A disproportionate number of Americans drive to work alone – at the individual state level, the figure ranges from a low of 58% in New York to 85% in Alabama. What factors explain this travel behavior and what sort of policy responses are required to effect changes? In responding to this question, we used multiple test beds and made the case for a demand side management approach to remedy parking problems particularly observed in cities central business districts. To this end, we provide an overview of travel behavior and information on policy levers by generating detailed profiles that capture the travel behavior of commuters in the Pacific states of the continental United States. Building off the result that revealed San Francisco as an outlier, we examine the efficacy of modifying parking rates, via elasticity measures, to influence the demand for parking by developing a two-stage panel data regression optimization model for managing parking in the City of San Francisco. A key contribution of the research is deriving these price elasticities of parking demand estimates using panel data methods. Coefficient estimates from the panel data regression are used to fit a linear prediction model that is the primary input to the optimization model. The balance of the thesis focuses on parking information by discussing the design and implementation of ParkPGH, a novel smart parking application that provides real time and predictive information on garage parking availability in downtown Pittsburgh. At its core is a predictive model that uses as input historical parking, weather and event data to provide estimates of available parking spaces. We provide an example of the model implementation using data from the Theater Square garage where we utilize neural network-based predictors and multiple net searches to generate both continuous and binary estimates of parking availability. Provision was made for the binary classifier given the need to reduce the possibility of Type II errors.

Master of Science / Department of Computing and Information Sciences / Daniel A. Andresen / Locating a parking spot during peak hours in most populated areas like shopping malls, universities, exhibitions or convention centers is difficult for the drivers. The difficulty rises from not knowing where the available spots may be at that required time. Smart parking is a solution to metropolitan cities to reduce congestion, cut vehicle emission totals and save persons' time by helping them in finding a spot to park. Smart Parking is a parking system, usually a new one that is equipped with special structured devices (things) to detect the available parking slots at any parking area. This is an application based on Internet of Things (IoT) that in Real-Time environment have sensors and devices embedded into parking spaces, transmitting data on the occupancy status; and the vehicle drivers can search for parking availability using their mobile phones or any infotainment system that is attached to the vehicle. Hence the driver would know where there is an available spot to park his vehicle in less time, reducing the energy consumption and air pollution. The Client or the sensor posts the parking slot occupancy status to a web service URL. The Java based web service is built using Spring and Hibernate to connect to the backend system. The web service (.war) file is deployed on Apache Tomcat Server and the backend used is MySQL database.

L’objectif de cette thèse est de développer, d’intégrer et de tester une nouvelle approche algorithmique d’aide au stationnement dans les centres urbains. Considérons différents types d’infrastructures déployées allant de la détection des entrées/sorties des véhicules jusqu'à la variation dans le temps du nombre de places de stationnement disponibles dans chaque portion de rue, nous montrons qu’il est possible de proposer une méthode efficace qui détermine un itinéraire qui minimise l’espérance de temps pour trouver une place de stationnement disponible et de prédire la disponibilité des placesde stationnement.Pour cela, la zone urbaine choisie sera donc considérée comme un ensemble de ressources de stationnement (segments de rues).Nous modélisons d’abord cette zone urbaine par un graphe où les sommets désignent les carrefours et les arcs représentent les portions de rues. Les paramètres essentiels pour notre modèle de réseau urbain sont la capacité de stationnement et le temps de parcours des portions de rue.L’originalité et l’aspect innovant de notre approche s’appuient sur deux principes.Le premier principe concerne le guidage comme une ressource : il ne s’agit pas de guider vers une place libre mais de proposer un parcours qui optimise l’espérance de temps de trouver une telle place. Pour cela nous déterminons dans une zone centrée sur une destination donnée, le parcours à effectuer par un véhicule pour minimiser son espérance de temps de trouver une place destationnement le plus rapidement possible.Ainsi nous avons mis en œuvre un algorithme d’apprentissage par renforcement basée sur la méthode LRI (Linear Reward Inaction) et la méthode Monte Carlo pour minimiser l’espérance de temps de trouver une place de stationnement en zone urbaine.Nous avons comparé cet algorithme avec une approche globale basée sur l’évaluation arborescente à profondeur bornée.Le second principe repose sur la prédiction des places de stationnement disponibles par périodes de temps homogènes où on ne s’intéresse pas à une place de stationnement en temps réel mais aux places de stationnement par zones. Il s’agit alors pour le système de pouvoir prédire le potentiel de places libres dans chacune des ressources pour les prochaines périodes. On ne vise donc pas ici la prédiction de la disponibilité de chaque place ; chaque ressource sera considérée comme une zone de stockage dont la disponibilité sera établie en grande partie en fonction des flux d’entrée et de sortie de la portion. Pour ce principe, nous avons donc déterminé par algorithmes de calculs et d’apprentissages la probabilité qu’il y ait au moins une place libre pour stationner dans un tronçon de rue pour un créneau de temps donné. Les principales données nécessaires pour effectuer ces calculs sont les séries temporelles d’entrée sortie de chaque véhicule aux intersections des rues et les variations des places de stationnement au cours du temps.Nous avons évalué les performances de notre approche par simulations sur des données générées aléatoirement et des données réelles obtenues sur un quartier de Versailles. / The objective of this thesis is to develop, to integrate and to test a new algorithmic approach to help parking in urban centers.Given the different types of deployed infrastructure : from input-output detection of vehicles to time variation of the number of available places within each street segment, we propose an efficient method to determine an itinerary that minimize the time expectation to find an available place and also to predict the availability of the parking places.We have chosen an urban area and we have considered it as a set of parking resources called street segments. More exactly, this urban area is considered as a graph where the vertexes represent the crossroads and the arcs represent the street segments. The essential parameters of our urban area model are the parking capacity and the time crossing of each street segment. The originality and the innovation of our approach are based on two principles.The first one is the guidance as a resource, i.e., it means that the proposed itinerary is not the one that lead to an available parking place but rather the one that minimized the time expectation to find an available parking place. In order to achieve that we determine, in a an area centered on a given destination, the itinerary to follow by the vehicle in order minimize its time expectation to find an available parking place as quickly aspossible.We have designed and realized a reinforcement learning algorithm based on the LRI method (Linear Reward Inaction) and a Monte Carlo method to minimize the time expectation to find an available parking place in the urban area. We have compared this algorithm to a global approach based on tree evaluation with bounded depth. The second principle is based on the prediction of the parking places by homogeneous time period where we are not interestedon a parking place in real time but rather on the parking places byarea. In other terms, the system predict the potential available parkingplaces by resource for the next time periods. Thus, we don’t aim to predict the availability of each parking place, i.e., each resource is considered as stock area and its availability is assessed in major part in function of the street segment input-output flow. For this principle, we have determined by a learning algorithm the probability that there is at least one available parking place in a street segment within a given time. The major data needed to compute this probability are the time series of input-output of each vehicle in street intersections, and the variation of the available parking places through the time.We have evaluated the performance of this approach by simulation based on random generated data and on real data of a district in Versailles.

Internet of Things är ett begrepp som innebär att alla tänkbara enheter kan kommunicera med varandra. Utvecklingen är snabb och antalet uppkopplade enheter ökar enormt. Detta medför bland annat att samhället blir effektivare vilket innebär både ekonomiska och miljömässiga fördelar. Genom att göra parkeringsplatser smarta kan de lediga platserna snabbare lokaliseras vilket minskar både miljöpåverkan och bränslekostnad. Eftersom strömförsörjning kan vara ett problem vid en del parkeringsplatser undersöks huruvida det är möjligt att åstadkomma smarta parkeringsplatser baserat på en enhet utan extern strömförsörjning. Undersökningen görs genom att konstruera en prototyp och på den utvärdera ström- och effektförbrukning samt batteritid. Dessutom analyseras om en annan design på prototypen skulle prestera bättre genom att uppskatta strömförbrukningen för en sådan design och därefter beräkna effektförbrukning och batteritid. Prototypens konstruktion bestod av en ultraljudsgivare inklusive styrenhet, en mikrokontroller kallad mDot, ett 9 V-batteri och en strömbrytare. Med mDot:en kunde data sändas till en server via LoRaWAN. De utförda mätningarna och beräkningarna visade att prototypen drar mycket ström. En enhet med tillräcklig prestanda är dock möjlig att konstruera genom att utföra beräkningar i mDot:en istället för i ultraljudsgivarens styrenhet. Detta skulle minska strömförbrukningen vilket förlänger batteritiden. Uppskattningar visade även att batteritiden för en sådan enhet ökar exponentiellt mot tiden i viloläge. Slutsatsen är att batteritiden varierar beroende på hur enheten är designad samt hur länge enheten är i viloläge. Det är dock möjligt att konstruera en enhet utan extern strömförsörjning som har tillräckligt bra prestanda för att åstadkomma smarta parkeringsplatser. / Internet of Things is a term for describing that every imaginable device can communicate with each other. The development in the field is fast and the amount of connected devices increases at an enormous rate. This means that the society becomes more efficient and some part of this is economic as well as environmental benefits. By making parking lots smart, the vacant lots can be located more quickly thus reducing environmental impact and fuel cost. At some parking lots there is no power supply. This report investigates whether or not it is possible to achieve smart parking lots based on a device without external power supply. The investigation is done by constructing a prototype and evaluate its current and power consumption as well as its battery life. Furthermore, an investigation is done to find out if another design can perform better than the prototype. This is done by making assumptions of how another design might look and from that estimate its current consumption and then calculating power consumption and battery life. The prototype constructed existed of an ultrasonic sensor including control unit, a microcontroller called mDot, a 9 V battery and a power switch. The mDot was able to send data to a server via LoRaWAN. The performed measurements and calculations showed that the prototype used to much current. However, a device with sufficient performance is possible to construct by doing the computation in the mDot instead of in the ultrasonic sensors control unit. This would increase the battery life of the device. Estimations showed that the battery life of such a device increases exponentially to the sleep time. The conclusion is that the battery life will vary depending on the design and the sleep time of the device. It is however possible to design a device without external power supply that has sufficiently good performance to enable smart parking lots.

With the exponential growth of vehicles on our streets, the need for finding an unoccupied parking spot today could most of the time be problematic, but even more in the coming future. Smart parking solutions have proved to be a helpful approach to facilitate the localization of unoccupied parking spots. In many smart parking solutions, sensors are used to determine the vacancy of a parking spot. The use of sensors can provide a highly accurate solution in terms of determining the status of parking lots. However, this is not ideal from a scalability point of view, since the need for installing and maintaining each of the sensors is not considered cost-effective. In the latest years vision based solutions have been considered more when building a smart parking solution, since cameras can easily be installed and used on a large parking area. Furthermore, the use of cameras can be developed to provide a more advanced solution for checking in at a parking spot and also for providing the information about whether a vehicle is placed unlawfully. In our thesis, we developed a dynamic vision-based smart parking prototype with the aim to detect vacant parking spots and illegally parked vehicles.

The concept of smart cities, which may have seemed distant and unachievable not very long ago, is becoming reality today. Behind the concept of a smart city lies a vast intelligence, namely the Internet of Things. As the population in urban areas grows, the development of smart parking solutions are becoming more relevant and crucial than ever. One of the biggest concerns regarding todays’ way of parking is congestion. Drivers’ are cruising around in search of a parking space which is both time consuming and causes big congestion. In this thesis project, a comparative analysis was conducted between two parking operators in Sweden, EasyPark and LinPark. A qualitative study in the forms of interviews and a literature study was conducted to further investigate and analyse technologies and methods used in smart parking today. The problems that this thesis focuses on are congestion due to poor parking management as well as the smartphone dependency regarding the management of a parking space. Highlighted in this report are key technologies used to track the parking occupancy status, the impact connected vehicles might have on the smart parking industry, as well as how smart parking solutions could help to decrease congestion. The results of this thesis project showed that there are several solutions that could significantly decrease traffic congestion. By aiding the drivers to a parking space, or allowing the driver to pre-book a parking space, the efficiency with regards to time and congestion could be improved. Furthermore, the establishment of electrical and connected vehicles seem to have a crucial impact on the smart parking industry. Parking applications need to adjust their services to be compatible with both types of vehicles. Even though there seem to be many new technologies available and developed, they may not be able to be implemented in the near future. That is why it is important for parking applications to provide a sufficient service with the technology available today. With regards to this, a feature addition was suggested where users are able to filter their search for certain parking spaces, such as filtering by the cheapest or closest parking space. Lastly, a feature for connected vehicles was suggested where the car is able to detect and track which parking operators are operating certain parking spaces. / Begreppet smarta städer, som må ha verkat ouppnåeligt för inte så länge sedan, blir verklighet idag. Bakom begreppet “smart cities” ligger en stor intelligens, nämligen “Internet of Things”, sakernas internet. När befolkningen i städer växer, blir utvecklingen av smarta parkeringslösningar mer relevant och avgörande än någonsin. Ett av de största bekymret för dagens parkeringssätt är trafikstockningar. Förarna åker runt på jakt efter en parkeringsplats vilket både är tidskrävande och bidrar till ytterligare trafikstockningar. I detta examensarbete genomfördes en komparativ analys mellan två parkeringsoperatörer i Sverige, EasyPark och LinPark. En kvalitativ studie i form av intervjuer och en litteraturstudie genomfördes för att ytterligare undersöka och analysera tekniker och metoder som används inom smart parkering idag. De viktigaste problemen som denna avhandling fokuserar på är trängsel på grund av ineffektiva parkeringsåtgärder samt smartphoneberoendet gällande hanteringen av en parkeringsplats. I denna rapport framhålls viktiga teknologier som används för att spåra status för parkeringsplatser, den påverkan anslutna fordon kan ha på smart parking industrin, samt hur smarta parkeringslösningar kan bidra till att minska trängseln. Resultaten av detta examensarbete visade att det finns flera lösningar som kan minska trafikstockningar avsevärt. Genom att guida förare till en parkeringsplats, eller genom att låta föraren förhandsboka en parkeringsplats, kan effektiviteten när det gäller tid och trängsel förbättras. Dessutom verkar etablering av elektriska och anslutna fordon ha en avgörande inverkan på smart parking industrin. Parkeringsapplikationer måste anpassa sina tjänster så att de är kompatibla med alla olika typer av fordon. Även om det verkar finnas många nya teknologier tillgängliga och utvecklade, är de inte implementerbara inom en snar framtid. Det är därför det är viktigt för parkeringsapplikationer att tillhandahålla en tillräckligt effektiv tjänst med den teknik som finns tillgänglig idag. Ett funktionstillägg föreslogs, där användare kan filtrera sin sökning efter vissa typer av parkeringsplatser, till exempel filtrering efter den billigaste eller närmaste parkeringsplatsen. Slutligen föreslogs en funktion för anslutna fordon där bilen kan upptäcka och spåra vilka parkeringsoperatörer som driver vissa parkeringsplatser.

В работе актуализируется проблема эффективности использования современных WEB-технологий при реализации WEB-приложений. Предлагаемый вариант решения позволяет успешно интегрировать стек современных WEB-технологий и применить его в разработке программного комплекса для бронирования и поиска свободного места на парковке. / The thesis updates the problem of the effectiveness of using modern WEB-technologies in the implementation of the WEB user interface, as well as the problem of finding and reserving parking spots in large parking spaces. The offered solution allows to integrate the stack of modern WEB-technologies and apply it in the development of a software package for simple reservation and search of free parking spots.

Le parking intelligent, permettant aux conducteurs d'accéder aux informations de stationnement sur leurs appareils mobiles, réduit les difficultés des usagers. Tout d'abord, nous mettons en lumière la manière de recueillir les informations de parking en introduisant une architecture de réseaux de capteurs multi-saut, et les modèles d'intensité applicative en examinant la probabilité d'arrivées et de départs de véhicules. Puis nous étudions la stratégie de déploiement des réseaux de capteurs et définissons un problème multi-objectifs, puis nous le résolvons sur deux cartes de parking réelles. Ensuite, nous définissons un service Publish-Subscribe pour fournir aux conducteurs des informations pertinentes. Nous illustrons le système dans des réseaux véhiculaires et mobiles et soulignons l'importance du contenu et du contexte du message au conducteur. Afin d'évaluer la résilience du système, nous proposons un modèle Publish-Subscribe étendu et nous l'évaluons dans différentes circonstances imprévues. Notre travail est basé sur la prémisse que les capteurs de parking sont déployés à une grande échelle dans la ville. Nous considérons une vue d'ensemble des services urbains du point de vue de la municipalité. Ainsi, nous faisons la lumière sur deux thèmes principaux: la collecte d'informations sur le déploiement de capteurs et un modèle étendu de Publish-Subscribe. Notre travail donne un guide avant de démarrer un projet de parking intelligent ou tout service urbain similaire en temps réel. Il fournit également une plate-forme d'évaluation valable pour tester des jeux de données plus réalistes, comme des traces de véhicules ou de trafic réseau. / Smart parking, allowing drivers to access parking information through their smart-phone, is proposed to ease drivers' pain. We first spotlight the manner to collect parking information by introducing the multi-hop sensor network architecture, and how the network is formed. We then introduce the traffic intensity models by looking at the vehicle's arrival and departure probabilities, following the heavy-tailed distribution. We study the deployment strategy of wireless on-street parking sensor layouts. We define a multiple-objective problem and solve it with two real street parking maps. In turn, we present a Publish-Subscribe service system to provide good parking information to drivers. We illustrate the system with a vehicular network and point out the importance of content and context of a driver’s message. To evaluate the resilience, we propose an extended Publish-Subscribe model, and evaluate it under different unforeseen circumstances. Our work is based on the premise that large-scale parking sensors are deployed in the city. We look at the whole picture of urban service from viewpoint of the municipality. As such, we shed light on two main topics: the information collection on sensor deployment and an extended version of Publish-Subscribe messaging paradigm. Our work gives a guideline from network-related perspectives for city before launching a smart parking or any similar real-time urban service. It also provides a meaningful evaluation platform for testing more realistic datasets, such as real vehicle traces or network traffic.