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Cataloged from PDF version of article. Traffic management during an evacuation and the decision of where to locate the shelters are of critical importance to the performance of an evacuation plan. From the evacuation management authority’s point of view, the desirable goal is to minimize the total evacuation time by computing a system optimum (SO). However, evacuees may not be willing to take long routes enforced on them by a SO solution; but they may consent to taking routes with lengths not longer than the shortest path to the nearest shelter site by more than a tolerable factor. We develop a model that optimally locates shelters and assigns evacuees to the nearest shelter sites by assigning them to shortest paths, shortest and nearest with a given degree of tolerance, so that the total evacuation time is minimized. As the travel time on a road segment is often modeled as a nonlinear function of the flow on the segment, the resulting model is a nonlinear mixed integer programming model. We develop a solution method that can handle practical size problems using second order cone programming techniques. Using our model, we investigate the importance of the number and locations of shelter sites and the trade-off between efficiency and fairness. 2014 Elsevier Ltd. All rights reserved.

Advanced Driver Assistance Systems (ADAS) are becoming ubiquitous, and gradually take over the role of human drivers in the vision of the automotive sector. Humans are different from most systems: while in general humans exhibit a much higher error rate when performing specific functions, they are also unmatched in their adaptability, and their ability to recognize patterns and anticipate on these. In this paper we derive temporal requirements on future ADAS operation, needed to at least match human driving behavior in dense traffic. We examine Adaptive Cruise Control and Automated Emergency Braking systems at highway speeds, derive temporal requirements, and show that in dense traffic situations intent communication has a significant benefit to improve systems operation. The resulting requirements will challenge ADAS developments in the coming years. cop. 2015 IEEE.

Advanced Driver Assistance Systems (ADAS) are becoming ubiquitous, and gradually take over the role of human drivers in the vision of the automotive sector. Humans are different from most systems: while in general humans exhibit a much higher error rate when performing specific functions, they are also unmatched in their adaptability, and their ability to recognize patterns and anticipate on these. In this paper we derive temporal requirements on future ADAS operation, needed to at least match human driving behavior in dense traffic. We examine Adaptive Cruise Control and Automated Emergency Braking systems at highway speeds, derive temporal requirements, and show that in dense traffic situations intent communication has a significant benefit to improve systems operation. The resulting requirements will challenge ADAS developments in the coming years. cop. 2015 IEEE.

Evacuation route planning is a fundamental task for building engineering projects. Safety regulations are established so that all occupants are driven on time out of a building to a secure place when faced with an emergency situation. As an example, Spanish building code requires the planning of evacuation routes on large and, usually, public buildings. Engineers often plan these routes on single building projects, repeatedly assigning clusters of rooms to each emergency exit in a trial-and-error process. But problems may arise for a building complex where distribution and use changes make visual analysis cumbersome and sometimes unfeasible. This problem could be solved by using well-known spatial analysis techniques, implemented as a specialized software able to partially emulate engineer reasoning. In this paper we propose and test an easily reproducible methodology that makes use of free and open source software components for solving a case study. We ran a complete test on a building floor at the University of Alicante (Spain). This institution offers a web service (WFS) that allows retrieval of 2D geometries from any building within its campus. We demonstrate how geospatial technologies and computational geometry algorithms can be used for automating the creation and optimization of evacuation routes. In our case study, the engineers' task is to verify that the load capacity of each emergency exit does not exceed the standards specified by Spain's current regulations. Using Dijkstra's algorithm, we obtain the shortest paths from every room to the most appropriate emergency exit. Once these paths are calculated, engineers can run simulations and validate, based on path statistics, different cluster configurations. Techniques and tools applied in this researchwould b