A Robust Longitudinal Control Strategy of Platoons under Model Uncertainties and Time Delays
Automated vehicles are designed to free drivers from driving tasks and are expected to improve traffic safety and efficiency when connected via vehicle-to-vehicle communication, that is, connected automated vehicles (CAVs). The time delays and model uncertainties in vehicle control systems pose chal...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2018-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2018/9852721 |
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| _version_ | 1850159659112988672 |
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| author | Na Chen Meng Wang Tom Alkim Bart van Arem |
| author_facet | Na Chen Meng Wang Tom Alkim Bart van Arem |
| author_sort | Na Chen |
| collection | DOAJ |
| description | Automated vehicles are designed to free drivers from driving tasks and are expected to improve traffic safety and efficiency when connected via vehicle-to-vehicle communication, that is, connected automated vehicles (CAVs). The time delays and model uncertainties in vehicle control systems pose challenges for automated driving in real world. Ignoring them may render the performance of cooperative driving systems unsatisfactory or even unstable. This paper aims to design a robust and flexible platooning control strategy for CAVs. A centralized control method is presented, where the leader of a CAV platoon collects information from followers, computes the desired accelerations of all controlled vehicles, and broadcasts the desired accelerations to followers. The robust platooning is formulated as a Min-Max Model Predictive Control (MM-MPC) problem, where optimal accelerations are generated to minimize the cost function under the worst case, where the worst case is taken over the possible models. The proposed method is flexible in such a way that it can be applied to both homogeneous platoon and heterogeneous platoon with mixed human-driven and automated controlled vehicles. A third-order linear vehicle model with fixed feedback delay and stochastic actuator lag is used to predict the platoon behavior. Actuator lag is assumed to vary randomly with unknown distributions but a known upper bound. The controller regulates platoon accelerations over a time horizon to minimize a cost function representing driving safety, efficiency, and ride comfort, subject to speed limits, plausible acceleration range, and minimal net spacing. The designed strategy is tested by simulating homogeneous and heterogeneous platoons in a number of typical and extreme scenarios to assess the system stability and performance. The test results demonstrate that the designed control strategy for CAV can ensure the robustness of stability and performance against model uncertainties and feedback delay and outperforms the deterministic MPC based platooning control. |
| format | Article |
| id | doaj-art-b2dcf9c8c1c046f0bc56d3d0b2e16b21 |
| institution | OA Journals |
| issn | 0197-6729 2042-3195 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-b2dcf9c8c1c046f0bc56d3d0b2e16b212025-08-20T02:23:27ZengWileyJournal of Advanced Transportation0197-67292042-31952018-01-01201810.1155/2018/98527219852721A Robust Longitudinal Control Strategy of Platoons under Model Uncertainties and Time DelaysNa Chen0Meng Wang1Tom Alkim2Bart van Arem3Department of Transport and Planning, Delft University of Technology, Stevinweg 1, 2628 CN Delft, NetherlandsDepartment of Transport and Planning, Delft University of Technology, Stevinweg 1, 2628 CN Delft, NetherlandsRijkswaterstaat, Ministry of Infrastructure and Water Management, Utrecht, NetherlandsDepartment of Transport and Planning, Delft University of Technology, Stevinweg 1, 2628 CN Delft, NetherlandsAutomated vehicles are designed to free drivers from driving tasks and are expected to improve traffic safety and efficiency when connected via vehicle-to-vehicle communication, that is, connected automated vehicles (CAVs). The time delays and model uncertainties in vehicle control systems pose challenges for automated driving in real world. Ignoring them may render the performance of cooperative driving systems unsatisfactory or even unstable. This paper aims to design a robust and flexible platooning control strategy for CAVs. A centralized control method is presented, where the leader of a CAV platoon collects information from followers, computes the desired accelerations of all controlled vehicles, and broadcasts the desired accelerations to followers. The robust platooning is formulated as a Min-Max Model Predictive Control (MM-MPC) problem, where optimal accelerations are generated to minimize the cost function under the worst case, where the worst case is taken over the possible models. The proposed method is flexible in such a way that it can be applied to both homogeneous platoon and heterogeneous platoon with mixed human-driven and automated controlled vehicles. A third-order linear vehicle model with fixed feedback delay and stochastic actuator lag is used to predict the platoon behavior. Actuator lag is assumed to vary randomly with unknown distributions but a known upper bound. The controller regulates platoon accelerations over a time horizon to minimize a cost function representing driving safety, efficiency, and ride comfort, subject to speed limits, plausible acceleration range, and minimal net spacing. The designed strategy is tested by simulating homogeneous and heterogeneous platoons in a number of typical and extreme scenarios to assess the system stability and performance. The test results demonstrate that the designed control strategy for CAV can ensure the robustness of stability and performance against model uncertainties and feedback delay and outperforms the deterministic MPC based platooning control.http://dx.doi.org/10.1155/2018/9852721 |
| spellingShingle | Na Chen Meng Wang Tom Alkim Bart van Arem A Robust Longitudinal Control Strategy of Platoons under Model Uncertainties and Time Delays Journal of Advanced Transportation |
| title | A Robust Longitudinal Control Strategy of Platoons under Model Uncertainties and Time Delays |
| title_full | A Robust Longitudinal Control Strategy of Platoons under Model Uncertainties and Time Delays |
| title_fullStr | A Robust Longitudinal Control Strategy of Platoons under Model Uncertainties and Time Delays |
| title_full_unstemmed | A Robust Longitudinal Control Strategy of Platoons under Model Uncertainties and Time Delays |
| title_short | A Robust Longitudinal Control Strategy of Platoons under Model Uncertainties and Time Delays |
| title_sort | robust longitudinal control strategy of platoons under model uncertainties and time delays |
| url | http://dx.doi.org/10.1155/2018/9852721 |
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