National Academies Press: OpenBook
« Previous: Abbreviations
Page 140
Suggested Citation:"References." National Academies of Sciences, Engineering, and Medicine. 2018. Dedicating Lanes for Priority or Exclusive Use by Connected and Automated Vehicles. Washington, DC: The National Academies Press. doi: 10.17226/25366.
×
Page 140
Page 141
Suggested Citation:"References." National Academies of Sciences, Engineering, and Medicine. 2018. Dedicating Lanes for Priority or Exclusive Use by Connected and Automated Vehicles. Washington, DC: The National Academies Press. doi: 10.17226/25366.
×
Page 141
Page 142
Suggested Citation:"References." National Academies of Sciences, Engineering, and Medicine. 2018. Dedicating Lanes for Priority or Exclusive Use by Connected and Automated Vehicles. Washington, DC: The National Academies Press. doi: 10.17226/25366.
×
Page 142
Page 143
Suggested Citation:"References." National Academies of Sciences, Engineering, and Medicine. 2018. Dedicating Lanes for Priority or Exclusive Use by Connected and Automated Vehicles. Washington, DC: The National Academies Press. doi: 10.17226/25366.
×
Page 143
Page 144
Suggested Citation:"References." National Academies of Sciences, Engineering, and Medicine. 2018. Dedicating Lanes for Priority or Exclusive Use by Connected and Automated Vehicles. Washington, DC: The National Academies Press. doi: 10.17226/25366.
×
Page 144

Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

140 Ahn, K., et al. (2013). Ecodrive Application. Transportation Research Record: Journal of the Transportation Research Board, No. 2341, pp. 1–11. https://doi.org/10.3141/2341-01. Altan, O. D., et al. (2017). GlidePath: Eco-Friendly Automated Approach and Departure at Signalized Inter- sections. IEEE Transactions on Intelligent Vehicles, Vol. 2(4), Institute of Electrical and Electronics Engineers, Piscataway, N.J., pp. 266–277. Arnaout, G., and S. Bowling (2011). Towards Reducing Traffic Congestion Using Cooperative Adaptive Cruise Control on a Freeway with a Ramp. Journal of Industrial Engineering and Management, Vol. 4(4), Omnia- Science, Omnia Publisher SL, Barcelona, Spain, pp. 699–717. Avelar, R., et al. (2016). The Influence of General Purpose Lane Traffic on Managed Lane Speeds: An Operational Study in Houston, Texas. Transportation Research Procedia, Vol. 15, Elsevier, New York, NY, pp. 548–560. Bliss, L. “Behind the Uber Self-Driving Car Crash: A Failure to Communicate.” CitiLab. Webpage: https://www. citylab.com/transportation/2018/05/behind-the-uber-self-driving-car-crash-a-failure-to-communicate/ 561230/. Booz Allen Hamilton (2016). Analysis, Modeling, and Simulation (AMS) Testbed Development and Evalua- tion to Support Dynamic Mobility Applications (DMA) and Active Transportation and Demand Manage- ment (ATDM) Programs—Calibration Report for San Mateo Testbed. FHWA-JPO-16-377. Federal Highway Administration, U.S. Department of Transportation, Washington, D.C. Brownstone, D., et al. (2003). Drivers’ Willingness-to-Pay to Reduce Travel Time: Evidence from the San Diego I-15 Congestion Pricing Project. Transportation Research Part A: Policy and Practice, Vol. 37(4), Elsevier, New York, NY, pp. 373–387. California DMV (2018). Second Modified Express Terms, Title 13, Division 1, Chapter 1, Article 3.7—Testing of Autonomous Vehicles. California Department of Motor Vehicles, Sacramento, CA. Online: https:// www.dmv.ca.gov/portal/wcm/connect/aa08dc20-5980-4021-a2b2-c8dec326216b/AV_Second15Day_ Notice_Express_Terms.pdf?MOD=AJPERES. Caltrans (2018). Performance Measurement System (PeMS). Website: http://pems.dot.ca.gov/. Carrion, C., and D. Levinson (2012). Value of Travel Time Reliability: A Review of Current Evidence. Transporta- tion Research Part A: Policy and Practice, Vol. 46(4), Elsevier, New York, NY, pp. 720–741. Carter, A. A., et al. (2009). Safety Impact Methodology (SIM): Evaluation of Pre-Production Systems. Pro- ceedings of the 21st International Technical Conference on the Enhanced Safety of Vehicles (June 2009). Paper No. 09-0259. National Highway Traffic Safety Administration, Washington, D.C. CATT Lab (2018). RITIS. Website: https://ritis.org/intro. Dahlgren, J. (2002). High-Occupancy/Toll Lanes: Where Should They Be Implemented? Transportation Research Part A: Policy and Practice, Vol. 36(3), Elsevier, New York, NY, pp. 239–255. Delis, A. I., et al. (2015). Macroscopic Traffic Flow Modeling with Adaptive Cruise Control: Development and Numerical Solution. Computers & Mathematics with Applications, Vol. 70(8), Elsevier, New York, NY, pp. 1921–1947. Dowling, R., et al. (2004). Traffic Analysis Toolbox, Volume III: Guidelines for Applying Traffic Microsimulation Modeling Software. FHWA-HRT-04-040. Federal Highway Administration, U.S. Department of Transportation, Washington, D.C. Dowling, R., et al. (2015). Impacts Assessment of Dynamic Speed Harmonization with Queue Warning: Task 3 Impacts Assessment Report. FHWA-JPO-15-222. Federal Highway Administration, U.S. Department of Transportation, Washington, D.C. Dovey, R. (2017). “S.F. Could Become National Model for Brighter Transit-Only Lanes.” NEXTCITY Webpage: https://nextcity.org/daily/entry/san-francisco-red-transit-only-lanes-expand (accessed March 14, 2018). References

References 141 Eindhoven University of Technology (n.d.). “Focus on Novel Steps of Cooperative Adaptive Cruise Con- trol.” Eindhoven University of Technology Webpage: https://www.tue.nl/universiteit/faculteiten/ werktuigbouwkunde/onderzoek/onderzoeksgroepen/dynamics-and-control/research/projects/ cooperative-adaptive-cruise-contrTol/ (accessed July 2017). FHWA (2008a). Income-Based Equity Impacts of Congestion Pricing: A Primer. Federal Highway Administration, U.S. Department of Transportation, Washington, D.C. FHWA (2008b). Managed Lanes: A Primer. FHWA Report No. FHWA-HOP-05-031. Federal Highway Adminis- tration, U.S. Department of Transportation, Washington, D.C. FHWA (2016a). Federal-Aid Highway Program Guidance on High Occupancy Vehicle (HOV) Lanes. FHWA Free- way Management Program, U.S. Department of Transportation, Washington, D.C. Online: https://ops.fhwa. dot.gov/freewaymgmt/hovguidance/hovguidance.pdf (accessed March 14, 2018). FHWA (2016b). Chapter 4: HOT Lane Operations and Management. Considerations for High Occupancy Vehicle (HOV) Lane to High Occupancy Toll (HOT) Lane Conversions Guidebook. Office of Operations, Federal Highway Administration, U.S. Department of Transportation, Washington, D.C. Online: http:// ops.fhwa.dot.gov/publications/fhwahop08034/hot4.0.htm. FHWA (2017a). Connected Vehicle Challenges: Potential Impact of Sharing the 5.9 GHZ Wireless Spec- trum. DSRC Fact Sheet. ITS Joint Program Office. FHWA-JPO-16-231. Federal Highway Administration, U.S. Department of Transportation, Washington, D.C. Online: https://www.its.dot.gov/cv_basics/pdf/ CV_basics_DSRC_factsheet.pdf (accessed July 2017). FHWA (2017b). Managed Lanes: A Primer. Website (updated February 2017): https://ops.fhwa.dot.gov/ publications/managelanes_primer/. FHWA (2017c). FHWA Request for Information on Integration of Automated Driving Systems (ADS) into the High- way Transportation System. (Docket No. FHWA-2017-0049). Federal Highway Administration, U.S. Depart- ment of Transportation, Washington, D.C. Online: https://www.transportation.gov/av/FHWA-RFI-ADS. Finkleman, J., et al. (2011). Empirical Evidence from the Greater Toronto Area on the Acceptability and Impacts of HOT Lanes. Transport Policy, Vol. 18(6), Elsevier, New York, NY, pp. 814–824. Fisher, B. L. (1995). Lane Conversion Strategy for the I-80 HOV Lane in New Jersey. Transportation Research Circular 442: 7th National HOV Systems Conference: HOV Systems in a New Light. Transportation Research Board, National Research Council, Washington, D.C. Online: https://rosap.ntl.bts.gov/view/dot/15032. Fitzpatrick, D., et al. (2016a). NCHRP Web-Only Document 231: Challenges to CV and AV Applications in Truck Freight Operations. Transportation Research Board of the National Academies of Science, Engineering, and Medicine, Washington, D.C. Fitzpatrick, K., et al. (2016b). NCHRP Web-Only Document 224: Research Supporting the Development of Guide- lines for Implementing Managed Lanes. Transportation Research Board of the National Academies of Science, Engineering, and Medicine, Washington, D.C. Florida DOT (1996). Florida Express Lanes. Website: http://floridaexpresslanes.com. Gettman, D., et al. (2003). Surrogate Safety Measures from Traffic Simulation Models. Transportation Research Record: Journal of the Transportation Research Board, No. 1840, pp. 104–115. http://dx.doi.org/ 10.3141/1840-12. Hao, P., et al. (2015). Developing a Framework of Eco-Approach and Departure Application for Actuated Signal Control. Proceedings of the 2015 IEEE Intelligent Vehicles Symposium (June 28–July 1, 2015, Seoul, Korea). Institute of Electrical and Electronics Engineers, Piscataway, N.J., pp. 796–801. Harding, J., et al. (2014). Vehicle-to-Vehicle Communications: Readiness of V2V Technology for Application. Report No. DOT HS 812 014. National Highway Traffic Safety Administration, Washington, D.C. Hedlund, J., (2017). Autonomous Vehicles Meet Human Drivers: Traffic Safety Issues for States, Governors High- way Safety Association, Washington, D.C. Online: http://www.ghsa.org/sites/default/files/2017-01/AV%20 2017%20-%29FINAL.pdf (accessed March 14, 2018). Hess, S., et al. (2011). Pay to Drive in My Bus Lane: A Stated Choice Analysis for the Proposed Lincoln Tunnel HOT Lane into Manhattan. Transport Policy, Vol. 18(5), Elsevier, New York, NY, pp. 649–656. Hlavacek, I., et al. (2007). Best Practices: Separation Devices Between Toll Lanes and Free Lanes. FHWA/TX-07/ 0-5426-1. Center for Transportation Research at the University of Texas at Austin, TX. Janson, M., and D. Levinson (2014). HOT or Not: Driver Elasticity to Price on the MnPASS HOT Lanes. Research in Transportation Economics, Vol. 44, Elsevier, New York, NY, pp. 21–32. Kall, D., et al. (2009). Effect of High-Occupancy Toll Lanes on Mass Vehicle Emissions: Application to I-85 in Atlanta, Georgia. Transportation Research Record: Journal of the Transportation Research Board, No. 2123, pp. 88–96. https://doi.org/10.3141/2123-10. Kamalanathsharma, R. K., et al. (2015). Networkwide Impacts of Vehicle Ecospeed Control in the Vicinity of Traffic Signalized Intersections. Transportation Research Record: Journal of the Transportation Research Board, No. 2503, pp. 91–99. https://doi.org/10.3141/2503-10.

142 Dedicating Lanes for Priority or Exclusive Use by Connected and Automated Vehicles Kim, A., et al. (2016). Review of Federal Motor Vehicle Safety Standards (FMVSS) for Automated Vehicles: Preliminary Report. Report No. DOT-VNTSC-OSTR-16-03. Volpe National Transportation Systems Center, Cambridge, MA, and United States Department of Transportation, Washington, D.C. Kwon, J., and P. Varaiya (2008). Effectiveness of California’s High Occupancy Vehicle (HOV) System, Transporta- tion Research Part C: Emerging Technologies, Vol. 16(1), Elsevier, New York, NY, pp. 98–115. Lee, J., et al. (2014). Mobility Impacts of Cooperative Adaptive Cruise Control (CACC) Under Mixed Traffic Conditions. Proceedings of the 21st ITS World Congress (September 7–11, 2011, Detroit, MI), ITS America, Washington, D.C. Lee, J., et al. (2016a). Simulation of Evolutionary Introduction of Cooperative Adaptive Cruise Control Equipped Vehicles into Traffic. Federal Highway Administration, U.S. Department of Transportation, Washington, D.C. Lee, J., et al. (2016b). CACC-VISSIM on U.S.DOT Open Source Application Development Portal. Online: https:// itsforge.net/index.php/community/explore-applications#/31/96. Li, D., et al. (2014). Integrated Approach Combining Ramp Metering and Variable Speed Limits to Improve Motorway Performance. Transportation Research Record: Journal of the Transportation Research Board, Vol. 2470, pp. 86–94. DOI: 10.3141/2470-09. Liu, H., et al. (2018). Using Cooperative Adaptive Cruise Control (CACC) to Form High-Performance Vehicle Streams: Simulation Results Analysis. California PATH Program, Institute of Transportation Studies, University of California–Berkeley, Berkeley, CA. Lu, M., et al. (2005). Technical Feasibility of Advanced Driver Assistance Systems (ADAS) for Road Traffic Safety. Transportation Planning and Technology, Vol. 28(3). Taylor & Francis Group, Oxford, UK, pp. 167–187. Lu, X.-Y., et al. (2014). Freeway Micro-Simulation Calibration: Case Study Using Aimsun and VISSIM with Detailed Field Data. Presented at 93d Annual Meeting of the Transportation Research Board, Washington, D.C. Ma, J., et al. (2016). Freeway Speed Harmonization. IEEE Transactions on Intelligent Vehicles, Vol. 1(1), Institute of Electrical and Electronics Engineers, New York, NY, pp. 78–89. Marinik, A., et al. (2014). Human Factors Evaluation of Level 2 and Level 3 Automated Driving Concepts: Concepts of Operation. DOT HS 812 044. National Highway Traffic Safety Administration, Washington, D.C. Martin, P., et al. (2012). TCRP Report 151: A Guide for Implementing Bus on Shoulder (BOS) Systems. Trans- portation Research Board of the National Academies, Washington, D.C. Michigan DOT (2018). Traffic Monitoring Information System. Website: https://mdotnetpublic.state.mi.us/ tmispublic/Search.aspx. Minnesota DOT (2017). MnDOT Traffic Data. Website: http://data.dot.state.mn.us/datatools/. McCune, K. (2015). Automated Occupancy Detection (Phase I) Demonstration Results. 2016 TRB Managed Lanes Conference (May 5, 2016). Online: http://onlinepubs.trb.org/onlinepubs/Conferences/2016/ML/ S6-McCune.pd (accessed November 22, 2016). MTA (n.d.) Curbside bus lanes (image). NYC Bus Rapid Transit - Select Bus Service Features. Webpage: http:// www.nyc.gov/html/brt/html/about/sbs-features.shtml. Murray, P., et al. (2000). Defining Special-Use Lanes: Case Studies and Guidelines. FHWA/TX-00/0-1832-1. Center for Transportation Research, University of Texas at Austin, TX. NCSL (2018). “Autonomous Vehicles/Self-driving Vehicles Enacted Legislation.” National Conference of State Legislatures Webpage: http://www.ncsl.org/research/transportation/autonomous-vehicles-self- driving-vehicles-enacted-legislation.aspx (accessed March 14, 2018). Ngoduy, D. (2013). Instability of Cooperative Adaptive Cruise Control Traffic Flow: A Macroscopic Approach. Communications in Nonlinear Science and Numerical Simulation, Vol. 18. Elsevier, New York, NY, pp. 2838–2851. NHTSA (2015). Traffic Safety Facts: Crash Stats—A Brief Statistical Summary. DOT HS 102 115. National Highway Transportation Safety Board, U.S. Department of Transportation, Washington, D.C. Online: https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/812115 NHTSA (2016). Federal Automated Vehicles Policy: Accelerating the Next Revolution in Roadway Safety. National Highway Transportation Safety Board, U.S. Department of Transportation, Washington, D.C. Online: https://www.transportation.gov/sites/dot.gov/files/docs/AV%20policy%20guidance%20PDF.pdf. NHTSA (2017a). Automated Driving Systems 2.0—A Vision for Safety. National Highway Transportation Safety Administration, U.S. Department of Transportation, Washington, D.C. Online: https://www.nhtsa.gov/sites/ nhtsa.dot.gov/files/documents/13069a-ads2.0_090617_v9a_tag.pdf (accessed March 14, 2018). NHTSA (2017b). Notice of Proposed Rulemaking (NPRM), Federal Motor Vehicle Safety Standard (FMVSS) No. 150. National Highway Transportation Safety Administration, U.S. Department of Transportation. Federal Register Vol. 82, Iss. 8 (January 12, 2017), pp. 3854–4019. NHTSA (2018). Removing Regulatory Barriers for Vehicles with Automated Driving Systems. Proposed Rule. National Highway Transportation Safety Administration, U.S. Department of Transportation. Federal Register Vol. 83, Iss. 12 (January 12, 2018), pp. 2607–2684).

References 143 Nikolos I., et al. (2015). Macroscopic Modeling and Simulation of ACC and CACC. Presented at IEEE-ITSC 18th International Conference on Intelligent Transportation Systems (September 15–18, 2015, Canary Islands, Spain). Institute of Electrical and Electronics Engineers, Piscataway, N.J. N.J. Turnpike Authority (n.d.). “NJ Turnpike Widening Program Overview.” New Jersey Turnpike Authority Webpage: http://www.njturnpikewidening.com/overview.php (accessed March 14, 2018). Nowakowski, C., et al. (2014). Cooperative Adaptive Cruise Control: Testing Drivers’ Choices of Following Distances. California PATH Program, Institute of Transportation Studies, University of California at Berkeley, CA. PANYNJ (n.d.). The Lincoln Tunnel Exclusive Bus Lane. Port Authority of New York and New Jersey Webpage: http://www.panynj.gov/bridges-tunnels/lincoln-tunnel-xbl.html (accessed March 14, 2018). Rakha, H., and Y. Ding (2003). Impact of Stops on Vehicle Fuel Consumption and Emissions. Journal of Trans- portation Engineering 129(1), American Society of Civil Engineers, Reston, VA, pp. 23–32. Rodriguez, J. F. (2017). “Federal Approval Will See Muni Red Lanes Spread to 50 Streets Across SF.” San Francisco Examiner, July 3, 2017. Online: http://www.sfexaminer.com/federal-approval-will-see-muni-red-lanes- spread-50-streets-across-sf/ (accessed March 14, 2018). Ryus, P., et al. (2016). TCRP Report 183: A Guidebook on Transit-Supportive Roadway Strategies. Transportation Research Board of the National Academies, Washington, D.C. SAE International (2016a). DSRC Message Communication Minimum Performance Requirements: Basic Safety Message for Vehicle Safety Applications. Draft Standard J2945, SAE International, Warrendale, PA. SAE International (2016b). Surface Vehicle Recommended Practice J3016: Taxonomy and Definitions for Terms Related to Driving Automation Systems for On-Road Motor Vehicles. SAE International, Warrendale, PA. SAE International (2018). SAE J3016: Taxonomy and Definitions for Terms Related to On-Road Motor Vehicle Automated Driving Systems. On-Road Automated Vehicle Standards Committee, SAE International, Warrendale, PA. Abstract available online: https://www.sae.org/standards/content/j3016_201401/. Schakel, W. J., et al. (2010). Effects of Cooperative Adaptive Cruise Control on Traffic Flow Stability. IEEE-ITSC 13th International Conference on Intelligent Transportation Systems (September 19–22, 2010, Funchal). Institute of Electrical and Electronics Engineers, Piscataway, N.J. Scott, T. (2014). “Truck Platooning.” ATA Webpage: http://www.trucking.org/ATA%20Docs/What% 20We%20Do/Trucking%20Issues/Documents/Engineering/Resources%20and%20Helpful%20Links/ Truck%20Platooning/Truck%20Platooning.pdf (accessed March 14, 2018). Scribner, M. (2017). “Authorizing Automated Vehicle Platooning: A Guide for State Legislators” (July 2017). Competitive Enterprise Institute Webpage: https://cei.org/content/authorizing-automated-vehicle- platooning. Semsar-Kazerooni, E., et al. (2016). Cooperative Adaptive Cruise Control: An Artificial Potential Field Approach. Proceedings of the 2016 IEEE Intelligent Vehicles Symposium (June 19–22, 2016, Gothenburg, Sweden). Institute of Electrical and Electronics Engineers, Piscataway, N.J., pp. 361–367. Shladover, S., and R. Bishop (2015). Road Transport Automation as a Public-Private Enterprise. TRB Confer- ence Proceedings 52: Towards Road Transportation Automation: Opportunities in Public-Private Collaboration. Transportation Research Board of the National Academies, Washington, D.C., pp. 14–15. Shladover, S., et al. (2009). Effects of Cooperative Adaptive Cruise Control on Traffic Flow: Testing Drivers’ Choices of Following Distances. California PATH Program, Institute of Transportation Studies, University of California at Berkeley, CA. Shladover, S., et al. (2012). Impacts of Cooperative Adaptive Cruise Control on Freeway Traffic Flow. Transporta- tion Research Record: Journal of the Transportation Research Board, No. 2324, Transportation Research Board of the National Academies, Washington, D.C., pp. 63–70. DOI: 10.3141/2324-08. Shladover S., et al. (2014). Using Cooperative Adaptive Cruise Control (CACC) to Form High-Performance Vehicle Streams. California PATH Program, Institute of Transportation Studies, University of California at Berkeley, CA. Shladover, S., et al. (2015). Cooperative Adaptive Cruise Control: Definitions and Operating Concepts, Trans- portation Research Record: Journal of the Transportation Research Board, No. 2489, Transportation Research Board of the National Academies, Washington, D.C., pp. 145–152. DOI: 10.3141/2489-17. Shladover, S., et al. (2018). Using Cooperative Adaptive Cruise Control (CACC) to Form High-Performance Vehicle Streams: Definitions, Literature Review, and Operational Concept Alternatives. California PATH Program, Institute of Transportation Studies, University of California at Berkeley, CA. Smit, R., et al. (2007). A New Modelling Approach for Road Traffic Emissions: VERSIT+. Transportation Research Part D: Transport and Environment, Vol. 12(6), Elsevier, New York, NY, pp. 414–422. Smith, S., et al. (2016). Benefits Estimation Framework for Automated Vehicle Operations. FHWA-JPO-16-229. John A. Volpe National Transportation Systems Center, Intelligent Transportation Systems Joint Program Office, U.S. Department of Transportation, Cambridge, MA. Talebpour, A., et al. (2013). Speed Harmonization: Evaluation of Effectiveness Under Congested Conditions. Transportation Research Record: Journal of the Transportation Research Board, No. 2391, pp. 69–79. DOI: 10.3141/2391-07.

144 Dedicating Lanes for Priority or Exclusive Use by Connected and Automated Vehicles Talebpour, A., et al. (2017). Investigating the Effects of Reserved Lanes for Autonomous Vehicles on Congestion and Travel Time Reliability. Transportation Research Record: Journal of the Transportation Research Board, No. 2622, pp. 1–12. DOI: 10.3141/2622-01. Treiber, M. (2016). Traffic-Simulation.de. Online: http://www.traffic-simulation.de. Turnbull, K. F. (2014). Impact of Exempt Vehicles on Managed Lanes. FHWA-HOP-14-006. Federal Highway Administration, U.S. Department of Transportation, Washington D.C. U.S.DOT (n.d.a). “Connected Vehicle Basics.” Intelligent Transportation Systems Joint Program Office Webpage: https://www.its.dot.gov/cv_basics/cv_basics_how.htm (accessed July 2017). U.S.DOT (n.d.b) FHWA: Open Source Application Development Portal. Website: https://www.itsforge.net/. U.S.DOT (n.d.c). “Connected Vehicles.” Intelligent Transportation Systems Joint Program Office Webpage: https://www.its.dot.gov/cv_basics/index.htm (accessed July 2017). U.S.DOT (2014). “The Value of Travel Time Savings: Departmental Guidance for Conducting Economic Evalua- tions, Guidance Document.” U.S. Department of Transportation Webpage: https://www.transportation.gov/ sites/dot.gov/files/docs/USDOT%20VOT%20Guidance%202014.pdf. U.S.DOT (2017). “FHWA Freeway Management Program, Frequently Asked HOV Questions.” Federal Highway Administration Webpage: https://ops.fhwa.dot.gov/freewaymgmt/faq.htm (accessed March 14, 2018). U.S.DOT (2018). “ITS JPO Data.” Intelligent Transportation Systems Joint Program Office Webpage: https:// www.its.dot.gov/data/. U.S. EPA (2016). “MOVES and Other Mobile Source Emissions Models.” U.S. Environmental Protection Agency Webpage: https://www.epa.gov/moves. U.S. House of Representatives Document Repository (2018). Amendment in the Nature of a Substitute to H.R. 3388 [a reference to Working Bill H.R. 3388, Safely Ensuring Lives Future Deployment and Research in Vehicle Evolution Act (SELF DRIVE Act)]. Online: http://docs.house.gov/meetings/IF/ IF00/20170727/106347/BILLS-115-HR3388-L000566-Amdt-9.pdf, (accessed March 14, 2018). Van Arem, B., et al. (1997). The MICroscopic Traffic Simulation Model MIXIC 1.3. INRO Centre for Infrastructure, Transport and Regional Development, Delft, The Netherlands. Van Arem, B., et al. (2006). The Impact of Cooperative Adaptive Cruise Control on Traffic-Flow Characteristics. IEEE Transactions on Intelligent Transportation Systems, Vol. 7(4), Institute of Electrical and Electronics Engineers, New York, NY, 429–436. Van Arem, B., et al. (2007). Design and Evaluation of an Integrated Full-Range Speed Assistant. TNO Report 2007-D-R0280/B, Traffic and Transport, Delft, The Netherlands. Virginia DOT, Virginia DRPT, and FHWA (2013). Transportation Technical Report: Interstate 66—From US Route 15 in Prince William County to Interstate 495 in Fairfax County. Virginia Department of Transportation, Virginia Department of Rail and Public Transportation, and Federal Highway Administration, U.S. Depart- ment of Transportation, Washington, D.C. Wang, M., et al. (2015). Connected Variable Speed Limits Control and Vehicle Acceleration Control to Resolve Moving Jams. Presented at 94th Annual Meeting of the Transportation Research Board, Washington, D.C. Weinstein, A., and G. C. Sciara (2004). Assessing the Equity Implications of HOT Lanes. Santa Clara Valley Trans- portation Authority, San Jose, CA. Yang, H., and W.-L. Jin (2014). A Control Theoretic Formulation of Green Driving Strategies Based on Inter- Vehicle Communications. Transportation Research Part C, Emerging Technologies, Vol. 41(2), Elsevier, New York, NY, pp. 48–60. Yelchuru, B., et al. (2016), Analysis, Modeling, and Simulation (AMS) Testbed Development and Evaluation to Sup- port Dynamic Mobility Applications (DMA) and Active Transportation and Demand Management (ATDM) Programs—Calibration Report for San Mateo Testbed, FHWA-JPO-16-377. U.S. Department of Transporta- tion, Washington, D.C. ZEV PITF (2014). Multi-State ZEV Action Plan. ZEV Program Implementation Task Force. [Online information about the ZEV PITF is available at: https://www.zevstates.us/about-us/.]

Dedicating Lanes for Priority or Exclusive Use by Connected and Automated Vehicles Get This Book
×
 Dedicating Lanes for Priority or Exclusive Use by Connected and Automated Vehicles
MyNAP members save 10% online.
Login or Register to save!
Download Free PDF

TRB’s National Cooperative Highway Research Program (NCHRP) Research Report 891: Dedicating Lanes for Priority or Exclusive Use by Connected and Automated Vehicles identifies and evaluates opportunities, constraints, and guiding principles for implementing dedicated lanes for connected and automated vehicles. This report describes conditions amenable to dedicating lanes for users of these vehicles and develops the necessary guidance to deploy them in a safe and efficient manner. This analysis helps identify potential impacts associated with various conditions affecting lane dedication, market penetration, evolving technology, and changing demand.

READ FREE ONLINE

  1. ×

    Welcome to OpenBook!

    You're looking at OpenBook, NAP.edu's online reading room since 1999. Based on feedback from you, our users, we've made some improvements that make it easier than ever to read thousands of publications on our website.

    Do you want to take a quick tour of the OpenBook's features?

    No Thanks Take a Tour »
  2. ×

    Show this book's table of contents, where you can jump to any chapter by name.

    « Back Next »
  3. ×

    ...or use these buttons to go back to the previous chapter or skip to the next one.

    « Back Next »
  4. ×

    Jump up to the previous page or down to the next one. Also, you can type in a page number and press Enter to go directly to that page in the book.

    « Back Next »
  5. ×

    To search the entire text of this book, type in your search term here and press Enter.

    « Back Next »
  6. ×

    Share a link to this book page on your preferred social network or via email.

    « Back Next »
  7. ×

    View our suggested citation for this chapter.

    « Back Next »
  8. ×

    Ready to take your reading offline? Click here to buy this book in print or download it as a free PDF, if available.

    « Back Next »
Stay Connected!