2020Unpublished venueRequires access

From Coverage Path Planning to parking lot exploration

Anna Ádám, László Kocsány, Emese Gincsainé Szádeczky-Kardoss

Open publisher page 2 citations

Abstract

Nowadays, it is getting really difficult to find an adequate free parking space, as there are more and more vehicles travelling on the roads. It is especially a difficult task to find a free parking place in huge parking garages and shopping malls, because the area of the parking zone is big, and there are a lot of cars searching for a free space. In some parking lots, a parking system is installed. These parking systems contain sensors at every parking space in order to perceive and indicate the occupancy of the given parking space. Using the signals of these systems, the vehicles can be navigated directly to the given parking space, for example using an IoT system. However, most of the parking lots are not equipped with these parking systems, so the driver must circumnavigate them, in order to be able to detect the free parking spaces. For an autonomous vehicle, a path should be planned, which drives along all the possible free parking spaces, so that the sensors of the vehicle could detect them. The parking lot exploration is very similar to the coverage path planning (CPP) problems. This paper presents CPP algorithm based parking lot exploration methods, in which personal preferences can be taken into account, too.

About this research paper

What this paper is about

Nowadays, it is getting really difficult to find an adequate free parking space, as there are more and more vehicles travelling on the roads. It is especially a difficult task to find a free parking place in huge parking garages and shopping malls, because the area of the parking zone is big, and there are a lot of cars searching for a free space. In some parking lots, a parking system is installed. These parking systems contain sensors at every parking space in order to perceive and indicate the occupancy of the given parking space. Using the signals of these systems, the vehicles can be navigated directly to the given parking space, for example using an IoT system. However, most of the parking lots are not equipped with these parking systems, so the driver must circumnavigate them, in order to be able to detect the free parking spaces. For an autonomous vehicle, a path should be planned, which drives along all the possible free parking spaces, so that the sensors of the vehicle could detect them. The parking lot exploration is very similar to the coverage path planning (CPP) problems. This paper presents CPP algorithm based parking lot exploration methods, in which personal preferences can be taken into account, too.

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Available abstract

Nowadays, it is getting really difficult to find an adequate free parking space, as there are more and more vehicles travelling on the roads. It is especially a difficult task to find a free parking place in huge parking garages and shopping malls, because the area of the parking zone is big, and there are a lot of cars searching for a free space. In some parking lots, a parking system is installed. These parking systems contain sensors at every parking space in order to perceive and indicate the occupancy of the given parking space. Using the signals of these systems, the vehicles can be navigated directly to the given parking space, for example using an IoT system. However, most of the parking lots are not equipped with these parking systems, so the driver must circumnavigate them, in order to be able to detect the free parking spaces. For an autonomous vehicle, a path should be planned, which drives along all the possible free parking spaces, so that the sensors of the vehicle could detect them. The parking lot exploration is very similar to the coverage path planning (CPP) problems. This paper presents CPP algorithm based parking lot exploration methods, in which personal preferences can be taken into account, too.

Key concepts: Parking guidance and information, Parking space, Parking lot, Space (punctuation), Computer science, Transport engineering, Occupancy, Order (exchange)

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