Khaoula Hassoune

Bio: Khaoula Hassoune is an academic researcher. The author has contributed to research in topics: Traffic congestion & Distributed algorithm. The author has an hindex of 2, co-authored 4 publications receiving 42 citations.

Smart parking systems: A survey

Abstract: Not finding a parking space for you sometimes is indeed a critical issue. The number of vehicles is also increasing daily adding to the parking vows at public places. Cities noticed that their drivers had real problems to find a parking space easily especially during peak hours, the difficulty roots from not knowing where the parking spaces are available at the given time. Even if this is known, many vehicles may pursue a small number of parking spaces which in turn leads to traffic congestion. The traffic on roads and parking space has been an area of concern in majority of cities. So, parking monitoring is an important solution. To avoid these problems, recently many new technologies have been developed that help in solving the parking problems to a great extent. Firstly, this paper gives an overview about the concept of smart parking system, their categories and different functionalities. Then we present the latest developments in parking infrastructures. We describe the technologies around parking availability monitoring, parking reservation and dynamic pricing and see how they are utilized in different settings. In addition, a theoretical comparison is presented to show advantages and drawbacks of each different smart parking system to discuss results and open directions for future research.

Dynamic Parking Guidance Architecture Using Ant Colony Optimization and Multi-agent Systems

Abstract: Nowadays, drivers have great difficulty finding a parking space easily due to the traffic congestion in some areas and the distribution of car parks within the city. This work aims to design a new system that will allow a vehicle driver to find the best route between his real-time position and parking with available places in a specific area. Our system is based on a distributed swarm intelligence strategy using the ant colony algorithm, cloud system, and multiagent systems to offer an optimal solution toward the nearest car park in the city. Our solution will improve the use of available parking in the city.

The Proposal of a Distributed Algorithm for Solving the Multiple Constraints Parking Problem

Abstract: The parking problem in big cities has become one of the key causes of the city traffic congestion, driver frustration and air pollution.So to avoid these problems, parking monitoring is an important solution. Recently many new technologies have been developed that allows vehicle drivers to effectively find the free parking places in the city but these systems still limited because they don 't take into consideration road networks constraints. In this paper, We design a distributed system that will help drivers to find the optimal route between their positions and an indoor parking in the city taking into consideration a set of constraints such as ( distance, traffic, amount of fuel in the car, available places in te parking, and parking cost). We propose a distributed technique based on multi objective Ant Colony Optimisation (ACO). The proposed method aim to manage multi objective parking problem in real time using the behavior of real ants and multi agent systems to decrease the traffic flow and to find the optimal route for drivers.

A Modular Multi-agent Architecture for Smart Parking System

Abstract: Cities noticed that their drivers had real problems to find a parking space easily, the difficulty roots from not knowing where the parking spaces are available at the given time. In this paper we will design an automatic smart parking architecture using multi-agent and expert systems which are the main domains of artificial intelligence. AI is accomplished by studying how human brain thinks and how humans learn, decide, and work while trying to solve a problem, and then using the outcomes of this study as a basis of developing intelligent software and systems. Implementing this scalable and low cost car parking framework will provides a lot of services for the driver: driver guidance, automatic payment, parking lot retrieval, Gate management, security and low cost of implementation.

Smart parking sensors, technologies and applications for open parking lots: a review

Abstract: Parking a vehicle in traffic dense environments often leads to excess time of driving in search for free space which leads to congestions and environmental pollution. Lack of guidance information to vacant parking spaces is one reason for inefficient parking behaviour. Smart parking sensors and technologies facilitate guidance of drivers to free parking spaces thereby improving parking efficiency. Currently, no such sensors or technologies is in use for open parking lot. This study reviews the literature on the usage of smart parking sensors, technologies, applications and evaluates their applicability to open parking lots. Magnetometers, ultrasonic sensors and machine vision were few of the widely used sensors and technologies on closed parking lots. However, this study suggests a combination of machine vision, convolutional neural network or multi-agent systems suitable for open parking lots due to less expenditure and resistance to varied environmental conditions. Few smart parking applications show drivers the location of common open parking lots. No application provided real-time parking occupancy information, which is a necessity to guide them along the shortest route to free space. To develop smart parking applications for open parking lots, further research is needed in the fields of deep learning and multi-agent systems.

A navigation and reservation based smart parking platform using genetic optimization for smart cities

Abstract: With the development of technology, smart devices are becoming more common in everyday life. The development of devices that can connect to the Internet and transmit data has been a source of inspiration for smart city designs. The common problem in our cities is the difficulty of finding free parking slots. The parking problem causes traffic to congest and people who go to work are looking for a place. In this study, a navigation and reservation based parking proposal system was developed for smart cities. The proposed method involves the development of small devices that send data to the internet using the internet of things (IoT) technology. The free parking space closest to the current location is found by genetic algorithm. The proposed method is tested for different scenarios and accurate results are obtained.

Towards Smart Parking Based on Fog Computing

Abstract: An experience of finding a vacant parking slot can be very stressful in densely populated areas, especially in peak hours. Such parking process takes a long time, wastes significant gasoline, and emits extra vehicle exhaust that harms the environment. Smart parking, aiming to assist drivers in finding desirable parking slots more efficiently through information and communication technologies such as vehicle ad hoc networks (VANETs), has received extensive attention recently. Current VANETs-based parking slot allocations cannot provide a fully satisfactory solution, because vehicle communication devices—on-board units—and roadside units lack computational capabilities to perform humanized and accurate service provisioning, such as real-time parking slots information and probabilistic prediction on future parking slots. Therefore, we, in this paper, propose a fog computing-based smart parking architecture to improve smart parking in real time. Fog nodes deployed at parking lots, cooperating with each other, enable real-time parking slot information provisioning as well as parking requests processing. The cloud center can further enhance smart parking capability by enforcing global optimization on parking requests allocation. The experimental results of our approaches show higher efficiency compared with other parking strategies. The proposed fog computing-based smart parking can lower the average parking cost and minimize gasoline wastes and vehicle exhaust emission.