Spelling suggestions: "subject:"truck platooning"" "subject:"truck aplatooning""
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Decentralized coordination for truck platooningZeng, Yikai, Wang, Meng, Rajan, Raj Thilak 19 January 2024 (has links)
Coordination for truck platooning refers to the active formation of a group of heavy-duty vehicles traveling at close spacing to reduce the overall truck operations costs. Conventionally, this coordination is achieved by optimizing various truck-related parameters, such as schedules, velocities, and routes, based on an objective function that minimizes a certain cost, for example, fuel usage. However, prevalent algorithms for the coordination problem are typically integer-constrained, which are not only hard to solve but are not readily scalable to increasing fleet sizes and networks. In this paper, to overcome these limitations, we propose a centralized formulation to optimize the truck parameters and solve a multidimensional objective cost function including fuel, operation time costs and preferential penalty. Furthermore, to improve the scalability of our proposed approach, we propose a decentralized algorithm for the platoon coordination problem involving multiple fleets and objectives.We perform both theoretical and numerical studies to evaluate the performance of our decentralized algorithm against the centralized solution. Our analysis indicates that the computation time of the proposed decentralized algorithms is invariant to the increasing fleet size, at the cost of a small relative gap to the optimum cost given by the centralized method.We discuss these results and present future directions for research.
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Impacts of Tires and Axle Configurations on Perpetual Pavement ResponseTarawneh, Derar Mohammad Hamed 24 May 2022 (has links)
No description available.
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The operational and safety effects of heavy duty vehicles platooningAlzahrani, Ahmed 01 January 2019 (has links)
Abstract
Although researchers have studied the effects of platooning, most of the work done so far has focused on fuel consumption. There are a few studies that have targeted the impact of platooning on the highway operations and safety. This thesis focuses on the impact of heavy-duty vehicles (HDVs) platooning on highway characteristics. Specifically, this study aims at evaluating the effects of platooning of HDVs on capacity, safety, and CO2 emissions.
This study is based on a hypothetical model that was created using the VISSIM software. VISSIM is a powerful simulation software designed to mimic the field traffic flow conditions. For model validity, the model outputs were compared with recommended values from guidelines such as the Highway Capacity Manual (HCM) (Transportation Research Board, 2016).
VISSIM was used to obtain the simulation results regarding capacity. However, in addition to VISSIM, two other software packages were used to obtain outputs that cannot be assessed in VISSIM. MOVES and SSAM are two simulation software packages that were used for emission and safety metrics, respectively. Both software packages depended on input from VISSIM for analysis.
It was found that with the presence of HDVs in the model, the capacity, the emission of CO2, and the safety of the roadway would improve positively. A capacity of 4200 PCE/h/ln could be achieved when there are enough HDVs in platoons. Furthermore, more than 3% of the traffic flow emission of CO2 reduction is possible when 100% of the HDVs used in the model are in platoons. In addition to that, a reduction of more than 75% of the total number of conflicts might be obtained.
Furthermore, with the analysis of the full factorial method and the Design of Experiment (DOE) conducted by using Excel and Minitab respectively, it was possible to investigate the impact of the platoons’ factors on the highway parameters. Most of these factors affect the parameters significantly. However, the change in the desired speed was found to insignificantly affect the highway parameters, due to the high penetration rate.
Keywords: VISSIM, MOVES, SSAM, COM-interface, HDVs, Platooning, Number of Conflicts
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Advanced Control Strategies for Diesel Engine Thermal Management and Class 8 Truck PlatooningJohn Foster (9179864) 29 July 2020 (has links)
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<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.
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<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.
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<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.
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<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.
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