Networks and Spatial Economics

, Volume 13, Issue 3, pp 229–254

Vortex-Based Zero-Conflict Design of Urban Road Networks

Article

Abstract

A novel approach is suggested for reducing traffic conflicts in at-grade (2D) urban networks. Intersections without primary vehicular conflicts are defined as zero traffic conflict (ZTC) designs. A complete classification of maximal ZTC designs is presented, including designs that combine driving on the right side in some streets and driving on the left side in other streets. It is shown that there are 9 four-way and 3 three-way maximal ZTC intersection designs, to within mirror, rotation, and arrow reversal symmetry. Vortices are used to design networks where all or most intersections are ZTC. Increases in average travel distance, relative to unrestricted intersecting flow, are explicitly calculated for grid-networks of sizes 10 by 10, 10 by 20 and 20 by 20 nodes with evenly distributed origins and destinations. The exact increases depend primarily on various short-range conditions, such as the access to the network. The average distance increase in most cases examined is up to four blocks. These results suggest that there is a potential for the new designs to be relevant candidates in certain circumstances, and that further study of them is worthwhile.

Keywords

Network design Traffic conflicts 

References

  1. Blunden WR, Bunton RB (1962) An analysis of route factors for one-way and two-way street systems. Proceeding of 1st conference, Australian Road Research Board 1:443–454. Australian Road Research Board, MelbourneGoogle Scholar
  2. Boyles SD (2012) Bush-based sensitivity analysis for approximating subnetwork diversion. Transport Res Part B 46(1):139–155CrossRefGoogle Scholar
  3. Cantarella GE, Vitetta A (2006) The multi-criteria road network design problem in an urban area. Transport 33:567–588CrossRefGoogle Scholar
  4. Cova TJ, Johnson JP (2003) A network flow model for lane-based evacuation routing. Transport Res Part A 37:579–604CrossRefGoogle Scholar
  5. Frank L, Bradley M, Kavage S, Chapman J, Lawton TK (2008) Urban form, travel time, and cost relationships with tour complexity and mode choice. Transport 35:37–54Google Scholar
  6. Fuerstenberg K (2009) Cooperative intersection safety: user needs and operational requirements for cooperative intersection safety system. Deliverable D3.1. http://www.intersafe-2.eu/public/public-documents/deliverables/d3_1_intersafe-2_user_needs_and_requirements_v1-05-final.pdf, accessed December 17, 2011
  7. HCM (2010) Highway capacity manual. Transportation Research Board of the National Academies, WashingtonGoogle Scholar
  8. Holroyd EM (1966) Theoretical average journey lengths in circular towns with various routeing systems. Report 43, Transport and Road Research Laboratory, Crowthorne, Berkshire, UKGoogle Scholar
  9. Holroyd EM (1968) Routeing traffic in a square town to minimize route-crossings. Road Research Laboratory technical note, Crowthorne, Berkshire, UK. Beiträge zur Theorie des Verkehrflusses, Strassenbau und Strassenverkehrstechnik 86:166–175Google Scholar
  10. Holroyd EM, Miller AJ (1966) Route crossings in urban areas. Proceeding of 3rd conference, Australian Road Research Board 3:394–419, Australian Road Research Board, MelbourneGoogle Scholar
  11. HSM (2010) Highway safety manual. The American Association of State Highway and Transportation Officials, WashingtonGoogle Scholar
  12. Hummer JE (1998) Unconventional left turn alternatives for urban and suburban arterials: part one. Institute of Transportation Engineering Journal 68(9):26–29Google Scholar
  13. Karoonsoontawong A, Waller ST (2010) Integrated network capacity expansion and traffic signal optimization problem: robust bi-level dynamic formulation. Network Spatial Econ 10:525–550. doi:10.1007/s11067-008-9071-x CrossRefGoogle Scholar
  14. Kornhauser AL (2005) Personal rapid transit for New-Jersey. http://www.princeton.edu/~alaink/Orf467F04/NJ%20PRT%20Final%20Small.pdf, accessed June 6, 2012
  15. Lin DY, Xie C (2011) The pareto-optimal solution set of the equilibrium network design problem with multiple commensurate objectives. Network Spatial Econ 11:727–751. doi:10.1007/s11067-010-9146-3 CrossRefGoogle Scholar
  16. Marshall WE, Garrick NW (2010) Effect of street network design on walking and biking. Transportation Research Record: Journal of the Transportation Research Board 2198:103–115CrossRefGoogle Scholar
  17. Marshall WE, Garrick NW (2011) Does street network design affect traffic safety? Accid Anal Prev 43:769–781CrossRefGoogle Scholar
  18. Mathew TV, Sharma S (2009) Capacity expansion problem for large urban transportation networks. ASCE J Transport Eng 135(7):406–415CrossRefGoogle Scholar
  19. Miandoabchi E, Zanjirani Farahani R, Wout Dullaert W, Szeto WY (2012) Hybrid evolutionary metaheuristics for concurrent multi-objective design of urban road and public transit networks. Network Spatial Econ Published on line. doi:10.1007/s11067-011-9163-x
  20. Parsons GF (2007) The parallel flow intersection: a new two-phase signal alternative. Institute of Transportation Engineering Journal 77(10):28–32Google Scholar
  21. Santos B, Antunes A, Miller EJ (2008) Integrating equity objectives in a road network design model. Transportation Research Record: Journal of the Transportation Research Board 2089:35–42CrossRefGoogle Scholar
  22. Sohn K (2011) Multi-objective optimization of a road diet network design. Transportation Research Part A 45:499–511Google Scholar
  23. Tabernero V, Sayed T (2006) Upstream signalized crossover intersection an unconventional intersection scheme. ASCE J Transport Eng 132(11):907–911CrossRefGoogle Scholar
  24. Uchida K, Sumalee A, Watling D, Connors R (2007) A study on network design problems for multi-modal networks by probit-based stochastic user equilibrium. Network Spatial Econ 7(3):213–240CrossRefGoogle Scholar
  25. Ukkusuri SV, Waller ST (2008) Linear programming models for the user and system optimal dynamic network design problem: formulations, comparisons and extensions. Network Spatial Econ 8:383–406. doi:10.1007/s11067-007-9019-6 CrossRefGoogle Scholar
  26. Tong CO, Wong SC (1997) The advantages of a high density, mixed land use, linear urban development. Transport 24:295–307CrossRefGoogle Scholar
  27. Vance C, Hedel R (2007) The impact of urban form on automobile travel: disentangling causation from correlation. Transport 34:575–588CrossRefGoogle Scholar
  28. Vaughan R (1987) Urban spatial traffic patterns. Pion Limited, LondonGoogle Scholar
  29. Vitins BJ, Axhausen KW (2009) Optimization of large transport networks using the ant colony heuristic. Comput Aided Civ Infrastruct Eng 24(1):1–14CrossRefGoogle Scholar
  30. Vitins BJ, Schüssler N, Axhausen KW (2012) Comparison of hierarchical network design shape grammars for roads and intersection. Paper presented at the 91th Annual Meeting of the Transportation Research Board, Washington DCGoogle Scholar
  31. Wang DZW, Lo HK (2010) Global optimum of the linearized network design problem with equilibrium flows. Transportation Research Part B 44:482–492CrossRefGoogle Scholar
  32. Won JM, Karray F (2007) A genetic algorithm with cycle representation and contraction digraph model for Guideway Network design of Personal Rapid Transit. IEEE Congress on Evolutionary ComputationGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  1. 1.Physics DepartmentBen-Gurion University of the NegevBeer-ShevaIsrael
  2. 2.Department of Industrial Engineering and ManagementBen-Gurion University of the NegevBeer-ShevaIsrael

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