<p>Pre obavljanja levog manevra, sa prioritetnog prilaza TWSC nesignalisane raskrsnice, vozač procenjuje interval koji se javlja u konfliktnom toku i bira onaj interval koji mu je najviše prihvatljiv. Vreme koje je potrebno za procenu prihvatljivog intervala je predstavljeno u vidu vremena čekanja u opsluzi vozila na raskrsnici. Sa pojavom prihvatljivog intervala, vreme čekanja u opsluzi vozila se završava, i tada počinje vreme za izvođenje manevra levog skretanja. Odluka o momentu početka izvođenja manevra levog skretanja je subjektivna i zasniva se na proceni vozača. Ispravna subjektivna procena uvek rezerviše bezbednosno vreme. U ovoj disertaciji je predstavljen razvoj detaljnog matematičkog postupka za proračun bezbednosnog vremena. Merenja na nesignalisanim raskrsnicama su dokazala primenjivost predloženog modela, mogućnost proračuna subjektivnog bezbednosnog vremena i visoko učešće bezbednosnog vremena u kritičnom intervalu (oko jedne trećine). Dobijeni rezultati su visoko saglasni sa HCM.</p> / <p>Before the left turn manoeuvre, from priority approach at TWSC unsignalized intersection, the driver estimates the interval occurring in the conflict flow and chooses the one which is most acceptable for him. The time required for evaluation of acceptable interval is presented by the service waiting time of vehicles at an intersection. With the appearance of an acceptable interval, service waiting time for vehicle ends, and then starts a time for performance of left turn manoeuvre. A decision about the moment of starting left turn manoeuvre is subjective and based on a driver&rsquo;s estimate. Correct subjective evaluation always reserves the safety time. This dissertation presents development of a detailed mathematical procedure for calculation form of safety time. Measurements at unsignalized intersections are proven applicability of the proposed model, possibility of calculation subjective safety time and high participation of safety time in critical gap (about one-third). The obtained results are highly consistent with HCM.</p>

Le déploiement des futurs véhicules autonomes promet d'avoir un impact socio-économique majeur, en raison de leur promesse d'être à la fois plus sûrs et plus efficaces que ceux conduits par des humains. Afin de satisfaire à ces attentes, la capacité des véhicules autonomes à planifier des trajectoires sûres et à manœuvrer efficacement dans le trafic sera capitale. Cependant, le problème de planification de trajectoire au milieu d'obstacles statiques ou mobiles a une combinatoire forte qui est encore aujourd'hui problématique pour les meilleurs algorithmes.Cette thèse explore une nouvelle approche de la planification de mouvement, basée sur l'utilisation de la notion de décision de conduite comme guide pour structurer le problème de planification en vue de faciliter sa résolution. Cette approche peut trouver des applications pour la conduite coopérative, par exemple pour coordonner plusieurs véhicules dans une intersection non signalisée, ainsi que pour la conduite autonome où chaque véhicule planifie sa trajectoire. Dans le cas de la conduite coopérative, les décisions correspondent au choix d'un ordonnancement des véhicules qui peut être avantageusement encodé comme un graphe. Cette thèse propose une représentation similaire pour la conduite autonome, où les décisions telles que dépasser ou non un véhicule sont nettement plus complexes. Une fois la décision prise, il devient aisé de déterminer la meilleure trajectoire y correspondant, en conduite coopérative comme autonome. Cette approche basée sur la prise de décision peut permettre d'améliorer la robustesse et l'efficacité de la planification de trajectoire, et ouvre d'intéressantes perspectives en permettant de combiner des approches mathématiques classiques avec des techniques plus modernes d'apprentissage automatisé. / The deployment of future self-driving vehicles is expected to have a major socioeconomic impact due to their promise to be both safer and more traffic-efficient than human-driven vehicles. In order to live up to these expectations, the ability of autonomous vehicles to plan safe trajectories and maneuver efficiently around obstacles will be paramount. However, motion planning among static or moving objects such as other vehicles is known to be a highly combinatorial problem, that remains challenging even for state-of-the-art algorithms. Indeed, the presence of obstacles creates exponentially many discrete maneuver choices, which are difficult even to characterize in the context of autonomous driving. This thesis explores a new approach to motion planning, based on using this notion of driving decisions as a guide to give structure to the planning problem, ultimately allowing easier resolution. This decision-based motion planning approach can find applications in cooperative driving, for instance to coordinate multiple vehicles through an unsignalized intersection, as well as in autonomous driving where a single vehicle plans its own trajectory. In the case of cooperative driving, decisions are known to correspond to the choice of a relative ordering for conflicting vehicles, which can be conveniently encoded as a graph. This thesis introduces a similar graph representation in the case of autonomous driving, where possible decisions -- such as overtaking the vehicle at a specific time -- are much more complex. Once a decision is made, planning the best possible trajectory corresponding to this decision is a much simpler problem, both in cooperative and autonomous driving. This decision-aware approach may lead to more robust and efficient motion planning, and opens exciting perspectives for combining classical mathematic programming algorithms with more modern machine learning techniques.

The main theme of the master’s thesis is optimization of traffic on the signalized intersection on náměstí Svobody in Kunovice. Here is project of new signal plans with minimal conversions at the crossroads to maximal lifetime of signalized intersection.

The diploma thesis solves construction of new public transport stops and relocation of tramway tracks route which follows new traffic organization in the area of Veveří, Šumavská, Kounicova and Nerudova streets in the city Brno. The project aims for an improvement of the public transportation level of service and of the quality of pedestrian routes in the area. The focus also lies on adjusting of routes of the private motorised transport with the goal of traffic calming in the Veveří street, on including cycling infrastructure into the plan and finally the emphasis is put on the overall improvement of the value of the area through urban planning. Part of the project are to one side public transport stops and tramway tracks and to the other side a planning of a park, defining of an area for building public amenities and planning a new underground car park on Akademické square. At the same time, the preservation of green space and of the character of tree avenues with their expansion is taken into consideration.

The diploma thesis is dealing with design of junction reconstruction in the framework of anurbanistic study. The junction is located in Slavkov village, Zlín region, where the I/54, II/498 and III/05417 roads intersect each other. The aim of the project is to design well-arranged intersection of three different types of roads and create safe, comfortable and pedestrian friendly crossroad. There are two basic versions. The modification of junction was elected as the most suitable version, which is designed and specified by technical report and drawings.

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Unmanned aerial vehicles are becoming more popular in today’s society, which results in the rise of laws intended to maintain safety. To abide by these, while allowing the technology to expand, functioning path-planning algorithms are required.This also includes having methods for detecting and managing obstacles. This project aims to improve an existing path-planning algorithm that is based on A* and implemented in Python.The solution consisted of using functions for finding polytopeintersection,as well as optimizing the collision avoidance and the search algorithm. In addition to that, realistic constraints were implemented on the generated trajectory in order to reflect real-life limitations. The results demonstrated that the paths were always feasible, with respect to input and position constraints. The program’s computation time was also reduced up to 89% of the original run-time. There is, however, still room for improvement since the original code generated a shorter path for the three scenarios it was created for. On the other hand,the improved algorithm could handle a new scenario, which the original code failed to do. / Obemannade flygfarkoster blir alltmer vanliga i dagens samhälle, vilket resulterar i uppkomsten av nya lagar ämnade åt att upprätthålla säkerhet. För att förhålla sig till dessa, samtidigt som teknologin tillåts expandera, krävs fungerande vägplaneringsalgoritmer. Där ingår det även att ha metoder för att upptäcka och hantera hinder. Detta projekt syftar till att förbättra en befintlig vägplaneringsalgoritm som är baserad på A* och implenterad i Python. Lösningsmetoden bestod av att använda inbyggda Python-funktioner ämnade åt att finna skärningar mellan polytoper, samt optimera kollisionshantering och sökalgoritmen. Dessutom infördes realistiska krav på den framställda vägen i syfte om att reflektera verlighetens begränsningar. Resultatet visade att vägarna alltid var genomförbara, med avseende på inmatningsoch positionsrelaterade villkor. Programmets beräkningstid hade även reducerats upptill 89% av den ursprungliga körtiden. Det finns dock utrymme för förbättringar då den ursprungliga koden generar en kortare väg för de tre scenarion den tillverkades för. Däremot kinde den förbättrade algoritmen hantera ett nytt scenario, en ursprungliga koden misslyckades med. / Kandidatexjobb i elektroteknik 2022, KTH, Stockholm

Movements of cyclists and m.otor vehicles at intersections involve a wide variety of potential conflicting interactions. In Australia, the high numbers of motor vehicles, particularly light passenger vehicles, mixed with cyclists results in many bicycle-light passengervehicle (LPV) crashes (3,135 crashes during 2002-2014). About 68% of cyclist deaths at Australian intersections in 2016 were due to crashes between bicycles and LPVs (DITRLDG, 2016). The high number ofLPV crashes among fatalities among cyclists is an increasing safety concem. When an LPV collides with a cyclist, the resulting impact forces in.tluence the probability of cyclist injury severity outcom.e. Therefore, the goa1 at intersections should be to understand whether and which particular crash patterns are more injurious, in order to better inform approaches to reduce the impact forces to levels that do not result in severe injury outcomes. To examine how crash pattem (or mechanism) influences the injury severity of cyclists in bicycle-motor vehicle crashes at intersections, researchers typically describe the crash mechanism in terms of crash types, such as angle crashes, head--on crashes, rear-end crashes, and sideswipe crashes (e.g., Kim et al., 2007; Pai, 2011 ). While crash types explain crash mechanisms to some extent, this study hypothesiz.es that the trajectories of the crash involved vehicles may provide additional information because they better capture the movements of the vehicles prior to collision. Furthermore, it is argued that injury pattem might be in.tluenced by vehicle travel direction and manoeuvre (Isaksson-Hellman and Wemeke, 2017). For example, when a car is moving straight ahead it is likely to have a higher speed than when it is turning, and if cyclists are struck at a higher impact speed, they tend to sustain more severe injury (Badea-Romero and Lenard, 2013). While many studies have evaluated the association between cyclist injwy severity and crash types, the factors that might influence cyclist injury severity related to trajectory types (vehicle movement and travel direction) have not yet been thoroughly investigated. This study aims to examine the factors associated with cyclists' injury severity for 'trajectory types• compared with the typically used 'crash types' at intersections.

The Interactive Highway Safety Design Model (IHSDM) is a suite of software developed by the Federal Highway Administration (FHWA) for monitoring and analyzing two-lane rural highways in the United States. As IHSDM is a fairly "young" program a limited amount of research has been conducted to evaluate its practicability and reliability. To determine if IHSDM can be adopted into the engineering decision making process in Utah, a study was conducted under the supervision of the Utah Department of Transportation (UDOT) to evaluate its applicability to audit safety of two-lane rural highways in Utah. IHSDM consists of six modules: Policy Review Module (PRM), Crash Prediction Module (CPM), Design Consistency Module (DCM), Traffic Analysis Module (TAM), Intersection Review Module (IRM), and Driver/Vehicle Module (DVM) (still under construction). Among the six modules, two were chosen for evaluation because of their applicability to audit safety of the two-lane rural highways in Utah, namely CPM and IRM. For the evaluation of the CPM, three two-lane rural highway sections were selected. The results of this evaluation show that the CPM can produce reasonably reliable crash predictions if appropriate input data, especially alignment data, reflect the existing conditions at reasonable accuracy and engineering judgment is used. Using crash records available from UDOT's crash database and CPM's crash prediction capability, UDOT's traffic and safety engineers can locate "hot spots" for detailed safety audit, thus making the safety audit task more focused and effective. Unlike the CPM, the outputs of the IRM are qualitative and include primarily suggestions and recommendations. They will help the traffic and safety engineers identify what to look for as they visit the sites, such as a lack of stopping sight distance and a lack of passing sight distance. The interpretation of the IRM requires knowledge of various aspects of highway design, familiarity with A Policy on Geometric Design of Highways and Streets by the American Association of State Highway and Transportation Officials (AASHTO), and experience in traffic engineering. Based on the findings of the study, it is concluded that the CPM and IRM of IHSDM could be a useful tool for engineering decision-making during safety audits of two-lane rural highways. But the outputs from these modules demand knowledge and experience in highway design. It is recommended that the other modules of IHSDM be tested to fully appreciate the capability of IHSDM. The software can be a knowledgebased program that can help novice engineers to learn how to design safe two-lane rural highways.