Algorithm to Compute Urban Road Network Resilience

2018 ◽  
Vol 2672 (48) ◽  
pp. 104-115 ◽  
Author(s):  
Bhattiyil Kuzhiyamkunnath Bhavathrathan ◽  
Gopal R. Patil
Keyword(s):  
Critical State ◽  
Road Network ◽  
Real Life ◽  
Identification Problem ◽  
Network Resilience ◽  
Problem Size ◽  
State Identification ◽  
Capacity Degradation ◽  
Planning Criterion ◽  
Capacity Disruptions

Road network resilience is emerging as a vital planning criterion. Yet, unique and cross-comparable indices for road network resilience are scarce. One of the recent approaches determines resilience as a unique network attribute based on the system travel time at an upper envelope of operable disruptions. This upper envelope represents ‘critical states’ (or tipping points) of capacity disruptions. Critical state gives a bounding capacity degradation vector, beyond which the network cannot wholly cater to the origin–destination demand even under the best possible traffic assignment. However, solving the critical state identification problem (CSP) on real-scale networks has remained a challenge. This paper presents a weighted fictitious play algorithm to fill this gap. CSP has been previously envisaged as a two-player game between a network attacker and a network defender. Here, we make the players play iteratively, and make them learn from the competitor’s past strategies so that they converge to an equilibrium. We illustrate the method on a simple toy network, and solve it on different real-life networks. Resilience of the Anaheim city network was computed in 42.8 min., considerably outperforming—both in problem-size and solution-time—the previous, two-space genetic algorithm.

EFFECT OF TRAFFIC DEMAND VARIATION ON ROAD NETWORK RESILIENCE

2016 ◽  
Vol 19 (01n02) ◽  
pp. 1650003 ◽  
Author(s):  
GOPAL R. PATIL ◽  
B. K. BHAVATHRATHAN
Keyword(s):  
Road Network ◽  
Optimization Problem ◽  
Network Size ◽  
Network Resilience ◽  
Traffic Demand ◽  
Capacity Degradation ◽  
Network Topologies ◽  
The Difference ◽  
Demand Variation ◽  
The Relationship

Certain capacity degradation levels increase travel times on road networks, while traffic demand remains met. Resilience of a road network is higher, if it can take-in higher levels of degradation without leaving any part of the demand unmet. It is important for planners to quantify this, and it can be obtained as the output of an optimization problem. The resultant measure of resilience is demand-specific. To generalize the resilience measure, its sensitivity to change in demand should be studied. We observe that irrespective of the difference in network size or network topology, resilience decreases with increase in demand. We perform computational experiments on different network topologies to investigate the relationship between network resilience and traffic demand. Based on this, we introduce the area under the demand-resilience curve as a generalized index of resilience (GIR). We compare the GIR with traditional network indicators and find that it is in certain ways, better.

scholarly journals Street Network Resilience Put to the Test: The Dramatic Crash of Genoa and Bologna Bridges

2020 ◽  
Vol 12 (11) ◽  
pp. 4706 ◽  
Author(s):  
Valerio Cutini ◽  
Camilla Pezzica
Keyword(s):  
Urban Form ◽  
Real Life ◽  
Design Decision ◽  
Network Resilience ◽  
Urban Resilience ◽  
Street Network ◽  
The Public ◽  
Planning And Design ◽  
Ex Post ◽  
Urban Futures

Various hazards and endemic threats are increasingly looming over cities, leading planners to rely on a rich toolbox of flexible and inclusive planning instruments and methods, capable of dealing with unpredicted events or sudden urban contingencies, when seeking sustainable urban futures. While sustainability-oriented innovative planning approaches are gaining momentum, ways to embed connected concepts in operational planning and design decision support systems have yet to be fully developed and validated. This paper tackles this issue by proposing and testing, in a real-life scenario, a method for the computational analysis of street network resilience, based on Space Syntax theory. The method is suitable to quantify the capacity of urban grids to absorb sudden disturbances and adapt to change, and to offer support for mitigation decisions and their communication to the public. It presents a set of configurational resilience indices, whose reliability is qualitatively assessed considering the ex-ante and ex-post urban configurations generated by two exceptional and dramatic bridge crashes. These events occurred almost simultaneously in two Italian cities with peculiarly similar characteristics. The results confirm the value of the proposal and highlight urban form, and particularly its grid, as a key driver in building urban resilience, together with the self-organisation capacity of local communities.

Modelling intra-dependencies to assess road network resilience to natural hazards

2020 ◽  
Vol 103 (1) ◽  
pp. 121-137
Author(s):  
Rita Der Sarkissian ◽  
Chadi Abdallah ◽  
Jean-Marc Zaninetti ◽  
Sara Najem
Keyword(s):  
Natural Hazards ◽  
Road Network ◽  
Network Resilience

Detecting sexual predators in chats using behavioral features and imbalanced learning

2017 ◽  
Vol 23 (4) ◽  
pp. 589-616 ◽  
Author(s):  
CLAUDIA CARDEI ◽  
TRAIAN REBEDEA
Keyword(s):  
Text Categorization ◽  
Real Life ◽  
Identification Problem ◽  
Online Discussions ◽  
Support Vector ◽  
Two Stage ◽  
Online Chat ◽  
Sexual Predator ◽  
Sexual Predators ◽  
Behavioral Features

AbstractThis paper presents a system developed for detecting sexual predators in online chat conversations using a two-stage classification and behavioral features. A sexual predator is defined as a person who tries to obtain sexual favors in a predatory manner, usually with underage people. The proposed approach uses several text categorization methods and empirical behavioral features developed especially for the task at hand. After investigating various approaches for solving the sexual predator identification problem, we have found that a two-stage classifier achieves the best results. In the first stage, we employ a Support Vector Machine classifier to distinguish conversations having suspicious content from safe online discussions. This is useful as most chat conversations in real life do not contain a sexual predator, therefore it can be viewed as a filtering phase that enables the actual detection of predators to be done only for suspicious chats that contain a sexual predator with a very high degree. In the second stage, we detect which of the users in a suspicious discussion is an actual predator using a Random Forest classifier. The system was tested on the corpus provided by the PAN 2012 workshop organizers and the results are encouraging because, as far as we know, our solution outperforms all previous approaches developed for solving this task.

scholarly journals Resilience-Based Optimization of Postdisaster Restoration Strategy for Road Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Xinhua Mao ◽  
Jibiao Zhou ◽  
Changwei Yuan ◽  
Dan Liu
Keyword(s):  
Travel Time ◽  
Road Network ◽  
Network Performance ◽  
Network Flows ◽  
Programming Model ◽  
Mixed Integer ◽  
Total System ◽  
Network Resilience ◽  
The Road ◽  
Restoration Strategies

This work proposes a framework for the optimization of postdisaster road network restoration strategies from a perspective of resilience. The network performance is evaluated by the total system travel time (TSTT). After the implementation of a postdisaster restoration schedule, the network flows in a certain period of days are on a disequilibrium state; thus, a link-based day-to-day traffic assignment model is employed to compute TSTT and simulate the traffic evolution. Two indicators are developed to assess the road network resilience, i.e., the resilience of performance loss and the resilience of recovery rapidity. The former is calculated based on TSTT, and the latter is computed according to the restoration makespan. Then, we formulate the restoration optimization problem as a resilience-based bi-objective mixed integer programming model aiming to maximize the network resilience. Due to the NP-hardness of the model, a genetic algorithm is developed to solve the model. Finally, a case study is conducted to demonstrate the effectiveness of the proposed method. The effects of key parameters including the number of work crews, travelers’ sensitivity to travel time, availability of budget, and decision makers’ preference on the values of the two objectives are investigated as well.

scholarly journals NUMERICAL ANALYSIS OF THE OBSERVABILITY OF THE CITY ROAD NETWORK EMISSION SOURCES USING THE SENSITIVITY OPERATOR OF THE ATMOSPHERIC CHEMISTRY TRANSPORT AND TRANSFORMATION MODEL

2021 ◽  
Vol 4 (1) ◽  
pp. 177-184
Author(s):  
Alexey V. Penenko ◽  
Alexander V. Gochakov
Keyword(s):  
Atmospheric Chemistry ◽  
Road Network ◽  
Identification Problem ◽  
Transformation Model ◽  
Emission Sources ◽  
Problem Solution ◽  
Accuracy Evaluation ◽  
Traffic Emission ◽  
The City ◽  
Sensitivity Operator

Within the scenario approach, the observability of traffic emission sources is estimated from indirect monitoring data. What is new is that an approach based on sensitivity operators is used to estimate observability, which allows us to obtain a family of quasilinear operator equations for the source identification problem. This allows both solving and analyzing its properties. For the city of Novosibirsk, realistic weather scenarios, a scenario for the distribution of traffic emission sources and the location of monitoring sites are considered. In numerical experiments, the road network is identified smoothed over space. Concentration fields are restored with greater accuracy. Evaluation of the information about the sources contained in the data based on the analysis of the sensitivity operator allows one to get an express estimate of the inverse problem solution.

Life-Assessment for Thin Flexible Batteries Under U-Flex-to-Install and Dynamic Folding

2021 ◽  
Author(s):  
Pradeep Lall ◽  
Ved Soni ◽  
Scott Miller
Keyword(s):  
Research And Development ◽  
Real Life ◽  
High Capacity ◽  
Rate Capability ◽  
Life Assessment ◽  
Wearable Electronics ◽  
Power Sources ◽  
Biomedical Equipment ◽  
Capacity Degradation ◽  
Dynamic Folding

Abstract The growing need for wearable devices, fitness accessories and biomedical equipment has led to the upsurge in research and development of thin flexible battery research and development. The current state of art wearable electronics products being developed in several fields require installation of power sources in different configurations and at times require the battery to undergo mechanical folding during product operation. This requires the product batteries to robustly withstand the imposed mechanical stresses during use along with the other desirable characteristics attributed to the power source such as high C-rate capability, high capacity and low capacity degradation rate. Works that explore the effects of static and dynamic folding on li-ion power sources is limited and oftentimes doesn’t adhere to definite test protocols resulting in non-standardized experimental data that can’t be applied to real-life product scenarios. Specifically, the effect of fold diameter on the battery state of health degradation when subjected to both static and dynamic folding is not yet completely explored. Present study aims to address this gap in the literature by investigating the effect of varying the fold diameter is both static (U-flex-to-install) and dynamic (dynamic U-fold) tests. Four different values of fold diameters have been chosen for experimentation and to study its effect during the aforementioned tests. Multiple samples have been tested for a given test condition so as to generate high fidelity data. Ultimately, a regression model developed previously has been augmented with the results generated in the current study.

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