Comparison of Microscopic and Mesoscopic Traffic Modeling Tools for Evacuation Analysis

Evacuation activities can be evaluated using different simulation models. However, recently, microscopic simulation models have become a more popular tool for this purpose. The objectives of this study are to model multiple evacuation scenarios and to compare a microscopic traffic simulation tool (in this case INTEGRATION) against a mesoscopic traffic simulation tool (MATSim). Given that the demand was the same for both models, the comparison was achieved based on two indicators: estimated evacuation time and average trip duration. The results show that the estimated evacuation times in both models are similar since the input traffic demand governed this measure. However, the evaluation also shows a considerable difference between the two models in the average trip duration. The microscopic traffic simulation tool produces logical results with trip durations increasing with increased traffic demand levels and decreasing road capacity scenarios, whereas the average trip duration using the mesoscopic simulation tool decreases with increasing demand levels and increasing road capacity scenarios.

[1]  Eric J. Miller,et al.  Comparison of MATSim and EMME/2 on Greater Toronto and Hamilton Area Network, Canada , 2010 .

[2]  Kay W. Axhausen,et al.  An event-driven parallel queue-based microsimulation for large scale traffic scenarios , 2007 .

[3]  Kai Nagel,et al.  Large Scale Microscopic Evacuation Simulation , 2010 .

[4]  Kay W. Axhausen,et al.  Performance improvements for large-scale traffic simulation in MATSim , 2015 .

[5]  N B Taylor CONTRAM 5: AN ENHANCED TRAFFIC ASSIGNMENT MODEL , 1990 .

[6]  Hesham A Rakha,et al.  Vehicle dynamics model for predicting maximum truck acceleration levels , 2001 .

[7]  Hesham Rakha,et al.  Analytical Procedures for Estimating Capacity of Freeway Weaving, Merge, and Diverge Sections , 2006 .

[8]  Edward Pye Chamberlayne,et al.  Optimal Evacuation Plans for Network Flows over Time Considering Congestion , 2011 .

[9]  Hubert Klüpfel,et al.  Large-Scale Multi-modal Evacuation Analysis with an Application to Hamburg , 2014 .

[10]  G. Lämmel Bottlenecks and Congestion in Evacuation Scenarios : A Microscopic Evacuation Simulation for Large-Scale Disasters , 2008 .

[11]  Peter R. Stopher,et al.  Review of Procedures Associated with Devising Emergency Evacuation Plans , 2004 .

[12]  Mansooreh Mollaghasemi,et al.  Framework for Modeling Emergency Evacuation , 2005 .

[13]  Kay W. Axhausen,et al.  Agent-Based Demand-Modeling Framework for Large-Scale Microsimulations , 2006 .

[14]  Brian Wolshon,et al.  Modeling and Performance Assessment of Contraflow Evacuation Termination Points , 2005 .

[15]  F. Benjamin Zhan,et al.  Agent-based modelling and simulation of urban evacuation: relative effectiveness of simultaneous and staged evacuation strategies , 2008, J. Oper. Res. Soc..

[16]  Brian Wolshon,et al.  Transportation's Role in Emergency Evacuation and Reentry , 2009 .

[17]  Zhao Zhang,et al.  Agent-based Modeling for Evacuation Traffic Analysis in Megaregion Road Networks , 2015, ANT/SEIT.

[18]  Hanif D. Sherali,et al.  Comparison of TRANSIMS’ Light Duty Vehicle Emissions with On-Road Emission Measurements , 2010 .

[19]  M. V. Aerde,et al.  INTEGRATION : An Overview of Traffic Simulation Features , 1998 .

[20]  Hesham A Rakha,et al.  Construction and Calibration of a Large-Scale Microsimulation Model of the Salt Lake Area , 1998 .

[21]  Antoine G. Hobeika,et al.  A Decision Support System for Developing Evacuation Plans around Nuclear Power Stations , 1994 .

[22]  Hesham Rakha,et al.  Microframework for Modeling of High-Emitting Vehicles , 2004 .

[23]  M. E. Williams,et al.  TRANSIMS: TRANSPORTATION ANALYSIS AND SIMULATION SYSTEM , 1995 .

[24]  Brian Wolshon,et al.  Criteria for Development of Evacuation Time Estimate Studies , 2010 .

[25]  Francois Dion,et al.  Estimating Vehicle Stops at Undersaturated and Oversaturated Fixed-Time Signalized Intersections , 2001 .

[26]  Yu Gao Calibration and Comparison of the VISSIM and INTEGRATION Microscopic Traffic Simulation Models , 2008 .

[27]  M. Maciejewski,et al.  Comparison of traffic assignment in visum and transport simulation in matsim , 2013 .

[28]  Hesham Rakha,et al.  Development of VT-Micro model for estimating hot stabilized light duty vehicle and truck emissions , 2004 .

[29]  Warren B. Powell,et al.  A transportation network evacuation model , 1982 .

[30]  Francois Dion,et al.  COMPARISON OF DELAY ESTIMATES AT UNDER-SATURATED AND OVER-SATURATED PRE-TIMED SIGNALIZED INTERSECTIONS , 2004 .

[31]  G. Lämmel Escaping the Tsunami: Evacuation Strategies for Large Urban Areas Concepts and Implementation of a Multi-Agent Based Approach , 2011 .

[32]  Sam Yagar,et al.  DYNAMIC INTEGRATED FREEWAY/TRAFFIC SIGNAL NETWORKS: PROBLEMS AND PROPOSED SOLUTIONS , 1988 .

[33]  Hesham Rakha,et al.  Comparison and calibration of FRESIM and INTEGRATION steady-state car-following behavior , 2003 .

[34]  Kay W. Axhausen,et al.  The Multi-Agent Transport Simulation , 2016 .

[35]  N Bellomo,et al.  Human behaviours in evacuation crowd dynamics: From modelling to "big data" toward crisis management. , 2016, Physics of life reviews.

[36]  Kay W. Axhausen,et al.  An Agent-Based Microsimulation Model of Swiss Travel: First Results , 2003 .

[37]  Kyoungho Ahn,et al.  Evaluating Alternative Truck Management Strategies along Interstate 81 , 2005 .

[38]  Hesham Rakha,et al.  Comparison of Greenshields, Pipes, and Van Aerde Car-Following and Traffic Stream Models , 2002 .