Vehicular communication is the enabling technology for the development of the intelligent transportation systems (ITS), which aims to improve the efficiency and safety of transportation. It can be used for a variety of useful applications such as adaptive traffic control, coordinated braking, emergency messaging, peer-to-peer networking for infotainment services and automatic toll collection etc... Accurate yet simple models for vehicular networks are required in order to understand and optimize their operation. For reliable communication between vehicles, the spectrum access is coordinated via carrier sense multiple access (CSMA) protocol. Existing models either use a simplified network abstraction and access control scheme for analysis or depend on simulation studies. Therefore it is important to develop an analytical model for CSMA coordinated communication between vehicles. In the first part of the thesis, stochastic geometry is exploited to develop a modeling framework for CSMA coordinated inter-vehicle communication (IVC) in a multi-lane highway scenario. The performance of IVC is studied in multi-lane highways taking into account the inter-lane separations and the number of traffic lanes and it is shown that for wide multi-lane highways, the line abstraction model that is widely used in literature loses accuracy and hence the analysis is not reliable. Since the analysis of CSMA in the vehicular setting makes the analysis intractable, an aggressive interference approximation and a conservative interference approximation is proposed for the probability of transmission success. These approximations are tight in the low traffic and high traffic densities respectively. In the subsequent part of the thesis, the developed model is extended to multi-hop IVC because several vehicular applications require going beyond the local communication and efficiently disseminate information across the roads via multi-hops. Two well-known greedy packet forwarding schemes are studied, that impose different tradeoffs between per-hop transmission success probability and forward packet progress, namely, the most forward with fixed radius (MFR) and the nearest with forward progress (NFP). In particular, a tractable and accurate modeling framework is developed to characterize the per-hop transmission success probability and the average forward progress for vehicular networks in a multi-lane highway setup. The developed model reveals the interplay between the spectrum sensing threshold of the CSMA protocol and the packet forwarding scheme. A new performance metric is defined, denoted as the aggregate packet progress (APP), which is a dimensionless quantity that captures the tradeoffs between the spatial frequency reuses efficiency, the per-hop transmission success probability, and the per-hop forward progress of the packets. To this end, in contrary to existing studies, the results show that with the proper manipulation of CSMA threshold, the MFR achieves the highest APP.

This study examines the safety effects of the improvements made on multi-lane arterials. The improvements were divided into two categories 1) corridor level improvements, and 2) intersection improvements. Empirical Bayes method, which is one of the most accepted approaches for conducting before-after evaluations, has been used to assess the safety effects of the improvement projects. Safety effects are estimated not only in terms of all crashes but also rear-end (most common type) as well as severe crashes (crashes involving incapacitating and/or fatal injuries) and also angle crashes for intersection improvements. The Safety Performance Functions (SPFs) used in this study are negative binomial crash frequency estimation models that use the information on ADT, length of the segments, speed limit, and number of lanes for corridors. And for intersections the explanatory variables used are ADT, number of lanes, speed limit on major road, and number of lanes on the minor road. GENMOD procedure in SAS was used to develop the SPFs. Corridor SPFs are segregated by crash groups (all, rear-end, and severe), length of the segments being evaluated, and land use (urban, suburban and rural). The results of the analysis show that the resulting changes in safety following corridor level improvements vary widely. Although the safety effect of projects involving the same type of improvement varied, the overall effectiveness of each of the corridor level improvements were found to be positive in terms of reduction in crashes of each crash type considered (total, severe, and rear-end) except for resurfacing projects where the total number of crashes slightly increased after the roadway section is resurfaced. Evaluating additional improvements carried out with resurfacing activities showed that all (other than sidewalk improvements for total crashes) of them consistently led to improvements in safety of multilane arterial sections. It leads to the inference that it may be a good idea to take up additional improvements if it is cost effective to do them along with resurfacing. It was also found that the addition of turning lanes (left and/or right) and paving shoulders were two improvements associated with a project�s relative performance in terms of reduction in rear-end crashes. No improvements were found to be associated with a resurfacing project�s relative performance in terms of changes in (i.e., reducing) severe crashes. For intersection improvements also the individual results of each project varied widely. Except for adding turn lane(s) all other improvements showed a positive impact on safety in terms of reducing the number of crashes for all the crash types (total, severe, angle, and rear-end) considered. Indicating that the design guidelines for this work type have to be revisited and safety aspect has to be considered while implementing them. In all it can be concluded that FDOT is doing a good job in selecting the sites for treatment and it is very successful in improving the safety of the sections being treated although the main objective(s) of the treatments are not necessarily safety related.

Reduction of crash occurrence on the various roadway locations (mid-block segments; signalized intersections; un-signalized intersections) and the mitigation of injury severity in the event of a crash are the major concerns of transportation safety engineers. Multi lane arterial roadways (excluding freeways and expressways) account for forty-three percent of fatal crashes in the state of Florida. Significant contributing causes fall under the broad categories of aggressive driver behavior; adverse weather and environmental conditions; and roadway geometric and traffic factors. The objective of this research was the implementation of innovative, state-of-the-art analytical methods to identify the contributing factors for crashes and injury severity. Advances in computational methods render the use of modern statistical and machine learning algorithms. Even though most of the contributing factors are known a-priori, advanced methods unearth changing trends. Heuristic evolutionary processes such as genetic programming; sophisticated data mining methods like conditional inference tree; and mathematical treatments in the form of sensitivity analyses outline the major contributions in this research. Application of traditional statistical methods like simultaneous ordered probit models, identification and resolution of crash data problems are also key aspects of this study. In order to eliminate the use of unrealistic uniform intersection influence radius of 250 ft, heuristic rules were developed for assigning crashes to roadway segments, signalized intersection and access points using parameters, such as 'site location', 'traffic control' and node information. Use of Conditional Inference Forest instead of Classification and Regression Tree to identify variables of significance for injury severity analysis removed the bias towards the selection of continuous variable or variables with large number of categories. For the injury severity analysis of crashes on highways, the corridors were clustered into four optimum groups. The optimum number of clusters was found using Partitioning around Medoids algorithm. Concepts of evolutionary biology like crossover and mutation were implemented to develop models for classification and regression analyses based on the highest hit rate and minimum error rate, respectively. Low crossover rate and higher mutation reduces the chances of genetic drift and brings in novelty to the model development process. Annual daily traffic; friction coefficient of pavements; on-street parking; curbed medians; surface and shoulder widths; alcohol / drug usage are some of the significant factors that played a role in both crash occurrence and injury severities. Relative sensitivity analyses were used to identify the effect of continuous variables on the variation of crash counts. This study improved the understanding of the significant factors that could play an important role in designing better safety countermeasures on multi lane highways, and hence enhance their safety by reducing the frequency of crashes and severity of injuries. Educating young people about the abuses of alcohol and drugs specifically at high schools and colleges could potentially lead to lower driver aggression. Removal of on-street parking from high speed arterials unilaterally could result in likely drop in the number of crashes. Widening of shoulders could give greater maneuvering space for the drivers. Improving pavement conditions for better friction coefficient will lead to improved crash recovery. Addition of lanes to alleviate problems arising out of increased ADT and restriction of trucks to the slower right lanes on the highways would not only reduce the crash occurrences but also resulted in lower injury severity levels.

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Dissertation describes new methodology of design turbo-roundabouts in Czech Republic. Especially innovative is approach to the design of traffic lanes with regards to standard vehicles and widening of traffic lanes according to their dimensions. Innovative is also approach to road signs, where details of current signs are modified, however, these details are important for drivers’ better understanding while driving through turbo-roundabouts. Dissertation fills legislative, but also technical, blank spot during turbo-roundabouts design and I believe that it will benefit particularly designers of these intersections.

[ES] Desde hace aproximadamente dos décadas, las ayudas tecnológicas a la conducciónn han ido creciendo a un ritmo vertiginoso con la intención de hacer estos sistemas más eficientes y seguros. Estas ayudas a la conducción han ido cubriendo fallos que los investigadores denominan "conducción errática" ó "comportamientos inseguros al volante" y que son decisiones arbitrarias tomadas por un conductor humano, que ponen en peligro a todos los usuarios de la carretera. Estas malas decisiones, sumadas al creciente número de viajes en coche en una ciudad hoy en día (post pandemia), muestran la necesidad de seguir haciendo propuestas tecnológicas, enfocadas a donde se producen interacciones más complejas entre vehículos; por ejemplo, una intersección en hora punta. Los desarrollos en ayudas a la conducción se han orientado en dos temas: el primero sobre la automatización de la conducción (Sistemas Avanzados de Asistencia al Conductor - ADAS y Vehículos Automatizados - AV) y el segundo sobre la gestión del tráfico vial (algoritmos centralizados o distribuidos para el control del tráfico). Aunque en la actualidad hay varias empresas automotrices y centros de investigación trabajando en los dos temas, y en especial en algunos casos eliminando de la ecuación el comportamiento humano, todavía hay carencias en las configuraciones, para que un vehículo autónomo sea capaz de tomar decisiones óptimas, frente a todas las posibles condiciones disponibles en un tráfico vial. Ahora bien, y teniendo en cuenta los dos temas antes mencionados sobre los desarrollos en ayudas a la conducción, los investigadores prevén a grandes rasgos, que para alcanzar mayores niveles de conducción autónoma en la próxima década, es necesario estudiar cómo hacer más eficientes las interacciones autónomas entre vehículos. Por ello, las intersecciones viales son un ejemplo clave, donde es posible analizar casos de interacciones de alta complejidad entre vehículos, ya que se trata de una parte de la infraestructura vial, donde los vehículos comparten carriles, vías, cruces o cambios de carril a voluntad, y que podría generar colisiones en puntos de conflicto y retrasos en los desplazamientos si no existe una cooperación adecuada. De esta forma, en esta tesis se propone una serie de algoritmos distribuidos para el control del tráfico en intersecciones, basados en el intercambio de comunicaciones entre vehículos autónomos (interacciones locales) cercano a las intersecciones y donde se muestran comportamientos emergentes en el tráfico, resultando en cruces de forma cooperativa, segura y eficiente, desde bajas a altas densidades de tráfico vehicular en las intersecciones. Esta investigación se desarrolla utilizando simuladores de tráfico vial, con calles estilo Manhattan; primero implementando escenarios menos complejos con calles urbanas de un carril, y luego incrementando la complejidad con múltiples carriles. / [CA] Des de fa aproximadament dues dècades, les ajudes tecnològiques a la conducció han anat creixent a un ritme vertiginós amb la intenció de fer aquests sistemes més eficients i segurs. Aquestes ajudes a la conducció han anat cobrint fallades que els investigadors denominen "conducció erràtica" o "comportaments insegurs al volant" i que són decisions arbitràries preses per un conductor humà, que posen en perill a tots els usuaris de la carretera. Aquestes males decisions, sumades al creixent nombre de viatges en cotxe en una ciutat avui dia (post pandèmia), mostren la necessitat de seguir fent propostes tecnològiques, enfocades a on es produeixen interaccions més complexes entre vehicles; per exemple, una intersecció en hora punta. Els desenvolupaments en ajudes a la conducció s'han orientat en dos temes: el primer sobre l'automatització de la conducció (Sistemes Avançats d'Assistència al Conductor - ADAS i Vehicles Automatitzats - AV) i el segon sobre la gestió del trànsit vial (algoritmes centralitzats o distribuïts per al control del trànsit). Encara que actualment hi ha diverses empreses automobilístiques i centres de recerca treballant en els dos temes, i en especial en alguns casos eliminant de l'equació el comportament humà, encara hi ha mancances en les configuracions, perquè un vehicle autònom siga capaç de prendre decisions òptimes, davant totes les possibles condicions disponibles en un trànsit vial. Ara bé, i tenint en compte els dos temes abans esmentats sobre els desenvolupaments en ajudes a la conducció, els investigadors preveuen a grans trets, que per assolir majors nivells de conducció autònoma en la propera dècada, és necessari estudiar com fer més eficients les interaccions autònomes entre vehicles. Per això, les interseccions vials són un exemple clau, on és possible analitzar casos d'interaccions d'alta complexitat entre vehicles, ja que es tracta d'una part de la infraestructura vial, on els vehicles comparteixen carrils, vies, creus o canvis de carril a voluntat, i que podria generar col·lisions en punts de conflicte i retards en els desplaçaments si no existeix una cooperació adequada. D'aquesta manera, en aquesta tesi es proposa una sèrie d'algoritmes distribuïts per al control del trànsit en interseccions, basats en l'intercanvi de comunicacions entre vehicles autònoms (interaccions locals) properes a les interseccions i on es mostren comportaments emergents en el trànsit, resultant en creus de forma cooperativa, segura i eficient, des de baixes a altes densitats de trànsit vehicular en les interseccions. Aquesta investigació es desenvolupa utilitzant simuladors de trànsit vial, amb carrers estil Manhattan; primer implementant escenaris menys complexos amb carrers urbans d'un carril, i després incrementant la complexitat amb múltiples carrils. / [EN] Since a couple of decades, the technological driving aids have gone growing at a dizzying pace with the intention of making these systems more efficient and safe. These driving aids have been covering failures that the researchers name "erratic driving" or "unsafe driving behaviors" and are arbitrary decisions taken by a human driver which endanger all road users. These bad decisions in addition to the increasing number of driving commutes in a city nowadays (post pandemic), show the need to continue doing technological proposals focused on where there are more complex interactions between vehicles when density increases; for instance, an intersection in rush hour. The developments in driving aids have been orientated in two topics: the first driving automation (Advanced Driver Assistance Systems - ADAS and Automated Vehicles - AV) and the second road traffic management (centralized or distributed algorithms to traffic control). Although there are currently several automotive companies and research centers working in the two topics, and in special in some cases removing the equation the human behavior, there are still lacks in the configurations for an vehicle autonomous be able to make optimal decisions front to all possible conditions available in a road traffic. Now, and take into account the two topics aforementioned about driving aids developments, researchers broadly envisage that in order to reach autonomous driving levels higher (first topic) in the next decade, is necessary to study how to do autonomous vehicle interactions (second topic) more efficient. Therefore, road intersections are an instance where it is possible to analyse cases of highly complexity interactions between vehicles, because it is a part of road infrastructure where the vehicles sharing lanes, paths, crossings or lane changes at will and it could generate collisions on conflict points and time delay in the commutes if there is not an appropriate cooperation. Hence, this thesis proposes a series of distributed algorithms to traffic control on intersections, based on interchange of communications between autonomous vehicles (local interactions) near to the intersections that show emergent behaviors to crossing cooperative, safe way and efficiency with high densities the traffic system on intersections. This research is developed using simulators with Manhattan-style streets; first implementing scenarios less complex with one-lane city streets and then increase the complexity with multiple-lanes. / González Pinzón, CL. (2024). Distributed Intersection Management Algorithms for Autonomous Vehicles [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/204406