Automated Electric Transportation (AET) proposes a system of automated platooning vehicles electrically powered by the roadway via wireless inductive power transfer. This has the potential to provide roadway transportation that is less congested, more flexible, cleaner, safer, and faster than the current system. The focus of this research is to show how platooning can be accomplished in a safe manner and what capacities such an automated platooning system can achieve. To accomplish this, first two collision models are developed to show the performance of automated platoons during an emergency braking scenario: a stochastic model coded in Matlab/Simulink and a deterministic model with closed-form solutions. The necessary parameters for safe platooning are then defined: brake variances, communication delays, and maximum acceptable collision speeds. The two collision models are compared using the Student's t-test to show their equivalence. It is shown that while the two do not yield identical results, in most cases the results of the deterministic model are more conservative than and reasonably close to the results of the deterministic model. The deterministic model is then used to develop a capacity model describing automated platooning flow as a function of speed and platoon size. For conditions where platooning is initially unsafe, three amelioration protocols are evaluated: brake derating, collaborative braking, and increasing the maximum acceptable collision speed. Automated platooning flow is evaluated for all of these scenarios, compared both with each other and with traditional roadway flow patterns. The results of these models show that when platooning is initially safe, very high vehicle flows are possible: for example, over 12,000 veh/hr for initial speeds of 30 m/s and 10 vehicle platoons. Varying system paramaters can have large ramifications for overall capacity. For example, autonomous (non-platooning) vehicles do not promise anywhere near this level, and in many cases struggle to approach the capacity of traditional roadways. Additionally, ensuring safety under an emergency braking standard requires very small communication delays and, most importantly, tight braking variances between the vehicles within a platoon. As proposed by AET, a single type of electric vehicle, combined with modern wireless communications, can make platooning safer than was previously possible without requiring amelioration. Both brake derating and collaborative braking can make platooning safer, but they reduce capacity and may not be practical for real-world implementation. Stricter versions of these, cumulative brake derating and exponential collaborative braking, are also evaluated. Both can degrade capacity to near current roadway levels, especially if a large degree of amelioration is required. Increasing maximum acceptable collision speed, such as through designing vehicles to better withstand rear-end collisions, shows more promise in enabling safe intraplatoon interactions, especially for scenarios with small communication delays (i.e. under 50 ms).

In the period between 1993-1998 a vision was presented of an Automated Highway System developed under a contract naming Virginia Tech one of the three ITS Research Centers of Excellence in the United States by the Federal Highway Administration. The AHS envisioned would consist of a guideway constructed in the rights-of-way of the Interstate Highway System which would utilized magnetic levitation ("maglev") to propel closely-space, individual vehicles at high speeds with full longitudinal and lateral control. In this dissertation the system architecture is described in detail. The system architecture is organized according to system structural, system operational, and vehicle subsystem technological elements. The structural aspects are concerned with the decision making capability allocated between a vehicle and the guideway, the characteristics of the control and sensing equipment contained within the guideway, the traveling unit configuration, and certain of the vehicle's structural and equipment considerations. The operational aspects are concerned with vehicle entrainment policy, system fleet mixture, network type and control functions, and guideway lane separation requirements. The vehicle subsystem and the vehicle longitudinal and lateral control subsystem. The operational architecture concentrates on developing and evaluating strategies for forming platoons of vehicles on the guideway since the average platoon sizes determine the practical capacity of the guideway as well as the safety of operation. It is instructive to review how platoons form naturally on conventional highways as a prelude to developing a strategy for forming platoon on the AHS Maglev Guideway. A novel, non-linear car-following model called "car maneuvering" is explored by defining the stimuli on the right-hand side of the model in terms of several vehicles ahead of the response vehicle. In order to add still more realism in developing a strategy for platoon formation in a guideway under automatic control, an additional spacing dependent term is introduced to achieve a "magnetic coupling headway" between platooned vehicles. Once vehicles are magnetically coupled, the desired intraplatoon headway is maintained through attraction and repulsion. In this dissertation the term "architecture" is interpreted in the broadest possible sense based on the assumption that any transportation system intended to serve society throughout the 21st Century and beyond must address a hierarchy of goals and issues ranging from the strategic (sustainable development) to the tactical (the concept of operations) and including the in-between (interfacing with the existing transportation system). In the past, transportation planning, policy, investment and operating decisions have been made in isolation from each other with incomplete information inputs from a broad base of disciplines and sectors, without a synthesizing instrumentality. A new approach is described to promote the best informed decisions governing planning and management. The approach features a realistic framework for allocating public sector-private sector effort, an instrumentality for generating the knowledge needed to conceive and implement the new transportation paradigm, and a strategic vision for rallying support. The new approach to the problem begins with a strategic vision for society's AHS infrastructure. We believe that the strategic vision must be based on the concept of "sustainable development." To affect this new strategic vision, higher budgets will be a necessary, but not a sufficient condition. A fundamental Decision Support System (DSS) with knowledge bases with contributions from the braid spectrum of science and engineering disciplines, and a methodology based on system dynamics capable of synthesizing these contributions is proposed. The AHS Maglev Alternative is compared to a "Do-Nothing" Alternative and a "Traditional Expansion" Alternative using user and nonuser benefit analyses. The advantages of AHS Maglev are seen to be overwhelming. Moreover, the ability of AHS Maglev to alleviate airport congestion by reducing short and medium range of flights, and to serve as a structuring device for rational population distribution is shown. / Ph. D.

Intelligent Transportation Systems (ITS), which uses modem electronics and communications technology to guide or control the operation of vehicles holds great promise for increasing the capacity of existing roads. reducing congestion and accident losses, and contributing to the ease and convenience of travel. The most sophisticated of all the ITS technologies that may ultimately yield the largest benefits is the Automated Highway Systems (AHS). The AHS approach to enhance the performance of our highways is to apply automation techniques to vehicles and roadways to increase the capacity and efficiency of existing facilities, while retaining the advantages of individual mobility. The idea is to have a system with instrumented highways and vehicles which allows the automation of the driving function. The overall objective of this research study involves the modeling and analysis of an AHS system, using a simulation tool specifically developed for this purpose. A multi-layer control system architecture that conforms to the one developed at the University of California, Berkeley, provides a framework for the micro and macroscopic modeling of the system. The focus of the system modeling is towards the lower layers of this control system architecture, involving a comprehensive modeling of the regulation and physical layers and a simple, yet realistic modeling of the functionalities of the link layer. The regulation and physical layer design incorporates a complete power train modeling of the vehicle that includes one-wheel rotational dynamics, linear vehicle dynamics, engine dynamics and actuator dynamics. / Master of Science

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 thesis presents a novel approach to several problems in intelligent transportation systems using collaborative driving coordination. With inter-vehicle communication and intelligent vehicle cooperation, important tasks in transportation such as lane position determination, lane assignment and platoon formation can be solved. Several topics in regard to inter-vehicle communication, lane positioning, lane assignment and platoon formation are explored in this thesis: First, the design and experimental results of low-cost lane-level positioning system that can support a large number of transportation applications are discussed. Using a Markov-based approach based on sharing information among a group of vehicles that are traveling within the communication range of each other, the lane positions of vehicles can be determined. The robustness effectiveness of the system is shown in both simulations and real road tests. Second, a decentralized approach to lane scheduling for vehicles with an aim to increase traffic throughput while ensuring the vehicles exit successfully at their destinations is presented. Most of current traffic management systems do not consider lane organization of vehicles and only regulate traffic flows by controlling traffic signals or ramp meters. However, traffic throughput and efficient use of highways can be increased by coordinating driver behaviors intelligently. The lane optimization problem is formulated as a linear programming problem that can be solved using the Simplex method. Finally, a direction for cooperative vehicle platoon formation is proposed. To enhance traffic safety, increase lane capacities and reduce fuel consumption, vehicles can be organized into platoons with the objective of maximizing the travel distance that platoons stay intact. Toward this end, this work evaluates a proposed strategy which assigns vehicles to platoons by solving an optimization problem. A linear model for assigning vehicles to appropriate platoons when they enter the highway is formulated. Simulation results demonstrate that lane capacity can be increased effectively when platooning operation is used.

This thesis presents a novel approach to several problems in intelligent transportation systems using collaborative driving coordination. With inter-vehicle communication and intelligent vehicle cooperation, important tasks in transportation such as lane position determination, lane assignment and platoon formation can be solved. Several topics in regard to inter-vehicle communication, lane positioning, lane assignment and platoon formation are explored in this thesis: First, the design and experimental results of low-cost lane-level positioning system that can support a large number of transportation applications are discussed. Using a Markov-based approach based on sharing information among a group of vehicles that are traveling within the communication range of each other, the lane positions of vehicles can be determined. The robustness effectiveness of the system is shown in both simulations and real road tests. Second, a decentralized approach to lane scheduling for vehicles with an aim to increase traffic throughput while ensuring the vehicles exit successfully at their destinations is presented. Most of current traffic management systems do not consider lane organization of vehicles and only regulate traffic flows by controlling traffic signals or ramp meters. However, traffic throughput and efficient use of highways can be increased by coordinating driver behaviors intelligently. The lane optimization problem is formulated as a linear programming problem that can be solved using the Simplex method. Finally, a direction for cooperative vehicle platoon formation is proposed. To enhance traffic safety, increase lane capacities and reduce fuel consumption, vehicles can be organized into platoons with the objective of maximizing the travel distance that platoons stay intact. Toward this end, this work evaluates a proposed strategy which assigns vehicles to platoons by solving an optimization problem. A linear model for assigning vehicles to appropriate platoons when they enter the highway is formulated. Simulation results demonstrate that lane capacity can be increased effectively when platooning operation is used.