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Karl H. Johansson - One of the best experts on this subject based on the ideXlab platform.
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Cooperative Look-Ahead Control for Fuel-Efficient and Safe Heavy-Duty Vehicle Platooning
IEEE Transactions on Control Systems Technology, 2017Co-Authors: Valerio Turri, Bart Besselink, Karl H. JohanssonAbstract:The operation of groups of heavy-Duty Vehicles at a short inter-vehicular distance, known as platoon, allows one to lower the overall aerodynamic drag and, therefore, to reduce fuel consumption and greenhouse gas emissions. However, due to the large mass and limited engine power of trucks, slopes have a significant impact on the feasible and optimal speed profiles that each Vehicle can and should follow. Maintaining a short inter-vehicular distance, as required by platooning, without coordination between Vehicles can often result in inefficient or even unfeasible trajectories. In this paper, we propose a two-layer control architecture for heavy-Duty Vehicle platooning aimed to safely and fuel-efficiently coordinate the Vehicles in the platoon. Here, the layers are responsible for the inclusion of preview information on road topography and the real-time control of the Vehicles, respectively. Within this architecture, dynamic programming is used to compute the fuel-optimal speed profile for the entire platoon and a distributed model predictive control framework is developed for the real-time control of the Vehicles. The effectiveness of the proposed controller is analyzed by means of simulations of several realistic scenarios that suggest a possible fuel saving of up to 12% for follower Vehicles compared with the use of standard platoon controllers.
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Heavy-Duty Vehicle Platoon Formation for Fuel Efficiency
IEEE Transactions on Intelligent Transportation Systems, 2016Co-Authors: Kuo-yun Liang, Jonas Mårtensson, Karl H. JohanssonAbstract:Heavy-Duty Vehicles driving close behind each other, also known as platooning, experience a reduced aerodynamic drag, which reduces the overall fuel consumption up to 20% for the trailing Vehicle. However, due to each Vehicle being assigned with different transport missions (with different origins, destinations, and delivery times), platoons should be formed, split, and merged along the highways, and Vehicles have to drive solo sometimes. In this paper, we study how two or more scattered Vehicles can cooperate to form platoons in a fuel-efficient manner. We show that when forming platoons on the fly on the same route and not considering rerouting, the road topography has a negligible effect on the coordination decision. With this, we then formulate an optimization problem when coordinating two Vehicles to form a platoon. We propose a coordination algorithm to form platoons of several Vehicles that coordinates neighboring Vehicles pairwise. Through a simulation study with detailed Vehicle models and real road topography, it is shown that our approach yields significant fuel savings.
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A Distributed Framework for Coordinated Heavy-Duty Vehicle Platooning
IEEE Transactions on Intelligent Transportation Systems, 2015Co-Authors: Jeffrey Larson, Kuo-yun Liang, Karl H. JohanssonAbstract:Heavy-Duty Vehicles (HDVs) traveling in single file with small interVehicle distances experience reduced aerodynamic drag and, therefore, have improved fuel economy. In this paper, we attempt to maximize the amount of fuel saved by coordinating platoon formation using a distributed network of controllers. These virtual controllers, placed at major intersections in a road network, help coordinate the velocity of approaching Vehicles so they arrive at the junction simultaneously and can therefore platoon. This control is initiated only if the cost of forming the platoon is smaller than the savings incurred from platooning. In a large-scale simulation of the German Autobahn network, we observe that savings surpassing 5% when only a few thousand Vehicles participate in the system. These results are corroborated by an analysis of real-world HDV data that show significant platooning opportunities currently exist, suggesting that a slightly invasive network of distributed controllers, such as the one proposed in this paper, can yield considerable savings.
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Fuel-saving potentials of platooning evaluated through sparse heavy-Duty Vehicle position data
2014 IEEE Intelligent Vehicles Symposium Proceedings, 2014Co-Authors: Kuo-yun Liang, Jonas Mårtensson, Karl H. JohanssonAbstract:Vehicle platooning is important for heavy-Duty Vehicle manufacturers, due to the reduced aerodynamic drag for the follower Vehicles, which gives an overall lower fuel consumption. Heavy-Duty Vehicle drivers are aware this fact and sometimes drive close to other heavy-Duty Vehicles. However, it is not currently well known how many Vehicles are actually driving in such spontaneous platoons today. This paper studies the platooning rate of 1,800 heavy-Duty Vehicles by analyzing sparse Vehicle position data from a region in Europe during one day. Map-matching and path-inference algorithms are used to determine which paths the Vehicles took. The spontaneous platooning rate is found to be 1.2 %, which corresponds to a total fuel saving of 0.07% compared to if none of the Vehicles were platooning. Furthermore, we introduce several virtual coordination schemes. We show that coordinations can increase the platooning rate and fuel saving with a factor of ten with minor adjustments from the current travel schedule. The platooning rate and fuel savings can be significantly greater if higher flexibility is allowed.
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Look-ahead cruise control for heavy Duty Vehicle platooning
16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013), 2013Co-Authors: Assad Al Alam, Jonas Mårtensson, Karl H. JohanssonAbstract:Vehicle platooning has become important for the Vehicle industry. Yet conclusive results with respect to the fuel reduction possibilities of platooning remain unclear, in particular when considering constraints imposed by the topography. The focus of this study is to establish whether it is more fuel-efficient to maintain or to split a platoon that is facing steep uphill and downhill segments. Two commercial controllers, an adaptive cruise controller and a look-ahead cruise controller, are evaluated and alternative novel control strategies are proposed. The results show that an improved fuel-efficiency can be obtained by maintaining the platoon throughout a hill. Hence, a cooperative control strategy based on preview information is presented, which initiates the change in velocity at a specific point in the road for all Vehicles rather than simultaneously changing the velocity to maintain the spacing. A fuel reduction of up to 14% can be obtained over a steep downhill segment and a more subtle benefit of 0.7% improvement over an uphill segment with the proposed controller, compared to the combination of the commercially available cruise controller and adaptive cruise controller that could be used for platooning. The findings show that it is both fuel-efficient and desirable in practice to consider preview information of the topography in the control strategy.
Jonas Mårtensson - One of the best experts on this subject based on the ideXlab platform.
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A Predictive Framework for Dynamic Heavy-Duty Vehicle Platoon Coordination
ACM Transactions on Cyber-Physical Systems, 2020Co-Authors: Sebastian Van De Hoef, Jonas Mårtensson, Dimos V. Dimarogonas, Karl Henrik JohanssonAbstract:This article describes a system to facilitate dynamic en route formation of heavy-Duty Vehicle platoons with the goal of reducing fuel consumption. Safe Vehicle platooning is a maturing technology ...
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Optimal Speed Control of a Heavy-Duty Vehicle in Urban Driving
IEEE Transactions on Intelligent Transportation Systems, 2019Co-Authors: Manne Held, Oscar Flärdh, Jonas MårtenssonAbstract:Fuel efficient driving patterns are well investigated for highway driving, but less so for applications with varying speed requirements, such as urban driving. In this paper, the driving mission of a heavy-Duty Vehicle in urban driving is formulated as an optimal control problem. The velocity of the Vehicle is restricted to be within upper and lower constraints referred to as the driving corridor. The driving corridor is constructed from a test cycle with large variations in the speed profile, together with statistics from Vehicles in real operation. The optimal control problem is first solved off-line using Pontryagin's maximum principle. A sensitivity analysis is performed in order to investigate how variations in the driving corridor influence the energy consumption of the optimal solution. The same problem is also solved using a model predictive controller with a receding horizon approach. Simulations are performed in order to investigate how the length of the control horizon influences the potential energy savings. Simulations on a test cycle with varying speed profile show that 7% energy can be saved without increasing the trip time or deviating from a normal driving pattern. A horizon length of 1000 m is sufficient to realize these savings by the model predictive controller. The Vehicle model used in these simulations is extended to include regenerative braking in order to investigate its influence on the optimal control policy and the results.
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Heavy-Duty Vehicle Platoon Formation for Fuel Efficiency
IEEE Transactions on Intelligent Transportation Systems, 2016Co-Authors: Kuo-yun Liang, Jonas Mårtensson, Karl H. JohanssonAbstract:Heavy-Duty Vehicles driving close behind each other, also known as platooning, experience a reduced aerodynamic drag, which reduces the overall fuel consumption up to 20% for the trailing Vehicle. However, due to each Vehicle being assigned with different transport missions (with different origins, destinations, and delivery times), platoons should be formed, split, and merged along the highways, and Vehicles have to drive solo sometimes. In this paper, we study how two or more scattered Vehicles can cooperate to form platoons in a fuel-efficient manner. We show that when forming platoons on the fly on the same route and not considering rerouting, the road topography has a negligible effect on the coordination decision. With this, we then formulate an optimization problem when coordinating two Vehicles to form a platoon. We propose a coordination algorithm to form platoons of several Vehicles that coordinates neighboring Vehicles pairwise. Through a simulation study with detailed Vehicle models and real road topography, it is shown that our approach yields significant fuel savings.
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Experimental evaluation of decentralized cooperative cruise control for heavy-Duty Vehicle platooning
Control Engineering Practice, 2015Co-Authors: Assad Al Alam, Jonas Mårtensson, Karl Henrik JohanssonAbstract:In this paper, we consider the problem of finding decentralized controllers for heavy-Duty Vehicle (HDV) platooning by establishing empiric results for a qualitative verification of a control desig ...
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fuel efficient heavy Duty Vehicle platooning by look ahead control
Conference on Decision and Control, 2014Co-Authors: Valerio Turri, Jonas Mårtensson, Bart Besselink, Karl Henrik JohanssonAbstract:The operation of groups of heavy-Duty Vehicles at close intervehicular distances (known as platoons) has been shown to be an effective way of reducing fuel consumption. For single Vehicles, it is also known that the availability of preview information on the road topography can be exploited to obtain fuel savings. The current paper aims at the inclusion of preview information in platooning by introducing a two-layer control system architecture for so-called look-ahead platooning. Here, the layers are responsible for the inclusion of preview information and real-time Vehicle control for platooning, respectively. Within this framework, a control strategy is presented, where dynamic programming is used for the calculation of fuel-optimal speed profiles, while a model predictive control approach is exploited for the real-time Vehicle control. The feasibility of this approach is illustrated by means of the simulation of relevant scenarios.
Karl Henrik Johansson - One of the best experts on this subject based on the ideXlab platform.
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A Predictive Framework for Dynamic Heavy-Duty Vehicle Platoon Coordination
ACM Transactions on Cyber-Physical Systems, 2020Co-Authors: Sebastian Van De Hoef, Jonas Mårtensson, Dimos V. Dimarogonas, Karl Henrik JohanssonAbstract:This article describes a system to facilitate dynamic en route formation of heavy-Duty Vehicle platoons with the goal of reducing fuel consumption. Safe Vehicle platooning is a maturing technology ...
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Disturbance observer approach for fuel-efficient heavy-Duty Vehicle platooning
Vehicle System Dynamics, 2019Co-Authors: Gyunghoon Park, Karl Henrik Johansson, Valerio Turri, Hyungbo Shim, Yongsoon EunAbstract:Heavy-Duty Vehicle platooning has received much attention as a method to reduce fuel consumption by keeping inter-Vehicle distance short. When a platoon follows a fuel-optimal velocity profile calc...
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Experimental evaluation of decentralized cooperative cruise control for heavy-Duty Vehicle platooning
Control Engineering Practice, 2015Co-Authors: Assad Al Alam, Jonas Mårtensson, Karl Henrik JohanssonAbstract:In this paper, we consider the problem of finding decentralized controllers for heavy-Duty Vehicle (HDV) platooning by establishing empiric results for a qualitative verification of a control desig ...
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fuel efficient heavy Duty Vehicle platooning by look ahead control
Conference on Decision and Control, 2014Co-Authors: Valerio Turri, Jonas Mårtensson, Bart Besselink, Karl Henrik JohanssonAbstract:The operation of groups of heavy-Duty Vehicles at close intervehicular distances (known as platoons) has been shown to be an effective way of reducing fuel consumption. For single Vehicles, it is also known that the availability of preview information on the road topography can be exploited to obtain fuel savings. The current paper aims at the inclusion of preview information in platooning by introducing a two-layer control system architecture for so-called look-ahead platooning. Here, the layers are responsible for the inclusion of preview information and real-time Vehicle control for platooning, respectively. Within this framework, a control strategy is presented, where dynamic programming is used for the calculation of fuel-optimal speed profiles, while a model predictive control approach is exploited for the real-time Vehicle control. The feasibility of this approach is illustrated by means of the simulation of relevant scenarios.
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guaranteeing safety for heavy Duty Vehicle platooning safe set computations and experimental evaluations
Control Engineering Practice, 2014Co-Authors: Assad Al Alam, Ather Gattami, Karl Henrik Johansson, Claire J TomlinAbstract:In this paper, we consider the problem of finding a safety criteria between neighboring heavy Duty Vehicles traveling in a platoon. We present a possible framework for analyzing safety aspects of heavy Duty Vehicle platooning. A nonlinear underlying dynamical model is utilized, where the states of two neighboring Vehicles are conveyed through radar information and wireless communication. Numerical safe sets are derived through the framework, under a worst-case scenario, and the minimum safe spacing is studied for heterogenous platoons. Real life experimental results are presented in an attempt to validate the theoretical results in practice. The findings show that a minimum relative distance of 1.2 m at maximum legal velocity on Swedish highways can be maintained for two identical Vehicles without endangering a collision. The main conclusion is that the relative distance utilized in commercial applications today can be reduced significantly with a suitable automatic control system.
Kuo-yun Liang - One of the best experts on this subject based on the ideXlab platform.
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Heavy-Duty Vehicle Platoon Formation for Fuel Efficiency
IEEE Transactions on Intelligent Transportation Systems, 2016Co-Authors: Kuo-yun Liang, Jonas Mårtensson, Karl H. JohanssonAbstract:Heavy-Duty Vehicles driving close behind each other, also known as platooning, experience a reduced aerodynamic drag, which reduces the overall fuel consumption up to 20% for the trailing Vehicle. However, due to each Vehicle being assigned with different transport missions (with different origins, destinations, and delivery times), platoons should be formed, split, and merged along the highways, and Vehicles have to drive solo sometimes. In this paper, we study how two or more scattered Vehicles can cooperate to form platoons in a fuel-efficient manner. We show that when forming platoons on the fly on the same route and not considering rerouting, the road topography has a negligible effect on the coordination decision. With this, we then formulate an optimization problem when coordinating two Vehicles to form a platoon. We propose a coordination algorithm to form platoons of several Vehicles that coordinates neighboring Vehicles pairwise. Through a simulation study with detailed Vehicle models and real road topography, it is shown that our approach yields significant fuel savings.
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A Distributed Framework for Coordinated Heavy-Duty Vehicle Platooning
IEEE Transactions on Intelligent Transportation Systems, 2015Co-Authors: Jeffrey Larson, Kuo-yun Liang, Karl H. JohanssonAbstract:Heavy-Duty Vehicles (HDVs) traveling in single file with small interVehicle distances experience reduced aerodynamic drag and, therefore, have improved fuel economy. In this paper, we attempt to maximize the amount of fuel saved by coordinating platoon formation using a distributed network of controllers. These virtual controllers, placed at major intersections in a road network, help coordinate the velocity of approaching Vehicles so they arrive at the junction simultaneously and can therefore platoon. This control is initiated only if the cost of forming the platoon is smaller than the savings incurred from platooning. In a large-scale simulation of the German Autobahn network, we observe that savings surpassing 5% when only a few thousand Vehicles participate in the system. These results are corroborated by an analysis of real-world HDV data that show significant platooning opportunities currently exist, suggesting that a slightly invasive network of distributed controllers, such as the one proposed in this paper, can yield considerable savings.
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Fuel-saving potentials of platooning evaluated through sparse heavy-Duty Vehicle position data
2014 IEEE Intelligent Vehicles Symposium Proceedings, 2014Co-Authors: Kuo-yun Liang, Jonas Mårtensson, Karl H. JohanssonAbstract:Vehicle platooning is important for heavy-Duty Vehicle manufacturers, due to the reduced aerodynamic drag for the follower Vehicles, which gives an overall lower fuel consumption. Heavy-Duty Vehicle drivers are aware this fact and sometimes drive close to other heavy-Duty Vehicles. However, it is not currently well known how many Vehicles are actually driving in such spontaneous platoons today. This paper studies the platooning rate of 1,800 heavy-Duty Vehicles by analyzing sparse Vehicle position data from a region in Europe during one day. Map-matching and path-inference algorithms are used to determine which paths the Vehicles took. The spontaneous platooning rate is found to be 1.2 %, which corresponds to a total fuel saving of 0.07% compared to if none of the Vehicles were platooning. Furthermore, we introduce several virtual coordination schemes. We show that coordinations can increase the platooning rate and fuel saving with a factor of ten with minor adjustments from the current travel schedule. The platooning rate and fuel savings can be significantly greater if higher flexibility is allowed.
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Coordination and routing for fuel-efficient heavy-Duty Vehicle platoon formation
2014Co-Authors: Kuo-yun LiangAbstract:Heavy-Duty Vehicle (HDV) manufacturers and fleet owners are facing great challenges for a maintained sustainable transport system as the demand for road freight transport is continuously increasing ...
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coordinated route optimization for heavy Duty Vehicle platoons
International Conference on Intelligent Transportation Systems, 2013Co-Authors: Jeffrey Larson, Kuo-yun Liang, Christoph Kammer, Karl Henrik JohanssonAbstract:Heavy-Duty Vehicles traveling in platoons consume fuel at a reduced rate. In this paper, we attempt to maximize this benefit by introducing local controllers throughout a road network to facilitate platoon formations with minimal information. By knowing a Vehicle's position, speed, and destination, the local controller can quickly decide how its speed should be possibly adjusted to platoon with others in the near future. We solve this optimal control and routing problem exactly for small numbers of Vehicles, and present a fast heuristic algorithm for real-time use. We then implement such a distributed control system through a large-scale simulation of the German autobahn road network containing thousands of Vehicles. The simulation shows fuel savings from 1-9%, with savings exceeding 5% when only a few thousand Vehicles participate in the system. We assume no Vehicles will travel more than the time required for their shortest paths for the majority of the paper. We conclude the results by analyzing how a relaxation of this assumption can further reduce fuel use.
Assad Al Alam - One of the best experts on this subject based on the ideXlab platform.
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Experimental evaluation of decentralized cooperative cruise control for heavy-Duty Vehicle platooning
Control Engineering Practice, 2015Co-Authors: Assad Al Alam, Jonas Mårtensson, Karl Henrik JohanssonAbstract:In this paper, we consider the problem of finding decentralized controllers for heavy-Duty Vehicle (HDV) platooning by establishing empiric results for a qualitative verification of a control desig ...
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guaranteeing safety for heavy Duty Vehicle platooning safe set computations and experimental evaluations
Control Engineering Practice, 2014Co-Authors: Assad Al Alam, Ather Gattami, Karl Henrik Johansson, Claire J TomlinAbstract:In this paper, we consider the problem of finding a safety criteria between neighboring heavy Duty Vehicles traveling in a platoon. We present a possible framework for analyzing safety aspects of heavy Duty Vehicle platooning. A nonlinear underlying dynamical model is utilized, where the states of two neighboring Vehicles are conveyed through radar information and wireless communication. Numerical safe sets are derived through the framework, under a worst-case scenario, and the minimum safe spacing is studied for heterogenous platoons. Real life experimental results are presented in an attempt to validate the theoretical results in practice. The findings show that a minimum relative distance of 1.2 m at maximum legal velocity on Swedish highways can be maintained for two identical Vehicles without endangering a collision. The main conclusion is that the relative distance utilized in commercial applications today can be reduced significantly with a suitable automatic control system.
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fuel efficient heavy Duty Vehicle platooning
2014Co-Authors: Assad Al AlamAbstract:The freight transport industry faces big challenges as the demand for transport and fuel prices are steadily increasing, whereas the environmental impact needs to be significantly reduced. Heavy-du ...
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Look-ahead cruise control for heavy Duty Vehicle platooning
16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013), 2013Co-Authors: Assad Al Alam, Jonas Mårtensson, Karl H. JohanssonAbstract:Vehicle platooning has become important for the Vehicle industry. Yet conclusive results with respect to the fuel reduction possibilities of platooning remain unclear, in particular when considering constraints imposed by the topography. The focus of this study is to establish whether it is more fuel-efficient to maintain or to split a platoon that is facing steep uphill and downhill segments. Two commercial controllers, an adaptive cruise controller and a look-ahead cruise controller, are evaluated and alternative novel control strategies are proposed. The results show that an improved fuel-efficiency can be obtained by maintaining the platoon throughout a hill. Hence, a cooperative control strategy based on preview information is presented, which initiates the change in velocity at a specific point in the road for all Vehicles rather than simultaneously changing the velocity to maintain the spacing. A fuel reduction of up to 14% can be obtained over a steep downhill segment and a more subtle benefit of 0.7% improvement over an uphill segment with the proposed controller, compared to the combination of the commercially available cruise controller and adaptive cruise controller that could be used for platooning. The findings show that it is both fuel-efficient and desirable in practice to consider preview information of the topography in the control strategy.
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VNC - The impact of heterogeneity and order in heavy Duty Vehicle platooning networks (poster)
2011 IEEE Vehicular Networking Conference (VNC), 2011Co-Authors: Kuo-yun Liang, Assad Al Alam, Ather GattamiAbstract:It is formally known that by establishing a heavy Duty Vehicle platoon, the fuel consumption is reduced for the follower Vehicle due to the lower air drag. However, it is not clear how the platoon should be formed with respect to the heavy Duty Vehicle properties. String stability is a well discussed issue in Vehicle platooning. However, each Vehicle's properties have to be taken into consideration when analyzing the platoon system. In this paper, we analyze one property of heavy Duty Vehicles — the mass. The results show that the robustness is influenced by the order and physical characteristics of the Vehicles in the platoon. When utilizing identical PID controllers for all Vehicles in the platoon, it is better to arrange the heaviest Vehicle first with decreasing mass order when considering the platoon behavior. However, in reality it is difficult to start rearranging a platoon in the middle of a highway and it would also require V2V-communication. A controller is often optimized for a particular configuration set that can cause slinky effects to the platoon. Therefore, a mass-dependent PID controller is introduced to establish a better platoon behavior for heavy Duty Vehicles. The results show no slinky effects regardless of the Vehicle order in the platoon.
