79,994 research outputs found
Assessment of sustainability of improving road safety process in the volga federal district
The article examines the issues of assessing the sustainability of traffic safety improvement process in the cities of the Volga Federal District of the Russian Federation. In 2015...2018 a sharp decrease in the overall level of road traffic accidents in the Russian Federation was recorded. However, in different regions and cities of the country this positive process runs extremely heterogeneously, with various speeds and different levels of qualitative changes in the field of road safety. The T-Wilcoxon criterion is an instrument, used in analyzing accident rate statistics, which can help in the argumentation of the opinion on the stability of this process or, vice versa, on the chaotic state and weak expression. On the example of accident rate statistics in subjects of the Volga Federal District of Russia, the article proves that improvement of road safety can be characterized as sustainable. © Published under licence by IOP Publishing Ltd
Methodology for development of drought Severity-Duration-Frequency (SDF) Curves
Drought monitoring and early warning are essential elements impacting drought
sensitive sectors such as primary production, industrial and consumptive water users. A
quantitative estimate of the probability of occurrence and the anticipated severity of drought
is crucial for the development of mitigating strategies. The overall aim of this study is to
develop a methodology to assess drought frequency and severity and to advance the
understanding of monitoring and predicting droughts in the future. Seventy (70)
meteorological stations across Victoria, Australia were selected for analysis. To achieve the
above objective, the analysis was initially carried out to select the most applicable
meteorological drought index for Victoria. This is important because to date, no drought
indices are applied across Australia by any Commonwealth agency quantifying drought
impacts. An evaluation of existing meteorological drought indices namely, the Standardised
Precipitation Index (SPI), the Reconnaissance Drought Index (RDI) and Deciles was first
conducted to assess their suitability for the determination of drought conditions. The use of
the Standardised Precipitation Index (SPI) was shown to be satisfactory for assessing and
monitoring meteorological droughts in Australia. When applied to data, SPI was also
successful in detecting the onset and the end of historical droughts.
Temporal changes in historic rainfall variability and the trend of SPI were investigated
using non-parametric trend techniques to detect wet and dry periods across Victoria,
Australia. The first part of the analysis was carried out to determine annual rainfall trends
using Mann Kendall (MK) and Sen’s slope tests at five selected meteorological stations with
long historical records (more than 100 years), as well as a short sub-set period (1949-2011) of
the same data set. It was found that different trend results were obtained for the sub-set. For
SPI trend analysis, it was observed that, although different results were obtained showing
significant trends, SPI gave a trend direction similar to annual precipitation (downward and
upward trends). In addition, temporal trends in the rate of occurrence of drought events (i.e.
inter-arrival times) were examined. The fact that most of the stations showed negative slopes
indicated that the intervals between events were becoming shorter and the frequency of
events was temporally increasing. Based on the results obtained from the preliminary
analysis, the trend analyses were then carried out for the remaining 65 stations. The main
conclusions from these analyses are summarized as follows; 1) the trend analysis was
observed to be highly dependent on the start and end dates of analysis. It is recommended
that in the selection of time period for the drought, trend analysis should consider the length
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of available data sets. Longer data series would give more meaningful results, thus improving
the understanding of droughts impacted by climate change. 2) From the SPI and inter-arrival
drought trends, it was observed that some of the study areas in Victoria will face more
frequent dry period leading to increased drought occurrence. Information similar to this
would be very important to develop suitable strategies to mitigate the impacts of future
droughts.
The main objective of this study was the development of a methodology to assess
drought risk for each region based on a frequency analysis of the drought severity series
using the SPI index calculated over a 12-month duration. A novel concept centric on drought
severity-duration-frequency (SDF) curves was successfully derived for all the 70 stations
using an innovative threshold approach. The methodology derived using extreme value
analysis will assist in the characterization of droughts and provide useful information to
policy makers and agencies developing drought response plans. Using regionalisation
techniques such as Cluster analysis and modified Andrews curve, the study area was
separated into homogenous groups based on rainfall characteristics. In the current Victorian
application the study area was separated into six homogeneous clusters with unique
signatures. A set of mean SDF curves was developed for each cluster to identify the
frequency and severity of the risk of drought events for various return periods in each cluster.
The advantage of developing a mean SDF curve (as a signature) for each cluster is that it
assists the understanding of drought conditions for an ungauged or unknown station, the
characteristics of which fit existing cluster groups. Non-homogeneous Markov Chain
modelling was used to estimate the probability of different drought severity classes and
drought severity class predictions 1, 2 and 3 months ahead. The non-homogeneous
formulation, which considers the seasonality of precipitation, is useful for understanding the
evolution of drought events and for short-term planning. Overall, this model predicted
drought situations 1 month ahead well. However, predictions 2 and 3 months ahead should be
used with caution.
Many parts of Australia including Victoria have experienced their worst droughts on
record over the last decade. With the threat of climate change potentially further exacerbating
droughts in the years ahead, a clear understanding of the impact of droughts is vital. The
information on the probability of occurrence and the anticipated severity of drought will be
helpful for water resources managers, infrastructure planners and government policy-makers
with future infrastructure planning and with the design and building of more resilient
communities
Demo: Making Plans Scrutable with Argumentation and Natural Language Generation.
Peer reviewedPublisher PD
Assessing the Value of Time Travel Savings – A Feasibility Study on Humberside.
It is expected that the opening of the Humber Bridge
will cause major changes to travel patterns around Humberside;
given the level of tolls as currently stated, many travellers
will face decisions involving a trade-off between travel time,
money outlay on tolls or fares and money outlay on private
vehicle running costs; this either in the context of
destination choice, mode choice or route choice.
This report sets out the conclusions of a preliminary
study of the feasibility of inferring values of travel time
savings from observations made on the outcomes of these
decisions. Methods based on aggregate data of destination
choice are found t o be inefficient; a disaggregate mode
choice study i s recommended, subject to caveats on sample size
Congestion analysis of unsignalized intersections
This paper considers an unsignalized intersection used by two traffic
streams. A stream of cars is using a primary road, and has priority over the
other, low-priority, stream. Cars belonging to the latter stream cross the
primary road if the gaps between two subsequent cars on the primary road is
larger than their critical headways. Questions that naturally arise are: given
the arrival pattern of the cars on the primary road, what is the maximum
arrival rate of low-priority cars such that the number of such cars remains
stable? In the second place, what can be said about the delay experienced by a
typical car at the secondary road? This paper addresses such issues by
considering a compact model that sheds light on the dynamics of the considered
unsignalized intersection. The model, which is of a queueing-theoretic nature,
reveals interesting insights into the impact of the user behavior on the above
stability and delay issues. The contribution of this paper is twofold. First,
we obtain new results for the aforementioned model with driver impatience.
Secondly, we reveal some surprising aspects that have remained unobserved in
the existing literature so far, many of which are caused by the fact that the
capacity of the minor road cannot be expressed in terms of the \emph{mean} gap
size; instead more detailed characteristics of the critical headway
distribution play a role.Comment: This paper appeared in the proceedings of the 8th International
Conference on Communication Systems and Networks (COMSNETS), 5-10 Jan. 2016.
A related but more extended paper which analyses a more general model than
the one in the present paper can be also found on arXiv:1802.0673
A fully-discrete-state kinetic theory approach to modeling vehicular traffic
This paper presents a new mathematical model of vehicular traffic, based on
the methods of the generalized kinetic theory, in which the space of
microscopic states (position and velocity) of the vehicles is genuinely
discrete. While in the recent literature discrete-velocity kinetic models of
car traffic have already been successfully proposed, this is, to our knowledge,
the first attempt to account for all aspects of the physical granularity of car
flow within the formalism of the aforesaid mathematical theory. Thanks to a
rich but handy structure, the resulting model allows one to easily implement
and simulate various realistic scenarios giving rise to characteristic traffic
phenomena of practical interest (e.g., queue formation due to roadworks or to a
traffic light). Moreover, it is analytically tractable under quite general
assumptions, whereby fundamental properties of the solutions can be rigorously
proved.Comment: 22 pages, 3 figure
A method to assess demand growth vulnerability of travel times on road network links
Many national governments around the world have turned their recent focus to monitoring the actual reliability of their road networks. In parallel there have been major research efforts aimed at developing modelling approaches for predicting the potential vulnerability of such networks, and in forecasting the future impact of any mitigating actions. In practice-whether monitoring the past or planning for the future-a confounding factor may arise, namely the potential for systematic growth in demand over a period of years. As this growth occurs the networks will operate in a regime closer to capacity, in which they are more sensitive to any variation in flow or capacity. Such growth will be partially an explanation for trends observed in historic data, and it will have an impact in forecasting too, where we can interpret this as implying that the networks are vulnerable to demand growth. This fact is not reflected in current vulnerability methods which focus almost exclusively on vulnerability to loss in capacity. In the paper, a simple, moment-based method is developed to separate out this effect of demand growth on the distribution of travel times on a network link, the aim being to develop a simple, tractable, analytic method for medium-term planning applications. Thus the impact of demand growth on the mean, variance and skewness in travel times may be isolated. For given critical changes in these summary measures, we are thus able to identify what (location-specific) level of demand growth would cause these critical values to be exceeded, and this level is referred to as Demand Growth Reliability Vulnerability (DGRV). Computing the DGRV index for each link of a network also allows the planner to identify the most vulnerable locations, in terms of their ability to accommodate growth in demand. Numerical examples are used to illustrate the principles and computation of the DGRV measure
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