Modeling the Effect of a Road Construction Project on Transportation System Performance

Road construction projects create physical changes on roads that result in capacity reduction and travel time escalation during the construction project period. The reduction in the posted speed limit, the number of lanes, lane width and shoulder width at the construction zone makes it difficult for the road to accommodate high traffic volume. Therefore, the goal of this research is to model the effect of a road construction project on travel time at road link-level and help improve the mobility of people and goods through dissemination or implementation of proactive solutions. Data for a resurfacing construction project on I-485 in the city of Charlotte, North Carolina (NC) was used evaluation, analysis, and modeling. A statistical t-test was conducted to examine the relationship between the change in travel time before and during the construction project period. Further, travel time models were developed for the freeway links and the connecting arterial street links, both before and during the construction project period. The road network characteristics of each link, such as the volume/ capacity (V/C), the number of lanes, the speed limit, the shoulder width, the lane width, whether the link is divided or undivided, characteristics of neighboring links, the time-of-the-day, the day-of-the-week, and the distance of the link from the road construction project were considered as predictor variables for modeling. The results obtained indicate that a decrease in travel time was observed during the construction project period on the freeway links when compared to the before construction project period. Contrarily, an increase in travel time was observed during the construction project period on the connecting arterial street links when compared to the before construction project period. Also, the average travel time, the planning time, and the travel time index can better explain the effect of a road construction project on transportation system performance when compared to the planning time index and the buffer time index. The influence of predictor variables seem to vary before and during the construction project period on the freeway links and connecting arterial street links. Practitioners should take the research findings into consideration, in addition to the construction zone characteristics, when planning a road construction project and developing temporary traffic control and detour plans

Using Non-Parametric Tests to Evaluate Traffic Forecasting Performance.

This paper proposes the use of a number of nonparametric comparison methods for evaluating traffic flow forecasting techniques. The advantage to these methods is that they are free of any distributional assumptions and can be legitimately used on small datasets. To demonstrate the applicability of these tests, a number of models for the forecasting of traffic flows are developed. The one-step-ahead forecasts produced are then assessed using nonparametric methods. Consideration is given as to whether a method is universally good or good at reproducing a particular aspect of the original series. That choice will be dictated, to a degree, by the user’s purpose for assessing traffic flow

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 xvi 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

Effects of Transit Signal Priority on Traffic Safety: Interrupted Time Series Analysis of Portland, Oregon, Implementations

Transit signal priority (TSP) has been implemented to transit systems in many cities of the United States. In evaluating TSP systems, more attention has been given to its operational effects than to its safety effects. Existing studies assessing safety effects of TSP reported mixed results, indicating that the safety effects of TSP vary in different contexts. In this study, TSP implementations in Portland, Oregon, were assessed using interrupted time series analysis (ITSA) on month-to-month changes in number of crashes from January 1995 to December 2010. Single-group and controlled ITSA were conducted for all crashes, property-damage-only crashes, fatal and injury crashes, pedestrian-involved crashes, and bike-involved crashes. Evaluation of the post-intervention period (2003 to 2010) showed a reduction in all crashes on street sections with TSP (-4.5 percent), comparing with the counterfactual estimations based on the control group data. The reduction in property-damage-only crashes (-10.0 percent) contributed the most to the overall reduction. Fatal and injury crashes leveled out after TSP implementation but did not change significantly comparing with the control group. Pedestrian and bike-involved crashes were found to increase in the post-intervention period with TSP, comparing with the control group. Potential reasons to these TSP effects on traffic safety were discussed.Comment: Published in Accident Analysis & Preventio

Analyzing Network Traffic for Malicious Hacker Activity

Since the Internet came into life in the 1970s, it has been growing more than 100% every year. On the other hand, the solutions to detecting network intrusion are far outpaced. The economic impact of malicious attacks in lost revenue to a single e-commerce company can vary from 66 thousand up to 53 million US dollars. At the same time, there is no effective mathematical model widely available to distinguish anomaly network behaviours such as port scanning, system exploring, virus and worm propagation from normal traffic. PDS proposed by Random Knowledge Inc., detects and localizes traffic patterns consistent with attacks hidden within large amounts of legitimate traffic. With the network’s packet traffic stream being its input, PDS relies on high fidelity models for normal traffic from which it can critically judge the legitimacy of any substream of packet traffic. Because of the reliability on an accurate baseline model for normal network traffic, in this workshop, we concentrate on modelling normal network traffic with a Poisson process

Time series classification based on fractal properties

The article considers classification task of fractal time series by the meta algorithms based on decision trees. Binomial multiplicative stochastic cascades are used as input time series. Comparative analysis of the classification approaches based on different features is carried out. The results indicate the advantage of the machine learning methods over the traditional estimating the degree of self-similarity.Comment: 4 pages, 2 figures, 3 equations, 1 tabl