Network Design Problem for Risk Reduction in Transport System: A Models Specification

Network Design Problem for Risk Reduction in Transport System: A Models Specification

Antonino Vitetta

Dipartimento di ingegneria dell’Informazione, delle Infrastrutture e dell’Energia Sostenibile, Università degli Studi Mediterranea di Reggio Calabria, Italy

Page: 
283-297
|
DOI: 
https://doi.org/10.2495/TDI-V6-N3-283-297
Received: 
N/A
|
Revised: 
N/A
|
Accepted: 
N/A
|
Available online: 
N/A
| Citation

© 2022 IIETA. This article is published by IIETA and is licensed under the CC BY 4.0 license (http://creativecommons.org/licenses/by/4.0/).

OPEN ACCESS

Abstract: 

With the occurrence of natural or anthropogenic events, which can cause damage to people, delayed in time, adequate actions must be implemented to evacuate the population from the areas at risk. In this context, the transport supply system must be adequately designed to facilitate rapid evacuation.

This paper presents the design methodologies of transport networks in the presence of disasters. The design variables considered concern the direction of travel of the links and the regulation strategies to be adopted in the junctions. The objective function considers risk minimization in terms of user exposure. In the problem, the main constraint considered concerns the users’ behaviour. In fact, the configuration of the supply system can be optimized but it is necessary to consider that users adopt choice strategies that tend to minimize their disutility. Therefore, the best possible configuration must be found for all users (system optimum), considering that the choices of individual users are with maximum individual utility (user choice).

The paper reports the main characteristics that a decision support system should have in terms of: general framework, model and resolution procedures. The decision support system can be used by the decisions that have to design the transport network through preventive actions or in real time.

Keywords: 

evacuation, risk reduction transport, network design problem

  References

[1] Russo, F. & Rindone, C., Safety of users in road evacuation: planning internal processes and guidelines. WIT Transactions on the Built Environment, 96, pp. 825–834, 2007.

[2] Russo, F., Rindone, C. & Trecozzi, M.R., The Role of Training in Evacuation. WIT Transactions on Information and Communication Technologies, 44, pp. 491–502, 2012.

[3] Russo, F. & Vitetta, A., Safety of users in road evacuation: general methodology and main results. WIT Transactions on the Built Environment, 96, pp. 763–772, 2007.

[4] Russo, F. & Chilà, G., Safety of users in road evacuation: RP vs. SP surveys in demand analysis. 14th International Conference on Urban Transport and the Environment in the 21st Century, URBAN TRANSPORT XIV, Vol. 101, pp.703–713, 2008.

[5] Musolino, G. & Vitetta A., Short-term forecasting in road evacuation: calibration of a travel time function. WIT Transactions on the Built Environment, 116, pp. 615–626, 2011.

[6] Di Gangi, M., Watling, D. & Di Salvo, R., Modeling evacuation risk using a stochastic process formulation of mesoscopic dynamic network loading. IEEE Transactions on Intelligent Transportation Systems, 2020.

[7] Russo, F. & Rindone, C., The planning process and logical framework approach in road evacuation: a coherent vision. WIT Transactions on the Built Environment, 117, pp. 415–425, 2011.

[8] Vitetta, A., Polimeni, A. & Quattrone, A., Safety of users in road evacuation: modelling and DSS for paths design of emergency vehicles. WIT Transactions on Ecology and the Environment, 120, pp. 485–495, 2009.

[9] Polimeni, A. & Vitetta A., The role of ITS in evacuation route optimization for emergency vehicles. WIT Transactions on Information and Communication Technologies, 44, pp. 517–529, WIT Press, 2012. doi: 10.2495/RISK120431.

[10] Billheimer, J.W. & Gray, P., Network design with fixed and variable cost elements. Transportation Science, 7, pp. 49–74, 1973.

[11] Chen, M. & Alfa, A.S., A network design algorithm using a stochastic incremental traffic assignment approach. Transportation Science, 25, pp. 215–224, 1991.

[12] Foulds, L.R., A multi-commodity flow network design problem. Transportation Research, 15B, pp. 273–283, 1981.

[13] Herrmann, J.W., Ioannou, G., Minis, I. & Proth, J.M., A dual ascent approach to the fixed-charge capacitated network design problem. European Journal of Operational Research, 95, pp. 476-490, 1996.

[14] Solanky, R.S., Gorti, J.K. & Southworth F., Using decomposition in large-scale highway network design with a quasi-optimization heuristic. Transportation Research Part B, 32(2), pp. 127–140, 1998.

[15] Gao, Z., Wu J. & Sun, H., Solution algorithm for the bi-level discrete network design problem. Transportation Research Part B, 39, pp. 479–495, 2005.

[16] Poorzahedy, H. & Rouhani, O.M., Hybrid meta-heuristic algorithms for solving network design problem. European Journal of Operational Research, 182(2), pp. 578–596, 2007.

[17] Xie, C. & Turnquist, M.A., Integrated evacuation network optimization and emergency vehicle assignment. TRB, 2009.

[18] Kalafatas, G. & Peeta, S., Planning for evacuation: insights from an efficient network design model. Journal of Infrastructure Systems, 15(1), pp. 21–30, 2009.

[19] He, X., Zheng H., Peeta S. & Li Y., Network design model to integrate shelter assignment with contraflow operations in emergency evacuation planning. Networks and Spatial Economics, 18(4), pp. 1027–1050, 2018.

[20] Webster F.V., Traffic Signal Settings. Road Research Technical. Paper No. 39, Road Research Laboratory, London, UK, 1958.

[21] Allsop, R.E., SIGSET: a computer program for calculating traffic capacity of signal controlled road junctions. Traffic Engineering Control, 12, pp. 58–60, 1971.

[22] Little, J.D.C., Kelson, M.D. & Gartner, N.H., MAXBAND: a program for setting signals on arteries and triangular networks. Transportation Research Record, 795, pp. 40–46, 1981.

[23] Robertson, D.I., TRANSYT method for area traffic control. Traffic Engineering & Control, 10, pp. 276–281, 1969.

[24] Little, J.D.C., The synchronisation of traffic signals by mixed-integer-linearprogramming. Operations Research, 14, pp. 568–594, 1966.

[25] Cantarella, G.E., Improta, G. & Sforza, A., Road network signal setting: equilibrium conditions. Concise Encyclopaedia of Traffic & Transportation Systems, ed. M. Papageorgiou, Pergamon Press, pp. 366–371, 1991.

[26] Cantarella, G.E., Pavone, G. & Vitetta, A., Heuristics for urban road network design: lane layout and signal settings. European Journal of Operational Research, 175(3), pp. 1682–1695, 2006.

[27] Marcianò, F.A, Musolino, G. & Vitetta A., Signal setting design on a road network: application of a system of models in evacuation conditions. WIT Transactions on Information and Communication Technologies, 43(1), pp. I443–I454, 2010.

[28] Marcianò, F.A., Musolino, G. & Vitetta, A., A system of models for signal setting design of a signalized road network in evacuation conditions. WIT Transactions on the Built Environment, 111, pp. 313–323, 2010.

[29] Marcianò, F.A., Musolino, G. & Vitetta, A., Within-day traffic assignment and signal setting in road evacuation: a procedure with explicit path enumeration. WIT Transactions on the Built Environment, 117, pp. 403–414, 2011.

[30]Marcianò, F.A, Musolino, G. & Vitetta A., Signal setting optimization on urban road transport networks: the case of emergency evacuation. Safety Science, 72, pp. 209–220, 2015.

[31] Vitetta, A., Risk reduction in transport system in emergency conditions: a framework for network design problem. WIT Transactions on the Built Environment, 206, pp. 267–274, 2021.

[32] Russo, F. & Vitetta, A., Risk evaluation in a transportation system. International Journal of Sustainable Development and Planning, WIT Press, 1, pp. 170–191, 2006.

[33] Liao, T., Hu, T. & Ko, Y., A resilience optimization model for transportation networks under disasters. Natural Hazards, 93(1), pp. 469–489, 2018.

[34] Pan, X., Dang, Y., Wang, H., Hong, D., Li, Y. & Deng, H., Resilience model and recovery strategy of transportation network based on travel OD-grid analysis. Reliability Engineering and System Safety, 223, 2022.

[35] Di Gangi, M. & Belcore, O.M., Risk reduction in transport system in emergency conditions: a framework for decision support systems. Paper presented at the WIT Transactions on the Built Environment, 206, pp. 299-311, 2021.

[36] Cascetta, E., Transportation Systems Engineering: Theory and Methods, Springer, New York, 2009.