Volume 7, Issue 1 (9-2022)                   NMCE 2022, 7(1): 70-83 | Back to browse issues page

XML Print

Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Barzegari V, Edrisi A. Optimal number and location of parking facilities in presence of autonomous vehicles. NMCE 2022; 7 (1) :70-83
URL: http://nmce.kntu.ac.ir/article-1-401-en.html
1- Ph.D. Candidate, Department of Civil Engineering, K. N. Toosi University of Technology, Tehran, Iran.
2- Assistant Professor, Department of Civil Engineering, K. N. Toosi University of Technology, Tehran, Iran. , edrisi@kntu.ac.ir
Abstract:   (267 Views)
Worldwide surveys have shown that autonomous vehicles will enter the transportation networks in the following decades. Therefore, investigating and analyzing the impacts of autonomous vehicles on traffic has been one of the most exciting issues. Autonomous vehicles affect facilities management, including parking location. For example, autonomous vehicles will change parking patterns. The conventional vehicle drivers have first to find a spot to park their vehicle and then walk to their destination. In contrast, the autonomous vehicle users can drop off right at their destination and do not experience walking or searching time for parking. Hence, the modeling of autonomous vehicles' effect on parking facilities' location is an important issue. This study seeks to present the optimal location of parking facilities in a mixed AV-HV traffic flow. We consider two structure layouts: (i) a corridor and (ii) a grid city. Also, we use the Continuum Approximation approach to model the problem and derive closed-form solutions. We prove that the demand (the infrastructure cost) increases (decreases) the required parking facilities. Numeric examples show that the share of autonomous vehicles decreases the number of parking facilities and the total cost.
Full-Text [PDF 649 kb]   (123 Downloads)    
Type of Study: Research | Subject: General
Received: 2022/03/15 | Revised: 2022/06/10 | Accepted: 2022/06/17 | ePublished ahead of print: 2022/06/29

1. Shoup, D.C. (2006). Cruising for Parking. Transport Policy 13(6), 479-486. [DOI:10.1016/j.tranpol.2006.05.005]
2. Gallivan, S. (2011). IBM Global Parking Survey: Drivers Share Worldwide Parking Woes Technical Report. New York, USA.
3. Najmi, A., Bostanara, M., Gu, Z., & Rashidi, T. H. (2021). On-Street Parking Management and Pricing Policies: An Evaluation from a System Enhancement Perspective. Transportation Research Part A: Policy and Practice, 146, 128-151. [DOI:10.1016/j.tra.2021.02.009]
4. Nourinejad, M., Bahrami, S., & Roorda, M.J., (2018). Designing Parking Facilities for Autonomous Vehicles. Transportation Research Part B: Methodological 109, 110-127. [DOI:10.1016/j.trb.2017.12.017]
5. Chester, M., Horvath, A., & Madanat, S., (2018). Parking and the Environment : Parking and the City. London, United Kingdom: Routledge, 171-176. [DOI:10.4324/9781351019668-15]
6. Litman, T. (2016). Parking Management: Strategies, Evaluation and Planning. Victoria, Canada: Victoria Transport Policy Institute.
7. Litman, T. (2018). Parking Management Strategies: Parking Management Best Practices. London, United Kingdom: Routledge, 86-225.
8. Nourinejad, M. (2017). Economics of Parking: Short, Medium, and Long-term Planning. Doctoral Dissertation. University of Toronto.
9. Etherington, D. (2019). Over 1,400 Self-driving Vehicles Are Now in Testing by 80+ Companies Across the US (Report). TechCrunch.
10. Chatman, D.G., & Moran, M. (2019). Autonomous Vehicles In the United States: Understanding Why and How Cities and Regions are Responding. UC Office of the President: University of California Institute of Transportation Studies.
11. Soteropoulos, A., Berger, M., & Ciari, F. (2019). Impacts of Automated Vehicles on Travel Behaviour and Land Use: An International Review of Modelling Studies. Transport Reviews, 39(1), 29-49. [DOI:10.1080/01441647.2018.1523253]
12. Zhang, W., Guhathakurta, S., Fang, J., & Zhang, G. (2015). Exploring the Impact of Shared Autonomous Vehicles on Urban Parking Demand: An Agent-based Simulation Approach. Sustainable Cities and Society, 19, 34-45. [DOI:10.1016/j.scs.2015.07.006]
13. Parmar, R.V.K. (2018). Impact of Driverless Vehicles on Urban Environments & Future of Mobility. Doctoral Dissertation. Polytechnic University of Milan.
14. Daganzo, C.F. (2005). Logistics Systems Analysis. Berlin, Germany: Springer.
15. Farahani, R. Z., Fallah, S., Ruiz, R., Hosseini, S., & Asgari, N. (2019). OR Models in Urban Service Facility Location: A Critical Review of Applications and Future Developments. European Journal of Operational Research, 276(1), 1-27. [DOI:10.1016/j.ejor.2018.07.036]
16. Ortiz-Astorquiza, C., Contreras, I., & Laporte, G. (2018). Multi-level Facility Location Problems. European Journal of Operational Research, 267(3), 791-805. [DOI:10.1016/j.ejor.2017.10.019]
17. Chauhan, D. R., Unnikrishnan, A., Figliozzi, M., & Boyles, S. D. (2021). Robust Maximum Coverage Facility Location Problem with Drones Considering Uncertainties in Battery Availability and Consumpti0on. Transportation Research Record, 2675(2), 25-39. [DOI:10.1177/0361198120968094]
18. Mingozzi, A., & Roberti, R. (2018). An Exact Algorithm for The Fixed Charge Transportation Problem Based on Matching Source and Sink Patterns. Transportation Science, 52(2), 229-238. [DOI:10.1287/trsc.2017.0742]
19. Zetina, C. A., Contreras, I., & Cordeau, J. F. (2019). Exact Algorithms Based on Benders Decomposition for Multicommodity Uncapacitated Fixed-charge Network Design. Computers & Operations Research, 111, 311-324. [DOI:10.1016/j.cor.2019.07.007]
20. Asadi, E., Habibi, F., Nickel, S., & Sahebi, H. (2018). A Bi-Objective Stochastic Location-inventory-routing Model for Microalgae-based Biofuel Supply Chain. Applied energy, 228, 2235-2261. [DOI:10.1016/j.apenergy.2018.07.067]
21. Shavarani, S. M. (2019). Multi-level Facility Location-Allocation Problem for Post-Disaster Humanitarian Relief Distribution: A Case Study. Journal of Humanitarian Logistics and Supply Chain Management, 9(1), 70-81. [DOI:10.1108/JHLSCM-05-2018-0036]
22. Quintero‐Araujo, C. L., Gruler, A., Juan, A. A., & Faulin, J. (2019). Using Horizontal Cooperation Concepts in Integrated Routing and Facility‐location Decisions. International Transactions in Operational Research, 26(2), 551-576. [DOI:10.1111/itor.12479]
23. Newell, G. F. (1971). Dispatching Policies for A Transportation Route. Transportation Science, 5(1), 91-105. [DOI:10.1287/trsc.5.1.91]
24. Newell, G. F. (1973). Scheduling, Location, Transportation, and Continuum Mechanics: Some Simple Approximations to Optimization Problems. SIAM Journal on Applied Mathematics, 25(3), 346-360. [DOI:10.1137/0125037]
25. Edrisi, A., Barzegari, V., & Nourinejad, M. (2021). Serial Formation and Parallel Competition in Public Transportation. Transportmetrica A: Transport Science, 17(4), 1193-1216. [DOI:10.1080/23249935.2020.1842940]
26. Ansari, S., Başdere, M., Li, X., Ouyang, Y., & Smilowitz, K. (2018). Advancements in Continuous Approximation Models for Logistics and Transportation Systems: 1996-2016. Transportation Research Part B: Methodological, 107, 229-252. [DOI:10.1016/j.trb.2017.09.019]
27. Wang, J. Y., Yang, H., & Lindsey, R. (2004). Locating and Pricing Park-and-ride Facilities in A Linear Monocentric City with Deterministic Mode Choice. Transportation Research Part B: Methodological, 38(8), 709-731. [DOI:10.1016/j.trb.2003.10.002]
28. Bouchery, Y., & Fransoo, J. (2015). Cost, Carbon Emissions and Modal Shift in Intermodal Network Design Decisions. International Journal of Production Economics, 164, 388-399. [DOI:10.1016/j.ijpe.2014.11.017]
29. Ouyang, Y., Wang, Z., & Yang, H. (2015). Facility Location Design Under Continuous Traffic Equilibrium. Transportation Research Part B: Methodological, 81, 18-33. [DOI:10.1016/j.trb.2015.05.018]
30. Byrne, T., & Kalcsics, J. (2022). Conditional Facility Location Problems with Continuous Demand and A Polygonal Barrier. European Journal of Operational Research, 296(1), 22-43. [DOI:10.1016/j.ejor.2021.02.032]
31. Cui, T., Ouyang, Y., & Shen, Z. J. M. (2010). Reliable Facility Location Design Under the Risk of Disruptions. Operations Research, 58, 998-1011. [DOI:10.1287/opre.1090.0801]
32. Lim, M. K., Bassamboo, A., Chopra, S., & Daskin, M. S. (2013). Facility Location Decisions with Random Disruptions and Imperfect Estimation. Manufacturing & Service Operations Management, 15(2), 239-249. [DOI:10.1287/msom.1120.0413]
33. Bai, Y., Li, X., Peng, F., Wang, X., & Ouyang, Y. (2015). Effects of Disruption Risks on Biorefinery Location Design. Energies, 8(2), 1468-1486. [DOI:10.3390/en8021468]
34. Dasci, A., & Laporte, G. (2005). A Continuous Model for Multistore Competitive Location. Operations Research, 53(2), 263-280. [DOI:10.1287/opre.1040.0175]
35. Wang, X., Lim, M. K., & Ouyang, Y. (2015). Infrastructure Deployment Under Uncertainties and Competition: The Biofuel Industry Case. Transportation Research Part B: Methodological, 78, 1-15. [DOI:10.1016/j.trb.2015.03.010]
36. Galvao, L. C., Novaes, A. G., De Cursi, J. S., & Souza, J. C. (2006). A Multiplicatively-weighted Voronoi Diagram Approach to Logistics Districting. Computers & Operations Research, 33(1), 93-114. [DOI:10.1016/j.cor.2004.07.001]
37. Novaes, A. G. N., Frazzon, E. M., Scholdz-Reiter, B., & Lima Jr, O. F. (2010, October 12-15). A Continuous Districting Model Applied to Logistics Distribution Problems. XVI International Conference on Industrial Engineering and Operations Management, Sao Carlos, SP, Brazil.
38. Ouyang, Y., & Daganzo, C. F. (2006). Discretization and Validation of the Continuum Approximation Scheme for Terminal System Design. Transportation Science, 40(1), 89-98. [DOI:10.1287/trsc.1040.0110]
39. Irawan, C. A., Luis, M., Salhi, S., & Imran, A. (2019). The Incorporation of Fixed Cost and Multilevel Capacities into the Discrete and Continuous Single Source Capacitated Facility Location Problem. Annals of Operations Research, 275(2), 367-392. [DOI:10.1007/s10479-018-3014-9]
40. Daganzo, C. F. (2010). Structure of Competitive Transit Networks. Transportation Research Part B: Methodological, 44(4), 434-446. [DOI:10.1016/j.trb.2009.11.001]
41. Laz'anyi, K. (2018, May 17-19). Are We Ready for Self-Driving Cars-a Case of Principal-Agent Theory. 2018 IEEE 12th International Symposium on Applied Computational Intelligence and Informatics (SACI), Timisoara, Romania. [DOI:10.1109/SACI.2018.8441011]
42. Fagnant, D. J., & Kockelman, K. (2015). Preparing a Nation for Autonomous Vehicles: Opportunities, Barriers and Policy Recommendations. Transportation Research Part A: Policy and Practice, 77, 167-181. [DOI:10.1016/j.tra.2015.04.003]
43. He, F., Yin, Y., Chen, Z., & Zhou, J. (2015). Pricing of Parking Games with Atomic Players. Transportation Research Part B: Methodological, 73, 1-12. [DOI:10.1016/j.trb.2014.12.003]
44. Liu, W., & Geroliminis, N. (2016). Modeling the Morning Commute for Urban Networks with Cruising-for-Parking: An MFD Approach. Transportation Research Part B: Methodological, 93, 470-494. [DOI:10.1016/j.trb.2016.08.004]
45. Arnott, R. (2006). Spatial Competition Between Parking Garages and Downtown Parking Policy. Transport Policy, 13(6), 458-469. [DOI:10.1016/j.tranpol.2006.05.003]
46. Zheng, N., & Geroliminis, N. (2016). Modeling and Optimization of Multimodal Urban Networks with Limited Parking and Dynamic Pricing. Transportation Research Part B: Methodological, 83, 36-58. [DOI:10.1016/j.trb.2015.10.008]
47. Amer, A., & Chow, J. Y. (2017). A Downtown On-Street Parking Model with Urban Truck Delivery Behavior. Transportation Research Part A: Policy and Practice, 102, 51-67. [DOI:10.1016/j.tra.2016.08.013]
48. Nourinejad, M., Roorda, M. J. (2021). Cruising for Parking with Autonomous and Conventional Vehicles. Journal of Advanced Transportation. [DOI:10.1155/2021/6269995]
49. Nourinejad, M., & Amirgholy, M. (2022). Parking Design and Pricing for Regular and Autonomous Vehicles: A Morning Commute Problem. Transportmetrica B: Transport Dynamics, 10(1), 159-183. [DOI:10.1080/21680566.2021.1981485]
50. Loeb, B., Kockelman, K. M., & Liu, J. (2018). Shared Autonomous Electric Vehicle (SAEV) Operations Across the Austin, Texas Network with Charging Infrastructure Decisions. Transportation Research Part C: Emerging Technologies, 89, 222-233. [DOI:10.1016/j.trc.2018.01.019]
51. Fagnant, D. J., & Kockelman, K. M. (2018). Dynamic Ride-Sharing and Fleet Sizing for A System of Shared Autonomous Vehicles in Austin, Texas. Transportation, 45(1), 143-158. [DOI:10.1007/s11116-016-9729-z]
52. Nourinejad, M., & Amirgholy, M. (2018). Parking Pricing and Design in the Morning Commute Problem with Regular and Autonomous Vehicles. Rotman School of Management Working Paper. [DOI:10.2139/ssrn.3186290]
53. de Almeida Correia, G. H., & van Arem, B. (2016). Solving the User Optimum Privately Owned Automated Vehicles Assignment Problem (UO-POAVAP): A Model to Explore the Impacts of Self-Driving Vehicles on Urban Mobility. Transportation Research Part B: Methodological, 87, 64-88. [DOI:10.1016/j.trb.2016.03.002]
54. Zakharenko, R. (2016). Self-driving Cars Will Change Cities. Regional Science and Urban Economics, 61, 26-37. [DOI:10.1016/j.regsciurbeco.2016.09.003]
55. Dasci, A., & Verter, V. (2001). A Continuous Model for Production-Distribution System Design. European Journal of Operational Research, 129(2), 287-298. [DOI:10.1016/S0377-2217(00)00226-5]

Add your comments about this article : Your username or Email:

Send email to the article author