The primary aim of this research is to analyse the influence of side friction on the capacity of undivided urban streets. Side friction is a composite variable signifying the degree of interaction between regular traffic flow and other surrounding activities. Three elements of side friction were considered in this work viz. on-street parking, pedestrian movements and non-motorized vehicles. The research is based on the data collected from six base sections and ten non-base sections located in different cities of India. To extract side friction data, the carriageway width was divided into ten equal segments by using longitudinal virtual lines. Capacity of both base and non-base sections were estimated using ‘fundamental diagram method’. Relationship between carriageway width and capacity was determined in absence of side friction. Capacity under the influence of side friction was observed significantly lower (up to 60.73%) than the capacity of base section of the same carriageway width. A number of parameters were considered under different side friction elements. Some of these parameters are conceptualized in this study and rest are taken from literature. These parameters were further shortlisted based on statistical measurers, then standardized using ‘feature scaling method’ and finally used as design variables to model the ‘reduction in capacity’. While majority of the previous research efforts were focussed on estimating the influence of side frictional elements on performance of divided urban roads, the model proposed in this study will be useful to find the capacity particularly for undivided urban streets under prevailing side friction conditions.

Side friction parameters and their influences on capacity of Indian undivided urban streets

The photovoltaic module testing apparatus being used presently for photovoltaic measurements acts principally on the method of photovoltaic module loading with resistive, capacitive, and electronic...

https://journals.sagepub.com/doi/pdf/10.1177/0020294019865752

Design of a low-cost measuring and plotting device for photovoltaic modules:

This paper outlines a novel design of low-cost, portable, fast, and precise Current-Voltage Curve Tracer (IVCT) with automated parameter extraction for high power rated Solar Photovoltaic (SPV) modules to effectively and efficiently determine the outdoor operating status of SPV power generators. The developed IVCT is based on a Raspberry Pi microprocessor, a super-capacitive load, heat sinkable discharge resistances, and sensors with high sensitivity and resolution for measuring light irradiance, module temperature, current, and voltage. The proposed Outdoor Test Facility (OTF) consists of an Current-Voltage ( $I-V$ ) and a Power-Voltage ( $P-V$ ) curve tracer that uses a dynamic loading supercapacitor to safely and quickly scan the SPV module performance characteristics under real-world operating conditions. It also helps to achieve uniform sampling with better data accuracy. It uses Raspberry Pi as a central processing unit for low-cost data acquisition, data logging, and data computation. Furthermore, results from on-field testing of various small-scale SPV modules show that the $I-V$ tracer can acquire higher-resolution characteristics curves and perform accurate model parameter recognition in real-time. Proposed IVCT can measure individual SPV modules without altering the electrical interconnection circuit, and the operating point can be shifted to 20 $A$ and $45~V$ in few seconds. The proposed system recomposes the SPV module $I-V$ characteristics based on this variance, with accuracies of 1 to 3% for the region near maximum power.

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Design and Development of Low Cost, Portable, On-Field I-V Curve Tracer Based on Capacitor Loading for High Power Rated Solar Photovoltaic Modules

Abutting land-use patterns always play an important role in the performance of a road section. Land use along rural highways in developing countries is significantly different from that in ...

Impact of Side Friction on Performance of Rural Highways in India

Traffic characteristics of a roadway are significantly influenced by bus stops, and it becomes more chaotic when a separate bus bay is not provided and the bus has to be stopped in the curb lane. The present study analyzes the effect of such bus stops on the midblock capacity of urban arterials under heterogeneous traffic conditions. Field data have been collected at six sections of six-lane divided urban arterial roads; out of that, three sections have not marked with bus stop and referred to as base sections, whereas the other three have designated bus stops and denoted as friction sections. A set of simultaneous equations are established using speed and flow data to estimate the midblock capacity of urban roads and found to be 6000 PCU/h for one direction of flow. Further, a set of simultaneous equations are developed between the speed of a vehicle type and the densities of all categories of vehicles with densities of stopped buses in their individual terms. These equations are solved for any number of stopping buses at a fixed proportion of vehicles in the traffic stream for different traffic volume levels and thus get the capacity curves. It has been found that the capacity of urban arterials is reduced by 6.6–28.3% when the frequency of stopping buses is as low as 20 bus/h to as high as 120 bus/h, respectively. The study outcomes are useful for designing bus stops and at the same time estimating the capacity of such sections in order to reduce the congestion on the urban roadway network.

Developing Capacity Reduction Factors for Curbside Bus Stops Under Heterogeneous Traffic Conditions

Substantial amount of money has been invested by Government of India and several State Governments to improve the level of service of various categories of roads in India. Roads have been widened and strengthened, surface condition has been improved but Level of Service has not been improved as expected because of various socio-economic factors. One of the important factors has been the presence of side friction along Indian rural highways. Existence of road-side markets at regular interval along rural highways is very common in India. These market areas act as pseudo bottleneck points and confusion zones to the through traffic of highways. Interaction among fast moving vehicles, pedestrian and non-motorized local vehicles is very unique phenomenon. Literature review reveals that not much work has been carried out to understand impact of side friction on travel speed and Level of Service. An attempt has been made in the present work to quantify the impact of roadside friction on travel speed and LOS of Indian rural highways. Based on data collected from three study sections, speed-flow curves were developed for various side friction levels and five threshold values for LOS are suggested considering operational speed and freedom of maneuver as measure of effectiveness.

/pdf/impact-of-roadside-friction-on-travel-speed-and-los-of-rural-3r926zksg1.pdf

Impact of Roadside Friction on Travel Speed and LOS of Rural Highways in India

Smooth and noise-free characterisation of photovoltaic (PV) generators have been revisited with renewed interest in view of large size PV arrays making inroads into the urban sector of major developing countries. Such practice has recently been observed to be confronted by the use of a suitable data acquisition system and also the lack of a supporting theoretical analysis to justify the accuracy of curve tracing. However, the use of a selected bank of supercapacitors can mitigate the said problems to a large extent. Assuming a piecewise linear analysis of the V–I characteristics of a PV generator, an accurate analysis of curve plotting time has been possible. The analysis has been extended to consider the effect of equivalent series resistance of the supercapacitor leading to increased accuracy (90–95%) of curve plotting times.

Estimation of Curve Tracing Time in Supercapacitor based PV Characterization

This paper aims to fabricate a facial expression recognition system using a convolution neural network (CNN). Since human evolution, human emotion interpretation has been an effective method for non-verbal communication. It helps to contend human perspectives or to reciprocate feelings and his or her mental state. With the development in science and technology, face detection and face recognition from sources have become relatively more straightforward. This project targets the fabrication of a real-time recognition system that traces the very mood of human beings through popular computer vision libraries and convolution neural networks. Facial action coding system (FACS), which uses action units (A.U.s), has been used as the base toward the integration of this research. This research has predominantly endeavored to detect specific subtle changes in facial components (A.U.s). Thus, relating those changes with the corresponding combinations has finally successfully seen the underlying emotion. “OpenCV,” an open-source computer vision library, has been used in the classification of the seven primary human emotions: fear, sadness, happiness, anger, disgust, surprise, and neutral. After the face is detected, image processing based on the feature point extraction method is used to extract a set of feature points. A considerable amount of significant research has been contributed toward the advancement of human–computer interaction (HCI).This paper tries to focus on the integration and implementation of a successful facial expression recognition system using CNN consists of a detailed work review and result from the analysis of automatic facial expression recognition systems.

Sudipta Basu Pal

Papers

Impact of Roadside Friction on Travel Speed and LOS of Rural Highways in India

Design of a low-cost measuring and plotting device for photovoltaic modules:

Estimation of Curve Tracing Time in Supercapacitor based PV Characterization

Impact of Side Friction on Performance of Rural Highways in India

Facial Expression Recognition Using Convoluted Neural Network (CNN)