Integrated Special Event Traffic Management Strategies in Urban Transportation Network

How to effectively optimize and control spreading traffic in urban network during the special event has emerged as one of the critical issues faced by many transportation professionals in the past several decades due to the surging demand and the often limited network capacity. The contribution of this dissertation is to develop a set of integrated mathematical programming models for unconventional traffic management of special events in urban transportation network. Traffic management strategies such as lane reorganization and reversal, turning restriction, lane-based signal timing, ramp closure, and uninterrupted flow intersection will be coordinated and concurrently optimized for best overall system performance. Considering the complexity of the proposed formulations and the concerns of computing efficiency, this study has also developed efficient solution heuristics that can yield sufficiently reliable solutions for real-world application. Case studies and extensive numerical analyses results validate the effectiveness and applicability of the proposed models

Optimizing and Simulating Evacuation in Urban Areas

Diese Doktorarbeit beschäftigt sich mit der Evakuierungsplanung in städtischen Gebieten. Nach einem Literaturüberblick zu Beginn der Arbeit wird das Cell-Transmission model verwendet, um ein grundlegendes mathematisches Optimierungsmodell zur Evakuierungsplanung mit Fahrzeugen zu formulieren. Anschließend werden eine erweiterte Version dieses Optimierungsmodells sowie mehrere heuristische Lösungsverfahren zur Lösung der Optimierungsmodelle vorgestellt. Darüber hinaus werden Erweiterungen der Optimierungsmodelle zur Berücksichtigung von Rettungskräften und Fußgängern in der Evakuierungsplanung betrachtet.This doctoral thesis deals with evacuation planning in urban areas. After a literature review at the beginning of the thesis, the Cell-Transmission model is utilized to formulate a basic mathematical optimization problem for evacuation planning with vehicles. Afterwards, an extended version of this basic optimization problem as well as several heuristic solution procedures to solve the optimization models are presented. Moreover, enhancements of the optimization models in terms of integrating rescue teams as well as pedestrians in evacuation planning are considered

Evacuation Trees with Contraflow and Divergence Considerations

In this thesis, we investigate how to evacuate people using the available road transportation network efficiently. To successfully do that, we need to design evacuation model that is fast, safe, and seamless. We enable the first two criteria by developing a macroscopic, time-dynamic evacuation model that aims to maximize the number of people in relatively safer areas of the network at each time point; the third criterion is optimized by constructing an evacuation tree, where the vehicles are evacuated using a single path to safety. Divergence and contraflow policies have been incorporated to enhance the network capacity. Divergence enables specific nodes to diverge their flows into two or more streets, while contraflow allows certain streets to reverse their flow, effectively increasing their capacity. We investigate the performance of these policies in the evacuation networks obtained, and present results on two benchmark networks of Sioux Falls and Chicago

Network flow solution method for optimal evacuation traffic routing and signal control with nonuniform threat

An efficient two-stage network flow approach is proposed for the determination of optimal scenarios for integrated traffic routing and signal timing in the evacuation of real-sized urban networks with several threat zones, where the threat levels may be nonuniform across zones. The objective is to minimize total exposure to the threat (severity multiplied by duration) for all evacuees during the evacuation. In the problem formulation, traffic flow dynamics are based on the well-known point queue model in a time-expanded network representation. The proposed solution approach is adapted from a general relaxation-based decomposition method in a network flow formulation. The decomposition method is developed on the basis of insights into the optimal flow of traffic at intersections in the solution of the evacuation routing problem. As for efficiency, the computation time associated with the decomposition method for solving the integrated optimal routing and signal control problem is equivalent to the time required for solving the same optimal routing problem (without optimizing the intersection control plan) because the computation time required for determining the optimal signal control is negligible. The proposed solution method proves to be optimal. The method is implemented and applied to a real-sized evacuation scenario in the transportation network of Tucson, Arizona. The method is stress-tested with some inflated demand scenarios, and computation aspects are reported

LED wristbands for cell-based crowd evacuation: an adaptive exit-choice guidance system architecture

Cell-based crowd evacuation systems provide adaptive or static exit-choice indications that favor a coordinated group dynamic, improving evacuation time and safety. While a great effort has been made to modeling its control logic by assuming an ideal communication and positioning infrastructure, the architectural dimension and the influence of pedestrian positioning uncertainty have been largely overlooked. In our previous research, a cell-based crowd evacuation system (CellEVAC) was proposed that dynamically allocates exit gates to pedestrians in a cell-based pedestrian positioning infrastructure. This system provides optimal exit-choice indications through color-based indications and a control logic module built upon an optimized discrete-choice model. Here, we investigate how location-aware technologies and wearable devices can be used for a realistic deployment of CellEVAC. We consider a simulated real evacuation scenario (Madrid Arena) and propose a system architecture for CellEVAC that includes: a controller node, a radio-controlled light-emitting diode (LED) wristband subsystem, and a cell-node network equipped with active Radio Frequency Identification (RFID) devices. These subsystems coordinate to provide control, display, and positioning capabilities. We quantitatively study the sensitivity of evacuation time and safety to uncertainty in the positioning system. Results showed that CellEVAC was operational within a limited range of positioning uncertainty. Further analyses revealed that reprogramming the control logic module through a simulation optimization process, simulating the positioning system's expected uncertainty level, improved the CellEVAC performance in scenarios with poor positioning systems.Ministerio de Economía, Industria y Competitivida

Robust dynamic traffic assignment for single destination networks under demand and capacity uncertainty

In this article, we discuss the system-optimum dynamic traffic assignment (SO-DTA) problem in the presence of time-dependent uncertainties on both traffic demands and road link capacities. Building on an earlier formulation of the problem based on the cell transmission model, the SO-DTA problem is robustly solved, in a probabilistic sense, within the framework of random convex programs (RCPs). Different from traditional robust optimization schemes, which find a solution that is valid for all the values of the uncertain parameters, in the RCP approach we use a fixed number of random realizations of the uncertainty, and we are able to guarantee a priori a desired upper bound on the probability that a new, unseen realization of the uncertainty would make the computed solution unfeasible. The particular problem structure and the introduction of an effective domination criterion for discarding a large number of generated samples enables the computation of a robust solution for medium- to large-scale networks, with low desired violation probability, with a moderate computational effort. The proposed approach is quite general and applicable to any problem that can be formulated through a linear programing model, where the stochastic parameters appear in the constraint constant terms only. Simulation results corroborate the effectiveness of our approach

DEVELOPMENT OF A MIXED-FLOW OPTIMIZATION SYSTEM FOR EMERGENCY EVACUATION IN URBAN NETWORKS

In most metropolitan areas, an emergency evacuation may demand a potentially large number of evacuees to use transit systems or to walk over some distance to access their passenger cars. In the process of approaching designated pick-up points for evacuation, the massive number of pedestrians often incurs tremendous burden to vehicles in the roadway network. Hence, one critical issue in a multi-modal evacuation planning is the effective coordination of the vehicle and pedestrian flows by considering their complex interactions. The purpose of this research is to develop an integrated system that is capable of generating the optimal evacuation plan and reflecting the real-world network traffic conditions caused by the conflicts of these two types of flows. The first part of this research is an integer programming model designed to optimize the control plans for massive mixed pedestrian-vehicle flows within the evacuation zone. The proposed model, integrating the pedestrian and vehicle networks, can effectively account for their potential conflicts during the evacuation. The model can generate the optimal routing strategies to guide evacuees moving toward either their pick-up locations or parking areas and can also produce a responsive plan to accommodate the massive pedestrian movements. The second part of this research is a mixed-flow simulation tool that can capture the conflicts between pedestrians, between vehicles, and between pedestrians and vehicles in an evacuation network. The core logic of this simulation model is the Mixed-Cellular Automata (MCA) concept, which, with some embedded components, offers a realistic mechanism to reflect the competing and conflicting interactions between vehicle and pedestrian flows. This study is expected to yield the following contributions * Design of an effective framework for planning a multi-modal evacuation within metropolitan areas; * Development of an integrated mixed-flow optimization model that can overcome various modeling and computing difficulties in capturing the mixed-flow dynamics in urban network evacuation; * Construction and calibration of a new mixed-flow simulation model, based on the Cellular Automaton concept, to reflect various conflicting patterns between vehicle and pedestrian flows in an evacuation network

Disaster management in industrial areas: perspectives, challenges and future research

Purpose: In most countries, development, growth, and sustenance of industrial facilities are given utmost importance due to the influence in the socio-economic development of the country. Therefore, special economic zones, or industrial areas or industrial cities are developed in order to provide the required services for the sustained operation of such facilities. Such facilities not only provide a prolonged economic support to the country but it also helps in the societal aspects as well by providing livelihood to thousands of people. Therefore, any disaster in any of the facilities in the industrial area will have a significant impact on the population, facilities, the economy, and threatens the sustainability of the operations. This paper provides review of such literature that focus on theory and practice of disaster management in industrial cities. Design/methodology/approach: In the paper, content analysis method is used in order to elicit the insights of the literature available. The methodology uses search methods, literature segregation and developing the current knowledge on different phases of industrial disaster management. Findings: It is found that the research is done in all phases of disaster management, namely, preventive phase, reactive phase and corrective phase. The research in each of these areas are focused on four main aspects, which are facilities, resources, support systems and modeling. Nevertheless, the research in the industrial cities is insignificant. Moreover, the modeling part does not explicitly consider the nature of industrial cities, where many of the chemical and chemical processing can be highly flammable thus creating a very large disaster impact. Some research is focused at an individual plant and scaled up to the industrial cities. The modeling part is weak in terms of comprehensively analyzing and assisting disaster management in the industrial cities. Originality/value: The comprehensive review using content analysis on disaster management is presented here. The review helps the researchers to understand the gap in the literature in order to extend further research for disaster management in large scale industrial cities.Peer Reviewe