Safety Aware Vehicle Routing Algorithm, A Weighted Sum Approach

Driving is an essential part of work life for many people. Although driving can be enjoyable and pleasant, it can also be stressful and dangerous. Many people around the world are killed or seriously injured while driving. According to the World Health Organization (WHO), about 1.25 million people die each year as a result of road traffic crashes. Road traffic injuries are also the leading cause of death among young people. To prevent traffic injuries, governments must address road safety issues, an endeavor that requires involvement from multiple sectors (transport, police, health, education). Effective intervention should include designing safer infrastructure and incorporating road safety features into land-use and transport planning. The aim of this research is to design an algorithm to help drivers find the safest path between two locations. Such an algorithm can be used to find the safest path for a school bus travelling between bus stops, a heavy truck carrying inflammable materials, poison gas, or explosive cargo, or any driver who wants to avoid roads with higher numbers of accidents. In these applications, a path is safe if the danger factor on either side of the path is no more than a given upper bound. Since travel time is another important consideration for all drivers, the suggested algorithm utilizes traffic data to consider travel time when searching for the safest route. The key achievements of the work presented in this thesis are summarized as follows. Defining the Safest and Quickest Path Problem (SQPP), in which the goal is to find a short and low-risk path between two locations in a road network at a given point of time. Current methods for representing road networks, travel times and safety level were investigated. Two approaches to defining road safety level were identified, and some methods in each approach were presented. An intensive review of traffic routing algorithms was conducted to identify the most well-known algorithms. An empirical study was also conducted to evaluate the performance of some routing algorithms, using metrics such as scalability and computation time. This research approaches the SQPP problem as a bi-objective Shortest Path Problem (SPP), for which the proposed Safety Aware Algorithm (SAA) aims to output one quickest and safest route. The experiments using this algorithm demonstrate its efficacy and practical applicability

A Critical Analysis of the Body of Work Method for Setting Cut-Scores

The recent increase in the use of constructed-response items in educational assessment and the dissatisfaction with the nature of the decision that the judges must make using traditional standard-setting methods created a need to develop new and effective standard setting procedures for tests that include both multiple-choice and constructed-response items. The Body of Work (BoW) method is an examinee-centered method for setting cut-scores that applies a holistic approach to student work in order to estimate the cut-scores that differentiate examinees according to their level of performance in situations where both item formats are used. A detailed review of Version 1 and the recent modification, Version 2, are first presented followed by a critical evaluation of the two versions in terms of Berk’s (1986) 10 criteria for defensibility. The results reveal that the BoW method appears to be a promising method for setting cut-scores that could be used on a wider scale in Canada. However, as with other methods, the experience gained from using the BoW method in the field will probably lead to further modifications in an attempt to increase efficiency without sacrificing accuracy.La décision d’augmenter l’emploi des questions à réponse construite dans l’évaluation scolaire a provoqué de l’insatisfaction à l’égard des décisions que doivent prendre les juges qui utilisent des méthodes traditionnelles pour établir les normes. Ce mécontentement a entraîné le besoin de développer de nouvelles procédures efficaces pour établir des normes dans le cas d’examens comportant des questions à choix multiples aussi bien que des questions à réponse construite. La méthode Body of Work (BoW) est une méthode d’établissement de notes de passage qui est centrée sur le candidat et qui repose sur une approche holistique au travail de l’élève pour déterminer les notes de passage qui distinguent les candidats selon leur rendement dans des situations impliquant les deux sortes de questions. Un examen détaillé de la 1re version et de la modification récente qu’on en a faite (la 2e version) est suivi d’une évaluation critique des deux versions d’après les 10 critères de validation établis par Berk (1986). D’après les résultats, la méthode BoW pourrait bien servir dans l’établissement des notes de passage et être mieux diffusée partout au Canada. Comme c’est le cas pour toutes les autres méthodes par contre, l’expérience qu’on retire de l’emploi de la méthode BoW entraînera probablement des modifications visant à la rendre plus efficace sans toutefois en sacrifier la précision

Ontologies for better project planning

Providing accurate estimation during project planning is crucial to meet the time lines of the project, however, with all the emphasis we put when estimating the activities in a project, we still have difficulties in predicting realistic estimation for some activities, especially the activities that have never experienced before. The problem here is that there are hidden variables that are difficult to anticipate, and sometimes cost a lot of time to fix them. Many techniques are available to help project managers successfully providing realistic estimation, one of these techniques advices to maintain the historical data for the work, during the planning process, if details of the same activities are available, then it will help the project manager to think about all variables related to an activity. Ontology has the potential to play an important role in classifying, storing and querying information. In this paper we suggest a solution that uses ontologies to maintain the historical data for the work, and to share the data between multiple teams.Scopu