A Method of Optimal Control for Class 8 Vehicle Platoons Over Hilly Terrain

2021 ◽  
Author(s):  
Jacob Ward ◽  
Evan Stegner ◽  
Mark Hoffman ◽  
David M. Bevly
Keyword(s):  
Fuel Consumption ◽  
Control Method ◽  
Final Analysis ◽  
Cruise Control ◽  
Optimal Velocity ◽  
Fuel Savings ◽  
Cooperative Adaptive Cruise Control ◽  
Vehicle Operation ◽  
Reference Vehicle ◽  
Vehicle Platoons

Abstract This work develops and implements an NMPC control system to facilitate fuel-optimal platooning of Class 8 vehicles over challenging terrain. Prior research has shown that Cooperative Adaptive Cruise Control (CACC), which allows multiple Class 8 vehicles to follow in close succession, can save between 3 and 8% in overall fuel consumption on flat terrain. However, on more challenging terrain, e.g. rolling hills, platooning vehicles can experience diminished fuel savings, and, in some cases, an increase in fuel consumption relative to individual vehicle operation. This research explores the use of Nonlinear Model Predictive Control (NMPC) with predefined route grade profiles to allow platooning vehicles to generate an optimal velocity trajectory with respect to fuel consumption. In order to successfully implement the NMPC system, a model relating vehicle velocity to fuel consumption was generated and validated using experimental data. Additionally, the predefined route grade profiles were created by using the vehicle's GPS velocity over the desired terrain. The real-time NMPC system was then implemented on a two-truck platoon operating over challenging terrain, with a reference vehicle running individually. The results from NMPC platooning are compared against fuel results from a classical proportional-integral-derivative (PID) headway control method. This comparison yields the comparative fuel savings and energy efficiency benefit of NMPC system. In the final analysis, significant fuel savings of greater than 14 and 20% were seen for the lead and following vehicles relative to their respective traditional cruise control and platooning architectures.

Multiobjective Optimization Framework for Cooperative Adaptive Cruise Control Vehicles in the Automated Vehicle Platooning Environment

2017 ◽  
Vol 2625 (1) ◽  
pp. 32-42 ◽  
Author(s):  
Zijia Zhong ◽  
Joyoung Lee ◽  
Liuhui Zhao
Keyword(s):  
Multiobjective Optimization ◽  
Fuel Consumption ◽  
Adaptive Cruise Control ◽  
Control Method ◽  
Cruise Control ◽  
Longitudinal Control ◽  
Target Time ◽  
Cooperative Adaptive Cruise Control ◽  
Vehicle Platoon ◽  
Unsafe Condition

Automated longitudinal control technology has been tested through cooperative adaptive cruise control (CACC), which is envisioned to improve highway mobility drastically by forming a vehicle platoon with short headway while maintaining stable traffic flow under disturbances. Compared with previous research efforts with the pseudomultiobjective optimization process, this paper proposes an automated longitudinal control framework based on multiobjective optimization (MOOP) for CACC by taking into consideration four optimization objectives: mobility, safety, driver comfort, and fuel consumption. Of the target time headways that have been tested, the proposed CACC platoon control method achieved the best performance with 0.9- and 0.6-s target time headways. Compared with a non-optimization-based CACC, the MOOP CACC achieved 98%, 93%, 42%, and 33% objective value reductions of time headway deviation, unsafe condition, jitter, and instantaneous fuel consumption, respectively. In comparison with a single-objective-optimization-based approach, which optimized only one of the four proposed objectives, it was shown that the MOOP-based CACC maintained a good balance between all of the objective functions and achieved Pareto optimality for the entire platoon.

Effects of adaptive and cooperative adaptive cruise control on the fuel consumption and emissions at the signalized intersection

2018 ◽  
Vol 32 (32) ◽  
pp. 1850396 ◽  
Author(s):  
Hongjun Cui ◽  
Jiangke Xing ◽  
Xia Li ◽  
Minqing Zhu
Keyword(s):  
Fuel Consumption ◽  
Red Light ◽  
Signalized Intersection ◽  
Environmental Benefit ◽  
Cruise Control ◽  
Car Following ◽  
Vehicle Type ◽  
Cooperative Adaptive Cruise Control ◽  
Car Following Model ◽  
Fuel Consumption And Emissions

In this paper, the HDM car-following model, the IIDM car-following model and the IDM car-following model with a constant-acceleration heuristic is utilized to explore the effects of ACC/CACC on the fuel consumption and emissionsat the signalized intersection. Two simulation experiments are studied: (i) one with free road ahead and (ii) the second with a red light 300 m downstream at the second intersection. The numerical results show that CACC vehicle is the best vehicle type among the three vehicle types from the perspective of vehicle’s cumulative fuel consumptions and cumulative exhaust emissions. The results of this paper also suggest a very high environmental benefit of ACC/CACC at little or no cost in infrastructure.

Safety, Energy, and Emissions Impacts of Adaptive Cruise Control and Cooperative Adaptive Cruise Control

2020 ◽  
Vol 2674 (6) ◽  
pp. 253-267 ◽  
Author(s):  
Iman Mahdinia ◽  
Ramin Arvin ◽  
Asad J. Khattak ◽  
Amir Ghiasi
Keyword(s):  
Fuel Consumption ◽  
Adaptive Cruise Control ◽  
Field Tests ◽  
System Level ◽  
Level Energy ◽  
Cruise Control ◽  
Driver Assistance Systems ◽  
Cooperative Adaptive Cruise Control ◽  
Vehicle Platoon ◽  
Fuel Consumption And Emissions

Connected and automated vehicle technologies have the potential to significantly improve transportation system performance. In particular, advanced driver-assistance systems, such as adaptive cruise control (ACC) and cooperative adaptive cruise control (CACC), may lead to substantial improvements in performance by decreasing driver inputs and taking over control of the vehicle. However, the impacts of these technologies on the vehicle- and system-level energy consumption, emissions, and safety have not been quantified in field tests. The goal of this paper is to study the impacts of automated and cooperative systems in mixed traffic containing conventional, ACC, and CACC vehicles. To reach this goal, experimental data based on real-world conditions are collected (in tests conducted by the Federal Highway Administration and the U.S. Department of Transportation) with presence of ACC, CACC, and conventional vehicles in a vehicle platoon scenario and a cooperative merging scenario. Specifically, a platoon of five vehicles with different vehicle type combinations is analyzed to generate new knowledge about potential safety, energy efficiency, and emission improvement from vehicle automation and cooperation. Results show that adopting the CACC system in a five-vehicle platoon substantially reduces the driving volatility and reduces the risk of rear-end collision which consequently improves safety. Furthermore, it decreases fuel consumption and emissions compared with the ACC system and manually-driven vehicles. Results of the merging scenario show that while the cooperative merging system slightly reduces the driving volatility, the fuel consumption and emissions can increase because of sharper accelerations of CACC vehicles compared with manually-driven vehicles.

Multi-Vehicle Trajectory Design During Cooperative Adaptive Cruise Control Platoon Formation

2020 ◽  
Vol 2674 (4) ◽  
pp. 30-41 ◽  
Author(s):  
Qinzheng Wang ◽  
Xianfeng (Terry) Yang ◽  
Zhitong Huang ◽  
Yun Yuan
Keyword(s):  
Fuel Consumption ◽  
Adaptive Cruise Control ◽  
Second Phase ◽  
Trajectory Design ◽  
Cruise Control ◽  
Basic Scenario ◽  
Vehicle Trajectories ◽  
Cooperative Adaptive Cruise Control ◽  
Proposed Model ◽  
Study Results

Cooperative adaptive cruise control (CACC) organizes connected and automated vehicles (CAVs) in platoons to improve traffic flow and reduce fuel consumption. Platoon formation involves a very complex process, however, because lateral and longitudinal misbehavior of CAVs results in greater fuel consumption and risk of collision. This study aims to design optimal vehicle trajectories of CAVs during CACC platoon formation. First, a basic scenario and a destination-based protocol are described to determine vehicle sequence in the platoon. A space-time lattice based model is then formulated to construct vehicle trajectories considering boundary conditions of kinematic limits, vehicle-following safety, and lane-changing rules. The objective is to optimize the vehicle sequence and fuel consumption simultaneously. A two-phase algorithm is proposed to solve this model, where the first phase is a heuristic algorithm that determines vehicle sequence and in the second phase dynamic programming is adapted to optimize fuel consumption based on the determined sequence. To evaluate the effectiveness of the proposed model in designing CAV trajectories, extensive experimental tests have been conducted in this study. Results show that the proposed model and algorithm can effectively optimize CAV sequence in the platoon based on their destinations. After optimization, CAV fuel consumption was reduced by 42%, 46%, and 43%, respectively, in three different tested scenarios.

A First Investigation of Truck Drivers’ Preferences and Behaviors using a Prototype Cooperative Adaptive Cruise Control System

2018 ◽  
Vol 2672 (34) ◽  
pp. 39-48 ◽  
Author(s):  
Shiyan Yang ◽  
Steven E. Shladover ◽  
Xiao-Yun Lu ◽  
Hani Ramezani ◽  
Aravind Kailas ◽  
...  
Keyword(s):  
Adaptive Cruise Control ◽  
Aerodynamic Drag ◽  
Truck Drivers ◽  
Cruise Control ◽  
Fuel Savings ◽  
The Road ◽  
Cooperative Adaptive Cruise Control ◽  
And Behaviors ◽  
On The Road ◽  
And Performance

Cooperative adaptive cruise control (CACC) is a driver-assist technology that uses vehicle-to-vehicle wireless communication to realize faster braking responses in following vehicles and shorter headways compared with adaptive cruise control. This technology not only enhances road safety, but also offers fuel savings benefits as a result of reduced aerodynamic drag. The amount of fuel savings is dictated by the following distances and the driving speeds. So, the overarching goal of this work is to explore driving preferences and behaviors when following in “CACC mode,” an area that remains largely unexplored. While in CACC mode, the brake and throttle actions are automated. A human factors study was conducted to investigate truck drivers’ experiences and performance using CACC at shorter-than-normal vehicle following time gaps. “On-the-road” experiments were conducted by recruiting drivers from commercial fleets to operate the second and third trucks in a three-truck CACC string. The driving route spanned 160 miles on freeways in Northern California and five different time gaps between 0.6 and 1.8 seconds were tested. Factors such as cut-ins by other vehicles, road grades, and traffic conditions were found to influence the drivers’ opinions about use of CACC. The findings presented in this paper provide insights into the factors that will influence driver reactions to the deployment of CACC in their truck fleets.

Robust stabilization of longitudinal tracking for cooperative adaptive cruise control considering input saturation

2020 ◽  
Vol 34 (35) ◽  
pp. 2050409
Author(s):  
Youguo He ◽  
Xiaoxiao Tian ◽  
Jie Shen ◽  
Chaochun Yuan ◽  
Yingkui Du
Keyword(s):  
Adaptive Cruise Control ◽  
Control Method ◽  
Controller Design ◽  
Actuator Saturation ◽  
Kinematic Model ◽  
Input Saturation ◽  
Robust Stabilization ◽  
State Feedback Control ◽  
Cruise Control ◽  
Cooperative Adaptive Cruise Control

This paper is concerned with the problem of constraint control for cooperative adaptive cruise control (CACC) with input saturation and input-additive uncertainties. An integrated longitudinal kinematic model of CACC system including vehicle model and constant time headway is established taking into account input saturation and input-additive uncertainties. According to the system’s robustness requirements under input saturation, the saturation control method is introduced. In order to achieve robust global stabilization of the system, a low-gain state feedback control law is designed by using linear low-gain feedback and gain scheduling. Meanwhile, in order to avoid the saturation of the control system, the low gain parameter [Formula: see text] is introduced into the controller design. Finally, the simulation of homogeneous and heterogeneous platoons is carried out by MATLAB/Simulink, which verifies the feasibility and effectiveness of the designed controller. Compared with the SMC controller, saturation controller successfully suppresses the acceleration amplification in the process of propagation along the vehicle platoon, avoids actuator saturation and realizes the stability of CACC system.

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