Cooperative Merging Strategy Between Connected Autonomous Vehicles in Mixed Traffic
In this work we propose a new cooperation strategy between connected autonomous vehicles in on-ramps merging scenarios and we implement the cut-in risk indicator (CRI) to investigate the safety effect of the proposed strategy. The new cooperation strategy considers a pair of vehicles approaching an...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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IEEE
2022-01-01
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| Series: | IEEE Open Journal of Intelligent Transportation Systems |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9994623/ |
| _version_ | 1797974422674472960 |
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| author | Eleonora Andreotti Selpi Maytheewat Aramrattana |
| author_facet | Eleonora Andreotti Selpi Maytheewat Aramrattana |
| author_sort | Eleonora Andreotti |
| collection | DOAJ |
| description | In this work we propose a new cooperation strategy between connected autonomous vehicles in on-ramps merging scenarios and we implement the cut-in risk indicator (CRI) to investigate the safety effect of the proposed strategy. The new cooperation strategy considers a pair of vehicles approaching an on-ramp. The strategy then makes decisions on the target speeds/accelerations of both vehicles, possible lane changing, and a dynamic decision-making approach in order to reduce the risk during the cut-in manoeuvre. In this work, the CRI was first used to assess the risk during the merging manoeuvre. For this purpose, scenarios with penetration rates of autonomous vehicles from 20% to 100%, with step of 10%, both connected and non-connected autonomous vehicles were evaluated. As a result, on average a 35% reduction of the cut-in risk manoeuvres in connected autonomous vehicles compared to non-connected autonomous vehicles is obtained. It is shown through the analysis of probability density functions characterising the CRI distribution that the reduction is not homogeneous across all indicator values, but depends on the penetration rate and the severity of the manoeuvre. |
| first_indexed | 2024-04-11T04:19:41Z |
| format | Article |
| id | doaj.art-8ea3cf84d9f445e19cd7a4b84530f7ba |
| institution | Directory Open Access Journal |
| issn | 2687-7813 |
| language | English |
| last_indexed | 2024-04-11T04:19:41Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Open Journal of Intelligent Transportation Systems |
| spelling | doaj.art-8ea3cf84d9f445e19cd7a4b84530f7ba2022-12-31T00:02:17ZengIEEEIEEE Open Journal of Intelligent Transportation Systems2687-78132022-01-01382583710.1109/OJITS.2022.31791259994623Cooperative Merging Strategy Between Connected Autonomous Vehicles in Mixed TrafficEleonora Andreotti0https://orcid.org/0000-0002-4500-2435 Selpi1https://orcid.org/0000-0003-2800-4479Maytheewat Aramrattana2https://orcid.org/0000-0003-4951-5315CINECA, Supercomputing Inter-University Consortium, Bologna, ItalyDepartment of Mechanics and Maritime Sciences, Chalmers University of Technology, Göteborg, SwedenDepartment of Traffic and Road Users, Swedish National Road and Transport Research Institute, Linköping, SwedenIn this work we propose a new cooperation strategy between connected autonomous vehicles in on-ramps merging scenarios and we implement the cut-in risk indicator (CRI) to investigate the safety effect of the proposed strategy. The new cooperation strategy considers a pair of vehicles approaching an on-ramp. The strategy then makes decisions on the target speeds/accelerations of both vehicles, possible lane changing, and a dynamic decision-making approach in order to reduce the risk during the cut-in manoeuvre. In this work, the CRI was first used to assess the risk during the merging manoeuvre. For this purpose, scenarios with penetration rates of autonomous vehicles from 20% to 100%, with step of 10%, both connected and non-connected autonomous vehicles were evaluated. As a result, on average a 35% reduction of the cut-in risk manoeuvres in connected autonomous vehicles compared to non-connected autonomous vehicles is obtained. It is shown through the analysis of probability density functions characterising the CRI distribution that the reduction is not homogeneous across all indicator values, but depends on the penetration rate and the severity of the manoeuvre.https://ieeexplore.ieee.org/document/9994623/Cooperative merging strategycut-in risk indicatormixed-trafficon-ramp mergingtraffic simulations |
| spellingShingle | Eleonora Andreotti Selpi Maytheewat Aramrattana Cooperative Merging Strategy Between Connected Autonomous Vehicles in Mixed Traffic IEEE Open Journal of Intelligent Transportation Systems Cooperative merging strategy cut-in risk indicator mixed-traffic on-ramp merging traffic simulations |
| title | Cooperative Merging Strategy Between Connected Autonomous Vehicles in Mixed Traffic |
| title_full | Cooperative Merging Strategy Between Connected Autonomous Vehicles in Mixed Traffic |
| title_fullStr | Cooperative Merging Strategy Between Connected Autonomous Vehicles in Mixed Traffic |
| title_full_unstemmed | Cooperative Merging Strategy Between Connected Autonomous Vehicles in Mixed Traffic |
| title_short | Cooperative Merging Strategy Between Connected Autonomous Vehicles in Mixed Traffic |
| title_sort | cooperative merging strategy between connected autonomous vehicles in mixed traffic |
| topic | Cooperative merging strategy cut-in risk indicator mixed-traffic on-ramp merging traffic simulations |
| url | https://ieeexplore.ieee.org/document/9994623/ |
| work_keys_str_mv | AT eleonoraandreotti cooperativemergingstrategybetweenconnectedautonomousvehiclesinmixedtraffic AT selpi cooperativemergingstrategybetweenconnectedautonomousvehiclesinmixedtraffic AT maytheewataramrattana cooperativemergingstrategybetweenconnectedautonomousvehiclesinmixedtraffic |