A framework for risk reduction for indoor parking facilities under constraints using positioning technologies

Abstract

Traffic simulation is a mature field, with several decades of development. While many mainstream aspects can be assumed to be at a level where most challenges have been overcome, there are still edge cases that are not adequately covered. For example, traffic simulation of mixed networks in conditions close to exceeding capacity or in emergency cases is still a challenge. This research aims at developing a risk-reduction framework for large-scale parking facilities and depots (for either passenger vehicles or commercial fleets) under constraints. An integrated methodological framework is therefore analyzed and then the emphasis is placed on the localization of vehicles under these conditions using a combination of state-of-the-art technologies. A case study is implemented to test the feasibility of the proposed technologies including smart-phone accelerometers, radio frequency identification technology, high-sensitivity GNSS receivers and Ultra-wideband technology. Then, an experiment was conducted in a large-scale parking facility, including vehicle positioning in indoor, outdoor and hybrid environments. This information is used as input for a simulation-based evacuation analysis of a large parking facility in Athens, Greece. The evaluation of four evacuation scenarios suggests that considerable risk reduction benefits can be obtained by suitable emergency response strategies.