Browsing by Author "Kumar, P"

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    Accessibility to transit station in multi modal transport framework for Delhi
    (2013-11-15) Kumar, P; Jain, SS; Kulkarni, SY; Parida, M
    Recently, Multi Modal Transit Station has been recognized as a symbol of ‘Urban Identity’ and ‘Urban Mobility’ in Delhi which integrates built environment with multiple modes and provides an important link to complete the journey. It is either as a single station or an interchange hub, accessed by human, mechanical and vehicular system. Hence, it is important that such transit station must meet minimal level of service and be a part of overall efforts to improve transit services for increasing rider ship. In this context, Multi Modal Oriented Design (M2OD) is used which defines neighborhood character in design and provides mobility friendly environment. It also encourages a mix of mobility options to cater needs of both present and future travel demands. Further, the role and responsibilities of transit operators, facilitators and users are crucial to extend better accessibility to transit station.
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    Assessment of present pavement condition using machine learning techniques
    (Springer, 2021) Sharma, M; Kumar, P; Pasindu, HR; Bandara, S; Mampearachchi, WK; Fwa, TF
    Quantification of present pavement condition in terms of an index term i.e., Pavement Condition Index (PCI) is one of the most important and primary steps while taking decision related to Maintenance and Rehabilitation of Pavements. PCI as proposed by ASTM D6433 rates pavement in seven conditions viz. Good, Satisfactory, Fair, Poor, Very Poor, Serious and Failed. Determination of rating condition of pavement using distress severity and extent turns out to be tedious process. Hence, present study investigates application machine learning techniques for assessment of present pavement condition. Three different algorithms i.e., Logistic Regression, Naïve Bayes and K-Nearest Neighbor have been tested in the present study using Long Term Pavement Performance database consisting of over 10,000 datapoints. The dataset was divided into 7:3 ratio for training and testing phase. Employed algorithms were tested based on accuracy, precision, recall and f-measure. Logistic Regression Classifier was found to have highest accuracy of 0.92 among three classifiers used in the study.
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    Functional condition evaluation of airfield pavements using automated road survey system—a case study of a small sized airport
    (Springer, 2021) Kumar, P; Sharma, M; Pasindu, HR; Bandara, S; Mampearachchi, WK; Fwa, TF
    Airports are vital national resources. Airfield Pavements within an airport represents a large capital investment in infrastructural development made by a country. Timely and appropriate maintenance and rehabilitation of such in-service facilities are essential to provide an all-weather surface for safe and regular operations of the aircraft. Pavement maintenance is done based on functional and structural pavement condition evaluation. This paper presents a case study dealing with functional evaluation of airfield pavements of a small sized airport in India. The considered airport consists of two runway, seven link taxiways, three apron areas and an isolation bay with different surface types. Present paper reports the methodology adopted for the functional condition evaluation of the airfield pavements with help of Automated Road Survey System. Further, the evaluated pavement condition was quantified in terms of Pavement Condition Index (PCI) as per the ASTM D5340 with help of PAVER and GIS based software. GIS was used for preparing inventory database and basemaps for the concerned pavementswhich were then used in PAVER software for determining the PCI. The airfield pavement network within the airport was divided into a four-level hierarchy consisting of the network, branch, section and sample. The obtained PCI rating shows that the overall condition of the airfield pavements within the considered airport is satisfactory to good, however some of the areas have distresses that needs to be repaired by localized maintenance.