Esta dissertação de mestrado apresenta um estudo do processo de formação de pelotões em rodovias de pista simples brasileiras e a dispersão desses pelotões nas faixas adicionais de subida. Este estudo foi realizado usando-se dados empíricos coletados na SP 255, uma rodovia de pista simples do estado de São Paulo. Um dos trechos estudados possuía faixas adicionais nos aclives e o outro era sem faixas adicionais. Para caracterizar a formação de pelotões, três aspectos foram estudados: a porcentagem de veículos em pelotões, o tamanho médio dos pelotões e a recomposição dos pelotões após o término de uma faixa adicional. Modelos matemáticos foram adaptados para representar o processo de formação de pelotões em rodovias brasileiras. Visando fornecer subsídios para futuros projetos de faixas adicionais, a dispersão dos pelotões nas faixas adicionais de subida foi analisada considerando-se as seguintes medidas de desempenho: taxa de ultrapassagem, velocidade média da corrente, porcentagem de veículos em pelotões e comprimento de faixa para a dispersão dos pelotões. Os resultados do estudo da dispersão dos pelotões mostram que as faixas adicionais melhoram o nível de serviço não apenas na direção onde são implantadas, mas também na direção do tráfego oposto uma vez que cerca de 70 a 75% do fluxo no sentido analisado divergem para as faixas adicionais, proporcionando uma porcentagem maior de gaps adequados para a dispersão dos pelotões do fluxo oposto. / This master thesis presents a study of the platoon formation process in the Brazilian two-lane roads and the dispersion of these platoons in the passing lanes. This study was developed using empirical data collected in the SP 255, a two-lane road of the state of São Paulo. One of the segments studied had passing lanes on upgrades and another was without passing lanes. In order to characterize the platoon formation, three aspects were studied: the percent of vehicle in platoon, the mean platoon size and the platoon recomposition after the end of a passing lane. Mathematical models were adapted to represent the platoon formation in the Brazilian roads. Aiming to aid future auxiliary lanes projects, the platoon dispersion in the climbing lanes was analyzed considering the following service measures: overtaking rate, mean speed, percent of vehicle traveling in platoons and lane length used to disperse the platoons. The results of the platoons dispersion study show that the auxiliary lanes improve the level of service not only in the direction of they are constructed, but also in the opposing flow. It\'s verified that around 70 to 75% of the flow in the analyzed direction diverge to auxiliary lanes, providing a greater percentage of gaps suitable to platoon dispersion in the opposing flow.

As the greenhouse effect is an imminent concern, motivation for the development of energy efficient systems has grown fast. Today heavy-duty vehicles (HDVs) account for a growing part of the emissions from the vehicular transport sector. One way to reduce those emissions is by driving at short intervehicular distances in so called platoons, mainly on highways. In such formations, the aerodynamic drag is decreased which allows for more fuel efficient driving, meanwhile the roads are used more efficiently. This thesis deals with the question of how those platoons can be controlled without using communications between the involved HDVs. In this thesis, artificial neural networks are designed and trained to predict the velocity profile for an HDV driving over a section of road where data on the topography are available. This information is used in a model predictive controller to control the HDV driving behind the truck for which the aforementioned prediction is made. By having accurate information about the upcoming behaviour of the preceding HDV, the controller can plan the velocity profile for the controlled HDV in a way which minimizes fuel consumption. To ensure fuel optimal performance, a state describing the mass of consumed fuel is derived and minimized in the controller. A system modelling gear shift dynamics is proposed to capture essential dynamics such as torque loss during shifting. The designed controller is able to predict and change between the three highest gears making it able to handle almost all highway platooning scenarios. The prediction system shows great potential and is able to predict the velocity profile for different HDVs with an average error as low as 0.04 km/h. The controller is implemented in a simulation environment and results show that compared to a platoon without these predictions of the preceding HDV, the fuel consumption for the controlled HDV can be reduced by up to 6 %.

Heavy duty vehicle (HDV) platooning is currently a big topic both in the academic world and in industry. Platooning is a smart way to solve problems such as safety, traffic congestion, fuel consumption and hazardous exhaust emissions since its concept enables several vehicles to drive close to each other while maintaining all the security requisites. This way, each vehicle will use the so called slipstream effect, an atmospheric drag reduction that occurs behind a traveling vehicle, consuming less fuel and consequently reducing the exhausted gases. Furthermore, it increases the traffic flow since the distance between vehicles is significantly reduced. The concept and idea of platooning is not particularly new, but only in the last few decades new technology made it possible. HDV platooning scenarios for scale model trucks were developed in the completely renovated Smart Mobility Lab, in KTH, Stockholm. A LabVIEW application was developed giving a robust and stable control of the trucks while following and driving on a newly designed and built road network. The trucks are able to follow a predefined trajectory, change lane and road, platoon with each other with different platooning distances, overtake when the platoon master is changed in order to take the lead of the platoon and change speed to catch up, among other features. The last part of this thesis covers the analysis of the scenarios developed in the testbed. These scenarios represent several situations of HDV platooning, particularly the platoon catch-up case. The main object of this study was the saved fuel due to platooning, and the break-even point, i.e. the distance ratio when neither driving alone nor catching up a platoon ahead would be more feasible. Using real HDV models and their fuel consumption models, simulations were performed in order to check the benefits of platooning and the data got from the scenarios was analyzed. Finally, conclusions were drawn from the experiments where the parameters such as HDV weight, speed increment when catching up and intermediate distance when platooning were different in each trial. It was concluded that a single HDV has to travel 8 to 15 times more than the initial distance that separates it from the HDV(s) ahead and it can save 5 to 13% of fuel depending if catching up a single HDV or a platoon an already existing platoon. Furthermore, it is less beneficial for a platoon already formed to decide to catch up another HDV.

The operation of groups of heavy-duty vehicles at small inter-vehicular distances, known as platoons, lowers the overall aerodynamic drag and, therefore, reduces fuel consumption and greenhouse gas emissions. Experimental tests conducted on a flat road and without traffic have shown that platooning has the potential to reduce the fuel consumption up to 10%. However, platoons are expected to drive on public highways with varying topography and traffic. Due to the large mass and limited engine power of heavy-duty vehicles, road slopes can have a significant impact on feasible and optimal speed profiles. Therefore, maintaining a short inter-vehicular distance without coordination can result in inefficient or even infeasible speed trajectories. Furthermore, external traffic can interfere by affecting fuel-efficiency and threatening the safety of the platooning vehicles. This thesis addresses the problem of safe and fuel-efficient control for heavy-duty vehicle platooning. We propose a hierarchical control architecture that splits this complex control problem into two layers. The layers are responsible for the fuel-optimal control based on look-ahead information on road topography and the real-time vehicle control, respectively. The top layer, denoted the platoon coordinator, relies on a dynamic programming framework that computes the fuel-optimal speed profile for the entire platoon. The bottom layer, denoted the vehicle control layer, uses a distributed model predictive controller to track the optimal speed profile and the desired inter-vehicular spacing policy. Within this layer, constraints on the vehicles' states guarantee the safety of the platoon. The effectiveness of the proposed controller is analyzed by means of simulations of several realistic scenarios. They suggest a possible fuel saving of up to 12% for the follower vehicles compared to the use of existing platoon controllers. Analysis of the simulation results shows how the majority of the fuel saving comes from a reduced usage of vehicles brakes. A second problem addressed in the thesis is model predictive control for obstacle avoidance and lane keeping for a passenger car. We propose a control framework that allows to control the nonlinear vehicle dynamics with linear model predictive control. The controller decouples the longitudinal and lateral vehicle dynamics into two successive stages. First, plausible braking and throttle profiles are generated. Second, for each profile, linear time-varying models of the lateral dynamics are derived and used to formulate a collection of linear model predictive control problems. Their solution provides the optimal control input for the steering and braking actuators. The performance of the proposed controller has been evaluated by means of simulations and real experiments. / <p>QC 20150911</p>

This bachelor degree project presents an extension of a base optimization model for a transit line which can be used to evaluate the efficiency of different configurations of a platoon with different scenarios of berths. Furthermore, different levels of autonomous vehicles are studied, three cases are presented. The first case implies that every vehicle has a driver, the second, semi-autonomous vehicles are used in the platoon which has a leading vehicle with driver. Then, the fully autonomous vehicles represent the last studied case. A new method to compute the service time in the stops which differentiate the time that passengers are boarding or alighting from delays or time lost in queues that may appear with an increasing demand is added to the base model. It is introduced also a two-step non-linear approach to the crowding factor that consider the sharp deterioration when the load factor of the bus is almost one. In this project the bus capacity has been considered as a variable to see if there is an optimum vehicle size that cover different values of demand. Numerical results are provided and the result show that vehicle platooning with equal number of vehicles than stop berths is always competitive in high-demands. Moreover, if semi-autonomous case is found the bus platooning gain effectiveness and is competitive with lower demand values. In the case of fully autonomous vehicles the gain of bus platooning is not as high as in the semiautonomous but has still an improvement and is competitive with medium demand values.

Platooning is a method where a chain of vehiclesdrive with small inter-vehicular distances. The many benefitsof autonomous platooning includes improved fuel economy,less congestion and safer transportation. To create a safe andfunctional platoon the operational software needs to be able tohandle various road surfaces without the risk of a crash. Thisreport is aiming to improve the safety of a platoon by includingcommunication of data between vehicles in the chain. Specificallythe focus has been on transferring information about the tireslip, to model a cooperative adaptive cruise control (C-ACC)and combine the two. A system was designed using the dynamicsfor a quarter-car model and then connected to a controller and aplatoon of four vehicles. Simulations of when the leading vehiclebraked hard on two different road surfaces with and withoutthe slip awareness was conducted. The tire slip awareness in thecontroller consisted of proportional control on the error and alow-pass filter. The simulations showed that the inclusion of thetire slip in the controller improved the platooning performance,in the sense that the inter-vehicle distance could be contained.It was also shown the controller could be tuned so that the slipratios were limited. / Konvojkörning är en metod där en kedjaav fordon åker med små interna distanser. De många fördelarnamed förarlösa konvojer inkluderar förbättrad bränsleförbukning, mindre trafik och säkrare transportering. För atten säker och funktionell konvoj ska kunna skapas krävs detatt mjukvaran kan handskas med varierande vägunderlag utanrisk att krocka. Den här rapporten siktar på att förbättrasäkerheten i konvojkörning genom att överföra data till andrafordon i konvojkedjan. Speciellt har fokuset legat på överförainformation om däcksliring, att modellera en kooperative adaptivfarthållare (C-ACC) och sedan kombinera de två. Ett systemdesignades genom att använda dynamiken av en fjärdedelsbil och sen ansluta modellen till en konvoj med fyra fordon.Simulationer av när det ledande fordonet tvärbromsade på olikavägunderlag med och utan däcksliringsinfromation genomfördes.Däckslirnings i regulatorn bestod av proportionerlig kontroll påfelet och ett lågpassfilter. Simulationerna visade att inkluderingenav däcksliringsinformation i regulatorn förbättrar konvojensprestanda, på så sätt att de interna distanserna kan hanteras.Det kunde också påvisas att kontrollern kunde kalibreras så attslirningen begränsades. / Kandidatexjobb i elektroteknik 2022, KTH, Stockholm

When multiple autonomous vehicles drive closelytogether behind each other, it is called a platoon. Platooningprovides several benefits, such as decreased congestion andreduced fuel consumption. In order for more vehicles to takeadvantage of these benefits, the platoon should be able to openup a space for other vehicles to merge into. Thus, our goal withthe project was to develop a system that can split a platoon.To achieve this, we are using model predictive control (MPC) tocontrol the system because it can handle constraints and controlsystems with multiple variables. To test the implemented system,we created a simulation environment in Python. We createdseveral plots to analyze and show the results of the simulations.To make the simulation more realistic, we introduced air drag tothe system. To counteract this effect, we added linearized air dragto the MPC. We showed that the constructed system could splitbetween any two adjacent vehicles in a platoon up to 50 meters.Another significant result was that the MPC could compensatefor the air drag without adding linearized air drag to the MPC. / När flera autonoma fordon kör nära varandra kallas det för en platoon. Det finns flera fördelar med platooning som minskad trafik samt minskad bränsleförbrukning. För att fler fordon ska kunna dra nytta av dessa fördelar bör nya fordon kunna sammansluta till en platoon och på grund av detta bör fordonen i platoonen kunna öppna ett utrymme för det nya fordonet. Därför är vårt mål med detta projekt att utveckla ett system som kan styra och dela på en platoon. För att åstadkomma detta använder vi model prediktiv reglering (MPC) eftersom den är bra på att hanterar bivilkor och styra system med många variabler. Vi implementerade systemet i Python, där en simuleringsmiljö skapades. För att se och analysera resultaten av simuleringen skapades grafer som visade hur fordonen hade färdats under simuleringen. Vi lade till luftmotstånd i simuleringen för att göra den mer realistisk. För att motverka luftmotståndet lade vi även till ett linjäriserat luftmotstånd till i MPC:n. I slutet av projektet kunde systemet dela platoonen mellan två fordon med ett avstånd upp till 50 meter. Vi observerade att MPC:n kunde kompensera motståndet utan implementationen av det linjäriserade luftmotståndet. / Kandidatexjobb i elektroteknik 2021, KTH, Stockholm

Platooning is when vehicles are driving close aftereach other at a set distance and it is a promising method toimprove the traffic of todays infrastructure. Several approachesfor platooning can be taken and in this paper a vision-basedimplementation has been studied. With a camera that detectsthe orientation of a marker attached to a small vehicle, it hasbeen examined how the pitch of the marker can be exploitedto perform vision-based platooning considering the road grade.A model predictive control strategy is presented to maintain aplatooning distance with the potential of utilizing road topography.The aim of the project was to use this information tominimize brake and motor forces of the platooning vehicle. Thestrategy was based on relative vehicle states, detectable by acamera. The model predictive controller was implemented onsmall robotic vehicles and tested on a flat surface. The controllerwas successful in converging towards the wanted distance andcapable of reaching a steady state speed. The results showed thatit took 15 seconds for the system to reach a steady state. / Konvojkörning är när fordon kör nära efter varandra med ett bestämt avstånd och det är en lovande metod för att förbättra trafiken i dagens infrastruktur. Åtskilliga tillvägagångssätt kan tas och i denna artikel så har ett visionsbaserat genomförande studerats. Med en kamera som upptäcker orienteringen av en markör som sitter på ett litet fordon så har det undersökts hur markörens lutningsvinkel kan utnyttjas för att utföra en visionsbaserad konvojkörning med hänsyn till vägens lutning. En model predictive control-strategi är presenterad för att bibehålla ett bestämt konvojavstånd med möjligheten att använda vägens topografi. Projektets mål var att använda denna information för att minska bromsoch motorkrafter för det konvojkörande fordonet. Strategin grundades på fordonets relativa tillstånd som var detekterbara med en kamera. En model predicitve control utfärdades på små robotfordon och testades på en platt yta. Kontrollern var framgångsrik i att konvergera mot det önskade avståndet och kapabel till att nå ett stabilt tillstånd för hastigheten. Resultaten t det tog 15 sekunder för fordonets hastighet att nå det stabila tillståndet. / Kandidatexjobb i elektroteknik 2021, KTH, Stockholm

<div> <div> <div> <p>Commercial vehicles in the United States account for a significant fraction of greenhouse gas emissions and NOx emissions. The objectives of this work are reduction in commercial vehicle NOx emissions through enhanced aftertreatment thermal management via diesel engine variable valve actuation and the reduction of commercial vehicle fuel consumption/GHG emissions by enabling more effective class 8 truck platooning. </p> <p><br></p><p>First, a novel diesel engine aftertreatment thermal management strategy is proposed which utilizes a 2-stroke breathing variable value actuation strategy to increase the mass flow rate of exhaust gas. Experiments showed that when allowed to operate with modestly higher engine-out emissions, temperatures comparable to baseline could be achieved with a 1.75x exhaust mass flow rate, which could be beneficial for heating the SCR catalyst in a cold-start scenario. </p> <p><br></p><p>Second, a methodology is presented for characterizing aerodynamic drag coefficients of platooning trucks using experimental track-test data, which allowed for the development of high-fidelity platoon simulations and thereby enabled rapid development of advanced platoon controllers. Single truck and platoon drag coefficients were calculated for late model year Peterbilt 579’s based on experimental data collected during J1321 fuel economy tests for a two-truck platoon at 65 mph with a 55’ truck gap. Results show drag coefficients of 0.53, 0.50, and 0.45 for a single truck, a platoon front truck, and a platoon rear truck, respectively. </p> <p><br></p><p>Finally, a PID-based platoon controller is presented for maximizing fuel savings and gap control on hilly terrain using a dynamically-variable platoon gap. The controller was vetted in simulation and demonstrated on a vehicle in closed-course functionality testing. Simulations show that the controller is capable of 6-9% rear truck fuel savings on a heavily-graded route compared to a production-intent platoon controller, while increasing control over the truck gap to discourage other vehicles from cutting in. </p></div></div></div>

Dans cette thèse, nous nous intéressons au problème du suivi en convoi, désigné en anglais par le terme platooning, où un train de robots essaie de suivre un chemin décrit par le leader. Ce chemin, n'étant pas prédéfini mais généré au cours du suivi, est inconnu de tous les robots suiveurs. Dans ce travail, nous choisissons une approche décentralisée locale où chaque robot du convoi observe son voisinage et calcule son contrôle de façon à avoir un suivi stable (absence d'oscillations) et précis (erreur latérale aussi faible que possible). Cette thèse étudie plus précisément le comportement latéral d'un robot du convoi et propose deux contrôleurs s'appuyant sur la mémorisation du chemin suivi par son prédécesseur. Un premier algorithme de contrôle Memo-LAT (Memorization and Look-Ahead Target) calcule une commande latérale continue en utilisant une loi de contrôle analytique. La stabilité de Memo-LAT n'étant pas toujours garantie, nous proposons l'algorithme de contrôle NOC (Non-Oscillatory Convergence) qui prend en compte la courbure du chemin à suivre dans le calcul du comportement latéral. NOC combine une approche géométrique avec une recherche heuristique pour calculer une commande discrète permettant au robot de suivre avec précision le chemin de son prédécesseur sans oscillation. / This thesis deals with the platooning problem which aims to concieve a control algorithm allowing a convoy of vehicles to follow their leader's path. This path, which is initially undefined and unknown to all the following robots, is generated as the leader moves. In this thesis, we choose a local decentralized approach in which each robot of the platoon uses its local perceptions to compute its own commands aiming to achieve a stable (no oscillations) and precise (with a lateral error as small as possible) platooning. More precisely, this thesis studies the lateral behavior of a platoon's robot and introduces two controllers based on the memorization of the robot's predecessor's path. The first algorithm, Memo-LAT (Memorization and Look-Ahead Target), computes a continuous lateral command using an analytic control law. As the stability of Memo-LAT is not always guaranteed, we present NOC (Non-Oscillatory Convergence), a control algorithm which takes into account the path's curvature in the robot's lateral behavior's computation. NOC combines a geometric approach to a heuristic search method to compute a discrete command allowing the robot to follow precisely and without oscillations its predecessor's path