1,720,958 research outputs found
Exploiting Traffic Light Coordination and Auctions for Intersection and Emergency Vehicle Management in a Smart City Mixed Scenario
Get PDFIoT (Internet-of-Things)-powered devices can be exploited to connect vehicles to smart city infrastructure, allowing vehicles to share their intentions while retrieving contextual information about diverse aspects of urban viability. In this paper, we place ourselves in a transient scenario in which next-generation vehicles that are able to communicate with the surrounding infrastructure coexist with traditional vehicles with limited or absent IoT capabilities. We focus on intersection management, in particular on reusing existing traffic lights empowered by a new management system. We propose an auction-based system in which traffic lights are able to exchange contextual information with vehicles and other nearby traffic lights with the aim of reducing average waiting times at intersections and consequently overall trip times. We use bid propagation to improve standard vehicle trip times while allowing emergency vehicles to free up the way ahead without needing ad hoc system for such vehicle, only an increase in their budget. The proposed system is then tested against two baselines: the classical Fixed Time Control system currently adopted for traffic lights, and an auction strategy that does not exploit traffic light coordination. We performed a large set of experiments using the well known MATSim transport simulator on both a synthetic Manhattan map and on a map we built of an urban area located in Modena, Northern Italy. Our results show that the proposed approach performs better than the classical fixed time control system and the auction strategy that does not exploit coordination among traffic lights
About auction strategies for intersection management when human-driven and autonomous vehicles coexist
No full textAutonomous vehicles are appearing in our streets, and will soon populate our transportation infrastructures, which must be equipped with appropriate sensors and actuators in order to manage vehicles in a fruitful way. Besides the infrastructures, appropriate algorithms must be defined in order to coordinate the vehicles and to enable them to exploit the resources in a fair yet effective way. In the immediate future, autonomous vehicles must coexist human-driven vehicles, and this transitory scenario poses several challenges in coordinating both kinds to exploit street resources. One of these resources, whose management is quite challenging, is represented by intersections: vehicles come and aim at passing the intersection, often as soon as possible, but they must compete with other vehicles having the same aim. A possible approach that has been used in literature to this problem uses auction based mechanisms. In this paper, we place ourselves in the above-mentioned transitory scenario in which both human-driven and autonomous vehicles will compete to cross intersections, and we investigate the effectiveness of auction-based mechanism to coordinate vehicles at intersections. We devise some simple auction policies, and assume vehicle coordination strategies that are suitable also for human drivers. Our results lead us to believe that, under these assumptions, simple auction mechanisms do not introduce advantages for what concern traveling times as they do in the case of exclusively autonomous vehicles
GPU implementation of the Frenet Path Planner for embedded autonomous systems: A case study in the F1tenth scenario
Get PDFAutonomous vehicles are increasingly utilized in safety-critical and time-sensitive settings like urban environments and competitive racing. Planning maneuvers ahead is pivotal in these scenarios, where the onboard compute platform determines the vehicle's future actions. This paper introduces an optimized implementation of the Frenet Path Planner, a renowned path planning algorithm, accelerated through GPU processing. Unlike existing methods, our approach expedites the entire algorithm, encompassing path generation and collision avoidance. We gauge the execution time of our implementation, showcasing significant enhancements over the CPU baseline (up to 22x of speedup). Furthermore, we assess the influence of different precision types (double, float, half) on trajectory accuracy, probing the balance between completion speed and computational precision. Moreover, we analyzed the impact on the execution time caused by the use of Nvidia Unified Memory and by the interference caused by other processes running on the same system. We also evaluate our implementation using the F1tenth simulator and in a real race scenario. The results position our implementation as a strong candidate for the new state-of-the-art implementation for the Frenet Path Planner algorithm
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Algoritmi di controllo, percezione e coordinamento per advanced driver-assistance system: implementazioni e simulazioni ottimizzate
No full textThe future of urban mobility is undergoing changes with the development of intelligent cities and the increased use of autonomous vehicles. The transition to this new paradigm is a gradual process over several years or decades, but progress has been made through the implementation of smart sensors and communication infrastructure. The development of Advanced Driver-Assistance Systems (ADAS) with growing autonomy is also in progress.
In this thesis, two main aspects are addressed: coordination algorithms to manage the smart city traffic flow and the perception-control pipeline of autonomous vehicles with specific emphasis on the localization and planning phases.
With regards to the first aspect, several novel algorithms are proposed that exploit the new smart city capabilities to address typical problems such as Traffic Lights and Intersection Management, Parking Management, and Emergency Vehicles Management. The work proposed in this thesis is a study of the current situation in which autonomous or able-to-communicate vehicles and traditional vehicles that are not able to communicate with city infrastructure co-exist. This is a crucial aspect since mixing ADAS and traditional vehicles impacts the algorithm design.
The proposed algorithms are tested in a simulated scenario in order to study unexpected behaviors since traffic flow is a complex system and some events can trigger unpredictable consequences. The results show that the proposed algorithms improve the city's livability by decreasing the waiting time at traffic lights, reducing the parking search time, and the emergency vehicle response time.
In regards to the localization and planning stages, the emphasis is placed on the execution time of the algorithms, as it is a critical aspect. If the perception and control pipeline takes too long, the intended maneuver may become outdated due to changes in the environment, potentially causing safety risks. In light of this, novel implementations for localization and planning algorithms are proposed, which make extensive use of the GPU as an accelerator in order to reduce computational time. The GPU is leveraged to parallelize the algorithm and minimize memory access. Additionally, the use of different floating-point precision types is investigated to assess the impact on the results.
The proposed implementations of the ORB-SLAM algorithm for the localization phase and the Frenet Path Planner algorithm for the planning phase show a consistent speedup, compared to the previously published CPU-based implementations of the algorithms.Il futuro della mobilità urbana sta cambiando con lo sviluppo di città intelligenti e l'aumento dell'uso di veicoli autonomi. Il passaggio a questo nuovo paradigma è un processo graduale che dura diversi anni o decenni, ma sono stati fatti progressi grazie all'implementazione di sensori intelligenti e infrastrutture di comunicazione. È in corso anche lo sviluppo di sistemi avanzati di assistenza alla guida (ADAS) con crescente autonomia.
In questa tesi si affrontano due aspetti principali: gli algoritmi di coordinamento per gestire il flusso di traffico delle smart city e la pipeline di percezione-controllo dei veicoli autonomi, con particolare attenzione alle fasi di localizzazione e pianificazione.
Per quanto riguarda il primo aspetto, vengono proposti diversi algoritmi innovativi che sfruttano le nuove funzionalità delle smart city per affrontare problemi tipici come la gestione dei semafori e delle intersezioni, la gestione dei parcheggi e la gestione dei veicoli di emergenza. Il lavoro proposto in questa tesi è uno studio della situazione attuale in cui coesistono veicoli autonomi o in grado di comunicare e veicoli tradizionali che non sono in grado di comunicare con le infrastrutture cittadine. Si tratta di un aspetto cruciale, poiché la commistione tra veicoli ADAS e tradizionali influisce sulla progettazione degli algoritmi.
Gli algoritmi proposti sono stati testati in uno scenario simulato per studiare comportamenti inaspettati, poiché il flusso del traffico è un sistema complesso e alcuni eventi possono innescare conseguenze imprevedibili. I risultati mostrano che gli algoritmi proposti migliorano la vivibilità della città diminuendo il tempo di attesa ai semafori, riducendo il tempo di ricerca del parcheggio e il tempo di risposta dei veicoli di emergenza.
Per quanto riguarda le fasi di localizzazione e pianificazione, l'enfasi è posta sul tempo di esecuzione degli algoritmi, in quanto si tratta di un aspetto critico. Se la pipeline di percezione e controllo richiede troppo tempo, la manovra prevista può diventare obsoleta a causa dei cambiamenti dell'ambiente, causando potenzialmente rischi per la sicurezza. Alla luce di ciò, vengono proposte nuove implementazioni per gli algoritmi di localizzazione e pianificazione, che fanno ampio uso della GPU come acceleratore per ridurre i tempi di calcolo. La GPU viene sfruttata per parallelizzare l'algoritmo e ridurre al minimo l'accesso alla memoria. Inoltre, viene analizzato l'uso di diversi tipi di precisione in virgola mobile per valutare l'impatto sui risultati.
Le implementazioni proposte dell'algoritmo ORB-SLAM per la fase di localizzazione e dell'algoritmo Frenet Path Planner per la fase di pianificazione mostrano una velocità consistente, rispetto alle implementazioni degli algoritmi basati su CPU pubblicate in precedenza
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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