Autonomous vehicles: challenges, opportunities, and future implications for transportation policies

This study investigates the challenges and opportunities pertaining to transportation policies that may arise as a result of emerging autonomous vehicle (AV) technologies. AV technologies can decrease the transportation cost and increase accessibility to low-income households and persons with mobility issues. This emerging technology also has far-reaching applications and implications beyond all current expectations. This paper provides a comprehensive review of the relevant literature and explores a broad spectrum of issues from safety to machine ethics. An indispensable part of a prospective AV development is communication over cars and infrastructure (connected vehicles). A major knowledge gap exists in AV technology with respect to routing behaviors. Connected-vehicle technology provides a great opportunity to implement an efficient and intelligent routing system. To this end, we propose a conceptual navigation model based on a fleet of AVs that are centrally dispatched over a network seeking system optimization. This study contributes to the literature on two fronts: (i) it attempts to shed light on future opportunities as well as possible hurdles associated with AV technology; and (ii) it conceptualizes a navigation model for the AV which leads to highly efficient traffic circulations

Microgrid Operational Planning Using Deviation Clustering Within a DDDAS Framework

As climate change progresses and the global population continues to increase, meeting the energy demand is an issue that has been brought to the forefront of the conversation. Microgrids (MGs) are groundbreaking tools that have risen in popularity to combat this crisis by capitalizing on renewable, distributed energy resources to efficiently satisfy the energy demand from environmental sensors via telemetry. In this work, we present a deviation clustering (DC) algorithm within a dynamic data-driven application systems (DDDAS) framework to reduce the length of the MG dispatch model’s planning horizon while retaining the temporal characteristics of the initial load profile. The DDDAS framework allows for the adjustment of the current dispatch decisions in near real-time. We develop two modules embedded within this framework; the first is a proposed rule-based policy (RBP) that modifies the sensing strategy and the second is the DC algorithm which reduces the execution time of the MG simulation. Numerical analysis was conducted on the IEEE-18 bus test network to assess the performance of the proposed framework and determine an appropriate threshold for clustering. The limitations of the presented framework were also determined by comparing the tradeoff between its the speed of the solver’s solution time and the accuracy of the resulting solution. The results indicate a decrease in solution time within the desired accuracy limits when using the proposed approach as opposed to traditional load dispatch

Contribution of conceptual modeling to enhancing historians' intuition : application to prosopography

International audienceHistorians, and in particular researchers in prosopography, focus a lot of effort on extracting and coding information from historical sources to build databases. To deal with this situation, they rely in some cases on their intuition. One important issue is to provide these researchers with the information extracted from the sources in a sufficiently structured form to allow the databases to be queried and to verify, and possibly, to validate hypotheses. The research in this paper attempts to take up the challenge of helping historians capturing and assessing information throughout automatic processes. The issue emerges when too many sources of uncertain information are available. Based on the high-level information fusion approach, we propose a process that automatically supports historians' intuition in the domain of prosopography. The contribution is threefold: a conceptual data model, a process model, and a set of rules combining the reliability of sources and the credibility of information