United States. Department of Transportation. Federal Highway Administration. Office of Safety
2016-12-01
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A Crash Modification Factor (CMF) is a numerical value that shows the expected change in crashes after implementing a countermeasure. It provides a quantitative estimate to replace anecdotal estimates of the safety effect of the countermeasure in benefit/cost analyses or project funding requests.
United States. Department of Transportation. Federal Highway Administration. Office of Safety (2016). Ensuring Consistency in Decision Making: Why and How Your State Should Develop a State CMF List (Report No. FHWA-SA-17-023). United States. Department of Transportation. Federal Highway Administration. Office of Safety. https://rosap.ntl.bts.gov/view/dot/50491
United States. Department of Transportation. Federal Highway Administration. Office of Safety. Ensuring Consistency in Decision Making: Why and How Your State Should Develop a State CMF List. Report no. FHWA-SA-17-023. United States. Department of Transportation. Federal Highway Administration. Office of Safety, 2016. https://rosap.ntl.bts.gov/view/dot/50491.
United States. Department of Transportation. Federal Highway Administration. Office of Safety Ensuring Consistency in Decision Making: Why and How Your State Should Develop a State CMF List. United States. Department of Transportation. Federal Highway Administration. Office of Safety, 2016, Report no. FHWA-SA-17-023, ROSA P. https://rosap.ntl.bts.gov/view/dot/50491.
The purpose of this primer is to assist transportation planners in effectively using archived operations data for developing, analyzing, and evaluating transportation plans and programs. This primer raises planners' awareness of the opportunities afforded through archived operations data and provides guidance on how to take advantage of that data t
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Bauer, J., Margiotta, R. A., & Pack, M. L. (2016). Applying Archived Operations Data in Transportation Planning – A Primer (Report No. FHWA-HOP-16-082). United States. Federal Highway Administration. https://rosap.ntl.bts.gov/view/dot/42441
Bauer, Jocelyn, Richard A. Margiotta, and Michael L. Pack. Applying Archived Operations Data in Transportation Planning – A Primer. Report no. FHWA-HOP-16-082. United States. Federal Highway Administration, 2016. https://rosap.ntl.bts.gov/view/dot/42441.
Bauer, Jocelyn, et al. Applying Archived Operations Data in Transportation Planning – A Primer. United States. Federal Highway Administration, 2016, Report no. FHWA-HOP-16-082, ROSA P. https://rosap.ntl.bts.gov/view/dot/42441.
The U.S. Department of Transportation Integrated Corridor Management (ICM) Initiative aims to advance the state of the practice in transportation corridor operations to manage congestion. Through the deployment of ICM at the two selected Demonstration Sites (Dallas, Texas and San Diego, California), this initiative thoroughly investigated and docum
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Alexiadis, V., & Chu, A. (2016). Integrated corridor management analysis, modeling, and simulation for the I-15 corridor in San Diego, California post-deployment assessment report (Report No. FHWA-JPO-16-403). United States. Department of Transportation. Intelligent Transportation Systems Joint Program Office. https://rosap.ntl.bts.gov/view/dot/32035
Alexiadis, Vassili and Alice Chu. Integrated corridor management analysis, modeling, and simulation for the I-15 corridor in San Diego, California post-deployment assessment report. Report no. FHWA-JPO-16-403. United States. Department of Transportation. Intelligent Transportation Systems Joint Program Office, 2016. https://rosap.ntl.bts.gov/view/dot/32035.
Alexiadis, Vassili, and Alice Chu Integrated corridor management analysis, modeling, and simulation for the I-15 corridor in San Diego, California post-deployment assessment report. United States. Department of Transportation. Intelligent Transportation Systems Joint Program Office, 2016, Report no. FHWA-JPO-16-403, ROSA P. https://rosap.ntl.bts.gov/view/dot/32035.
This study is the second in a series of four experiments exploring human factors issues associated with the introduction of cooperative adaptive cruise control (CACC). Specifically, this study explored drivers’ abilities to merge into a stream of continuously moving vehicles in a dedicated lane. Participants were asked to complete one of three diff
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Balk, S. A., Jackson, S., & Philips, B. H. (2016). Cooperative Adaptive Cruise Control Human Factors Study : Experiment 2 : Merging Behavior (Report No. FHWA-HRT-16-057). United States. Federal Highway Administration. https://rosap.ntl.bts.gov/view/dot/35844
Balk, Stacy A., Steven Jackson, and Brian H. Philips. Cooperative Adaptive Cruise Control Human Factors Study : Experiment 2 : Merging Behavior. Report no. FHWA-HRT-16-057. United States. Federal Highway Administration, 2016. https://rosap.ntl.bts.gov/view/dot/35844.
Balk, Stacy A., et al. Cooperative Adaptive Cruise Control Human Factors Study : Experiment 2 : Merging Behavior. United States. Federal Highway Administration, 2016, Report no. FHWA-HRT-16-057, ROSA P. https://rosap.ntl.bts.gov/view/dot/35844.
United States. Department of Transportation. Federal Highway Administration. Office of Safety
2016-12-01
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Data can be a powerful tool for telling a story. Evaluating performance both before and after implementing a Road Diet is key to an agency successfully implementing its next Road Diet project. Data helps agencies choose the most appropriate projects to meet their needs, supports design decisions, helps garner public support, and provides a building
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United States. Department of Transportation. Federal Highway Administration. Office of Safety (2016). Road Diet: Road Diet Evaluation Metrics (Report No. FHWA-SA-17-022). United States. Department of Transportation. Federal Highway Administration. Office of Safety. https://rosap.ntl.bts.gov/view/dot/50490
United States. Department of Transportation. Federal Highway Administration. Office of Safety. Road Diet: Road Diet Evaluation Metrics. Report no. FHWA-SA-17-022. United States. Department of Transportation. Federal Highway Administration. Office of Safety, 2016. https://rosap.ntl.bts.gov/view/dot/50490.
United States. Department of Transportation. Federal Highway Administration. Office of Safety Road Diet: Road Diet Evaluation Metrics. United States. Department of Transportation. Federal Highway Administration. Office of Safety, 2016, Report no. FHWA-SA-17-022, ROSA P. https://rosap.ntl.bts.gov/view/dot/50490.
Public-Private Partnerships (P3s) concessions are an integrated service delivery approach where a public transportation agency enters a contractual agreement with a private sector entity to deliver a service and/or facility for a specific period. Under the P3 approach, the private sector entity is singly responsible for the design, construction, fi
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Guiny, S., Mirchandani, D., Clark, B. Y., Ham, M., Hallikeri, V., & Page, S. (2016). Public-Private Partnership Toll Concessions: Model Contract Guide (Report No. FHWA-HIN-17-001). United States. Department of Transportation. Federal Highway Administration. Office of Innovative Program Delivery. https://rosap.ntl.bts.gov/view/dot/92615
Guiny, Sophie, Dolly Mirchandani, Benjamin Y Clark, Marcel Ham, Varun Hallikeri, and Sasha Page. Public-Private Partnership Toll Concessions: Model Contract Guide. Report no. FHWA-HIN-17-001. United States. Department of Transportation. Federal Highway Administration. Office of Innovative Program Delivery, 2016. https://rosap.ntl.bts.gov/view/dot/92615.
Guiny, Sophie, et al. Public-Private Partnership Toll Concessions: Model Contract Guide. United States. Department of Transportation. Federal Highway Administration. Office of Innovative Program Delivery, 2016, Report no. FHWA-HIN-17-001, ROSA P. https://rosap.ntl.bts.gov/view/dot/92615.
A basic part of travel demand model validation is running the model for a “base year” and comparing the outputs to observed data. Sensitivity testing and temporal validation are also critical components of any model validation effort. In this project, two model versions for each of two metropolitan areas were run twice each: 1) the more recent vers
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Rossi, T. (2016). Making a Model a Good Predictive Tool (Report No. FHWA-HEP-17-048). United States. Federal Highway Administration. https://rosap.ntl.bts.gov/view/dot/55807
Rossi, Thomas. Making a Model a Good Predictive Tool. Report no. FHWA-HEP-17-048. United States. Federal Highway Administration, 2016. https://rosap.ntl.bts.gov/view/dot/55807.
Rossi, Thomas Making a Model a Good Predictive Tool. United States. Federal Highway Administration, 2016, Report no. FHWA-HEP-17-048, ROSA P. https://rosap.ntl.bts.gov/view/dot/55807.
The Illinois Department of Transportation (IDOT) published the AASHTO Highway Safety Manual Illinois User Guide with Illinois Calibration Factor and Default Values in 2014. This book provides guidance on incorporating AASHTO Highway Safety Manual methods into Illinois roadway safety management practices. Also in 2014, IDOT published the Systemic Sa
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Hall, J. P. (2016). State-Specific Highway Safety Manual and Systemic Safety Analysis in Illinois: Roadway Safety Data and Analysis Case Study (Report No. FHWA-SA-17-014). United States. Department of Transportation. Federal Highway Administration. Office of Safety. https://rosap.ntl.bts.gov/view/dot/50450
Hall, James P.. State-Specific Highway Safety Manual and Systemic Safety Analysis in Illinois: Roadway Safety Data and Analysis Case Study. Report no. FHWA-SA-17-014. United States. Department of Transportation. Federal Highway Administration. Office of Safety, 2016. https://rosap.ntl.bts.gov/view/dot/50450.
Hall, James P. State-Specific Highway Safety Manual and Systemic Safety Analysis in Illinois: Roadway Safety Data and Analysis Case Study. United States. Department of Transportation. Federal Highway Administration. Office of Safety, 2016, Report no. FHWA-SA-17-014, ROSA P. https://rosap.ntl.bts.gov/view/dot/50450.
The South Carolina Department of Transportation (SCDOT) and the South Carolina Department of Public Safety (SCDPS) implemented the South Carolina Collision and Ticket Tracking System (SCCATTS), a long-term initiative to improve law enforcement data quality. SCCATTS supports decision making with quality data and efficient data sharing among stakehol
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Scopatz, R. A., & Brown, R. (2016). South Carolina Safety Data Improvements through Electronic Crash System Deployment: Roadway Safety Data and Analysis Case Study (Report No. FHWA-SA-16-109). United States. Department of Transportation. Federal Highway Administration. Office of Safety. https://rosap.ntl.bts.gov/view/dot/42848
Scopatz, Robert A. and Richard Brown. South Carolina Safety Data Improvements through Electronic Crash System Deployment: Roadway Safety Data and Analysis Case Study. Report no. FHWA-SA-16-109. United States. Department of Transportation. Federal Highway Administration. Office of Safety, 2016. https://rosap.ntl.bts.gov/view/dot/42848.
Scopatz, Robert A., and Richard Brown South Carolina Safety Data Improvements through Electronic Crash System Deployment: Roadway Safety Data and Analysis Case Study. United States. Department of Transportation. Federal Highway Administration. Office of Safety, 2016, Report no. FHWA-SA-16-109, ROSA P. https://rosap.ntl.bts.gov/view/dot/42848.
North Carolina is one of a small number of States that have actively pursued developing their own crash modification factor (CMF) "short list" for countermeasures that are deployed throughout the State. The North Carolina Department of Transportation (NCDOT) wanted to develop a list of CMFs to use in benefit cost analyses across the State. To devel
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Smith, S., & Scopatz, R. A. (2016). North Carolina's State-Specific CMFs: Roadway Safety Data and Analysis (Report No. FHWA-SA-16-107). United States. Department of Transportation. Federal Highway Administration. Office of Safety. https://rosap.ntl.bts.gov/view/dot/50449
Smith, Sarah and Robert A. Scopatz. North Carolina's State-Specific CMFs: Roadway Safety Data and Analysis. Report no. FHWA-SA-16-107. United States. Department of Transportation. Federal Highway Administration. Office of Safety, 2016. https://rosap.ntl.bts.gov/view/dot/50449.
Smith, Sarah, and Robert A. Scopatz North Carolina's State-Specific CMFs: Roadway Safety Data and Analysis. United States. Department of Transportation. Federal Highway Administration. Office of Safety, 2016, Report no. FHWA-SA-16-107, ROSA P. https://rosap.ntl.bts.gov/view/dot/50449.
United States. Federal Highway Administration. Office of Planning, Environment, and Realty
2016-11-17
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This digest shares the latest information from a range of Federal and non-Federal sources, addressing transportation and its relationship to the human environment. Through this information exchange, FHWA hopes to foster dialogue at all levels and continue to further the state of the practice on these important topics in support of safety; infrastru
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United States. Federal Highway Administration. Office of Planning, Environment, and Realty (2016). Human Environment Digest: November 17, 2016. United States. Federal Highway Administration. Office of Planning, Environment, and Realty. https://rosap.ntl.bts.gov/view/dot/55218
United States. Federal Highway Administration. Office of Planning, Environment, and Realty. Human Environment Digest: November 17, 2016. United States. Federal Highway Administration. Office of Planning, Environment, and Realty, 2016. https://rosap.ntl.bts.gov/view/dot/55218.
United States. Federal Highway Administration. Office of Planning, Environment, and Realty Human Environment Digest: November 17, 2016. United States. Federal Highway Administration. Office of Planning, Environment, and Realty, 2016, ROSA P. https://rosap.ntl.bts.gov/view/dot/55218.
The ETFOMM (Enhanced Transportation Flow Open Source Microscopic Model) Cloud Service (ECS) is a software product sponsored by the U.S. Department of Transportation in conjunction with the “Microscopic Traffic Simulation Models and Software—An Open Source Approach” project. ETFOMM’s primary components are the core microscopic traffic Simulation Eng
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Bared, J. (2016). Open Source Surrogate Safety Assessment Model, 2017 Enhancement and Update: SSAM Version 3.0 [Tech Brief] (Report No. FHWA-HRT-17-027). United States. Federal Highway Administration. https://rosap.ntl.bts.gov/view/dot/35919
Bared, Joe. Open Source Surrogate Safety Assessment Model, 2017 Enhancement and Update: SSAM Version 3.0 [Tech Brief]. Report no. FHWA-HRT-17-027. United States. Federal Highway Administration, 2016. https://rosap.ntl.bts.gov/view/dot/35919.
Bared, Joe Open Source Surrogate Safety Assessment Model, 2017 Enhancement and Update: SSAM Version 3.0 [Tech Brief]. United States. Federal Highway Administration, 2016, Report no. FHWA-HRT-17-027, ROSA P. https://rosap.ntl.bts.gov/view/dot/35919.
Pennsylvania Department of Transportation (PennDOT) used Part C of the Highway Safety Manual (HSM) to develop State-specific safety performance functions (SPFs). For some facility types, PennDOT calibrated the SPFs at the district or regional level within the State. PennDOT believes that pre-selecting applicable CMFS, and developing State-specific
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Scopatz, R. A., & Smith, S. M. (2016). Pennsylvania's State-Specific SPFs and CMFs: Roadway Safety Data and Analysis Case Study (Report No. FHWA-SA-16-062). United States. Department of Transportation. Federal Highway Administration. Office of Safety. https://rosap.ntl.bts.gov/view/dot/42845
Scopatz, Robert A. and Sarah M. Smith. Pennsylvania's State-Specific SPFs and CMFs: Roadway Safety Data and Analysis Case Study. Report no. FHWA-SA-16-062. United States. Department of Transportation. Federal Highway Administration. Office of Safety, 2016. https://rosap.ntl.bts.gov/view/dot/42845.
Scopatz, Robert A., and Sarah M. Smith Pennsylvania's State-Specific SPFs and CMFs: Roadway Safety Data and Analysis Case Study. United States. Department of Transportation. Federal Highway Administration. Office of Safety, 2016, Report no. FHWA-SA-16-062, ROSA P. https://rosap.ntl.bts.gov/view/dot/42845.
Federal Highway Administration (U.S.) How Healthy is Your Road System?. Federal Highway Administration (U.S.), 2016, ROSA P. https://rosap.ntl.bts.gov/view/dot/54375.
This TechBrief describes research on the development of an open source microscopic traffic simulation software with proven traffic models, advanced computing algorithms, and a distributed/cross platform application programming interface. The research was conducted between 2008 and 2017. The ETFOMM (Enhanced Transportation Flow Open-source Microscop
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Zhang, L. (2016). Microscopic Traffic Simulation Models and Software: An Open Source Approach, Tech Brief (Report No. FHWA-HRT-17-028). Federal Highway Administration (U.S.). https://rosap.ntl.bts.gov/view/dot/39834
Zhang, Li. Microscopic Traffic Simulation Models and Software: An Open Source Approach, Tech Brief. Report no. FHWA-HRT-17-028. Federal Highway Administration (U.S.), 2016. https://rosap.ntl.bts.gov/view/dot/39834.
Zhang, Li Microscopic Traffic Simulation Models and Software: An Open Source Approach, Tech Brief. Federal Highway Administration (U.S.), 2016, Report no. FHWA-HRT-17-028, ROSA P. https://rosap.ntl.bts.gov/view/dot/39834.
United States. Department of Transportation. Federal Highway Administration
2016-11-07
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The Moving Ahead for Progress in the 21st Century Act (MAP-21) transformed the policy and programmatic framework for surface transportation investments. Transportation performance management will transform Federal highway programs and provide a means to more efficient investment of Federal transportation funds by focusing on national transportation
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United States. Department of Transportation. Federal Highway Administration (2016). Let's Talk Performance Webinar FAQs Safety Performance Management Measures. United States. Department of Transportation. Federal Highway Administration. https://rosap.ntl.bts.gov/view/dot/89862
United States. Department of Transportation. Federal Highway Administration. Let's Talk Performance Webinar FAQs Safety Performance Management Measures. United States. Department of Transportation. Federal Highway Administration, 2016. https://rosap.ntl.bts.gov/view/dot/89862.
United States. Department of Transportation. Federal Highway Administration Let's Talk Performance Webinar FAQs Safety Performance Management Measures. United States. Department of Transportation. Federal Highway Administration, 2016, ROSA P. https://rosap.ntl.bts.gov/view/dot/89862.
United States. Federal Highway Administration. Office of Planning, Environment, and Realty
2016-11-03
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This digest shares the latest information from a range of Federal and non-Federal sources, addressing transportation and its relationship to the human environment. Through this information exchange, FHWA hopes to foster dialogue at all levels and continue to further the state of the practice on these important topics in support of safety; infrastru
...
United States. Federal Highway Administration. Office of Planning, Environment, and Realty (2016). Human Environment Digest: November 3, 2016. United States. Federal Highway Administration. Office of Planning, Environment, and Realty. https://rosap.ntl.bts.gov/view/dot/55219
United States. Federal Highway Administration. Office of Planning, Environment, and Realty. Human Environment Digest: November 3, 2016. United States. Federal Highway Administration. Office of Planning, Environment, and Realty, 2016. https://rosap.ntl.bts.gov/view/dot/55219.
United States. Federal Highway Administration. Office of Planning, Environment, and Realty Human Environment Digest: November 3, 2016. United States. Federal Highway Administration. Office of Planning, Environment, and Realty, 2016, ROSA P. https://rosap.ntl.bts.gov/view/dot/55219.
On December 4, 2015, the President signed into law the Fixing America's Surface Transportation Act (FAST Act) (Pub. L.114-94). Section 1410 of the FAST Act amended 23 U.S.C. 127, Vehicle weight limitations-Interstate System, by revising the weight limits for certain vehicles on the Interstate System. The purpose of this memorandum is to provide gui
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Hartmann, J. (2016). Load Rating for the FAST Act's Emergency Vehicles [Memorandum]. United States. Department of Transportation. Federal Highway Administration. https://rosap.ntl.bts.gov/view/dot/92781
Hartmann, Joseph. Load Rating for the FAST Act's Emergency Vehicles [Memorandum]. United States. Department of Transportation. Federal Highway Administration, 2016. https://rosap.ntl.bts.gov/view/dot/92781.
Hartmann, Joseph Load Rating for the FAST Act's Emergency Vehicles [Memorandum]. United States. Department of Transportation. Federal Highway Administration, 2016, ROSA P. https://rosap.ntl.bts.gov/view/dot/92781.
Characterization of subsurface conditions is one of the most challenging yet important activities required for successful planning, design, construction, and operation of transportation infrastructure. This manual is intended to provide a technical resource for geotechnical and highway engineers responsible for planning and performing subsurface in
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Loehr, J. E., Lutenegger, A., Rosenblad, B. L., & Boeckmann, A. (2016). Geotechnical Site Characterization Geotechnical Engineering Circular No. 5 (Report No. FHWA-NHI-16-072). National Highway Institute (U.S.). https://rosap.ntl.bts.gov/view/dot/40558
Loehr, J. Erik, Alan Lutenegger, Brent L. Rosenblad, and Andrew Boeckmann. Geotechnical Site Characterization Geotechnical Engineering Circular No. 5. Report no. FHWA-NHI-16-072. National Highway Institute (U.S.), 2016. https://rosap.ntl.bts.gov/view/dot/40558.
Loehr, J. Erik, et al. Geotechnical Site Characterization Geotechnical Engineering Circular No. 5. National Highway Institute (U.S.), 2016, Report no. FHWA-NHI-16-072, ROSA P. https://rosap.ntl.bts.gov/view/dot/40558.
The objective of this project was to develop practical methods for prioritizing and mitigating traffic bottlenecks, which are one of the top causes of surface transportation congestion in the United States. Through this project, the following were developed: a new approach for ranking traffic bottlenecks, a new playbook of 70 bottleneck mitigation
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Hale, D., Jagannathan, R., Xyntarakis, M., Su, P., Jiang, X., Ma, J., Hu, J., & Krause, C. (2016). Traffic Bottlenecks: Identification and Solutions (Report No. FHWA-HRT-16-064). United States. Federal Highway Administration. Office of Operations Research and Development. https://rosap.ntl.bts.gov/view/dot/39938
Hale, David, Ramanujan Jagannathan, Michalis Xyntarakis, Peng Su, Ximiao Jiang, Jiaqi Ma, Jia Hu, and Cory Krause. Traffic Bottlenecks: Identification and Solutions. Report no. FHWA-HRT-16-064. United States. Federal Highway Administration. Office of Operations Research and Development, 2016. https://rosap.ntl.bts.gov/view/dot/39938.
Hale, David, et al. Traffic Bottlenecks: Identification and Solutions. United States. Federal Highway Administration. Office of Operations Research and Development, 2016, Report no. FHWA-HRT-16-064, ROSA P. https://rosap.ntl.bts.gov/view/dot/39938.
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