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A conflict–congestion model for pedestrian–vehicle mixed evacuation based on discrete particle swarm optimization algorithm
Affiliation:1. School of Computer Science and Technology, Hubei University of Technology, Wuhan 430068, China;2. School of Computer Science and Technology, Wuhan University of Technology, Wuhan 430070, China;3. State Key Laboratory for Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, 129 Luoyu Road, Wuhan 430079, China;1. Department of Transportation Technology and Management, Kainan University, Taiwan;2. Department of Civil Engineering, National Taiwan University, Taiwan;1. College of Business, Embry-Riddle Aeronautical University, 600 S. Clyde Morris Blvd., Daytona Beach, FL 32114, USA;2. Department of Civil and Environmental Engineering, Southern Methodist University, P.O. Box 750340, Dallas, TX 75275-0340, USA;3. Northwestern University Transportation Center, 215 Chambers Hall, 600 Foster St., Evanston, IL 60208, USA;4. The Custodian of the Two Holy Mosques Institute for Hajj Research, Umm Al-Qura University, Saudi Arabia;1. College of Electronics and Information Engineering, Tongji University, Shanghai 201804, China;2. School of Engineering & Information Technology, The University of New South Wales, Canberra, Australia;3. The Key Laboratory of Embedded System and Service Computing, Tongji University, Shanghai, China;1. Department of Civil & Environmental Engineering, Florida A&M University-Florida State University, 2525 Pottsdamer Street, Building A, Suite A124, Tallahassee, FL, 32310-6046, USA;2. Department of Civil & Environmental Engineering, Florida A&M University-Florida State University, 2525 Pottsdamer Street, Building B, Suite B339, Tallahassee, FL, 32310-6046, USA;3. Department of Civil & Environmental Engineering, Florida A&M University-Florida State University, 2525 Pottsdamer Street, Building B, Suite B313, Tallahassee, FL, 32310-6046, USA;4. Department of Civil & Environmental Engineering, Florida A&M University-Florida State University, 2525 Pottsdamer Street, Building A, Suite A129, Tallahassee, FL, 32310-6046, USA;5. Department of Psychology, Florida State University, 1107 W Call St., Suite B432, Tallahassee, FL, 32306-4301, USA;6. School of Engineering, University of North Florida, 1 UNF Drive, Building 50, Suite 2102, Jacksonville, FL, 32256, USA;1. Department of Civil Engineering, University of Toronto, M5S 1A4, Canada;2. Cairo University, Faculty of Engineering, 12631 Giza, Egypt
Abstract:A simulation model based on temporal–spatial conflict and congestion for pedestrian–vehicle mixed evacuation has been investigated. Assuming certain spatial behaviors of individuals during emergency evacuation, a discrete particle swarm optimization with neighborhood learning factor algorithm has been proposed to solve this problem. The proposed algorithm introduces a neighborhood learning factor to simulate the sub-group phenomenon among evacuees and to accelerate the evacuation process. The approach proposed here is compared with methods from the literatures, and simulation results indicate that the proposed algorithm achieves better evacuation efficiency while maintaining lower pedestrian–vehicle conflict levels.
Keywords:Simulation  Pedestrian–vehicle mixed evacuation  Discrete particle swarm optimization algorithm  Temporal–spatial conflict  Temporal–spatial congestion
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