ORCID Profile
0000-0001-7643-409X
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UNSW Sydney
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Publisher: SAGE Publications
Date: 2012
DOI: 10.3141/2312-17
Abstract: The decision of whether and when to evacuate can be characterized as decision making under risk. Presently, most models assume linear utility functions through which it is impossible to disentangle factors that influence risk attitudes and other factors that affect decision making under risk. There is a need to disentangle and study factors that affect risk attitudes from factors that affect an evacuee's preparation time. The aim in doing so is to provide planners and practitioners with an ability to measure a person's risk attitude and develop appropriate strategies that could motivate people to evacuate. This study is expected to connect the theory of risk developed in economic theory with behavior under threat. The paper uses the Hurricane Andrew response data in conjunction with time-dependent data on the probability of a hurricane strike and the category of the hurricane data to develop a model for evacuation departure choice. A constant relative risk aversion specification is used to model risk attitudes. The process of an evacuation is abstracted as an in idual being given a choice between two lotteries: either to stay or leave. The results show that the model is able to predict the total number of evacuees and the time varying evacuation rates with reasonable accuracy. Factors such as time of day, length of time spent in a region, and whether a mandatory evacuation order was issued affected risk attitudes. The presence of children affected the amount of time spent preparing if the family decided to stay.
Publisher: Springer Science and Business Media LLC
Date: 13-01-2022
DOI: 10.1038/S41598-021-04639-0
Abstract: Drive cycles in vehicle systems are important determinants for energy consumption, emissions, and safety. Estimating the frequency of the drive cycle quickly is important for control applications related to fuel efficiency, emission reduction and improving safety. Quantum computing has established the computational efficiency that can be gained. A drive cycle frequency estimation algorithm based on the quantum Fourier transform is exponentially faster than the classical Fourier transform. The algorithm is applied on real world data set. We evaluate the method using a quantum computing simulator, demonstrating remarkable consistency with the results from the classical Fourier transform. Current quantum computers are noisy, a simple method is proposed to mitigate the impact of the noise. The method is evaluated on a 15 qubit IBM-q quantum computer. The proposed method for a noisy quantum computer is still faster than the classical Fourier transform.
Publisher: SAGE Publications
Date: 2011
DOI: 10.3141/2229-08
Abstract: The experiences of several recent evacuations have demonstrated how a mass evacuation of a major city can affect traffic throughout an entire region. This realization has brought the need for analyzing and evaluating evacuation plans at a regional level. Numerous recent studies have devoted themselves to the topic of simulating large-scale evacuations. However, few studies have developed procedures for the validation of large-scale models. This paper discusses validation within the context of the recent development of the regional multimodal evacuation model for New Orleans, Louisiana. The New Orleans model is unique because it is among the first ever to incorporate qualitative and quantitative model validation procedures based on field data collected during an actual mass evacuation. The paper discusses the various statistics considered for validation, including their inherent advantages and disadvantages. It also presents the results obtained from the validation exercises of the New Orleans model. The study concluded that regression analyses were the most appropriate for statistically analyzing the spatial and temporal data correlations between the traffic patterns produced within the simulation and those actually observed during the Hurricane Katrina evacuation. From a qualitative standpoint, colorized spatiotemporal maps were also found to be quite effective for visualizing traffic speed and volume patterns. The maps were also invaluable for quickly identifying and analyzing bottleneck areas at both the local and regional levels.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2015
Publisher: Elsevier BV
Date: 11-2007
Publisher: Elsevier BV
Date: 09-2011
DOI: 10.1016/J.AAP.2011.01.006
Abstract: The two-fluid model for vehicular traffic flow explains the traffic on arterials as a mix of stopped and running vehicles. It describes the relationship between the vehicles' running speed and the fraction of running vehicles. The two parameters of the model essentially represent 'free flow' travel time and level of interaction among vehicles, and may be used to evaluate urban roadway networks and urban corridors with partially limited access. These parameters are influenced by not only the roadway characteristics but also by behavioral aspects of driver population, e.g., aggressiveness. Two-fluid models are estimated for eight arterial corridors in Orlando, FL for this study. The parameters of the two-fluid model were used to evaluate corridor level operations and the correlations of these parameters' with rates of crashes having different types/severity. Significant correlations were found between two-fluid parameters and rear-end and angle crash rates. Rate of severe crashes was also found to be significantly correlated with the model parameter signifying inter-vehicle interactions. While there is need for further analysis, the findings suggest that the two-fluid model parameters may have potential as surrogate measures for traffic safety on urban arterial streets.
Publisher: Springer Science and Business Media LLC
Date: 24-11-2008
DOI: 10.1038/ONC.2008.341
Publisher: Elsevier BV
Date: 09-2016
DOI: 10.1016/J.AAP.2016.05.027
Abstract: This study employs game theory to investigate behavioural norms of interaction between drivers at a signalised intersection. The choice framework incorporates drivers' risk perception as well as their risk attitudes. A laboratory experiment is conducted to study the impact of risk attitudes and perception in crossing behaviour at a signalised intersection. The laboratory experiment uses methods from experimental economics to induce incentives and study revealed behaviour. Conflicting drivers are considered to have symmetric disincentives for crashing, to represent a no-fault car insurance environment. The study is novel as it uses experimental data collection methods to investigate perceived risk. Further, it directly integrates perceived risk of crashing with other active drivers into the modelling structure. A theoretical model of intersection crossing behaviour is also developed in this paper. This study shows that right-of-way entitlements assigned without authoritative penalties to at-fault drivers may still improve perceptions of safety. Further, risk aversion amongst drivers attributes to manoeuvring strategies at or below Nash mixed strategy equilibrium. These findings offer a theoretical explanation for interactive manoeuvres that lead to crashes, as opposed to purely statistical methods which provide correlation but not necessarily explanation.
Publisher: Elsevier BV
Date: 09-2018
Publisher: Elsevier BV
Date: 03-2022
Publisher: Elsevier BV
Date: 10-2022
Publisher: Elsevier BV
Date: 10-2014
Publisher: Elsevier BV
Date: 11-2016
Publisher: IEEE
Date: 10-2014
Publisher: Elsevier BV
Date: 11-2014
Publisher: Elsevier BV
Date: 09-2017
Publisher: Elsevier BV
Date: 2002
Publisher: Oxford University Press (OUP)
Date: 09-2004
DOI: 10.1534/GENETICS.104.026617
Abstract: Cyclin E together with its kinase partner Cdk2 is a critical regulator of entry into S phase. To identify novel genes that regulate the G1- to S-phase transition within a whole animal we made use of a hypomorphic cyclin E mutation, DmcycEJP, which results in a rough eye phenotype. We screened the X and third chromosome deficiencies, tested candidate genes, and carried out a genetic screen of 55,000 EMS or X-ray-mutagenized flies for second or third chromosome mutations that dominantly modified the DmcycEJP rough eye phenotype. We have focused on the DmcycEJP suppressors, S(DmcycEJP), to identify novel negative regulators of S-phase entry. There are 18 suppressor gene groups with more than one allele and several genes that are represented by only a single allele. All S(DmcycEJP) tested suppress the DmcycEJP rough eye phenotype by increasing the number of S phases in the postmorphogenetic furrow S-phase band. By testing candidates we have identified several modifier genes from the mutagenic screen as well as from the deficiency screen. DmcycEJP suppressor genes fall into the classes of: (1) chromatin remodeling or transcription factors (2) signaling pathways and (3) cytoskeletal, (4) cell adhesion, and (5) cytoarchitectural tumor suppressors. The cytoarchitectural tumor suppressors include scribble, lethal-2-giant-larvae (lgl), and discs-large (dlg), loss of function of which leads to neoplastic tumors and disruption of apical-basal cell polarity. We further explored the genetic interactions of scribble with S(DmcycEJP) genes and show that hypomorphic scribble mutants exhibit genetic interactions with lgl, scab (αPS3-integrin—cell adhesion), phyllopod (signaling), dEB1 (microtubule-binding protein—cytoskeletal), and moira (chromatin remodeling). These interactions of the cytoarchitectural suppressor gene, scribble, with cell adhesion, signaling, cytoskeletal, and chromatin remodeling genes, suggest that these genes may act in a common pathway to negatively regulate cyclin E or S-phase entry.
Publisher: The Company of Biologists
Date: 15-04-2008
DOI: 10.1242/DEV.016295
Abstract: The endocycle is a commonly observed variant cell cycle in which cells undergo repeated rounds of DNA replication with no intervening mitosis. How the cell cycle machinery is modified to transform a mitotic cycle into endocycle has long been a matter of interest. In both plants and animals, the transition from the mitotic cycle to the endocycle requires Fzr/Cdh1, a positive regulator of the Anaphase-Promoting Complex/Cyclosome (APC/C). However, because many of its targets are transcriptionally downregulated upon entry into the endocycle, it remains unclear whether the APC/C functions beyond the mitotic/endocycle boundary. Here, we report that APC/CFzr/Cdh1 activity is required to promote the G/S oscillation of the Drosophila endocycle. We demonstrate that compromising APC/C activity, after cells have entered the endocycle, inhibits DNA replication and results in the accumulation of multiple APC/C targets, including the mitotic cyclins and Geminin. Notably, our data suggest that the activity of APC/CFzr/Cdh1 during the endocycle is not continuous but is cyclic,as demonstrated by the APC/C-dependent oscillation of the pre-replication complex component Orc1. Taken together, our data suggest a model in which the cyclic activity of APC/CFzr/Cdh1 during the Drosophilaendocycle is driven by the periodic inhibition of Fzr/Cdh1 by Cyclin E/Cdk2. We propose that, as is observed in mitotic cycles, during endocycles,APC/CFzr/Cdh1 functions to reduce the levels of the mitotic cyclins and Geminin in order to facilitate the relicensing of DNA replication origins and cell cycle progression.
Publisher: Springer Science and Business Media LLC
Date: 23-11-2021
DOI: 10.1038/S41597-021-01083-7
Abstract: Autonomous Vehicles (AVs) are being widely tested on public roads in several countries such as the USA, Canada, France, Germany, and Australia. For the transparent deployment of AVs in California, the California Department of Motor Vehicles (CA DMV) commissioned AV manufacturers to draft and publish reports on disengagements and crashes. These reports must be processed before any statistical analysis, which is cumbersome and time-consuming. Our dataset presents the processed disengagement data from 2014 to 2019, crash data till the 10 th of March 2020 and supplementary road network and land-use data extracted from OpenStreetMap. Primary data are manually assessed and converted into an easily processed format. Our processed data will be advantageous to the research community and enable accelerated research in this domain. For ex le, the data can be utilised to discern trends in disengagement, observe the distribution of disengagement causes, and investigate the contributory factors of the crashes. Such investigations can subsequently improve the reporting protocols and make policies and laws for the smooth deployment of this disruptive technology.
Publisher: Wiley
Date: 06-09-2018
DOI: 10.1111/MICE.12292
Publisher: MDPI AG
Date: 07-11-2021
Abstract: COVID-19 has had tremendous effects worldwide, resulting in large-scale death and upheaval. An abundance of studies have shown that traffic patterns have changed worldwide as working from home has become dominant, with many facilities, restaurants and retail services being closed due to the lockdown orders. With regards to road safety, there have been several studies on the reduction in fatalities and crash frequencies and increase in crash severity during the lockdown period. However, no scientific evidence has been reported on the impact of COVID-19 lockdowns on traffic incident duration, a key metric for crash management. It is also unclear from the existing literature whether the impacts on traffic incidents are consistent across multiple lockdowns. This paper analyses the impact of two different COVID-19 lockdowns in Sydney, Australia, on traffic incident duration and frequency. During the first (31 March–28 April 2020) and second (26 June–31 August 2021) lockdowns, the number of incidents fell by 50% and 60%, respectively, in comparison to the same periods in 2018 and 2019. The proportion of incidents involving towing increased significantly during both lockdowns. The mean duration of crashes increased by 16% during the first lockdown, but the change was less significant during the subsequent lockdown. Crashes involving ersions, emergency services and towing saw an increase in the mean duration by 67%, 16%, and 47%, respectively, during the first lockdown. However, this was not reflected in the 2021 data, with only major crashes seeing a significant increase, i.e., by 58%. There was also a noticeable shift in the location of incidents, with more incidents recorded in suburban areas, away from the central business area. Our findings suggest drastic changes in incident characteristics, and these changes should be considered by policymakers in promoting a safer and more sustainable transportation network in the future.
Publisher: IEEE
Date: 09-2019
Publisher: Elsevier BV
Date: 10-1999
Publisher: IEEE
Date: 10-2014
Publisher: Wiley
Date: 02-10-2017
DOI: 10.1111/MICE.12278
Publisher: Springer Science and Business Media LLC
Date: 15-01-2022
Publisher: Informa UK Limited
Date: 2021
Publisher: SAGE Publications
Date: 2017
DOI: 10.3141/2616-06
Abstract: Speed and flow of vehicles tend to have several effects on the dynamics of a transport system. Fluctuations of these variables can implicate congestion, can lower predictability, and may even catalyze crashes. A concept of fractal theory called the Hurst exponent—a measure of the long-range dependence (LRD) of a time series—was used to understand the fluctuations in flow and speed of a motorway in Sydney, Australia. The spatial and temporal variation of the LRD for flow ( H flow ) and speed ( H speed ) at several monitor sites is discussed. Furthermore, the effects of number of lanes on flow and speed predictability are explored. It was observed that the flow predictability of two-lane sections was significantly lower when compared with three-lane and four-lane sections. Conversely, the speed predictability of four-lane sections was considerably higher than that of two-lane and three-lane sections. Finally, traffic congestion was defined with regard to the LRD of speed, and its correlation with historical incident rates was measured. It was ascertained that monitor sites with a historically high proportion of large H speed were correlated with unsafe locations. This study could lead to many applications of fractal analysis on highways and urban traffic.
Publisher: SAGE Publications
Date: 2014
DOI: 10.3141/2467-02
Publisher: Elsevier BV
Date: 2021
DOI: 10.2139/SSRN.3977598
Publisher: Elsevier BV
Date: 10-2015
Publisher: Informa UK Limited
Date: 15-06-2010
Publisher: Portland Press Ltd.
Date: 28-08-2012
DOI: 10.1042/BSE0530141
Abstract: The Scribble, Par and Crumbs modules were originally identified in the vinegar (fruit) fly, Drosophila melanogaster, as being critical regulators of apico–basal cell polarity. In the present chapter we focus on the Scribble polarity module, composed of Scribble, discs large and lethal giant larvae. Since the discovery of the role of the Scribble polarity module in apico–basal cell polarity, these proteins have also been recognized as having important roles in other forms of polarity, as well as regulation of the actin cytoskeleton, cell signalling and vesicular trafficking. In addition to these physiological roles, an important role for polarity proteins in cancer progression has also been uncovered, with loss of polarity and tissue architecture being strongly correlated with metastatic disease.
Publisher: Rockefeller University Press
Date: 21-02-2000
Abstract: Bcl-2 family of proteins are key regulators of apoptosis. Both proapoptotic and antiapoptotic members of this family are found in mammalian cells, but no such proteins have been described in insects. Here, we report the identification and characterization of Debcl, the first Bcl-2 homologue in Drosophila melanogaster. Structurally, Debcl is similar to Bax-like proapoptotic Bcl-2 family members. Ectopic expression of Debcl in cultured cells and in transgenic flies causes apoptosis, which is inhibited by coexpression of the baculovirus caspase inhibitor P35, indicating that Debcl is a proapoptotic protein that functions in a caspase-dependent manner. debcl expression correlates with developmental cell death in specific Drosophila tissues. We also show that debcl genetically interacts with diap1 and dark, and that debcl-mediated apoptosis is not affected by gene dosage of rpr, hid, and grim. Biochemically, Debcl can interact with several mammalian and viral prosurvival Bcl-2 family members, but not with the proapoptotic members, suggesting that it may regulate apoptosis by antagonizing prosurvival Bcl-2 proteins. RNA interference studies indicate that Debcl is required for developmental apoptosis in Drosophila embryos. These results suggest that the main components of the mammalian apoptosis machinery are conserved in insects.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 02-2015
Publisher: Elsevier BV
Date: 09-2017
Publisher: Elsevier BV
Date: 08-2021
Publisher: American Society of Civil Engineers (ASCE)
Date: 08-2013
Publisher: SAGE Publications
Date: 07-07-2020
Abstract: Driving in congested traffic is a nuisance that not only results in longer travel times, but also triggers frustration and impatience among drivers. A few studies have modeled the effects of congested traffic in the resulting route choice behavior of car drivers. The studies used frequentist models such as discrete choice models to analyze large s les. However, these studies did not compare the inferences obtained from the frequentist and Bayesian approaches, particularly for datasets which are not sufficiently large. It has been shown by researchers that Bayesian models perform well, especially when the s le size is small. Thus, this paper develops and compares a multinomial logit (frequentist) and a Naïve Bayes (Bayesian) model on a mid-sized dataset of size around 100 participants which was obtained from a driving simulator experiment to understand driver’s route choice under stop-and-go traffic. The results show that the prediction power of the Naïve Bayes model is much higher than the multinomial logit model (MNL). The Naïve Bayes model is also found to perform better than machine learning algorithms like the decision tree model. The findings from this study will be useful to researchers and practitioners as they should test both the approaches and select the appropriate model, particularly in the case of seemingly large datasets.
Publisher: Springer Science and Business Media LLC
Date: 07-04-2010
Abstract: Neoplastic overgrowth depends on the cooperation of several mutations ultimately leading to major rearrangements in cellular behaviour. Precancerous cells are often removed by cell death from normal tissues in the early steps of the tumourigenic process, but the molecules responsible for such a fundamental safeguard process remain in part elusive. With the aim to investigate the molecular crosstalk occurring between precancerous and normal cells in vivo , we took advantage of the clonal analysis methods that are available in Drosophila for studying the phenotypes due to lethal giant larvae ( lgl ) neoplastic mutation induced in different backgrounds and tissues. We observed that lgl mutant cells growing in wild-type imaginal wing discs show poor viability and are eliminated by Jun N-terminal Kinase (JNK)-dependent cell death. Furthermore, they express very low levels of dMyc oncoprotein compared with those found in the surrounding normal tissue. Evidence that this is a cause of lgl mutant cells elimination was obtained by increasing dMyc levels in lgl mutant clones: their overgrowth potential was indeed re-established, with mutant cells overwhelming the neighbouring tissue and forming tumourous masses displaying several cancer hallmarks. Moreover, when lgl mutant clones were induced in backgrounds of slow- iding cells, they upregulated dMyc, lost apical-basal cell polarity and were able to overgrow. Those phenotypes were abolished by reducing dMyc levels in the mutant clones, thereby confirming its key role in lgl -induced tumourigenesis. Furthermore, we show that the eiger -dependent Intrinsic Tumour Suppressor pathway plays only a minor role in eliminating lgl mutant cells in the wing pouch lgl -/- clonal death in this region is instead driven mainly by dMyc-induced Cell Competition. Our results provide the first evidence that dMyc oncoprotein is required in lgl tumour suppressor mutant tissue to promote invasive overgrowth in larval and adult epithelial tissues. Moreover, we show that dMyc abundance inside versus outside the mutant clones plays a key role in driving neoplastic overgrowth.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 08-2015
Publisher: SAGE Publications
Date: 2013
DOI: 10.3141/2390-09
Abstract: Recent advances in urban traffic network modeling have led to the proposal of several large-scale control strategies aimed at improving network efficiency, including metering vehicle entry, pricing network use, and allocating limited street space between multiple modes. However, these strategies typically require accurate real-time predictions of networkwide traffic conditions to be implemented, and it is often taken for granted that this information is available. In practice, this is not a trivial issue, because measuring traffic conditions across a large urban network in real time is not straightforward. For that purpose, this paper presents a method of indirectly estimating average vehicle densities across a network in real time by combining travel speed information from a few circulating probe vehicles with the macroscopic fundamental diagram (MFD) of urban traffic. The proposed method is advantageous because it requires relatively little data and involves few calculations. Tests of this methodology on a simulated network showed that the results were not accurate when the network was uncongested, but reliable density estimates could be obtained when the network was congested or approaching congestion, even if only a small fraction of vehicles served as probes. This result is promising because congested states are the most critical. Therefore, this methodology seems useful as a traffic-monitoring scheme to complement networkwide control strategies, provided that the network exhibits a well-defined and reproducible MFD.
Publisher: Elsevier BV
Date: 04-2017
DOI: 10.1016/J.AAP.2017.01.023
Abstract: This paper describes a project that was undertaken using naturalistic driving data collected via Global Positioning System (GPS) devices to demonstrate a proof-of-concept for proactive safety assessments of crash-prone locations. The main hypothesis for the study is that the segments where drivers have to apply hard braking (higher jerks) more frequently might be the "unsafe" segments with more crashes over a long-term. The linear referencing methodology in ArcMap was used to link the GPS data with roadway characteristic data of US Highway 101 northbound (NB) and southbound (SB) in San Luis Obispo, California. The process used to merge GPS data with quarter-mile freeway segments for traditional crash frequency analysis is also discussed in the paper. A negative binomial regression analyses showed that proportion of high magnitude jerks while decelerating on freeway segments (from the driving data) was significantly related with the long-term crash frequency of those segments. A random parameter negative binomial model with uniformly distributed parameter for ADT and a fixed parameter for jerk provided a statistically significant estimate for quarter-mile segments. The results also indicated that roadway curvature and the presence of auxiliary lane are not significantly related with crash frequency for the highway segments under consideration. The results from this exploration are promising since the data used to derive the explanatory variable(s) can be collected using most off-the-shelf GPS devices, including many smartphones.
Publisher: Elsevier BV
Date: 04-2020
Publisher: Elsevier BV
Date: 2015
Publisher: Elsevier BV
Date: 02-2022
Publisher: Public Library of Science (PLoS)
Date: 07-04-2020
Publisher: American Society of Civil Engineers (ASCE)
Date: 08-2012
Publisher: Elsevier BV
Date: 09-2016
Publisher: Springer Science and Business Media LLC
Date: 05-07-2017
Publisher: SAGE Publications
Date: 2017
DOI: 10.3141/2667-09
Abstract: Dynamic transportation models route vehicles by using the principles of dynamic user equilibrium. These models include a dynamic network loading (DNL) module that is used to evaluate link costs. However, an element of stochasticity creeps into the modeling framework when the analytical dynamic assignment (DA) procedure is used along with a stochastic microscopic DNL. A methodologically correct way of approaching this problem is by solving the entire DA with a microscopic DNL (DA-microDNL) model until convergence for a given random seed and then repeating the process with different seed values. This paper proposes an approach to determine the minimum number of replications of the DA-microDNL model to determine a statistically valid estimate of the measure of effectiveness (MOE). The approach was tested on a small and medium-size network having different demand and network characteristics. Results show that running the integrated DA-microDNL framework for a minimum number of replications provides a statistically significant MOE at much lower computation time. The consistent estimates obtained by using this approach would provide robust information to transportation planners and practitioners in evaluating the impacts of several policy decisions on network performance.
Publisher: MDPI AG
Date: 16-07-2021
DOI: 10.3390/SU13147938
Abstract: Autonomous vehicles (AVs) are being extensively tested on public roads in several states in the USA, such as California, Florida, Nevada, and Texas. AV utilization is expected to increase into the future, given rapid advancement and development in sensing and navigation technologies. This will eventually lead to a decline in human driving. AVs are generally believed to mitigate crash frequency, although the repercussion of AVs on crash severity is ambiguous. For the data-driven and transparent deployment of AVs in California, the California Department of Motor Vehicles (CA DMV) commissioned AV manufacturers to draft and publish reports on disengagements and crashes. This study performed a comprehensive assessment of CA DMV data from 2014 to 2019 from a safety standpoint, and some trends were discerned. The results show that decrement in automated disengagements does not necessarily imply an improvement in AV technology. Contributing factors to the crash severity of an AV are not clearly defined. To further understand crash severity in AVs, the features and issues with data are identified and discussed using different machine learning techniques. The CA DMV accident report data were utilized to develop a variety of crash AV severity models focusing on the injury for all crash typologies. Performance metrics were discussed, and the bagging classifier model exhibited the best performance among different candidate models. Additionally, the study identified potential issues with the CA DMV data reporting protocol, which is imperative to share with the research community. Recommendations are provided to enhance the existing reports and append new domains.
Publisher: Informa UK Limited
Date: 19-06-2019
Publisher: CRC Press
Date: 22-08-2013
DOI: 10.1201/B15372-14
Publisher: Informa UK Limited
Date: 15-08-2010
Publisher: Elsevier BV
Date: 12-2000
Publisher: Institute for Operations Research and the Management Sciences (INFORMS)
Date: 09-2019
Abstract: We address the network maintenance scheduling problem, which consists of finding the optimal schedule for the coordination of road maintenance projects in a transport network over a planning period. Road works and maintenance operations that require partial or total road closures over a period of time may considerably impact network performance and result in significant delays. In addition, the effects of conducting multiple maintenance projects simultaneously may be nonadditive, hence increasing the difficulty to anticipate congestion effects. In this paper, we propose a new bilevel mixed integer programming formulation for the network maintenance scheduling problem, which relies on the enumeration of maintenance project combinations—patterns—to incorporate congestion effects within the scheduling process. We present a new branch-and-price algorithm that relies on customized branching and bounding rules, and a tailored column generation framework to price patterns. In addition, a statistical regression model is introduced to approximate congestion effects and provide approximate lower bounds on the formulations therein. The proposed branch-and-price algorithm is implemented on instances derived from realistic transport networks and is shown to be able to solve the network maintenance scheduling problem in a reasonable time using only a fraction of the patterns.
Publisher: Elsevier BV
Date: 2019
Publisher: MDPI AG
Date: 07-10-2020
DOI: 10.3390/SU12198244
Abstract: Traffic incidents such as crashes, vehicle breakdowns, and hazards impact traffic speeds and induce congestion. Recognizing the factors that influence the frequency of these traffic incidents is helpful in proposing countermeasures. There have been several studies on evaluating crash frequencies. However, research on other incident types is sparse. The main objective of this research is to identify critical variables that affect the number of reported vehicle breakdowns. A traffic incident dataset covering 4.5 years (January 2012 to June 2016) in the Australian state of New South Wales (NSW) was arranged in a panel data format, consisting of monthly reported vehicle breakdowns in 28 SA4s (Statistical Area Level 4) in NSW. The impact of different independent variables on the number of breakdowns reported in each month–SA4 observation is captured using a random-effect negative binomial regression model. The results indicate that increases in population density, the number of registered vehicles, the number of public holidays, average temperature, the percentage of heavy vehicles, and percentage of white-collared jobs in an area increase the number of breakdowns. On the other hand, an increase in the percentage of unrestricted driving licenses and families with children, number of school holidays, and average rainfall decrease the breakdown frequency. The insights offered in this study contribute to a complete picture of the relevant factors that can be used by transport authorities, vehicle manufacturers, sellers, roadside assistance companies, and mechanics to better manage the impact of vehicle breakdowns.
Publisher: SAGE Publications
Date: 2016
DOI: 10.3141/2548-10
Abstract: This paper addresses a special case of periodic vehicle routing problem in which each node has a nonnegative supply or demand of a single product that is unpaired. The product collected from a pickup node can be delivered to any one node or multiple delivery nodes, and the demand of a delivery node can be met by the product collected from any one node or multiple pickup nodes. This periodic unpaired pickup and delivery vehicle-routing problem is a novel variant of the periodic vehicle routing problem. The objective of the problem was to design the pickup and delivery vehicle routes to meet required service levels of delivery nodes, minimizing the total transportation cost while satisfying certain operational constraints. This problem was driven by food relief operations in Sydney, Australia. The logistics aspect of the approach was to design and execute a vehicle routing problem for a food rescue and delivery network. The specific goals were to develop an integrated linear programming model for this new variant of the periodic vehicle routing problem and to propose an integer programming–based heuristic solution approach to solve the problem introduced in the paper. The heuristic algorithm was tested with small instances created from Cordeau's benchmark instances, and the solution approach was validated against optimal solutions obtained through the exact method before implementation on a food rescue and delivery network. The heuristic approach was found to be comparable with the optimal solution and can solve the real-world scenarios with significantly fewer resources than are used in practice.
Publisher: Weston Medical Publishing
Date: 03-2015
Abstract: Manual traffic control is an intersection control strategy in which law enforcement officers allocate intersection right-of-way to turning movements. Many emergency traffic management plans call for manual traffic control in response to oversaturated roadway conditions. This is because it is thought to more effectively move traffic during temporary surges in demand. The goal of this research was to evaluate the current state-of the- practice used by the Army Corps of Engineers (ACE) in selecting intersections for manual traffic control and allocating police personnel to them during emergencies.This research uses the emergency traffic management plans developed by the ACE for nine counties in the Maryland Eastern Shore region. This area encompassing 14,318 intersections of which 74 were selected for manual traffic control during emergencies. This work sought to quantify the correlations that exist between intersection attributes and the ACE' decision to allocate officers to control them. The research findings suggest that US routes, State routes, and emergency evacuation routes are statistically significant in determining the need for police control at intersections. Also significant are intersection on contraflow corridors and intersections near grade separated interchanges. The model also determined that intersections isolated from evacuation routes and county exits were more likely to be selected for manual control, indicating that rural areas may rely on manual traffic control in the absence of multilane highway and freeways. This research also found that intersections involving evacuation routes, contraflow corridors, and grade separated interchanges may warrant additional police personnel (two or more officers) for manual traffic control.
Publisher: The Company of Biologists
Date: 09-2010
DOI: 10.1242/DEV.049585
Abstract: An unresolved question regarding the RNA-recognition motif (RRM) protein Half pint (Hfp) has been whether its tumour suppressor behaviour occurs by a transcriptional mechanism or via effects on splicing. The data presented here demonstrate that Hfp achieves cell cycle inhibition via an essential role in the repression of Drosophila myc (dmyc) transcription. We demonstrate that regulation of dmyc requires interaction between the transcriptional repressor Hfp and the DNA helicase subunit of TFIIH, Haywire (Hay). In vivo studies show that Hfp binds to the dmyc promoter and that repression of dmyc transcription requires Hfp. In addition, loss of Hfp results in enhanced cell growth, which depends on the presence of dMyc. This is consistent with Hfp being essential for inhibition of dmyc transcription and cell growth. Further support for Hfp controlling dmyc transcriptionally comes from the demonstration that Hfp physically and genetically interacts with the XPB helicase component of the TFIIH transcription factor complex, Hay, which is required for normal levels of dmyc expression, cell growth and cell cycle progression. Together, these data demonstrate that Hfp is crucial for repression of dmyc, suggesting that a transcriptional, rather than splicing, mechanism underlies the regulation of dMyc and the tumour suppressor behaviour of Hfp.
Publisher: Elsevier BV
Date: 09-2008
Publisher: American Society of Civil Engineers (ASCE)
Date: 08-2013
Publisher: Elsevier BV
Date: 10-2019
DOI: 10.1016/J.AAP.2019.06.001
Abstract: The transportation network can provide additional utility by addressing the safety concerns on roads. On-road fatalities are an unfortunate loss of life and lead to significant costs for society and the economy. Connected and Autonomous Vehicles (CAVs), envisaged as operating with idealised safety and cooperation, could be a means of mitigating these costs. This paper intends to provide insights into the safety improvements to be attained by incrementally transitioning the fleet to CAVs. This investigation is done by constructing a calibrated microsimulation environment in Vissim and deploying the custom developed Virdi CAV Control Protocol (VCCP) algorithm for CAV behaviour. The CAV behaviour is implemented using an application programming interface and a dynamic linking library. CAVs are introduced to the environment in 10% increments, and safety performance is assessed using the Surrogate Safety Assessment Module (SSAM). The results of this study show that CAVs at low penetrations result in an increase in conflicts at signalised intersections but a decrease at priority-controlled intersections. The initial 20% penetration of CAVs is accompanied by a +22%, -87%, -62% and +33% change in conflicts at the signalised, priority, roundabout and DDI intersection respectively. CAVs at high penetrations indicate a global reduction in conflicts. A 90% CAV penetration is accompanied by a -48%, -100%, -98% and -81% change in conflicts at the signalised, priority, roundabout and DDI intersection respectively.
Publisher: Elsevier BV
Date: 08-2019
DOI: 10.1016/J.AAP.2019.04.017
Abstract: A current issue within the driver distraction community centres around different findings regarding the impact of mobile phone conversation on driving found in driving simulators versus instrumented vehicles employed in real-world naturalistic driving studies (NDSs). This paper compares and contrasts the two types of studies and aims to provide reasons for the differences in findings that have been documented. A comprehensive review of literature and consultations with human factors experts highlighted that simulator studies tend to show degradation in driving performance, suggestive of increased crash risk as a result of mobile phone conversation. Whilst NDSs, at times, present data suggesting that mobile phone conversation distraction actually reduces crash risk. This study identifies that these differences may be attributed to behavioural hypotheses associated with driver self-regulation, arousal from cognitive loading, task displacement and gaze concentration - all of which need to be explicitly tested in future driving studies. Metric estimation and application was also revealed to be polarising results and the subsequent assessment of the crash risk. A common metric applied in this domain is the 'Odds Ratio', particularly prevalent in NDSs. This study presents a detailed investigation into the assumptions and application of the Odds Ratio which revealed the potential for over- and under-estimation of the metric depending on the core data and s ling assumptions. Furthermore, this research presents a comparative analysis of select driving simulator studies and an NDS considering only driving behaviour data as a means to consistently compare the findings of both methodologies. The findings from this investigation implores the need for greater consistency in the application of analysis methods and metrics across both simulator and NDSs. Improvements can yield a more robust platform to systematically compare and interpret data across both approaches, ultimately leading to enhanced planning and safety regarding mobile phone use while driving.
Publisher: MDPI AG
Date: 19-06-2018
Publisher: Elsevier BV
Date: 04-2017
Publisher: Public Library of Science (PLoS)
Date: 13-09-2017
Publisher: Elsevier BV
Date: 02-2017
Publisher: Elsevier BV
Date: 06-2015
Publisher: Elsevier BV
Date: 2021
Publisher: Springer Science and Business Media LLC
Date: 29-06-2022
DOI: 10.1007/S11116-022-10276-X
Abstract: In the transport policy development process, four-step models are commonly used to estimate transport costs and flows based on representations of travel demands and networks. However, these models typically do not account for broader changes in the economy, which may significantly shift travel patterns in the case of larger transport projects. LUTI models are often applied to simulate changes in land-use patterns, and regional production function models have been used to estimate changes in production, but these methods rely on fixed economic parameters that may not capture the structural economic changes induced by large transport projects. In a separate line of development, computable general equilibrium (CGE) models, which simulate entire economies, have been increasingly applied to estimate the magnitude and distribution of economic impacts from transport improvements both spatially and through markets, including GDP and welfare. Some CGE models are linked with transport network models, but none incorporate detailed networks or generate a complete set of travel demands. This paper presents an integrated CGE and transport model that generates household and freight trips and simulates a detailed road network for different time periods, such that the transport submodel can be calibrated and run as a conventional transport model. The model provides a tool for the rapid strategic assessment of transport projects and policies when economic responses cannot be assumed to remain static. In the model, the CGE submodel simulates the behaviour of households and firms interacting in markets, where their behaviour takes trip costs into account. The model then generates trips as a derived demand from agent activities and assigns them to the road network according to user equilibrium, before feeding back trip costs to the CGE submodel. The model is then tested by simulating the WestConnex motorway project under construction in Sydney, with results showing significant increases in welfare for regions close to the improvements. Further development of the model is required to incorporate land-use and mode choice.
Publisher: Elsevier BV
Date: 11-2019
Publisher: Informa UK Limited
Date: 03-04-2014
Publisher: IEEE
Date: 06-2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2021
Publisher: Cold Spring Harbor Laboratory
Date: 15-10-2001
DOI: 10.1101/GAD.916201
Abstract: We have identified a Drosophila homolog of the DNA replication initiation inhibitor Geminin ( Dm geminin ) and show that it has all of the properties of Xenopus and human Geminin. During Drosophila development, Dm Geminin is present in cycling cells protein accumulates during S phase and is degraded at the metaphase to anaphase transition. Overexpression of Dm geminin in embryos inhibits DNA replication, but cells enter mitosis arresting in metaphase, as in dup ( cdt1 ) mutants, and undergo apoptosis. Overexpression of Dm Geminin also induces ectopic neural differentiation. Dm geminin mutant embryos exhibit anaphase defects at cycle 16 and increased numbers of S phase cells later in embryogenesis. In a partially female-sterile Dm geminin mutant, excessive DNA lification in the ovarian follicle cells is observed. Our data suggest roles for Dm Geminin in limiting DNA replication, in anaphase and in neural differentiation.
Publisher: Cold Spring Harbor Laboratory
Date: 11-1992
Abstract: We have cloned four cyclin-B homologs from Saccharomyces cerevisiae, CLB1-CLB4, using the polymerase chain reaction and low stringency hybridization approaches. These genes form two classes based on sequence relatedness: CLB1 and CLB2 show highest homology to the Schizosaccharomyces pombe cyclin-B homolog cdc13 involved in the initiation of mitosis, whereas CLB3 and CLB4 are more highly related to the S. pombe cyclin-B homolog cig1, which appears to play a role in G1 or S phase. CLB1 and CLB2 mRNA levels peak late in the cell cycle, whereas CLB3 and CLB4 are expressed earlier in the cell cycle but peak later than the G1-specific cyclin, CLN1. Analysis of null mutations suggested that the CLB genes exhibit some degree of redundancy, but clb1,2 and clb2,3 cells were inviable. Using clb1,2,3,4 cells rescued by conditional overproduction of CLB1, we showed that the CLB genes perform an essential role at the G2/M-phase transition, and also a role in S phase. CLB genes also appear to share a role in the assembly and maintenance of the mitotic spindle. Taken together, these analyses suggest that CLB1 and CLB2 are crucial for mitotic induction, whereas CLB3 and CLB4 might participate additionally in DNA replication and spindle assembly.
Publisher: Elsevier BV
Date: 2021
Publisher: Informa UK Limited
Date: 31-03-2009
Publisher: Springer Science and Business Media LLC
Date: 15-05-2019
Publisher: American Society of Civil Engineers (ASCE)
Date: 08-2012
Publisher: Informa UK Limited
Date: 17-08-2015
Publisher: Elsevier BV
Date: 08-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2023
Publisher: Inderscience Publishers
Date: 2012
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 08-2022
Publisher: Elsevier BV
Date: 2020
Publisher: MDPI AG
Date: 08-05-2022
Abstract: Road traffic crashes cause social, economic, physical and emotional losses. They also reduce operating speed and road capacity and increase delays, unreliability, and productivity losses. Previous crash duration research has concentrated on in idual crashes, with the contributing elements extracted directly from the incident description and records. As a result, the explanatory variables were more regional, and the effects of broader macro-level factors were not investigated. This is in contrast to crash frequency studies, which normally collect explanatory factors at a macro-level. This study explores the impact of various factors and the consistency of their effects on vehicle crash duration and frequency at a macro-level. Along with the demographic, vehicle utilisation, environmental, and responder variables, street network features such as connectedness, density, and hierarchy were added as covariates. The dataset contains over 95,000 vehicle crash records over 4.5 years in Greater Sydney, Australia. Following a dimension reduction of independent variables, a hazard-based model was estimated for crash duration, and a Negative Binomial model was estimated for frequency. Unobserved heterogeneity was accounted for by latent class models for both duration and frequency. Income, driver experience and exposure are considered to have both positive and negative impacts on duration. Crash duration is shorter in regions with a dense road network, but crash frequency is higher. Highly connected networks, on the other hand, are associated with longer length but lower frequency.
Publisher: Springer Science and Business Media LLC
Date: 18-05-2013
Publisher: Elsevier BV
Date: 2014
DOI: 10.1016/J.AAP.2013.08.023
Abstract: We examine the subjective risks of driving behavior using a controlled virtual reality experiment. Use of a driving simulator allows us to observe choices over risky alternatives that are presented to the in idual in a naturalistic manner, with many of the cues one would find in the field. However, the use of a simulator allows us the type of controls one expects from a laboratory environment. The subject was tasked with making a left-hand turn into incoming traffic, and the experimenter controlled the headways of oncoming traffic. Subjects were rewarded for making a successful turn, and lost income if they crashed. The experimental design provided opportunities for subjects to develop subjective beliefs about when it would be safe to turn, and it also elicited their attitudes towards risk. A simple structural model explains behavior, and showed evidence of heterogeneity in both the subjective beliefs that subjects formed and their risk attitudes. We find that subjective beliefs change with experience in the task and the driver's skill. A significant difference was observed in the perceived probability to successfully turn among the inexperienced drivers who did and did not crash even though there was no significant difference in drivers' risk attitudes among the two groups. We use experimental economics to design controlled, incentive compatible tasks that provide an opportunity to evaluate the impact on driver safety of subject's subjective beliefs about when it would be safe to turn as well as their attitudes towards risk. This method could be used to help insurance companies determine risk premia associated with risk attitudes or beliefs of crashing, to better incentivize safe driving.
Publisher: SAGE Publications
Date: 2017
DOI: 10.3141/2606-07
Abstract: In the search for benefits to justify transport projects, economic appraisals have increasingly incorporated the valuation of impacts to the wider economy. Computable general equilibrium (CGE) models provide a framework to estimate these impacts by simulating the interactions of urban economies and transport networks. In CGE models, households and firms are represented by microeconomic behavioral functions, and markets adjust according to prices. As markets both inside and outside the transport network are taken into account, a wide variety of measures that can assist in economic appraisals can be extracted. However, urban CGE models are computationally burdensome and require detailed, spatially disaggregate data. This paper discusses the methodology used to develop a database, including an input–output table, for the calibration of an urban CGE model for Sydney, Australia. Official and publicly available data sources were manipulated by using a number of mathematical and statistical techniques to compile a table for 249 regions and 20 sectors across Sydney. Issues, such as determining the appropriate level of aggregation, generating incomplete data, and managing conflicting data, that other input–output table developers may encounter when constructing multiregional tables were addressed in the study. The table entries themselves were mapped and explored, as they provide a useful study of the spatial economy of Sydney. Future work will focus on streamlining the construction of input–output tables and incorporating new data sources.
Publisher: Elsevier BV
Date: 12-2021
Publisher: Springer Science and Business Media LLC
Date: 20-07-2005
DOI: 10.1038/NRC1671
Abstract: The development of human cancer is a multistep process, involving the cooperation of mutations in signalling, cell-cycle and cell-death pathways, as well as interactions between the tumour and the tumour microenvironment. To dissect the steps of tumorigenesis, simple animal models are needed. This article discusses the use of the genetically amenable, multicellular organism, the vinegar fly Drosophila melanogaster. In particular, recent studies have highlighted the power of D. melanogaster for examining cooperative interactions between tumour suppressors and oncogenes and for generating in vivo models of tumour development and metastasis.
Publisher: Elsevier BV
Date: 03-2018
DOI: 10.1016/J.AAP.2017.12.023
Abstract: The repercussions from congestion and accidents on major highways can have significant negative impacts on the economy and environment. It is a primary objective of transport authorities to minimize the likelihood of these phenomena taking place, to improve safety and overall network performance. In this study, we use the Hurst Exponent metric from Fractal Theory, as a congestion indicator for crash-rate modeling. We analyze one month of traffic speed data at several monitor sites along the M4 motorway in Sydney, Australia and assess congestion patterns with the Hurst Exponent of speed (H
Publisher: Public Library of Science (PLoS)
Date: 07-08-2018
Publisher: Public Library of Science (PLoS)
Date: 20-12-2016
Publisher: Elsevier BV
Date: 10-2019
Publisher: Wiley
Date: 07-2002
DOI: 10.1093/EMBOJ/CDF334
Publisher: Informa UK Limited
Date: 18-09-2017
Publisher: Elsevier BV
Date: 02-2011
Publisher: Elsevier BV
Date: 2019
Publisher: The Company of Biologists
Date: 15-01-2012
DOI: 10.1242/DEV.073288
Abstract: The recent Company of Biologists workshop ‘Growth, Division and Differentiation: Understanding Developmental Control’, which was held in September 2011 at Wiston House, West Sussex, UK, brought together researchers aiming to understand cell proliferation and differentiation in various metazoans, ranging from flies to mice. Here, we review the common themes that emerged from the meeting, highlighting novel insights into the interplay between regulators of cell proliferation and differentiation during development.
Publisher: Elsevier BV
Date: 04-2019
DOI: 10.1016/J.AAP.2019.02.005
Abstract: Autonomous Vehicles have captured the imagination of our society and have promised a future of safe and efficient mobility. However, there is a need to understand behaviour and its consequences in the use of autonomous vehicles. Using paradigms of behavioural and experimental economics, we show that risk attitudes play a role in acceptability of autonomous vehicles, productivity in autonomous vehicles and safety under risk of failures of autonomous systems. We found that risk attitudes and age have a significant impact on these. We believe these findings will help provide guidance to insurance agencies, licensing, vehicle design, and policies around automated vehicles.
Publisher: Elsevier BV
Date: 11-2019
Publisher: Elsevier BV
Date: 2001
Publisher: Elsevier BV
Date: 04-2019
DOI: 10.1016/J.AAP.2019.02.007
Abstract: The study employs a Quantal Response Equilibrium framework to model lane changing manoeuvres. Prior game theoretic studies in lane changing have pre-eminently assumed Nash equilibrium solutions with deterministic payoffs for actions. The study method involves developing expected utility models for drivers' merge and give-way decisions. These utility models incorporate explanatory variables representing driver trajectories during a lane changing manoeuvre. The model parameters are estimated using maximum likelihood on lane changing data at a freeway on-r using the NGSIM dataset. Based on the estimated parameters it was concluded that longer acceleration lanes and reduction of speed limits on on-r s could help significantly reduce likelihood of conflict. To demonstrate the robustness of the model, predictions of lane changing on an out-of-s le data were found to be reasonably accurate.
Publisher: American Society of Civil Engineers
Date: 20-06-2016
Publisher: Elsevier BV
Date: 02-2016
Publisher: SAGE Publications
Date: 2010
DOI: 10.3141/2196-17
Abstract: Effective communication of transportation-related information to vulnerable populations is a critical need during emergencies. Despite its importance, various factors still hinder the development of comprehensive and effective plans for communicating emergency information to mobility-limited in iduals during evacuations and other major emergencies. Such limiting factors include the wide ersity of vulnerable populations, their special needs, existing contact and communication barriers, and lack of resources and mechanisms to locate those populations and assist them during emergencies. This paper illustrates the complexity of communicating with vulnerable populations in emergency evacuations through a critical review of the existing literature and state-of-the-practice information gathered recently from transportation and emergency management agency personnel. First, the paper reviews definitions, characteristics, and size of the vulnerable population. Next, principles of effective communication and the special provisions for communicating with vulnerable populations are presented, along with ex les of effective communications and communications barriers. Finally, the paper identifies numerous important emergency evacuation communications topics that were not discussed in the literature and offers recommendations for bridging those gaps. Ex les include the limited involvement of experts in emergency evacuation communication, the lack of information about the financial aspects and cost-effectiveness of such communications, the need to establish an information clearinghouse to assist in future evacuations, and the lack of standardization and cataloging of appropriate evacuation messages. The paper is presented as a foundation for developing a framework for effective communications strategies, policies, and practices that focus on vulnerable populations before, during, and after all-hazards emergencies.
Publisher: SAGE Publications
Date: 2016
DOI: 10.3141/2567-01
Abstract: One-way carsharing, providing users with more flexibility on returning stations, has attracted larger market demand than has the traditional round-trip service. However, the main challenge faced by a one-way carsharing system is the vehicle stock imbalance due to the uneven distribution of user demand. This study attempted to address this problem by proposing an optimization model that integrated with a discrete choice model. The model accounts for the interdependent relationship between carshare demand and supply. User demand is influenced by the availability of carshare vehicles meanwhile, conversely, the demand further changes vehicle availability as well as vehicle stock distribution. The model determines the optimal relocation decisions to maximize the profit for carshare operators that offer both one-way and round-trip services. This model was applied to the network of a carshare operator in Australia to evaluate the impacts of different pricing and capacity policies on the system profit. The results indicate that the one-way trip price has a more significant impact on system profit than does vehicle pod capacity. Further, the maximum profit occurs when the price of a one-way trip is around four times higher than that of the round trip.
Publisher: Elsevier BV
Date: 12-2021
Publisher: Informa UK Limited
Date: 17-07-2019
Publisher: Elsevier BV
Date: 08-2010
Publisher: Elsevier BV
Date: 12-2004
Publisher: IEEE
Date: 11-2016
Publisher: Elsevier BV
Date: 10-2013
Publisher: Springer Science and Business Media LLC
Date: 07-04-2020
DOI: 10.1038/S41467-020-15353-2
Abstract: The spread of traffic jams in urban networks has long been viewed as a complex spatio-temporal phenomenon that often requires computationally intensive microscopic models for analysis purposes. In this study, we present a framework to describe the dynamics of congestion propagation and dissipation of traffic in cities using a simple contagion process, inspired by those used to model infectious disease spread in a population. We introduce two macroscopic characteristics for network traffic dynamics, namely congestion propagation rate β and congestion dissipation rate μ . We describe the dynamics of congestion spread using these new parameters embedded within a system of ordinary differential equations, similar to the well-known susceptible-infected-recovered (SIR) model. The proposed contagion-based dynamics are verified through an empirical multi-city analysis, and can be used to monitor, predict and control the fraction of congested links in the network over time.
Publisher: Elsevier BV
Date: 07-2020
Publisher: SAGE Publications
Date: 2008
DOI: 10.3141/2041-10
Abstract: Better use of the available road network is critical to improving the evacuation operation during a disaster. Contraflow operations help increase the capacity of the available network by reversing the direction of inbound lanes to outbound lanes. This helps improve the outflow from a region threatened by disaster. One of the major issues associated with contraflow operations is determining the locations for access to the contraflow lanes from the normal-flow lanes. These accesses are also referred to as crossovers. Four different strategies with different crossover locations were tested on the I-4 evacuation route from T a to Orlando, Florida. It was found that the provision of two crossovers, one after T a and another after Plant City, performed the best but was only marginally better than the provision of one crossover after T a. Therefore, considering the cost and personnel needed to provide a crossover, the provision of one crossover after T a was found to be a more logical choice than the provision of two crossovers. It was observed that the time required to run the microscopic simulation to arrive at the results was extremely long. To overcome this drawback, the cell transmission model (CTM) was calibrated and run for the same four strategies. It was observed that the results were extremely close to the results from the microscopic simulation. The robustness and speed of CTM make it ideal for use as part of a decision support system to help determine the best strategies in real time. This will help emergency management officials make real-time decisions in the event of unforeseen drops in capacities because of incidents or vehicle breakdowns.
Publisher: Institution of Engineering and Technology (IET)
Date: 30-07-2018
Publisher: Springer Science and Business Media LLC
Date: 20-05-2021
Publisher: Oxford University Press (OUP)
Date: 05-2011
DOI: 10.1534/GENETICS.111.127910
Abstract: We have shown previously that mutations in the apico-basal cell polarity regulators cooperate with oncogenic Ras (RasACT) to promote tumorigenesis in Drosophila melanogaster and mammalian cells. To identify novel genes that cooperate with RasACT in tumorigenesis, we carried out a genome-wide screen for genes that when overexpressed throughout the developing Drosophila eye enhance RasACT-driven hyperplasia. RasACT-cooperating genes identified were Rac1 Rho1, RhoGEF2, pbl, rib, and east, which encode cell morphology regulators. In a clonal setting, which reveals genes conferring a competitive advantage over wild-type cells, only Rac1, an activated allele of Rho1 (Rho1ACT), RhoGEF2, and pbl cooperated with RasACT, resulting in reduced differentiation and large invasive tumors. Expression of RhoGEF2 or Rac1 with RasACT upregulated Jun kinase (JNK) activity, and JNK upregulation was essential for cooperation. However, in the whole-tissue system, upregulation of JNK alone was not sufficient for cooperation with RasACT, while in the clonal setting, JNK upregulation was sufficient for RasACT-mediated tumorigenesis. JNK upregulation was also sufficient to confer invasive growth of RasV12-expressing mammalian MCF10A breast epithelial cells. Consistent with this, HER2+ human breast cancers (where human epidermal growth factor 2 is overexpressed and Ras signaling upregulated) show a significant correlation with a signature representing JNK pathway activation. Moreover, our genetic analysis in Drosophila revealed that Rho1 and Rac are important for the cooperation of RhoGEF2 or Pbl overexpression and of mutants in polarity regulators, Dlg and aPKC, with RasACT in the whole-tissue context. Collectively our analysis reveals the importance of the RhoGEF/Rho-family/JNK pathway in cooperative tumorigenesis with RasACT.
Publisher: Elsevier BV
Date: 10-2018
Publisher: Wiley-VCH Verlag GmbH & Co. KGaA
Date: 15-09-2006
Publisher: SAGE Publications
Date: 2010
DOI: 10.3141/2143-06
Abstract: Transit is an integral part of a sustainable transportation system in any region. Proposals for transit initiatives that are brought to referenda include a funding vehicle, either tax based or bond based. A tax-funded proposal imposes the cost on the present generation of residents, whereas a bond-funded proposal delays the burden to future generations. The aim is to investigate whether the success of proposals in referenda is related to the use of taxes or bonds for funding. This question is investigated with the use of data from 111 transit referenda held in the United States from 1999 to 2007. It was found that proposals that use taxes for funding are less likely to pass than those that use bonds.
Publisher: Elsevier BV
Date: 04-2022
Publisher: Springer Science and Business Media LLC
Date: 29-09-2011
Abstract: Epithelial neoplasias are associated with alterations in cell polarity and excessive cell proliferation, yet how these neoplastic properties are related to one another is still poorly understood. The study of Drosophila genes that function as neoplastic tumor suppressors by regulating both of these properties has significant potential to clarify this relationship. Here we show in Drosophila that loss of Scribbled (Scrib), a cell polarity regulator and neoplastic tumor suppressor, results in impaired Hippo pathway signaling in the epithelial tissues of both the eye and wing imaginal disc. scrib mutant tissue overgrowth, but not the loss of cell polarity, is dependent upon defective Hippo signaling and can be rescued by knockdown of either the TEAD/TEF family transcription factor Scalloped or the transcriptional coactivator Yorkie in the eye disc, or reducing levels of Yorkie in the wing disc. Furthermore, loss of Scrib sensitizes tissue to transformation by oncogenic Ras-Raf signaling, and Yorkie-Scalloped activity is required to promote this cooperative tumor overgrowth. The inhibition of Hippo signaling in scrib mutant eye disc clones is not dependent upon JNK activity, but can be significantly rescued by reducing aPKC kinase activity, and ectopic aPKC activity is sufficient to impair Hippo signaling in the eye disc, even when JNK signaling is blocked. In contrast, warts mutant overgrowth does not require aPKC activity. Moreover, reducing endogenous levels of aPKC or increasing Scrib or Lethal giant larvae levels does not promote increased Hippo signaling, suggesting that aPKC activity is not normally rate limiting for Hippo pathway activity. Epistasis experiments suggest that Hippo pathway inhibition in scrib mutants occurs, at least in part, downstream or in parallel to both the Expanded and Fat arms of Hippo pathway regulation. Loss of Scrib promotes Yorkie/Scalloped-dependent epithelial tissue overgrowth, and this is also important for driving cooperative tumor overgrowth with oncogenic Ras-Raf signaling. Whether this is also the case in human cancers now warrants investigation since the cell polarity function of Scrib and its capacity to restrain oncogene-mediated transformation, as well as the tissue growth control function of the Hippo pathway, are conserved in mammals.
Publisher: Elsevier BV
Date: 11-2022
Publisher: Hindawi Limited
Date: 11-03-2012
DOI: 10.5402/2012/507269
Abstract: Traffic safety and mobility of roadway work zones have been considered to be one of the major concerns in highway traffic safety and operations in Florida. Dynamic lane merging (DLM) systems—ITS-based lane management technology—were introduced by several states in an attempt to enhance both safety and mobility of roadway work zones. Two forms of lane merging, namely, the early merge and the late merge were designed to advise drivers on definite merging locations. Up to date, there are no studies that contrast both merging schemes under matching work zone settings. This study simulates a two-to-one work zone lane closure configuration under three different Maintenance of Traffic (MOT) plans in VISSIM. The first MOT is the conventional plans used in Florida’s work zones, the second MOT is a simplified dynamic early merging system (early SDLMS), and the third MOT is a simplified dynamic late merging systems (late SDLMSs). Field data was collected to calibrate and validate the simulation models. Simulation results indicated that overall, under different levels of drivers’ compliance rate and different percentages of trucks in the traffic composition, the early SLDMS outperformed the conventional MOT and the late SDLMS in terms of travel times and throughputs.
Publisher: Hindawi Limited
Date: 2017
DOI: 10.1155/2017/3268371
Publisher: SAGE Publications
Date: 2008
DOI: 10.3141/2041-06
Abstract: It is not uncommon for a region to be affected by multiple hurricanes in a span of a few weeks. The behavior of the evacuees during a subsequent hurricane in the same season is affected by the damage to the infrastructure and to the vehicles and assets belonging to evacuees, as well as by the psychological impact of the preceding hurricane. One such behavioral aspect that affects traffic-loading rates during a hurricane is the evacuation delay or mobilization time. In this study, “mobilization time for an evacuee” is defined as the difference between the time at which the decision to leave is made and the actual time of departure. This paper proposes a methodology that can be used to understand the factors associated with the mobilization time during a subsequent hurricane while accounting for the effects of the preceding hurricane. The effects of the preceding hurricane were accounted for by modeling mobilization times simultaneously with an ordinal variable representing evacuation participation levels during Hurricane Charley. The data from a survey conducted with the evacuees of Hurricane Frances, which made landfall 3 weeks after Hurricane Charley, were used in this study. The errors for the two simultaneously estimated models were significantly correlated. The results showed that home ownership, the number of in iduals in the household, income levels, and the level or the risk of a surge were significant in the model and explained the mobilization times for households. Pet ownership and the number of children in households, known to increase mobilization times during isolated hurricanes, were not found to be significant in the model. The implications of these findings for the demand S-curve are briefly discussed.
Publisher: Elsevier BV
Date: 09-2014
DOI: 10.1016/J.AAP.2014.03.005
Abstract: Carshare systems are considered a promising solution for sustainable development of cities. To promote carsharing it is imperative to make them cost effective, which includes reduction in costs associated to crashes and insurance. To achieve this goal, it is important to characterize carshare users involved in crashes and understand factors that can explain at-fault and not-at fault drivers. This study utilizes data from GoGet carshare users in Sydney, Australia. Based on this study it was found that carshare users who utilize cars less frequently, own one or more cars, have less number of accidents in the past ten years, have chosen a higher insurance excess and have had a license for a longer period of time are less likely to be involved in a crash. However, if a crash occurs, carshare users not needing a car on the weekend, driving less than 1000km in the last year, rarely using a car and having an Australian license increases the likelihood to be at-fault. Since the dataset contained information about all members as well as not-at-fault drivers, it provided a unique opportunity to explore some aspects of quasi-induced exposure. The results indicate systematic differences in the distribution between the not-at-fault drivers and the carshare members based on the kilometres driven last year, main mode of travel, car ownership status and how often the car is needed. Finally, based on this study it is recommended that creating an incentive structure based on training and experience (based on kilometres driven), possibly tagged to the insurance excess could improve safety, and reduce costs associated to crashes for carshare systems.
Publisher: Elsevier BV
Date: 03-2017
Publisher: Elsevier BV
Date: 12-2014
Publisher: Public Library of Science (PLoS)
Date: 16-04-2019
Publisher: Elsevier BV
Date: 09-2018
Publisher: SAGE Publications
Date: 2016
DOI: 10.3141/2581-13
Abstract: Urban roads in developing countries become congested more often because of the substantial lateral movement of vehicles and fluctuations in speed. Popular microscopic models such as car-following and lane-changing models are not suitable for the analysis of such traffic conditions unless some modifications accounting for heterogeneity are included. However, there seems to be an underlying mechanism behind the fluctuations that needs to be investigated thoroughly. The Hurst exponent concept of chaos theory was used to identify the hidden trends in vehicular movement. Real-life trajectory data from an urban arterial in Chennai, India, were analyzed and then compared with a homogeneous data set in the United States. The Hurst exponent for mixed traffic was found to be significantly less than that for the homogeneous data this finding indicated the strong trends of lateral movement and speed in homogeneous traffic. The variation of Hurst exponents with vehicle type and average lateral positions was explored in mixed traffic. Results from this study will help modelers propose better microscopic simulation models accounting for the fluctuations in speed and lateral movement.
Publisher: Elsevier BV
Date: 04-1994
Publisher: MDPI AG
Date: 10-10-2021
DOI: 10.3390/SU132011171
Abstract: A traffic assignment model is a critical tool for developing future transport systems, road policies, and evaluating future network upgrades. However, the development of the network and demand data is often highly intensive, which limits the number of cases where some form of the models are available on a global basis. These problems include licensing restrictions, bureaucracy, privacy, data availability, data quality, costs, transparency, and transferability. This paper introduces Rapidex, a novel origin–destination (OD) demand estimation and visualisation tool. Firstly, Rapidex enables the user to download and visualise road networks for any city using a capacity-based modification of OpenStreetMap. Secondly, the tool creates traffic analysis zones and centroids, as per the user-specified inputs. Next, it enables the fetching of travel time data from pervasive traffic data providers, such as TomTom and Google. With Rapidex, we tailor the genetic-algorithm (GA)-based metaheuristic approach to derive the OD demand pattern. The tool produces critical outputs such as link volumes, link travel times, OD travel times, average trip length and duration, and congestion level, which can also be used for validation. Finally, Rapidex enables the user to perform scenario evaluation, where changes to the network and/or demand data can be made and the subsequent impacts on performance metrics can be identified. In this article, we demonstrate the applicability of Rapidex on the network of Sydney, which has 15,646 directional links, 8708 nodes, and 178 zones. Further, the model was validated using the Household Travel Survey data of Sydney using the aggregated metrics and a novel project selection method. We observed that 88% of the time, the “estimated” and “observed” OD matrices identified the same project (i.e., the rapid process estimated the more intensive traditional approach in 88% of cases). This tool would help practitioners in rapid decision making for strategic long-term planning. Further, the tool would provide an opportunity for developing countries to better manage traffic congestion, as cities in these countries are prone to severe congestion and rapid urbanisation while often lacking the traditional models entirely.
Publisher: Elsevier BV
Date: 02-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2014
No related grants have been discovered for Vinayak Dixit.