Augmented betweenness centrality for environmentally aware traffic monitoring in transportation networks

Journal of Intelligent Transportation Systems: Technology, Planning, and Operations

Volumn 17, Issue 1, 2013, Pages 91-105

  Puzis, Rami ^a   Altshuler, Yaniv ^b   Elovici, Yuval ^c   Bekhor, Shlomo ^d   Shiftan, Yoram ^d   Pentland, Alex ^b  

^a UNIVERSITY OF MARYLAND   (United States)

^b MIT MEDIA LAB   (United States)

^c BEN GURION UNIVERSITY OF THE NEGEV   (Israel)

^d TECHNION ISRAEL INSTITUTE OF TECHNOLOGY   (Israel)

Author keywords

Betweenness; Monitoring; Traffic Assignment

Indexed keywords

BETWEENNESS; BETWEENNESS CENTRALITY; CELLULAR PHONE; DATA SET; EMISSION MEASUREMENT; HIGH RESOLUTION; HOUSEHOLD SURVEYS; MERIT FUNCTION; NETWORK PLANNING; NETWORK TOPOLOGY; NONLOCAL; OPTIMAL DEPLOYMENT; ORIGIN-DESTINATION PAIRS; SHORTEST PATH; TOTAL EMISSIONS; TRAFFIC ASSIGNMENT; TRAFFIC ASSIGNMENT MODELS; TRAFFIC ASSIGNMENT PROBLEM; TRAFFIC FLOW; TRAFFIC MONITORING; TRANSPORTATION NETWORK; TRAVEL COSTS; VEHICLE FLEETS;

ELECTRIC NETWORK TOPOLOGY; MONITORING; OPTIMIZATION;

TRAFFIC CONTROL;

DATA ACQUISITION; DATA SET; EMISSION INVENTORY; ENVIRONMENTAL IMPACT; HOUSEHOLD SURVEY; MOBILE COMMUNICATION; OPTIMIZATION; TRAFFIC MANAGEMENT; TRANSPORTATION PLANNING; TRANSPORTATION SYSTEM;

ISRAEL;

EID: 84874450496     PISSN: 15472450     EISSN: 15472442     Source Type: Journal    
DOI: 10.1080/15472450.2012.716663     Document Type: Article

References (78)

1. Altshuler, Y., & Bruckstein, A. (2011). Static and expanding grid coverage with ant robots: Complexity results. Theoretical Computer Science, 4121(35), 4661-4674.
2. Altshuler, Y., Wagner, I., & Bruckstein, A. (2005). On swarm optimality in dynamic and symmetric environments. In Second International Conference on Informatics in Control, Automation and Robotics (ICINCO), the First International Workshop on Multi-Agent Robotic Systems (MARS), 64-71.
3. Altshuler, Y., Wagner, I., & Bruckstein, A. (2006). Shape factor' s effect on a dynamic cleaners swarm. In Third International Conference on Informatics in Control, Automation and Robotics (ICINCO), the Second International Workshop on Multi-Agent Robotic Systems (MARS), 13-21.
4. Altshuler, Y., Yanovsky, V., Bruckstein, A., & Wagner, I. (2008). Efficient cooperative search of smart targets using uav swarms. ROBOTICA, 26, 551-557.
5. Anthonisse, J.M. (1971). The rush in a directed graph. Technical Report BN 9/71, Stichting Mathematisch Centrum, Amsterdam, The Netherlands.
6. Armstrong, J., & Khan, A. (2004). Modelling urban transportation emissions: Role of GIS. Computers, Environment and Urban Systems, 28(4), 421-433. (Pubitemid 38527444)
7. Atabani, A., Badruddin, I., Mekhilef, S., & Silitonga, A. (2011). A review on global fuel economy standards, labels and technologies in the transportation sector. Renewable and Sustainable Energy Reviews, 15(9), 4586-4610.
8. Barabasi, A.-L., & Albert, R. (1999). Emergence of scaling in random networks. Science, 286, 509-512.
9. Barkenbus, J. (2010). Eco-driving: An overlooked climate change initiative. Energy Policy, 38(2), 762-769.
10. Barth, M., & Boriboonsomsin, K. (2009a). Energy and emissions impacts of a freeway-based dynamic eco-driving system. Transportation Research Part D, 14(6), 400-410.
11. Barth, M., & Boriboonsomsin, K. (2009b). Traffic congestion and greenhouse gases. ACCESS, 35, 2-9.
12. Barth́elemy, M. (2004). Betweenness centrality in large complex networks. European Physical Journal B-Condensed Matter, 38(2), 163-168.
13. Bekhor, S., Cohen, Y., & Solomon, C. (2011). Evaluating longdistance travel patterns in israel by tracking cellular phone positions. Journal of Advanced Transportation.
14. Bekhor, S., & T., Toledo (2005). Investigating path-based solution algorithms to the stochastic user equilibrium problem. Transportation Research Part B, 39(3), 279-295. (Pubitemid 40058681)
15. Ben-Akiva, M., Bierlaire, M., Koutsopoulos, H. N., & Mishalani, R. (2002). Real-time simulation of traffic demand-supply interactions within Dyna MIT. Transportation and network analysis: Current trends. Miscellenea in honor of Michael Florian. Dordrecht, The Netherlands: Kluwer Academic.
16. Bertsekas, D., & Gallager, R. (1987). Data networks. Englewood Cliffs, NJ: Prentice-Hall International.
17. Bertsekas, D. P., & Gafni, E. M. (1982). Projection methods for variational inequalities with application to the traffic assignment problem. Mathematical Programming Study, 17, 139-159.
18. Bianco, L., Confessore, G., & Gentili, M. (2006). Combinatorial aspects of the sensor location problem. Annals of Operation Research, 144(1), 201-234. (Pubitemid 44286450)
19. Bianco, L., Confessore, G., & Reverberi, P. (2001). A network based model for traffic sensor location with implications on o/d matrix estimates. Transportation Science, 35(1), 50-60. (Pubitemid 32839501)
20. Bork, P., Jensen, L. J., von Mering, C., Ramani, A. K., Lee, I., & Marcotte, E. M. (2004). Protein interaction networks from yeast to human. Current Opinions in Structural Biology, 14(3), 292-299. (Pubitemid 38749056)
21. Brandes, U. (2008). On variants of shortest-path betweenness centrality and their generic computation. Social Networks, 30(2), 136-145.
22. Ĉamara Pereira, F., Rodrigues, F., & Ben-Akiva, M. (2012). Internet as a sensor: a case study with special events. In Transportation Research Board 91st Annual Meeting, number 12-3365.
23. Castillo, E., Gallego, I., Meńendez, J., & Jiḿenez, P. (2011). Link flow estimation in traffic networks on the basis of link flow observations. Journal of Intelligent Transportation Systems, 15(4), 205-222.
24. Chandra, S., & Al-Deek, H. (2009). Predictions of freeway traffic speeds and volumes using vector autoregressive models. Journal of Intelligent Transportation Systems, 13(2), 53-72.
25. Cheu, R., Lei, H., & Aldouri, R. (2010). Optimal assignment of emergency response service units with time-dependent service demand and travel time. Journal of Intelligent Transportation Systems, 14(4), 220-231.
26. Colvile, R. N., Hutchinson, E., Mindell, J., & Warren, R. F. (2001). The transport sector as a source of air pollution. Atmospheric Environment, 35, 1537-65.
27. Cort́es, C., Vargas, L., & Corvaĺan, R. (2008). A simulation platform for computing energy consumption and emissions in transportation networks. Transportation Research Part D: Transport and Environment, 13(7), 413-427.
28. De Nevers, N. (2000). Air pollution control engineering, volume 463. New York, NY: McGraw-Hill.
29. Dolev, S., Elovici, Y., & Puzis, R. (2010). Routing betweenness centrality. Journal of the ACM, 57(4), 25:1-25:27.
30. Dolev, S., Elovici, Y., Puzis, R., & Zilberman, P. (2009). Incremental deployment of network monitors based on group betweenness centrality. Information Processing Letters, 109, 1172-1176.
31. Ehlert, A., Bell, M., & Grosso, S. (2006). The optimisation of traffic count locations in road networks. Transportation Research Part B, 40(6), 460-479.
32. Everett, M. G. & Borgatti, S. P. (1999). The centrality of groups and classes. Mathematical Sociology, 23(3), 181-201.
33. Faloutsos, M., Faloutsos, P., & Faloutsos, C. (1999). On power-law relationships of the internet topology. SIGCOMM Computer Communication Review, 29(4), 251-262. (Pubitemid 32081870)
34. Fei, X., Mahmassani, H. S., & Eisenman, S. M. (2007). Sensor coverage and location for real-time traffic prediction in large-scale networks. Transportation Research Record, 2039(1), 1-15. (Pubitemid 351532626)
35. Freeman, L. C(1977). A set of measures of centrality based on betweenness. Sociometry ,40(1) 35-41.
36. Freeman, L. C., Borgatti, S. P., & White, D. R(1991). Centrality in valued graphs: A measure of betweenness based on network flow. Social Networks, 13(2) 141-154.
37. Golob, T. F., & Regan, A. C. (2001). Impacts of information technology on personal travel and commercial vehicle operations: research challenges and opportunities. Transportation Research Part C: Emerging Technologies, 9(2), 87-121.
38. Gonzalez, M. C., Hidalgo, C. A., & Barabasi, A.-L. (2008). Understanding individual human mobility patterns. Nature, 453(7196), 779-782. (Pubitemid 351793783)
39. Gur, Y., Bekhor, S., Solomon, C., & Kheifits, L. (2009). Intercity person trip tables for nationwide transportation planning in israel obtained from massive cell phone data. Transportation Research Record: Journal of the Transportation Research Board, 2121, 145-151.
40. Holme, P. (2003). Congestion and centrality in traffic flow on complex networks. Advances in Complex Systems, 6(2), 163-176.
41. Hu, S.-R., Peeta, S., & Chu, C.-H. (2009). Identification of vehicle sensor locations for link-based network traffic applications. Transportation Research Part B, 43(8-9), 873-894.
42. IsraeliMinistry of Environmental Protection. (2011). The environment in Israel: Indicators, data and trends, 2010. Technical report, Israeli Ministry of Environmental Protection, Jerusalem, Israel.
43. Jayakrishnan, R., Tsai, W. T., Prashker, J. N., & Rajadhyaksha, S. (1994). A faster path-based algorithm for traffic assignment. Transportation Research Record, 1443, 75-83.
44. Kean, A. J., Harley, R. A., & Kendall, G. R. (2003). Effects of vehicle speed and engine load on motor vehicle emissions. Environmental Science and Technology, 37(17), 3739-3746. (Pubitemid 37071583)
45. Kim, M., Miller-Hooks, E., & Nair, R. (2011). A geographic information system-based real-time decision support framework for routing vehicles carrying hazardous materials. Journal of Intelligent Transportation Systems, 15(1), 28-41.
46. Korf, R. E., & Zhang, W. (1995). Performance of linear-space search algorithms. Artificial Intelligence, 79(2), 241-292.
47. Lam, W., & Lo, H. (1990). Accuracy of o-d estimates from traffic counts. Traffic Engineering and Control, 31, 358-367.
48. Larsson, H., & Ericsson, E. (2009). The effects of an acceleration advisory tool in vehicles for reduced fuel consumption and emissions. Transportation Research part D, 14, 141-146.
49. Lerner, J. (2005). Role assignments. In Network analysis: Methodological foundations, chapter Role Assignments (pp. 215-250). Springer, Secaucus, NJ. LNCS 3418.
50. Li, X., & Ouyang, Y. (2011). Reliable sensor deployment for network traffic surveillance. Transportation Research Part B, 45, 218-231.
51. Litman, T. (2011). Online TDM encyclopedia. The Victoria Transportation Institute. Retrieved from http://www.vtpi.org/tdm/(accessed December 13, 2012).
52. Lorrain, F., & White, H. C. (1971). Structural equivalence of individuals in social networks. The Journal of Mathematical Sociology, 1(1), 49-80.
53. Newman, M. E. J. (2005). A measure of betweenness centrality based on random walks. Social Networks, 27(1), 39-54. (Pubitemid 40272648)
54. Parra, R., Jiḿenez, P., & Baldasano, J. (2006). Development of the high spatial resolution emicat2000 emission model for air pollutants from the north-eastern iberian peninsula (catalonia, spain). Environmental Pollution, 140(2), 200-219. (Pubitemid 43052945)
55. Puzis, R., Elovici, Y., & Dolev, S. (2007a). Fast algorithm for successive computation of group betweenness centrality. Physics Review E, 76(5), 056709.
56. Puzis, R., Elovici, Y., & Dolev, S. (2007b). Finding the most prominent group in complex networks. AI Communications, 20, 287-296. (Pubitemid 350096314)
57. Puzis, R., Klippel, M. D., Elovici, Y., & Dolev, S. (2008). Optimization of NIDS placement for protection of intercommunicating critical infrastructures. Springer European Conference on Intelligence and Security Informatics (EuroISI), Esbjerg, Denmark, 191-203.
58. Puzis, R., Yagil, D., Elovici, Y., & Braha, D. (2009). Collaborative attack on internet users' anonymity. Internet Research, 19(1), 60-77.
59. Rakha, H., & Ahn, K. (2004). Integration modeling framework for estimating mobile source emissions. Journal of Transportation Engineering, 130(183).
60. Rentziou, A., Gkritza, K., & Souleyrette, R. (2012). VMT, energy consumption, and ghg emissions forecasting for passenger transportation. Transportation Research Part A: Policy and Practice, 46(3), 487-500.
61. Reynolds, A., & Broderick, B. (2000). Development of an emissions inventory model for mobile sources. Transportation Research Part D: Transport and Environment, 5(2), 77-101. (Pubitemid 30132575)
62. Ross Morrow, W., Gallagher, K., Collantes, G., & Lee, H. (2010). Analysis of policies to reduce oil consumption and greenhouse-gas emissions from the us transportation sector. Energy Policy, 38(3), 1305-1320.
63. Scott, J. (2000). Social Network Analysis: A Handbook. Sage Publications, London, UK: Sage.
64. Simini, F., Gonźalez, M., Maritan, A., & Barab́asi, A. (2012). A universal model for mobility and migration patterns. Nature, 484, 96-100.
65. Song, C., Qu, Z., Blumm, N., & Barab́asi, A. (2010). Limits of predictability in human mobility. Science, 327(5968), 1018-1021.
66. Stern, R., Puzis, R., & Felner, A. (2011). Potential search: A boundedcost search ́yalgorithm. In AAAI 21st International Conference on Automated Planning and Scheduling (ICAPS), 234-241.
67. Stopher, P., Wilmot, C., Stecher, C., & Alsnih, R. (2006). Household travel surveys: Proposed standards and guidelines. In Travel Survey Methods, Quality and Future Directions. Eds. Stopher, P. & Stecher, C. C. Elsevier, Kidlington, Oxford, UK, 19-74.
68. Strogatz, S. H. (2001). Exploring complex networks. Nature, 410, 268-276. (Pubitemid 32216604)
69. Toledo, G. (2010). Analysis and modeling of driving behavior using in-vehicle data recorders. Ph.D. thesis, the Technion, Israel Institute of Technology, Haifa, Israel.
70. Toledo, T., & Beinhaker, R. (2006). Evaluation of the potential benefits of advanced traveler information systems. Journal of Intelligent Transportation Systems, 10(4), 173-183. (Pubitemid 44684062)
71. Tubi, M., Puzis, R., & Elovici, Y. (2007). Deployment of DNIDS in social networks. IEEE Intelligence and Security Informatics (ISI), New Brunswick, NJ, USA.
72. Wasserman, S. & Faust, K. (1994). Social network analysis: Methods and applications. Cambridge, England: Cambridge University Press.
73. White, D. R., & Borgatti, S. P. (1994). Betweenness centrality measures for directed graphs. Social Networks, 16, 335-346.
74. Yan, X., & Crookes, R. (2010). Energy demand and emissions from road transportation vehicles in china. Progress in Energy and Combustion Science, 36(6), 651-676.
75. Yang, H., Yang, C., & Gan, L. (2006). Models and algorithms for the screen line-based traffic-counting location problems. Computers and Operations Research, 33(3), 836-858. (Pubitemid 41101127)
76. Yang, H., & Zhou, J. (1998). Optimal traffic counting locations for origin-destination matrix estimation. Transportation Research Part B, 32(2), 109-126. (Pubitemid 128714057)
77. Yook, S., Jeong, H., & Barabasi, A.-L. (2002). Modeling the Internet's large-scale topology. Proceedings of the National Academy of Science, USA, 99(21), 13382-13386. (Pubitemid 35215389)
78. Zilberstein, S. (1996). Using anytime algorithms in intelligent systems. AI Magazine, 17(3), 73-83. (Pubitemid 126669856)