EMPARCO - Efficient Management of Parking under Constraints
Overview
Background & policy context:
Simulation is a very useful tool that has been applied in many fields, including parking management (Zorn et al. (2011), Gallo et al. (2011) and Arnott and Inci (2006), Martens et al. (2007)). These models were macroscopic or mesoscopic, thus lacking some of the finer modeling details that might be useful in capturing specific parameters of detailed parking modeling. While Van der Waerden et al. (2002) and Caicedo et al. (2006) used microscopic models in simulating parking, most of this work is dedicated to the “normal” operations. Modeling and management of special events has seen some attention in the literature (Shao et al. (2008), Sarasua et al. (2005)). Although existing models of driver behavior do not take into account adverse disaster scenarios, they do take into account factors such as aggression (e.g. Toledo et al., 2009) and risk aversion that are known to be impacted by emotion. Behavioral aspects have been considered in traffic management applications (Antoniou et al., 2011), often in the context of adverse/emergency conditions (e.g. Balakrishna, Antoniou et al., 2008; Prionisti and Antoniou, 2012). The use of multiple, diverse technologies for localization in the context of indoor and harsh environments has seen a lot of interest in the literature recently (Addesso et al., 2010; Dedes et al., 2011; Prieto et al., 2012; Tanigawa et al., 2004) and is considered a critical source of accurate and reliable data for the applications in this research.
Objectives:
The objective of the EMPARCO (Efficient Management of Parking under Constraints) project is to develop solutions for the management of large-scale parking facilities and depots (for either passenger vehicles or commercial fleets) under constraints including (i) near-capacity demand, (ii) temporally concentrated arrivals/departures and (iii) need for emergency evacuation. The specific modeling requirements that need to be covered in terms of both the demand/behavioral and supply side mainly include:
- Modeling of parking spot choice and the process of finding a spot in a facility that is almost at capacity
- Modeling of parking facilities, including parking spots, access corridors and ramps (for multi-story facilities).
- Modeling of the traffic dynamics of vehicles operating in parking facilities and commercial vehicle depots, both under regular conditions, but also under stress or unusual conditions.
Regarding the localization support, existing localization techniques and methodologies for hybrid and indoor parking areas should be evaluated. This includes evaluation of GNSS- and GNSS/MEMS-based systems and radio access technologies. Finally, given a reliable simulation model of the operating facility, based on robust localization data from available sources, a response strategy should be determined, comprising (in general) (i) information to be provided to the drivers and (ii) control strategies that may be used to guide and restrict the movement of the same drivers.
Methodology:
An integrated methodological framework is developed that operationalizes a cycle created from the following main methodological and technological challenges/ components:
- Microscopic parking facility simulation to provide the modeling and simulation capabilities to accurately model the required scenarios for the execution of this project, both in terms of the supply- and the demand-side.
- Novel methodologies and algorithms for vehicle localization support, including data fusion of various data sources
- Information generation and dissemination and control
- Strategy generation for the optimal parking management schemes
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