With the fast development of 5G networks and the advancement in networking technologies, more and more new technologies such as internet of vehicles (IoV) is catching our eyes. With technologies of artificial intelligence and automatic control, IoV is transformed into an intelligent transportation system (ITS). The object of this thesis is to analyze the connectivity probability issues in vehicle ad hoc networks (VANETs), which is a subset of ITS. This will be achieved by a platoon-based two dimensional model. In order to make the results more accurate and more close to real scenario, different situations will be analyzed separately, and different types of platoon will be included. In addition, other system parameters are also discussed and stimulated. The results show that many parameters like the increases of traffic density, ratio of platoon, and lane numbers will improve connectivity probability. No-leader based platoons are easier to connect to the base stations compared to leader based platoons.

This diploma thesis is focused on CFD simulation of two platooning DrivAer cars with varying bodyworks. CFD models are made for bodywork variants Estateback, Fastback and Notchback, which are solved by k-epsilon turbulent model. Influence of rear body design on platooning and aerodynamics characteristics is analyzed.

<div>The United States Environmental Protection Agency (EPA) is charged with pro-tecting human health and the environment. Part of this mission involves regulating heavy-duty trucks that produce particulate matter (PM), unburned hydrocarbons (UHC), carbon dioxide (CO2), and nitrogen oxides (NOx). A byproduct of lean burn combustion in diesel engines is NOx. NOx output limits from commercial vehicles have been reduced significantly from 10 g/hp-hr in 1979 to 0.2 g/hp-hr in 2010. Ad-ditional reductions are expected in the near future.</div><div><br></div><div>One pathway to meet future NOx emissions regulations in a fuel efficient manner is with higher performing exhaust aftertreatment systems through improved engine air handling. As exhaust aftertreatment’s capability to convert harmful NOx into harmless N2 and H2O is a function of temperature, a key performance factor is how quickly does the exhaust aftertreatment system heat up (warm-up), and how well does the system stay at elevated temperatures (stay-warm).</div><div><br></div><div>When the warm-up strategy of iEGR was implemented over the heavy duty federal test procedure (HD-FTP) drive-cycle, it was able to get the SCR above the critical 250◦C peak NOx conversion threshold 100 seconds earlier than the TM baseline. While iEGR consumed 2.1% more fuel than the TM baseline, it reduced predicted tailpipe NOx by 7.9%.</div><div><br></div><div>CDA implemented as a stay-warm strategy over the idle portions of the HD-FTP successfully kept the SCR above the 250◦C threshold for as long as the TM baseline and consumed 3.0% less fuel. Implementing CDA both at idle and from 0 to 3 bar BMEP consumed an additional 0.4% less fuel, for a total fuel consumption reduction of 3.4%.</div><div><br></div><div>A method to predict and avoid compressor surge (which can destroy turbochargers and in fact did so during the HD-FTP experiments) instigated by CDA was devel-oped, as discussed later, and implemented with staged cylinder deactivation to avoid compressor surge.</div><div><br></div><div>The literature does not consider the fidelity of road grade data required to ad-equately predict vehicle fuel consumption and operational behavior. This work ad-dresses this issue for Class 8 trucks by comparing predicted fuel consumption and operation (shifting, engine torque/speed, and braking) of a single Class 8 truck simu-lated with grade data for the same corridor from different sources. The truth baseline road grade (best fidelity available with LiDAR) was obtained previously. This work compares road grade data to the truth baseline from four other typical methods i) utilizing GPS to record horizontal position and vertical elevation, ii) logging the pitch of a cost effective, commercially available IMU, iii) integrating the horizontal and ver-tical velocities of the same IMU, and iv) a commercially available dataset (Comm). Comm grade data (R2=0.992) best matches the LiDAR reference over a 5,432 m stretch of US 231 where high quality LiDAR data was available, followed in quality by the integrated IMU velocity road grade (R2=0.979). Limitations of the Comm dataset are shown, namely missing road grade (decreased point density) for up to 1 km spans on other sections of US 231, as well as for Interstate 69. Vehicle simulations show that both the Comm data (where available and accurate) and integrated IMU road grade data result in fuel consumption predictions within 2.5% of those simulated with the truth reference grade data.</div><div><br></div><div>The simulation framework described in Chapter 6 combines high fidelity vehicle and powertrain models (from Chapter 5) with a novel production-intent platooning controller. This controller commands propulsive engine torque, engine-braking, or friction-braking to a rear vehicle in a two-truck platoon to maintain a desired following distance. Additional unique features of the framework include high fidelity road grade and traffic speed data. A comparison to published experimental platooning results is performed through simulation with the platooning trucks traveling at a constant 28.6 m/s (64 MPH) on flat ground and separated by 11 m (36 ft). Simulations of platooning trucks separated by a 16.7 m (54.8 ft) gap are also performed in steady-state operation, at different speeds and on different grades (flat, uphill, and downhill), to demonstrate how platooning affects fuel consumption and torque demand (propulsive and braking) as speed and grade are varied. For instance, while platooning trucks with the same 16.7 m gap at 28.6 m/s save the same absolute quantity of fuel on a 1% grade as on flat ground (1.00 per-mile, normalized), the trucks consume more fuel overall as grade increases, such that relative savings for the platoon average decrease from 6.90% to 4.94% for flat vs. 1% grade, respectively. Furthermore, both absolute and relative fuel savings improve during platooning as speed increases, due to increase in aerodynamic drag force with speed. There are no fuel savings during the downhill operation, regardless of speed, as the trucks are engine braking to maintain reasonable speeds and thus not consuming fuel. Results for a two-truck platoon are also shown for moderately graded I-74 in Indiana, using traffic speed from INDOT for a typical Friday at 5PM. A 16.7 m (54.8 ft) gap two-truck platoon decreases fuel consumption by 6.18% over the baseline without degradation in trip time (average speed of 28.3 m/s (63.3 MPH)). The same platooning trucks operating on aggressively graded I-69 in Indiana shows a lower platoon-average 3.71% fuel savings over baseline at a slower average speed of 24.5 m/s (54.8 MPH). The impact of speed variation over, and grade difference between, these realistic routes (I-74 & I-69) on two-truck platooning is described in detail.<br></div><div><br></div>

Platooning has the potential to significantly reduce fuel consumption, but with heavy duty vehicles scattered on roads driving alone, there is a need for coordination. One solution is for a vehicle to increase its speed to catch up and platoon with a preceding vehicle. This could reduce the fuel consumption of a mission, but it could also increase it if too much fuel is spent catching up. By finding the fuel consumption of catching up and platooning and comparing it to driving alone the decision of whether or not to catch up can be made. This thesis proposes a fuel-optimal algorithm based on a look-ahead controller taking future road topography into account to find the optimal trajectory and merge point when catching up to a preceding vehicle. By weighting time against fuel in the objective function, the addition of a state to keep track of time can be avoided and thus the algorithm can remain low in complexity, making it suitable for dynamic programming (DP). The DP algorithm is iterated in a forward fashion keeping track of the time-to-come for each state until it catches up to the preceding vehicle, then the platooning is simulated with a constant time gap, making it easy and fast to simulate. The algorithm is tested on real-world road topography data where it showed that taking road topography into account when choosing the merge point can have a significant fuel reduction.

Freight transport demand has escalated and will continue to do so as economiesgrow. As the traffic intensity increases, the drivers are faced with increasinglycomplex tasks and traffic safety is a growing issue. Simultaneously, fossil fuel usageis escalating. Heavy duty vehicle (HDV) platooning is a plausible solution to theseissues. Even though there has been a need for introducing automated HDV platooningsystems for several years, they have only recently become possible to implement.Advancements in on-board and external technology have ushered in new possibilitiesto aid the driver and enhance the system performance. Each vehicle is able to serveas an information node through wireless communication; enabling a cooperativenetworked transportation system. Thereby, vehicles can semi-autonomously travel atshort intermediate spacings, effectively reducing congestion, relieving driver tension,improving fuel consumption and emissions without compromising safety. This thesis presents contributions to a framework for the design and implementation of HDV platooning. The focus lies mainly on establishing and validating realconstraints for fuel optimal control for platooning vehicles. Nonlinear and linearvehicle models are presented together with a system architecture, which dividesthe complex problem into manageable subsystems. The fuel reduction potentialis investigated through simulation models and experimental results derived fromstandard vehicles traveling on a Swedish highway. It is shown through analyticaland experimental results that it is favorable with respect to the fuel consumption tooperate the vehicles at a much shorter intermediate spacing than what is currentlydone in commercially available systems. The results show that a maximum fuelreduction of 4.7–7.7 % depending on the inter-vehicle time gap, at a set speedof 70 km/h, can be obtained without compromising safety. A systematic designmethodology for inter-vehicle distance control is presented based on linear quadraticregulators (LQRs). The structure of the controller feedback matrix can be tailoredto the locally available state information. The results show that a decentralizedcontroller gives good tracking performance, a robust system and lowers the controleffort downstream in the platoon. It is also shown that the design methodologyproduces a string stable system for an arbitrary number of vehicles in the platoon,if the vehicle configurations and the LQR weighting parameters are identical for theconsidered subsystems. With the results obtained in this thesis, it is argued that a vast fuel reductionpotential exists for HDV platooning. Present commercial systems can be enhancedsignificantly through the introduction of wireless communication and decentralizedoptimal control. / QC 20111012

Class 8 heavy-duty truck platooning has demonstrated significant fuel economy benefits on routes with road grade less than±2% in literature, but there is little to no platooning research on routes with road grade greater than±2% - which make up a significant portion of U.S. highways. Therefore, the effort described in this thesis is aimed at assessing currently available two-truck platoon control strategies as well as developing new strategies to improve platoon performance on hilly terrain. Specifically, the strategies tested in this work include four types of lead truck speed control strategies and two types of platoon transmission shifting strategies. These strategies are tested using two experimentally validated heavy-duty, two-truck platoon simulation approaches where each approach has its own advantages and disadvantages. The trends observed from these two simulation approaches indicate that the lead truck speed control and transmission shifting strategies have a significant effect on the platoon fuel economy and gap control performance when the platoon operates on a hilly terrain route.

The urge to consume does not seem to stop, thus, the need for transportation of goods will most likely not decrease. At the same time jurisdictions and regulations around greenhouse gas emissions are sharpening and pushing the industry towards a more environmentally friendly state. The freight and transportation industry is facing a huge challenge in the upcoming years and solutions are needed to feed the demand of society. Two, of many, proposals of solving, at least, parts of the above mentioned problem is platooning and the look-ahead controller. Platooning denotes the concept of slipstream where maximum utilization of aerodynamic drag reduction is endeavoured. The lookahead controller exploits the surrounding topographical information in order to yield an optimal driving strategy, often resulting in that the vehicle initiates the phenomenon of pulse and glide, which denotes alternating between high load operation points and freewheeling, i.e. engaging neutral gear. This work has sought to investigate these concepts to determine whether or not additional fuel-efficiency can be added by manipulating and re-designing the control unit of the system. The proposed addition is built upon the look-ahead controller and supplements it by enabling communication between vehicles such that micro-transactions may occur in order to aid decision making regarding the choice of driving strategies. A vehicle model, a platoon model and the novel optimization based look-ahead-controller was synthesized and developed, where dynamic programming was used as the optimization solver of the controller. The look-ahead controller was verified such that one can conclude that it behaves according to the assumptions of such a system. The proposed micro-transaction system was also verified to conclude that it behaves as assumed, yielding a reduction in fuel consumption. For a platoon of two members, a 1.2% and 1.7% reduction in fuel consumption for the leading and following vehicle respectively was obtained, compared to an identical platooning setup, using a lookahead controller, but where no negotiations using micro-transactions are allowed between the vehicles.

Safety is a paramount concern when considering implementation of an automated highway where computers control the vehicles. Even with computer-fast reaction time there is inevitably some delay and if vehicles do not follow at safe distances, emergency braking maneuvers can cause dangerous collisions. This research investigates situations that might make automated vehicles have dangerous collisions and what standards the system design must hold to keep passengers safe.

Platooning concept involves a group of vehicles acting as a single unit through coordination of movements. While Platooning as an evolving trend in mobility and transportation diminishes the individual and manual driving concerns, it creates new risks. New technologies and passenger’s safety and security further complicate matters and make platooning attractive target for the malicious minds. To improve the security of the vehicular platooning, threats and their potential impacts on vehicular platooning should be identified to protect the system against security risks. Furthermore, algorithms should be proposed to detect intrusions and mitigate the effects in case of attack. This dissertation introduces a new vulnerability in vehicular platooning from the control systems perspective and presents the detection and mitigation algorithms to protect vehicles and passengers in the event of the attack.

The goal of this project was to create an accurate and flexible visualization of an already existing platooning simulation with the use of Unity. This was done by using the output of the simulation as input for the visualiza- tion with information about the speed, position and status of each vehicle in the platoon. A simple steering algorithm was created for test cases with a curved road. With no exact information between two input points, linear interpolation was utilized to estimate the velocity. Without adjusting the position at each input, the maximum errors between the visualization and the simulation for each vehicle were approximately 3.5 meters. After intro- ducing a position adjustment at each input, the maximum errors decreased to between 0.6 and 0.8 meters at the cost of non-continuous motion. The error threshold for the visualization to be considered accurate is 2 meters, implying that the position adjustment is required for good results. / Målet med detta projekt var att skapa en noggrann och exibel visualisering av en existerande konvojkörning simulering med hjälp av Unity. Detta gjordes genom att använda utdata från simuleringen som indata i visualiseringen med information om hastighet, position och status för varje fordon i konvojen. En enkel styrningsalgoritm skapades för testfall där vägen svänger. Utan exakt information mellan varje indata användes linjär interpolering för att uppskatta hastigheten. Utan att justera positionen vid varje indata blev de maximala felen mellan visualiseringen och simuleringen ungefär 3.5 meter för varje fordon. Efter det att positionsjustering introducerats minskade felen till mellan 0.6 och 0.8 meter men med icke-kontinuerlig rörelse hos fordonen. Felgränsen för att visualiseringen ska räknas som noggrann är 2 meter, vilket betyder att positionsjustering är nödvändig för bra resultat.