Different Time Periods Of Day Research Articles

Impact of Side Friction on Travel Time Reliability of Urban Public Transit

Travel time reliability is the key aspect that indicates the quality of urban public transit service. The studies on travel time reliability of the public transit system in Indian traffic conditions are few. Also, the impact of side friction elements on travel time reliability has not been considered in the previous studies. Hence, the present study aims to quantify the different types of side friction elements and analyse their impact on the travel time reliability of the public bus transit system. The field data consisting of side friction elements, traffic volume, and travel time of public bus transit have been collected and extracted at two different road sections (divided and undivided) in the Mysore city (Karnataka, India) during weekdays and weekends. The data are grouped into static and dynamic side frictions. An approach has been proposed to represent different types of side friction elements with a single index called the Side Friction Index (SFI) using relative weight analysis. Travel time reliability is represented using measures such as Buffer Time Index (BTI), Planning Time Index (PTI), Travel Time Index (TTI) and Reliable Buffer Index (RBI). The impact of side friction on travel time reliability was found to be sensitive to traffic volume, and hence the thresholds for different traffic volume levels have been determined using K-means clustering method. It was observed from relative weight analysis that the static side friction has a higher weightage (0.509 and 0.327 for the undivided road and divided road respectively) than the dynamic side friction elements in describing the variation of travel time. The impact of side friction on reliability measures at different traffic volume levels has been studied and found to have a non-linear (exponential) relationship. The impact of SFI has been observed to be higher on TTI and PTI in comparison with BTI. The study outcomes show that the impact of side friction on TTI and PTI is sensitive to traffic volume, especially at higher traffic volume level and impact of side friction on BTI is less, especially at medium traffic volume level. The inference from the study shows that the impact of side friction elements varies with respect to the type of road (divided and undivided), traffic volume levels, different days of week (weekday and weekend), and different time periods of day.

Enforcement of Dynamic Sector Division for Massive MIMO Using Code Fed Antenna Arrays

A PAT code fed arrays are utilized to implement a dynamic sector division in a simple way to enforce following the sectors’ varying data traffic in modern multiple access environment. However, the previous solutions include hardware installations which are complex, expensive, and difficult to adjust for changing requirements throughout different time periods of day. This paper presents a novel idea to perform sector division using uniform PAT code-fed linear antenna arrays which simplified the implementation of such a dynamic system. These arrays are fed with fixed polyphase codes with optimum correlation properties. Only linear phase shifts of antenna elements in the array sub-groups of the different users are necessary to simply implement the needed division. The radiated pattern for each user’s data set is controlled by selecting the corresponding active sub-group of antenna elements to transmit through. The azimuth beamwidth can be adjusted by selecting a combination of different sub-groups. The simulation results proved that a dynamic sector division can be simply and efficiently implemented by using the proposed linear phase code fed arrays within the base station.

An analysis of Emergency Medical Services demand: Time of day, day of the week, and location in the city

ObjectiveEffective planning of Emergency Medical Services (EMS), which is highly dependent on the analysis of past data trends, is important in reducing response time. Thus, we aimed to analyze demand for these services based on time and location trends to inform planning for an effective EMS. Materials and methodsData for this retrospective study were obtained from the Izmir EMS 112 system. All calls reaching these services during first six months of 2013 were descriptively analyzed, based on time and location trends as a heat-map form. ResultsThe analyses showed that demand for EMS varied within different time periods of day, and according to day of the week. For the night period, demand was higher at the weekend compared to weekdays, whereas for daytime hours, demand was higher during the week. For weekdays, a statistically significant relation was observed between the call distribution of morning and evening periods. It was also observed that the percentage of demand changed according to location. Among 30 locations, the five most frequent destinations for ambulances, which are also correlated with high population densities, accounted for 55.66% of the total. ConclusionThe results of this study shed valuable light on the areas of call center planning and optimal ambulance locations of Izmir, which can also be served as an archetype for other cities.

Effects of Shock Waves on Freeway Crash Likelihood

This study examines how the formation and dissipation of a queue indicated by shock waves affect the likelihood of crash occurrence on freeways. Using one-minute average volume and density data collected from a section of the Gardiner Expressway in Toronto, changes in volume and density 3-10 minutes prior to the time of crash occurrence were observed. Types of shock wave and the shock wave speeds were estimated and related to the frequencies of the crashes where the shock wave existed before they occurred. It was found that typical shock wave types vary in different time periods of day due to different traffic conditions. The comparison with the volume-density data for the non-crash cases using logistic regression models shows that crashes are more likely to occur when the forward shock wave speed is lower. This indicates that slower vehicle progression in near-capacity conditions and slower dissipation of a queue in congested conditions are more likely to cause crashes. The results provide insights into better understanding of how shock waves affect the crash likelihood.

Examining Headway Distribution Models with Urban Freeway Loop Event Data

Vehicle headway distribution is fundamental for several important traffic research and simulation issues. Many headway models have been developed over the past decades. Each has its own strength and weakness. Selection of the most suitable model for a certain traffic condition remains an open issue. A comprehensive study of the performance of typical headway distribution models on urban freeways is presented. With the advanced loop event data analyzer system, many accurate headway observations were obtained from I-5 in the area of Seattle, Washington. These headway data were used to calibrate and examine the performance of various headway models. The goodness of fit for several most commonly used headway distribution models was investigated by using headways observed on regular lanes and high-occupancy-vehicle (HOV) lanes from different time periods of day. To evaluate the performance of these headway models, the analytical Kolmogorov-Smirnov test statistic and visualized comparison curves were used to measure and reflect their overall goodness of fit to the collected headway data. Although each model has its own practicability to a certain extent, the test results showed that the double-displaced negative exponential distribution model provided the best fit to these urban freeway headway data, especially for HOV lanes at wideranging flow levels. The shifted lognormal distribution also fits the general purpose lane headways very well. As a byproduct, a new standard parameter estimation method was developed for calibrating complex multiparameter headway models.