): 218–236. https://doi.org/10.1016/j.trf.2021.04.007.
Ponnaluri, R. V. 2012. “Road traffic crashes and risk groups in India: Analysis, interpretations, and prevention strategies.” IATSS Res. 35 (2): 104–110. https://doi.org/10.1016/j.iatssr.2011.09.002.
Preston, H., R. Storm, M. Donath, and C. H. M. Hill. 2004. Review of Minnesota’ s rural intersection crashes: Methodology for identifying intersections for intersection decision support (IDS). St. Paul, MN: Minnesota DOT.
Pulugurtha, S. S., V. R. Duddu, and Y. Kotagiri. 2013. “Traffic analysis zone level crash estimation models based on land use characteristics.” Accid. Anal. Prev. 50 (Jan): 678–687. https://doi.org/10.1016/j.aap.2012.06.016.
Reddy, S. K. A., A. Chepuri, and S. S. Arkatkar. 2019. “Developing proximal safety indicators for assessment of un-signalized intersection—A case study in Surat city.” Transp. Lett. 12 (5): 303–315. https://doi.org/10.1080/19427867.2019.1589162.
Rousseeuw, P. J. 1987. “Silhouettes: A graphical aid to the interpretation and validation of cluster analysis.” J. Comput. Appl. Math. 20 (Nov): 53–65. https://doi.org/10.1016/0377-0427(87)90125-7.
Sayed, T., and S. Zein. 1999. “Traffic conflict standards for intersections.” Transp. Plann. Technol. 22 (4): 309–323. https://doi.org/10.1080/03081069908717634.
Songchitruksa, P., and A. P. Tarko. 2006. “The extreme value theory approach to safety estimation.” Accid. Anal. Prev. 38 (4): 811–822. https://doi.org/10.1016/j.aap.2006.02.003.
Spicer, B. R. 1971. A pilot study of traffic conflicts at a rural dual carriageway intersection. Crowthorne, UK: Road Research Laboratory.
Tarko, A. P. 2012. “Use of crash surrogates and exceedance statistics to estimate road safety.” Accid. Anal. Prev. 45 (Mar): 230–240. https://doi.org/10.1016/j.aap.2011.07.008.
Tarko, A. P. 2018. “Surrogate measures of safety.” In Vol. 11 of Safe mobility: Challenges, methodology and solutions (transport and sustainability), 383–405. Bingley, UK: Emerald Publishing Limited. https://doi.org/10.1108/S2044-994120180000011019.
Tarko, A. P., and P. Songchitruksa. 2005. Estimating the frequency of crashes as extreme traffic events. In Proc., 84th Annual Meeting of the Transportation Research Board. Washington, DC: Transportation Research Board.
Theofilatos, A., and A. Ziakopoulos. 2018. “Examining injury severity of moped and motorcycle occupants with real-time traffic and weather data.” J. Transp. Eng. Part A. Syst. 144 (11): 04018066. https://doi.org/10.1061/JTEPBS.0000193.
Troutbeck, R. J., and W. Brilon. 1997. “Unsignalized intersection theory.” In Monograph on traffic flow theory. Washington, DC: Federal Highway Administration.
Tupper, S. M., M. A. Knodler Jr., and D. S. Hurwitz. 2011. “Connecting gap acceptance behavior with crash.” In Proc., 3rd Int. Conf. Road Safety and Simulation. Washington, DC: Transportation Research Board.
Vasconcelos, L., L. Neto, Á. M. Seco, and A. B. Silva. 2014. “Validation of the surrogate safety assessment model for assessment of intersection safety.” Transp. Res. Rec. 2432 (1): 1–9. https://doi.org/10.3141/2432-01.
Vogel, K. 2003. “A comparison of headway and time to collision as safety indicators.” Accid. Anal. Prev. 35 (3): 427–433. https://doi.org/10.1016/S0001-4575(02)00022-2.
Wang, C., and N. Stamatiadis. 2013. “Surrogate safety measure for simulation-based conflict study.” Transp. Res. Rec. 2386 (1): 72–80. https://doi.org/10.3141/2386-09.
Wang, C., and N. Stamatiadis. 2014. “Evaluation of a simulation-based surrogate safety metric.” Accid. Anal. Prev. 71 (Oct): 82–92. https://doi.org/10.1016/j.aap.2014.05.004.
Wang, C., C. Xu, and Y. Dai. 2019. “A crash prediction method based on bivariate extreme value theory and video-based vehicle trajectory data.” Accid. Anal. Prev. 123 (Feb): 365–373. https://doi.org/10.1016/j.aap.2018.12.013.
Xia, D., F. Wu, X. Zhang, and Y. Zhuang. 2008. “Local and global approaches of affinity propagation clustering for large scale data.” J. Zhejiang Univ. A 9 (10): 1373–1381. https://doi.org/10.1631/jzus.A0720058.
Yan, X., E. Radwan, and D. Guo. 2007. “Effects of major-road vehicle speed and driver age and gender on left-turn gap acceptance.” Accid. Anal. Prev. 39 (4): 843–852. https://doi.org/10.1016/j.aap.2006.12.006.
Zheng, L., and T. Sayed. 2019a. “Application of extreme value theory for before-after road safety analysis.” Transp. Res. Rec. 2673 (4): 1001–1010. https://doi.org/10.1177/0361198119841555.
Zheng, L., and T. Sayed. 2019b. “Comparison of traffic conflict indicators for crash estimation using peak over threshold approach.” Transp. Res. Rec. 2673 (5): 493–502. https://doi.org/10.1177/0361198119841556.
Zheng, L., and T. Sayed. 2019c. “From univariate to bivariate extreme value models: Approaches to integrate traffic conflict indicators for crash estimation.” Transp. Res. Part C Emerging Technol. 103 (Jun): 211–225. https://doi.org/10.1016/j.trc.2019.04.015.
Zheng, L., T. Sayed, and M. Essa. 2019. “Validating the bivariate extreme value modeling approach for road safety estimation with different traffic conflict indicators.” Accid. Anal. Prev. 123 (Feb): 314–323. https://doi.org/10.1016/j.aap.2018.12.007.

Information & Authors

Information

Published In

Go to Journal of Transportation Engineering, Part A: Systems
Journal of Transportation Engineering, Part A: Systems
Volume 148Issue 6June 2022

History

Received: Jan 20, 2021
Accepted: Dec 23, 2021
Published online: Mar 24, 2022
Published in print: Jun 1, 2022
Discussion open until: Aug 24, 2022

Permissions

Request permissions for this article.

Authors

Affiliations

Nishant Mukund Pawar [email protected]
Postgraduate Student, Dept. of Civil Engineering, Sardar Vallabhbhai National Institute of Technology, Surat 395007, India. Email: [email protected]
Research Scholar, Dept. of Civil Engineering, Sardar Vallabhbhai National Institute of Technology, Surat 395007, India. Email: [email protected]
Shriniwas Arkatkar [email protected]
Associate Professor, Dept. of Civil Engineering, Sardar Vallabhbhai National Institute of Technology, Surat 395007, India (corresponding author). Email: [email protected]

Metrics & Citations

Metrics

Citations

Download citation

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.

Cited by

  • Assessing the impact of reaction time on the crossing and merging conflicts and identifying suitable reaction time to detect the critical conflict, Transportation Planning and Technology, 10.1080/03081060.2024.2341313, (1-23), (2024).
  • Exploratory analysis of evasion actions of powered two-wheeler conflicts at unsignalized intersection, Accident Analysis & Prevention, 10.1016/j.aap.2023.107363, 194, (107363), (2024).
  • Drivers’ Dilemma at High-Speed Unsignalized Intersections, Transportation Research Record: Journal of the Transportation Research Board, 10.1177/03611981231178813, 2678, 3, (82-97), (2023).
  • Impact assessment of professional drivers’ speed compliance and speed adaptation with posted speed limits in different driving environments and driving conditions, Transportation Letters, 10.1080/19427867.2023.2252222, (1-11), (2023).
  • Examining the effect of vehicle type on right-turn crossing conflicts of minor road traffic at unsignalized T-intersections, IATSS Research, 10.1016/j.iatssr.2023.12.002, 47, 4, (545-556), (2023).
  • Identification of Crash Severity Level of Unsignalized Intersection Blackspots in Mixed Traffic Scenario, Recent Advances in Traffic Engineering, 10.1007/978-981-99-4464-4_35, (559-574), (2023).
  • Critical Gap Estimation and Its Implication on Capacity and Safety of High-Speed Un-Signalised T-Intersection under Heterogeneous Traffic Conditions, Communications - Scientific letters of the University of Zilina, 10.26552/com.C.2022.4.D215-D228, 24, 4, (D215-D228), (2022).
  • Categorization of gaps at mid-block median openings in heterogeneous traffic: adjudging the applicability of support vector machine and occupancy time methods, Transportation Letters, 10.1080/19427867.2022.2133375, 15, 9, (1126-1139), (2022).
  • Investigating and modeling the influence of PET-types on crossing conflicts at urban unsignalized intersections in India, International Journal of Injury Control and Safety Promotion, 10.1080/17457300.2022.2147194, 30, 2, (239-254), (2022).

View Options

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Media

Figures

Other

Tables

Share

Share

Copy the content Link

Share with email

Email a colleague

Share