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Automotive transport unavoidably raises safety concerns for drivers, passengers, and indeed, all road users alike. Advancements in vehicle safety technologies have come a long way, and have had a major impact on the reduction of road-related accidents and fatalities. However, as the push towards autonomous vehicle systems gains momentum, assumptions must be avoided about the global application of such technologies.This paper proposes an idea for a road safety alert system, which is realized in the form of small-scale prototype, subsequently tested and evaluated to study its theoretical application to real world scenarios. The system is geared towards developing regions of the world where a reduction in road-related accidents and death is needed most. Reviews of various existing and proposed safety systems within the realm of Intelligent Transportation Systems (ITS) are conducted, with a focus on Vehicle-to-Vehicle (V2V) and non-V2V applications, which are compared to and contrasted with our proposal.We hope to foster further discussion and research into suitable technologies and their application, in regions of the world that require a different approach when trying to realistically reduce the consistent destructive trend of accidents and fatalities when humans are still behind the wheel.

The need for sustainable transportation solutions is urgent as the demand for mobility of goods and people is expected to multiply in the upcoming decades. One promising solution is truck platooning, which shows great potential in reducing the fuel consumption and operational costs of trucks.  In order to utilize the benefits of truck platooning to the fullest, trucks with different routes in a transportation network need coordination to efficiently meet and form platoons. This thesis addresses platoon coordination when trucks form  platoons at hubs, where some trucks need to wait for others in order to meet, and there is a reward for platooning and a cost for waiting. Three contributions on the topic platoon coordination are presented in this thesis. In the first contribution, we consider platoon coordination among trucks that have pre-defined routes in a network of hubs, and the travel times are either deterministic or stochastic. The trucks are owned by competing transportation companies, and each truck decides on its waiting times at hubs in order to optimize its own operational cost. We consider a group of trucks to form a platoon if it departs from a hub and enters the road at the same time. The strategic interaction among trucks when they coordinate for platooning is modeled by non-cooperative game theory, and the Nash equilibrium is considered as the solution concept when the trucks make their decisions at the beginning of their journeys. In case of stochastic travel times, we also develop feedback-based solutions wherein trucks repeatedly update their decisions. We show in a simulation study of the Swedish transportation network that the feedback-based solutions achieve platooning rates up to 60 %. In the second contribution, we propose models for sharing the platooning profit among platoon members. The platooning benefit is not equal for all trucks in a platoon; typically, the lead truck benefits less than its followers. The incentive for transportation companies to cooperate in platooning may be low unless the profit is shared. We formulate platoon coordination games based on profit-sharing models, and in a simulation of a single hub, the outcomes of the platoon coordination games are evaluated. The evaluation shows that the total profit achieved when the trucks aim to maximize their own profits, but the platooning benefit is evened out among platoon members, is nearly as high as when each truck aims to maximize the total profit in the platooning system.  In the last contribution, we study a problem where trucks arrive to a hub according to a stochastic arrival process. The trucks do not share a priori information about their arrivals; this may be sensitive information to share with others. A coordinator decides, based on the statistical distribution of arrivals, when to release the trucks at the hub in the form of a platoon. Under the assumption that the arrivals are independent and identically distributed, we show that it is optimal to release the trucks at the hub when the number of trucks exceeds a certain threshold. This contribution shows that simple and dynamic coordination approaches can obtain a high profit from platooning, even under high uncertainty and limited a priori information. / Under de kommande decennierna förväntas efterfrågan på transport av varor och passagerare mångfaldigas, vilket innebär att behovet av hållbara transportlösningar är brådskande. En lovande lösning är konvojkörning, som visar stor potential att minska bränsleförbrukningen och driftskostnaderna för lastbilar. För att utnyttja fördelarna med konvojkörning till fullo behöver lastbilar koordineras för att effektivt mötas och bilda konvojer. Den här avhandlingen behandlar koordinering av lastbilar som kan bilda konvojer på transporthubbar, där vissa lastbilar måste vänta på andra lastbilar för att bilda konvojer, och det finns en belöning för konvojkörning och en kostnad för att vänta. Tre bidrag som behandlar konvojkoordinering presenteras i den här avhandlingen. Det första bidraget behandlar koordinering av lastbilar med förutbestämda rutter i ett transportnätverk med deterministiska eller stokastiska restider. Lastbilarna ägs av konkurrerande transportföretag, och varje lastbil beslutar om sina väntetider på hubbarna längs med sin rutt för att optimera sin driftskostnad. Vi antar att lastbilar bildar en konvoj om de avgår från en hubb och kör in på vägen samtidigt. Den strategiska interaktionen mellan lastbilar när de koordinerar för konvojbildning modelleras med icke-kooperativ spelteori, och vi betraktar Nashjämvikt som lösningskoncept när lastbilarna beslutar om sina väntetider i början av sina resor. I fallet med stokastiska restider utvecklar vi även lösningar där lastbilarna tillåts uppdatera sina väntetider längs med sina resor. I en simuleringsstudie över det svenska transportnätverket visas att när lastbilarna tillåts uppdatera sina väntetider uppnås en konjovkörningsgrad på 60%. I det andra bidraget utreds modeller för att dela på vinsten från konvojkörning. Fördelarna med konvojkörning är inte lika för alla lastbilar i en konvoj; vanligtvis är fördelen större för följarlastbilarna än för ledarlastbilen. Således kan incitamenten för transportföretag att samarbeta i form av konvojkörning vara låga om inte vinsterna från konvojkörning delas. Baserat på vinstdelningsmodeller formulerar vi konvojkoordineringsspel. I en simulering av en transporthubb utvärderar vi utfallet från konvojkoordinationsspelen. Det visar sig att den totala vinsten som uppnås när lastbilarna försöker maximera sina egna vinster, men vinsten från konvojkörning jämnas ut helt bland konvojmedlemmar, är nästan lika hög som när varje lastbil försöker att maximera den totala vinsten i systemet. I det sista bidraget studeras ett koordineringsproblem där lastbilar anländer till en transporthubb enligt en stokastisk ankomstprocess. Lastbilarna delar inte förhandsinformation om sina ankomster; detta kan vara känslig information att dela. En koordinator bestämmer, baserat på den statistiska sannolikhetsfördelningen av ankomster, när lastbilarna på transporthubben ska släppas iväg i form av en konvoj. Under antagandet att ankomsterna är statistiskt oberoende och likafördelade, visar vi att det är optimalt att släppa iväg lastbilarna från transporthubben i form av en konvoj när antalet lastbilar överskrider en viss tröskel. Detta bidrag visar att enkla och dynamiska koordineringsmetoder kan erhålla en hög vinst från konvojkörning, även under hög osäkerhet och begränsad förhandsinformation. / <p>Länk till den offentliga granskningen tillkännages via: https://www.kth.se/profile/alexjoha</p><p>QC 20200609</p>

This paper presents a theoretical development of adaptive cruise control models and platoon operation logic for Automated Highway Systems in the Advanced Vehicle Control Systems (AVeS). Three control modes, constant speed, emergency and vehicle-following, are defined based on the minimum safe stopping distance, and applied to the platoon operations. Desired acceleration model is built for the different cruise control mode by considering the relative velocity, the difference between the relative distance and desired spacing, and the acceleration of the preceding vehicle. A control system model is proposed based on the analysis of vehicle dynamics. The contribution of uncontrolled forces from the air, slop and friction to the vehicle acceleration is considered. Application of control models for two successive vehicles is simulated under the situations of speed transition and emergency stopping. Proper control parameters are determined for different operation mode subject to the conditions: collision avoidance and stability. Same criteria are utilized to the platoon simulation in which the operation logic is regulated so that the platoon leader is operated under either emergency mode or constant speed mode depending upon the . distance from the downstream vehicle, while the intraplatoon vehicles are forced to operate under vehicle-following mode. Three cases under speed transition, emergency stopping and platoon leader splitting are simulated to determine the stable control parameters. Lane capacity analysis shows the tradeoff between safety and efficiency for platoon. modal operations on freeway with guideline or automated highway. / Master of Science

Cities worldwide are faced with the challenge of improving transit service in urban areas using lower cost means. Transit signal priority is considered to be one of the most effective ways to improve the service of transit vehicles. Transit signal priority has become a very popular topic in transportation in the past 20 to 30 years and it has been implemented in many places around the world. In this thesis, transit signal priority strategies are categorized and an extensive literature review on past research on transit signal priority is conducted. Then a case study on Columbia Pike in Arlington (including 21 signalized intersections) is conducted to assess the impacts of integrating transit signal priority and SCOOT adaptive signal control. At the end of this thesis, an isolated intersection is designed to analyze the sensitivity of major parameters on performance of the network and transit vehicles. The results of this study indicate that the prioritized vehicles usually benefit from any priority scheme considered. During the peak period, the simulations clearly indicate that these benefits are typically obtained at the expense of the general traffic. While buses experience reductions in delay, stops, fuel consumption, and emissions, the opposite typically occurs for the general traffic. Furthermore, since usually there are significantly more cars than buses, the negative impacts experienced by the general traffic during this period outweigh in most cases the benefits to the transit vehicles, thus yielding overall negative impacts for the various priority schemes considered. For the off-peak period, there are no apparent negative impacts, as there is more spare capacity to accommodate approaching transit vehicles at signalized intersections without significantly disrupting traffic operations. It is also shown in this study that it is generally difficult to improve the system-wide performance by using transit priority when the signal is already optimized according to generally accepted traffic flow criteria. In this study it is also observed that the system-wide performance decreases rapidly when transit dwell time gets longer. / Master of Science

Connected and Automated Vehicles (CAVs) have the potential to revolutionize transportation efficiency and safety through collaborative behavior. This dissertation explores the challenges and opportunities associated with achieving socially optimal cooperative maneuvers, using the problem of cooperative lane-changing to showcase the significance of cooperativeness. Cooperative lane-changing serves as an ideal testbed for examining decentralized optimal control, interactions with uncooperative vehicles, accommodating diverse human driving preferences, and integrating planning and execution processes. Initially, the research focuses on scenarios where all vehicles are cooperative CAVs, leveraging their communication and coordination capabilities. Decentralized optimal control problems are formulated to minimize energy consumption, travel time, and traffic disruption during sequential cooperative lane changes, balancing individual vehicle objectives with system-level goals. The dissertation then extends the analysis to mixed-traffic scenarios involving uncooperative human-driven vehicles (HDVs). A novel approach is developed to ensure safety assurance, combining optimal control with Control Barrier Functions (CBFs) and fixed-time convergence (FxT-OCBF). Robust methods for handling disturbances from uncooperative vehicles are introduced, enhancing the resilience and dependability of cooperative lane-changing maneuvers. An innovative online learning framework is presented to address the complexities of CAVs interacting with HDVs exhibiting diverse driving preferences. Safety preferences are characterized using parameterized CBFs, and an extended Kalman filter dynamically adjusts control parameters based on observed interactions, enabling real-time adaptation to evolving human behaviors. The proposed methodologies bridge the gap between high-level planning and low-level control execution, facilitating safe and near-optimal cooperative maneuvers. Comprehensive analysis demonstrates improved traffic throughput, reduced energy consumption, and enhanced safety compared to non-cooperative or reactive approaches. This research lays the foundation for deploying CAV technologies that prioritize social optimality while addressing uncertainties in mixed-traffic settings, ultimately paving the way for safer and more efficient transportation systems. / 2025-03-11T00:00:00Z

Intelligent Transportation Systems are advanced technologies used to reduce traffic and increase road safety for vulnerable road users. Real-time traffic monitoring is an important technology for collecting and reporting the information required to achieve these goals through the detection and tracking of road users inside an intersection. To be effective, these systems must be robust to all environmental conditions. This thesis explores the fusion of camera and Light Detection and Ranging (LiDAR) sensors to create an accurate and real-time traffic monitoring system. Sensor fusion leverages complimentary characteristics of the sensors to increase system performance in low- light and inclement weather conditions. To achieve this, three primary components are developed: a 3D LiDAR detection pipeline, a camera detection pipeline, and a decision-level sensor fusion module. The proposed pipeline is lightweight, running at 46 Hz on modest computer hardware, and accurate, scoring 3% higher than the camera-only pipeline based on the Higher Order Tracking Accuracy metric. The camera-LiDAR fusion system is built on the ROS 2 framework, which provides a well-defined and modular interface for developing and evaluated new detection and tracking algorithms. Overall, the fusion of camera and LiDAR sensors will enable future traffic monitoring systems to provide cities with real-time information critical for increasing safety and convenience for all road-users. / Thesis / Master of Applied Science (MASc) / Accurate traffic monitoring systems are needed to improve the safety of road users. These systems allow the intersection to “see” vehicles and pedestrians, providing near instant information to assist future autonomous vehicles, and provide data to city planers and officials to enable reductions in traffic, emissions, and travel times. This thesis aims to design, build, and test a traffic monitoring system that uses a camera and 3D laser-scanner to find and track road users in an intersection. By combining a camera and 3D laser scanner, this system aims to perform better than either sensor alone. Furthermore, this thesis will collect test data to prove it is accurate and able to see vehicles and pedestrians during the day and night, and test if runs fast enough for “live” use.

No description available.

Highway Capacity Manual (HCM) 2010 methodology for freeway operations contain procedures for calculating traffic performance measures both for undersaturated and oversaturated flow conditions. However, one of the limitations regarding oversaturated freeway weaving segments is that the HCM procedures have not been extensively calibrated based on field observations on U.S. freeways. This study validates the HCM2010 methodology for oversaturated freeway weaving segment by comparing space mean speed and density obtained from HCM procedure to those generated by a microsimulation model. A VISSIM model is extensively calibrated and validated based on NGSIM field data for the US 101 Highway. Abundance of the NGSIM data is utilized to calibrate and validate the VISSIM model. Results show that HCM methodology has significant limitations and while in some cases it can reproduce density correctly, the study finds that speeds estimated by the HCM methodology significantly differ from those observed in the field. / by Dusan Jolovic. / Thesis (M.S.C.S.)--Florida Atlantic University, 2012. / Includes bibliography. / Electronic reproduction. Boca Raton, Fla., 2012. Mode of access: World Wide Web.

Abstract : Embedded intelligence in vehicular applications is becoming of great interest since the last two decades. Position estimation has been one of the most crucial pieces of information for Intelligent Transportation Systems (ITS). Real time, accurate and reliable localization of vehicles has become particularly important for the automotive industry. The significant growth of sensing, communication and computing capabilities over the recent years has opened new fields of applications, such as ADAS (Advanced driver assistance systems) and active safety systems, and has brought the ability of exchanging information between vehicles. Most of these applications can benefit from more accurate and reliable localization. With the recent emergence of multi-vehicular wireless communication capabilities, cooperative architectures have become an attractive alternative to solving the localization problem. The main goal of cooperative localization is to exploit different sources of information coming from different vehicles within a short range area, in order to enhance positioning system efficiency, while keeping the cost to a reasonable level. In this Thesis, we aim to propose new and effective methods to improve vehicle localization performance by using cooperative approaches. In order to reach this goal, three new methods for cooperative vehicle localization have been proposed and the performance of these methods has been analyzed. Our first proposed cooperative method is a Cooperative Map Matching (CMM) method which aims to estimate and compensate the common error component of the GPS positioning by using cooperative approach and exploiting the communication capability of the vehicles. Then we propose the concept of Dynamic base station DGPS (DDGPS) and use it to generate GPS pseudorange corrections and broadcast them for other vehicles. Finally we introduce a cooperative method for improving the GPS positioning by incorporating the GPS measured position of the vehicles and inter-vehicle distances. This method is a decentralized cooperative positioning method based on Bayesian approach. The detailed derivation of the equations and the simulation results of each algorithm are described in the designated chapters. In addition to it, the sensitivity of the methods to different parameters is also studied and discussed. Finally in order to validate the results of the simulations, experimental validation of the CMM method based on the experimental data captured by the test vehicles is performed and studied. The simulation and experimental results show that using cooperative approaches can significantly increase the performance of the positioning methods while keeping the cost to a reasonable amount. / Résumé : L’intelligence embarquée dans les applications véhiculaires devient un grand intérêt depuis les deux dernières décennies. L’estimation de position a été l'une des parties les plus cruciales concernant les systèmes de transport intelligents (STI). La localisation précise et fiable en temps réel des véhicules est devenue particulièrement importante pour l'industrie automobile. Les améliorations technologiques significatives en matière de capteurs, de communication et de calcul embarqué au cours des dernières années ont ouvert de nouveaux champs d'applications, tels que les systèmes de sécurité active ou les ADAS, et a aussi apporté la possibilité d'échanger des informations entre les véhicules. Une localisation plus précise et fiable serait un bénéfice pour ces applications. Avec l'émergence récente des capacités de communication sans fil multi-véhicules, les architectures coopératives sont devenues une alternative intéressante pour résoudre le problème de localisation. L'objectif principal de la localisation coopérative est d'exploiter différentes sources d'information provenant de différents véhicules dans une zone de courte portée, afin d'améliorer l'efficacité du système de positionnement, tout en gardant le coût à un niveau raisonnable. Dans cette thèse, nous nous efforçons de proposer des méthodes nouvelles et efficaces pour améliorer les performances de localisation du véhicule en utilisant des approches coopératives. Afin d'atteindre cet objectif, trois nouvelles méthodes de localisation coopérative du véhicule ont été proposées et la performance de ces méthodes a été analysée. Notre première méthode coopérative est une méthode de correspondance cartographique coopérative (CMM, Cooperative Map Matching) qui vise à estimer et à compenser la composante d'erreur commune du positionnement GPS en utilisant une approche coopérative et en exploitant les capacités de communication des véhicules. Ensuite, nous proposons le concept de station de base Dynamique DGPS (DDGPS) et l'utilisons pour générer des corrections de pseudo-distance GPS et les diffuser aux autres véhicules. Enfin, nous présentons une méthode coopérative pour améliorer le positionnement GPS en utilisant à la fois les positions GPS des véhicules et les distances inter-véhiculaires mesurées. Ceci est une méthode de positionnement coopératif décentralisé basé sur une approche bayésienne. La description détaillée des équations et les résultats de simulation de chaque algorithme sont décrits dans les chapitres désignés. En plus de cela, la sensibilité des méthodes aux différents paramètres est également étudiée et discutée. Enfin, les résultats de simulations concernant la méthode CMM ont pu être validés à l’aide de données expérimentales enregistrées par des véhicules d'essai. La simulation et les résultats expérimentaux montrent que l'utilisation des approches coopératives peut augmenter de manière significative la performance des méthodes de positionnement tout en gardant le coût à un montant raisonnable.