Optimal allocation of protective resources in urban rail transit networks against intentional attacks |
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| Institution: | 1. School of Naval Architecture, Ocean & Civil Engineering, and State Key Laboratory of Ocean Engineering, Shanghai Jiao Tong University, Shanghai 200240, China;2. Future Cities Laboratory, Singapore-ETH Centre, Singapore 138602, Singapore;1. School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, China;2. College of Transport and Communications, Shanghai Maritime University, 1550 Haigang Avenue, Shanghai 201306, China;3. College of Transportation Engineering, Tongji University, 4800 Cao’an Road, Shanghai 201804, China;1. Future Cities Laboratory, Singapore-ETH Centre, Singapore 138602, Singapore;2. Department of Civil & Environmental Engineering, National University of Singapore, Singapore 117576, Singapore;3. School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China;4. Institute for Transport Planning and Systems (IVT), ETH Zürich, Zürich CH 8093, Switzerland;1. Universitat Politècnica de Catalunya-BarcelonaTech, C/Colom no. 11, Terrassa 08222, Spain;2. Volotea, Travessera de Gràcia, 56, Barcelona 08006, Spain;1. Department of Geographic Information Science, Nanjing University, Nanjing, Jiangsu Province 210023, PR China;2. Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing University, Nanjing, Jiangsu Province 210023, PR China;1. Alibaba Business School, Hangzhou Normal University, China;2. Shenzhen Research Institute of Big Data, China |
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| Abstract: | This paper advances the field of network interdiction analysis by introducing an application to the urban rail transit network, deploying protective resources against intentional attacks. The resource allocation problem for urban rail transit systems is considered as a game between two players, the attacker interdicting certain rail stations to generate greatest disruption impact and the system defender fortifying the network to maximize the system’s robustness to external interdictions. This paper introduces a game-theoretic approach for enhancing urban transit networks’ robustness to intentional disruptions via optimally allocating protection resources. A tri-level defender–attacker–user game-theoretic model is developed to allocate protective resources among rail stations in the rail transit network. This paper is distinguished with previous studies in that more sophisticated interdiction behaviors by the attacker, such as coordinated attack on multiple locations and various attacking intensities, are specifically considered. Besides, a more complex multi-commodity network flow model is employed to model the commuter travel pattern in the degraded rail network after interdiction. An effective nested variable neighborhood search method is devised to obtain the solution to the game in an efficient manner. A case study based on the Singapore rail transit system and actual travel demand data is finally carried out to assess the protective resources’ effectiveness against intentional attacks. |
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| Keywords: | Urban rail transit Public transport Network interdiction Multilevel programming Resource allocation |
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