No abstract
Improving road safety through proper pavement engineering and maintenance should be one of the major objectives of pavement management systems. When pavements are evaluated in terms of safety, a number of factors related to pavement engineering properties are raised, such as pavement geometric design, paving materials and mix design, pavement surface properties, shoulder type, and pavement color and visibility. Each year there are voluminous annual reports on traffic accident statistics and discussions of such road safety issues as road safety modeling and pavement safety measurements and criteria. Although road safety may be considered a separate area, it should be incorporated into pavement management systems. The main pavement engineering relationships associated with road safety are identified, and the various aspects of road safety related to pavement management, such as pavement types, pavement surface macrotexture and microtexture, and pavement safety measurements, criteria, and evaluation methods, are discussed. A systematic approach is proposed for the coordination of pavement maintenance programs with road safety improvement and the incorporation or integration of safety management with pavement and other management systems. Finally, a list of possible remedial measures for road safety improvements associated with pavement maintenance activities is recommended.
In the past, intellectually talented engineers with strong technical skills were sufficient for the needs of society. In the 21st century engineers are now working in the corporate world, often disconnected from the hands-on aspect of engineering. Professional skills such as leadership have become critical for graduating engineers entering the workforce. A review was conducted of current engineering leadership programs' goals and competencies to determine consistencies and variations, and to suggest prominent themes. Five themes emerged for the fundamental goal of engineering leadership education programs: effective leadership, innovation and technology, independent learning, experiential learning and systems thinking. The analysis of the competencies found a diverse spread across the programs. Overall, six key competencies emerged: communication, innovation, creativity, execution, personal drive, and teamwork. This analysis provides insight on the focus of engineering leadership education and the progress of the field. The findings can be used for the development of new engineering leadership programs.
One of the primary objectives of highway agencies in Canada is providing a safe and reliable road network with a good level of service. In the Province of Alberta specific International Roughness Index (IRI) threshold values classify pavements into good, fair, and poor condition categories to manage and schedule rehabilitation and maintenance programs. This research investigated the significant factors that affect the perception of road roughness and established IRI threshold values for good, fair, and poor road condition based on public perception. A questionnaire was designed to investigate the road users' perception and included questions covering gender, age, familiarity with the road, type and model of car, and perception of road roughness. In addition, psychometric scaling analysis was used to develop a set of IRI threshold values for classifying road condition based on public perception in the Province of Alberta. According to the results of the survey, Alberta Transportation threshold values of IRI do not agree with the road users' opinion and an alternate set of threshold values was developed. The analysis of the survey results identified that trip purpose, driving experience, dry surface, and familiarity with the road are the most significant factors that influence the perception of road roughness.
One of the challenges in asset management is the integration of asset categories in the decision-making process. Asset management frameworks provide a structure to manage separate categories, and integration is assumed through database design. “Silo” management systems such as pavement and bridge management systems have parallel components that include all major elements of the classic asset management system, yet there is no integration of the results of each component system at the decision-making or expert system stage of the process. Senior decision makers are presented with the outputs of each component system and can clearly see the top priorities for each asset category; however, there is no mechanism for producing a single program list that has been developed with cross-optimization techniques. Trying to establish a multiyear priority program is difficult because of the number of asset categories, the different performance models used by each asset, and the challenges of multilevel optimization. This paper explores the links between silo systems and proposes an integration mechanism for cross optimization that recognizes the unique characteristics of individual asset categories.
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