Real-Time Suitable Predictive Control Using SPaT Information from Automated Traffic Lights
Traffic intersections throughout the United States combine fixed, semi-actuated, and fully actuated intersections. In the case of the semi-actuated and actuated intersections, uncertainties are considered in phase duration. These uncertainties are due to car waiting queues and pedestrian crossing. I...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-05-01
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| Series: | Future Transportation |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2673-7590/3/2/38 |
| _version_ | 1797594733849083904 |
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| author | Pradeep Krishna Bhat Bo Chen |
| author_facet | Pradeep Krishna Bhat Bo Chen |
| author_sort | Pradeep Krishna Bhat |
| collection | DOAJ |
| description | Traffic intersections throughout the United States combine fixed, semi-actuated, and fully actuated intersections. In the case of the semi-actuated and actuated intersections, uncertainties are considered in phase duration. These uncertainties are due to car waiting queues and pedestrian crossing. Intelligent transportation systems deployed in traffic infrastructure can communicate Signal and Phase Timing messages (SPaT) to vehicles approaching intersections. In the connected and automated vehicle ecosystem, the fuel savings potential has been explored. Prior studies have predominantly focused on fixed time control for the driver. However, in the case of actuated signals, there is a different and significant challenge due to the randomness caused by uncertainties. We have developed a predictive control using the SPaT information communicated from the actuated traffic intersections. The developed MPC-based algorithm was validated using model-based design platforms such as AMBER<sup>®</sup>, Autonomie<sup>®</sup>, MATLAB<sup>®</sup>, and SIMULINK<sup>®</sup>. It was observed that the proposed algorithm can save energy in a single phase, in multiple phase scenarios, and in compelled stopping at stop signs when employed considering communications. |
| first_indexed | 2024-03-11T02:26:24Z |
| format | Article |
| id | doaj.art-6bc687d6bd8747d7b6bd74d21d16a181 |
| institution | Directory Open Access Journal |
| issn | 2673-7590 |
| language | English |
| last_indexed | 2024-03-11T02:26:24Z |
| publishDate | 2023-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Future Transportation |
| spelling | doaj.art-6bc687d6bd8747d7b6bd74d21d16a1812023-11-18T10:30:58ZengMDPI AGFuture Transportation2673-75902023-05-013264366210.3390/futuretransp3020038Real-Time Suitable Predictive Control Using SPaT Information from Automated Traffic LightsPradeep Krishna Bhat0Bo Chen1Department of Mechanical Engineering-Engineering Mechanics, Michigan Technological University, Houghton, MI 49931, USADepartment of Mechanical Engineering-Engineering Mechanics, Michigan Technological University, Houghton, MI 49931, USATraffic intersections throughout the United States combine fixed, semi-actuated, and fully actuated intersections. In the case of the semi-actuated and actuated intersections, uncertainties are considered in phase duration. These uncertainties are due to car waiting queues and pedestrian crossing. Intelligent transportation systems deployed in traffic infrastructure can communicate Signal and Phase Timing messages (SPaT) to vehicles approaching intersections. In the connected and automated vehicle ecosystem, the fuel savings potential has been explored. Prior studies have predominantly focused on fixed time control for the driver. However, in the case of actuated signals, there is a different and significant challenge due to the randomness caused by uncertainties. We have developed a predictive control using the SPaT information communicated from the actuated traffic intersections. The developed MPC-based algorithm was validated using model-based design platforms such as AMBER<sup>®</sup>, Autonomie<sup>®</sup>, MATLAB<sup>®</sup>, and SIMULINK<sup>®</sup>. It was observed that the proposed algorithm can save energy in a single phase, in multiple phase scenarios, and in compelled stopping at stop signs when employed considering communications.https://www.mdpi.com/2673-7590/3/2/38connected and automated vehiclesactuated signalsoptimal controlmodel predictive controlshort-term traffic |
| spellingShingle | Pradeep Krishna Bhat Bo Chen Real-Time Suitable Predictive Control Using SPaT Information from Automated Traffic Lights Future Transportation connected and automated vehicles actuated signals optimal control model predictive control short-term traffic |
| title | Real-Time Suitable Predictive Control Using SPaT Information from Automated Traffic Lights |
| title_full | Real-Time Suitable Predictive Control Using SPaT Information from Automated Traffic Lights |
| title_fullStr | Real-Time Suitable Predictive Control Using SPaT Information from Automated Traffic Lights |
| title_full_unstemmed | Real-Time Suitable Predictive Control Using SPaT Information from Automated Traffic Lights |
| title_short | Real-Time Suitable Predictive Control Using SPaT Information from Automated Traffic Lights |
| title_sort | real time suitable predictive control using spat information from automated traffic lights |
| topic | connected and automated vehicles actuated signals optimal control model predictive control short-term traffic |
| url | https://www.mdpi.com/2673-7590/3/2/38 |
| work_keys_str_mv | AT pradeepkrishnabhat realtimesuitablepredictivecontrolusingspatinformationfromautomatedtrafficlights AT bochen realtimesuitablepredictivecontrolusingspatinformationfromautomatedtrafficlights |