A Queueing Model and Analysis for Autonomous Vehicles on Highways

References

• Aguilar J (2018) A 10-lane highway and Colorado’s first autonomous vehicle lane could be prescription for west-suburban Denver traffic jams. Denver Post (January 22), https://www.denverpost.com/2018/01/21/colorado-10-lane-highway-autonomous-vehicle-lane-traffic/.Google Scholar
• Albright J, Bell A, Schneider J, Nyce C (2015) Market place of change: Automobile insurance in the era of autonomous vehicles. Accessed September 25, 2018, https://assets.kpmg.com/content/dam/kpmg/pdf/2016/06/id-market-place-of-change-automobile-insurance-in-the-era-of-autonomous-vehicles.pdf.Google Scholar
• Alfa AS, Neuts MF (1995) Modelling vehicular traffic using the discrete time Markovian arrival process. Transportation Sci. 29(2):109–117.Link, Google Scholar
• Amoozadeh M, Raghuramu A, Chuah CN, Ghosal D, Zhang HM, Rowe J, Levitt K (2015) Security vulnerabilities of connected vehicle streams and their impact on cooperative driving. IEEE Comm. Magazine 53(6):126–132.Crossref, Google Scholar
• Bando M, Hasebe K, Nakayama A, Shibata A, Sugiyama Y (1995) Dynamical model of traffic congestion and numerical simulation. Physical Rev. E 51(2):1035.Crossref, Google Scholar
• Baron O, Berman O, Nourinejad M (2018) Introducing autonomous vehicles: Formulation and analysis of public policies. Working paper, University of Toronto, Toronto, Canada.Google Scholar
• Benjaafar S, Dooley K, Setyawan W (1997) Cellular automata for traffic flow modeling. Report, Center for Transportation Studies, University of Minnesota, Minneapolis.Google Scholar
• Benjaafar S, Kong G, Li X, Courcoubetis C (2019) Peer-to-peer product sharing: Implications for ownership, usage, and social welfare in the sharing economy. Management Sci. 65(2):477–493.Link, Google Scholar
• Bergenhem C, Shladover S, Coelingh E, Englund C, Tsugawa S (2012) Overview of platooning systems. Proc. 19th ITS World Congress (Intelligent Transportation Society of America, Washington, DC).Google Scholar
• Bierstedt J, Gooze A, Gray C, Peterman J, Raykin L, Walters J (2014) Effects of next-generation vehicles on travel demand and highway capacity. Report, FP Think Working Group, Fehr & Peers, Washington, DC.Google Scholar
• Breuer L, Alfa AS (2005) An EM algorithm for platoon arrival processes in discrete time. Oper. Res. Lett. 33(5):535–543.Crossref, Google Scholar
• Cheah JY, Smith JM (1994) Generalized M/G/C/C state dependent queueing models and pedestrian traffic flows. Queueing Systems 15(1):365–386.Crossref, Google Scholar
• Chen D, Ahn S, Chitturi M, Noyce DA (2017) Toward vehicle automation: Roadway capacity formulation for traffic mixed with regular and automated vehicles. Transportation Res. Part B: Methodological 100(June):196–221.Crossref, Google Scholar
• Daganzo CF (1994) The cell transmission model: A dynamic representation of highway traffic consistent with the hydrodynamic theory. Transportation Res. Part B: Methodological 28(4):269–287.Crossref, Google Scholar
• Daw A, Hampshire RC, Pender J (2019) Beyond safety drivers: Staffing a teleoperations system for autonomous vehicles. Working paper, Cornell University, NY.Google Scholar
• Del Castillo J, Benitez F (1995) On the functional form of the speed-density relationship-I: General theory. Transportation Res. Part B: Methodological 29(5):373–389.Crossref, Google Scholar
• Dunne MC (1967) Traffic delay at a signalized intersection with binomial arrivals. Transportation Sci. 1(1):24–31.Link, Google Scholar
• Eliot L (2019) An inconvenient truth: Human drivers and autonomous cars mix like oil and water. Forbes (May 7), https://www.forbes.com/sites/lanceeliot/2019/05/07/an-inconvenient-truth-human-drivers-and-autonomous-cars-mix-like-oil-and-water/#1bd295103b84.Google Scholar
• Federal Highway Administration (2011) Our nation’s highways. Accessed September 25, 2018, https://www.fhwa.dot.gov/policyinformation/pubs/hf/pl11028/chapter2.cfm.Google Scholar
• Ghiasi A, Hussain O, Qian Z, Li X (2017) A mixed traffic capacity analysis and lane management model for connected automated vehicles: A Markov chain method. Transportation Res. Part B: Methodological 106(December):266–292.Crossref, Google Scholar
• Guzzella L, Kiencke U (1995) Advances in Automotive Control (Elsevier, Ascona, Switzerland).Google Scholar
• Harchol-Balter M (2013) Performance Modeling and Design of Computer Systems: Queueing Theory in Action (Cambridge University Press, New York).Crossref, Google Scholar
• He L, Hu Z, Zhang M (2020) Robust repositioning for vehicle sharing. Manufacturing Service Oper. Management 22(2):241–256.Link, Google Scholar
• He L, Mak HY, Rong Y, Shen ZJM (2017) Service region design for urban electric vehicle sharing systems. Manufacturing Service Oper. Management 19(2):309–327.Link, Google Scholar
• He QM (2014) Fundamentals of Matrix-Analytic Methods, vol. 365 (Springer, New York).Crossref, Google Scholar
• Heidemann D (1996) A queueing theory approach to speed-flow-density relationships. Proc. 13th Internat. Sympos. Transportation Traffic Theory (Elsevier, Oxford, UK), 103–118.Google Scholar
• Holtzman JM, Goodman DJ (2012) Wireless Communications: Future Directions, vol. 217 (Springer Science & Business Media, New York).Google Scholar
• INRIX (2019) Global Traffic Scorecard. Accessed July 3, 2020, https://www2.inrix.com/l/171932/2020-03-06/45lh8p/171932/120396/2019_INRIX_Traffic_Scorecard_Infographic__US_Version_.pdf.Google Scholar
• Jain R, Smith JM (1997) Modeling vehicular traffic flow using M/G/C/C state dependent queueing models. Transportation Sci. 31(4):324–336.Link, Google Scholar
• Kuwahara M, Newell GF (1987) Queue evolution on freeways leading to a single core city during the morning peak. Gartner NH, Wilson NHM, eds. Proc. 10th Internat. Sympos. Transportation Traffic Theory (Elsevier Science Publishing, New York), 21–40.Google Scholar
• Law AM, Kelton WD, Kelton WD (2000) Simulation Modeling and Analysis (McGraw-Hill, New York).Google Scholar
• Lehoczky J (1972) Traffic intersection control and zero-switch queues under conditions of Markov chain dependence input. J. Appl. Probab. 9(2):382–395.Crossref, Google Scholar
• Lim MK, Mak HY, Rong Y (2014) Toward mass adoption of electric vehicles: Impact of the range and resale anxieties. Manufacturing Service Oper. Management 17(1):101–119.Link, Google Scholar
• Liu H, Xiao L, Kan X, Shladover S, Lu X, Men M, Shakel W, van Arem B (2018) Using cooperative adaptive cruise control (CACC) to form high-performance vehicle streams—Final report. Working paper, University of California, Berkeley, Berkeley.Google Scholar
• Lucantoni DM (1991) New results on the single server queue with a batch Markovian arrival process. Comm. Statist. Stochastic Models 7(1):1–46.Crossref, Google Scholar
• Mak HY, Rong Y, Shen ZJM (2013) Infrastructure planning for electric vehicles with battery swapping. Management Sci. 59(7):1557–1575.Link, Google Scholar
• Mohajerpoor R, Ramezani M (2019) Mixed flow of autonomous and human-driven vehicles: Analytical headway modeling and optimal lane management. Transportation Res. Part C: Emerging Tech. 109(December):194–210.Crossref, Google Scholar
• Muoio D (2017) The 18 companies most likely to get self-driving cars on the road first. Business Insider (September 27), http://www.businessinsider.com/the-companies-most-likely-to-get-driverless-cars-on-the-road-first-2017-4/.Google Scholar
• National League of Cities (2018) Autonomous vehicle pilots across America. Accessed October 26, 2018, https://www.nlc.org/resource/autonomous-vehicle-pilots-across-america.Google Scholar
• Neuts MF (1979) A versatile Markovian point process. J. Appl. Probab. 16(4):764–779.Crossref, Google Scholar
• Neuts MF, Chakravarthy S (1981) A single server queue with platooned arrivals and phase type services. Eur. J. Oper. Res. 8(4):379–389.Crossref, Google Scholar
• National Highway Traffic Safety Administration (2015) Why your reaction time matters at speed. Accessed September 25, 2018, one.nhtsa.gov/nhtsa/Safety1nNum3ers/august2015/S1N_Speeding-August2015_812008.pdf.Google Scholar
• Pelletier S, Jabali O, Laporte G (2016) 50th anniversary invited article—Goods distribution with electric vehicles: Review and research perspectives. Transportation Sci. 50(1):3–22.Link, Google Scholar
• Qi W, Li L, Liu S, Shen ZJM (2018) Shared mobility for last-mile delivery: Design, operational prescriptions, and environmental impact. Manufacturing Service Oper. Management 20(4):737–751.Link, Google Scholar
• Qom SF, Xiao Y, Hadi M (2016) Evaluation of cooperative adaptive cruise control (CACC) vehicles on managed lanes utilizing macroscopic and mesoscopic simulation. Transportation Res. Board 95th Annual Meeting (Transportation Research Board, Washington, DC), 16-6384.Google Scholar
• Ross SM (2006) Simulation (Elsevier Academic Press, San Diego).Google Scholar
• Shladover S, Su D, Lu XY (2012) Impacts of cooperative adaptive cruise control on freeway traffic flow. Transportation Res. Record 2324(1):63–70.Crossref, Google Scholar
• Siciliano B, Khatib O (2016) Springer Handbook of Robotics (Springer, Berlin, Heidelberg).Crossref, Google Scholar
• Stern RE, Cui S, Delle Monache ML, Bhadani R, Bunting M, Churchill M, Hamilton N, et al. (2018) Dissipation of stop-and-go waves via control of autonomous vehicles: Field experiments. Transportation Res. Part C: Emerging Tech. 89(April):205–221.Crossref, Google Scholar
• Talebpour A, Mahmassani HS, Elfar A (2017) Investigating the effects of reserved lanes for autonomous vehicles on congestion and travel time reliability. Transportation Res. Record 2622(1):1–12.Crossref, Google Scholar
• Tientrakool P, Ho YC, Maxemchuk NF (2011) Highway capacity benefits from using vehicle-to-vehicle communication and sensors for collision avoidance. IEEE Vehicular Tech. Conf. (Institute of Electrical and Electronics Engineers, San Francisco, CA), 1–5.Google Scholar
• Tiwari H, Marsani A (2014) Calibration of conventional macroscopic traffic flow models for Nepalese roads. Inst. Engrg. Graduate Conf. (Institute of Engineering, Kathmandu, Nepal), 225–232.Google Scholar
• Transportation Research Board (2000) Highway Capacity Manual (Transportation Research Board, Washington, DC).Google Scholar
• Treiber M, Hennecke A, Helbing D (2000) Congested traffic states in empirical observations and microscopic simulations. Physical Rev. E. 62(2):1805–1824.Crossref, Google Scholar
• 2025AD (2018) Milestones—The automated driving timeline. Accessed September 25, 2018, https://www.2025ad.com/latest/milestones-the-ad-timeline/.Google Scholar
• Van Woensel T, Vandaele N (2006) Empirical validation of a queueing approach to uninterrupted traffic flows. 4OR 4(1):59–72.Google Scholar
• Van Woensel T, Vandaele N (2007) Modeling traffic flows with queueing models: A review. Asia-Pacific J. Oper. Res. 24(4):435–461.Crossref, Google Scholar
• Vandaele N, Van Woensel T, Verbruggen A (2000) A queueing based traffic flow model. Transportation Res. Part D: Transportation Environ. 5(2):121–135.Crossref, Google Scholar
• Vander Werf J, Shladover S, Miller M, Kourjanskaia N (2002) Effects of adaptive cruise control systems on highway traffic flow capacity. Transportation Res. Record 1800(1):78–84.Google Scholar
• Varaiya P (2005) What we’ve learned about highway congestion. Access 1(27):2–7.Google Scholar
• Virginia Department of Motor Vehicles (2016) Virginia driver’s manual. Accessed September 25, 2018, https://www.dmv.virginia.gov/webdoc/pdf/dmv39.pdf.Google Scholar
• Wang H, Rudy K, Li J, Ni D (2010) Calculation of traffic flow breakdown probability to optimize link throughput. Appl. Math. Model. 34(11):3376–3389.Crossref, Google Scholar
• Zhao L, Sun J (2013) Simulation framework for vehicle platooning and car-following behaviors under connected-vehicle environment. Procedia Soc. Behav. Sci. 96(November):914–924.Crossref, Google Scholar