Evaluation of the Traffic Impacts of Mass Evacuation of Halifax: Flood Risk and Dynamic Traffic Microsimulation Modeling

2018 ◽  
Vol 2672 (1) ◽  
pp. 148-160 ◽  
Author(s):  
MD Jahedul Alam ◽  
Muhammad Ahsanul Habib ◽  
Kevin Quigley ◽  
Tim L. Webster
Keyword(s):  
Flood Risk ◽  
Network Performance ◽  
Comprehensive Evaluation ◽  
Dynamic Traffic Assignment ◽  
Network Capacity ◽  
Transport Network ◽  
Dynamic Traffic ◽  
Traffic Impacts ◽  
Microsimulation Modeling ◽  
Mass Evacuation

This paper presents a comprehensive evaluation of traffic impacts of a mass evacuation of the Halifax Peninsula under several flooding scenarios. Flood extent and associated damages to the transport network are identified through digital elevation modeling that intersects with the Halifax stream and transport networks. The resulting flood scenarios inform a traffic microsimulation model that uses a dynamic traffic assignment-based microsimulation approach and simulates the evacuation of 34,808 evacuees estimated from the Halifax Regional Transport Network Model. The simulation results suggest that flooding of the links by 7.9 m flood reduces alternative evacuation routes by 31.2%. It takes 15 hours to evacuate 83% of evacuees while the remaining 17% are not accommodated in the network due to reduced network capacity. The number of vehicles in the network has peaked at 13,000 in this flooding scenario. An evaluation of network performance reveals a sustained congestion prevailing from 4th to 7th hour of the evacuation. The novelty of this study is that it develops a comprehensive tool of flood risk and dynamic traffic microsimulation modeling to offer an in-depth evaluation of potential impacts during evacuation. The results will help emergency professionals in evacuation planning and making emergency decisions.

Dynamic User Optimal of Traffic Assignment Based on Optimal Signal Timing

2014 ◽  
Vol 587-589 ◽  
pp. 2040-2044
Author(s):  
Lu Zhang
Keyword(s):  
Variational Inequality ◽  
Network Performance ◽  
Traffic Assignment ◽  
Dynamic Traffic Assignment ◽  
Equivalent Model ◽  
Signal Timing ◽  
Optimal Model ◽  
Dynamic Traffic ◽  
The Relationship ◽  
Optimal Signal

At the beginning the paper summarizes the research status,models and algorithms of dynamic traffic assignment and analyzes the relationship between dynamic user optimal model and variational inequality.Secondly,a dynamic user optimal model of traffic assignment based on optimal signal timing is established,equivalent model of the variational inequality is built at the same time.Finally,we discuss the superiority of the model and apply this model to a simple example,the results show that the model can improve the network performance significantly.

scholarly journals Multivariable Analysis of Transport Network Seismic Performance: Mexico City

2020 ◽  
Vol 12 (22) ◽  
pp. 9726
Author(s):  
Azucena Román-de la Sancha ◽  
Rodolfo Silva
Keyword(s):  
Mexico City ◽  
Seismic Performance ◽  
Urban Areas ◽  
Network Performance ◽  
Multivariable Analysis ◽  
Performance Measure ◽  
Transport Network ◽  
Traffic Modeling ◽  
Dynamic Traffic ◽  
Traffic Behavior

In densely populated urban areas, predicting the post-earthquake performance of a transport network is a particularly challenging task that requires the integration of modeled structural seismic response, damage scenarios, and resulting traffic behavior. Previous approaches assessing the vulnerability and performance of networks after earthquakes have not succeeded in capturing and estimating the interdependencies between seismic risk parameters and key traffic behavior variables. This paper presents a methodology, based on data analysis and optimization, where the dynamic traffic modeling and probabilistic seismic hazard assessment are coupled, to link and characterize key network performance variables after extreme earthquakes and establish a multivariable seismic performance measure. The methodology is used to study the transport network in the southern part of Mexico City for a set of scenarios. The seismic environment is established through uniform hazard spectra derived for firm soil. Damage to structures is estimated considering site response and using fragility functions. Dynamic traffic modeling is developed to simulate damage-induced road closures and resulting in traffic variations. Post-earthquake network performance is evaluated through data envelopment analyses, obtaining sets of seismic performance boundaries, and seismic performance maps. The methodology offers a quantitative tool with applications in the planning of urban areas that are sustainable and seismic resilient.

Dynamic Traffic Assignment in Design and Evaluation of High-Occupancy Toll Lanes

2000 ◽  
Vol 1733 (1) ◽  
pp. 39-48 ◽  
Author(s):  
Ahmed F. Abdelghany ◽  
Khaled F. Abdelghany ◽  
Hani S. Mahmassani ◽  
Pamela M. Murray
Keyword(s):  
Network Performance ◽  
Traffic Assignment ◽  
Dynamic Traffic Assignment ◽  
Access Point ◽  
Operating Characteristics ◽  
Dynamic Traffic ◽  
Route Choice Behavior ◽  
South Central ◽  
Hot Lanes ◽  
High Occupancy Toll

Application of a dynamic traffic assignment-simulation methodology to the analysis and evaluation of network performance under various schemes for the design and operation of high-occupancy toll (HOT) lanes is described. The DYNASMART traffic simulation-assignment model, which combines the ability to simulate traffic flow and to represent dynamic route choice behavior, is used to model the problem. Different dimensions for the design and operation of HOT lanes are considered in this study, including ( a) lane utilization in terms of adding a new lane or using an existing lane of the facility as a HOT lane; ( b) physical separation of the HOT lane in terms of access point frequency; ( c) access restriction based on vehicle occupancy; ( d) HOT lane pricing structure, which may be fixed or congestion dependent; and ( e) different demand levels with different percentages of high-occupancy vehicles (HOV). A set of experiments was designed to compare the performance of the HOT lanes and the total network under these different operating characteristics. A network in Texas that represents the south central part of the Fort Worth area is used in these experiments. The results were analyzed under each of these different operating characteristics, yielding useful insights for the design and evaluation of HOT lanes.

scholarly journals Global Optimization for Transport Network Expansion and Signal Setting

2015 ◽  
Vol 2015 ◽  
pp. 1-18 ◽  
Author(s):  
Haoxiang Liu ◽  
David Z. W. Wang ◽  
Hao Yue
Keyword(s):  
Global Optimization ◽  
Network Design ◽  
Network Performance ◽  
Network Capacity ◽  
Capacity Allocation ◽  
Urban Transport ◽  
Transport Network ◽  
Mixed Integer ◽  
Planning Problem ◽  
Transport Planning

This paper proposes a model to address an urban transport planning problem involving combined network design and signal setting in a saturated network. Conventional transport planning models usually deal with the network design problem and signal setting problem separately. However, the fact that network capacity design and capacity allocation determined by network signal setting combine to govern the transport network performance requires the optimal transport planning to consider the two problems simultaneously. In this study, a combined network capacity expansion and signal setting model with consideration of vehicle queuing on approaching legs of intersection is developed to consider their mutual interactions so that best transport network performance can be guaranteed. We formulate the model as a bilevel program and design an approximated global optimization solution method based on mixed-integer linearization approach to solve the problem, which is inherently nnonlinear and nonconvex. Numerical experiments are conducted to demonstrate the model application and the efficiency of solution algorithm.

scholarly journals A Strategic Model for Dynamic Traffic Assignment

2004 ◽  
Vol 4 (3) ◽  
pp. 291-315 ◽  
Author(s):  
Younes Hamdouch ◽  
Patrice Marcotte ◽  
Sang Nguyen
Keyword(s):  
Traffic Assignment ◽  
Dynamic Traffic Assignment ◽  
Dynamic Traffic ◽  
Strategic Model
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