Safe and Ecological Speed Profile Planning Algorithm for Autonomous Vehicles Using a Parametric Multiobjective Optimization Procedure
This paper proposes and evaluates an algorithm called Multi-Objective planning based on Simulated Annealing (MOSA) that plans a trajectory (speed profile) for a passenger car on a free, single lane road. This algorithm is relying on a decomposition of the decision space into “chunks” that are optimi...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Society of Automotive Engineers of Japan, Inc.
2019-01-01
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| Series: | International Journal of Automotive Engineering |
| Online Access: | https://www.jstage.jst.go.jp/article/jsaeijae/10/1/10_20194079/_article/-char/ja |
| _version_ | 1797356812874285056 |
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| author | Olivier Orfila Dominique Gruyer Karima Hamdi Sébastien Glaser |
| author_facet | Olivier Orfila Dominique Gruyer Karima Hamdi Sébastien Glaser |
| author_sort | Olivier Orfila |
| collection | DOAJ |
| description | This paper proposes and evaluates an algorithm called Multi-Objective planning based on Simulated Annealing (MOSA) that plans a trajectory (speed profile) for a passenger car on a free, single lane road. This algorithm is relying on a decomposition of the decision space into “chunks” that are optimized separately. Two objectives have been taken into account: travel time and fuel consumption. Optimization constraints are built from safety modelings combining legal speed, curves speed limits and junctions limits. The multi-objective optimization is performed through a linear scalairisation method and the optimization is a parametric optimization based on simulated annealing. The algorithm has been tested on simulated annealing convergence and results show a good convergence under 500 iterations and a small sensitivity to variables initialization. However, sensitivity to core parameters of the simulated annealing (initial temperature and temperature decreasing rate) is very high and some guidelines for the calibration of these parameters are given in this paper. Then, the algorithm has been tested and compared to experimental results and it shows that, even if some drivers can drive the road quicker than the algorithm, they cannot drive with a lower fuel consumption. Furthermore, the algorithm results are better than the most of the experimental results according to the Pareto definition of dominance and global results outperform results from another planning algorithm based on Dijkstra’s algorithm. Future works will concentrate on improving the algorithm to be more reactive to unexpected obstacles and more consistant in the “chunks” transitions. |
| first_indexed | 2024-03-08T14:35:16Z |
| format | Article |
| id | doaj.art-750514af711b423e9f96ac33ababcd2e |
| institution | Directory Open Access Journal |
| issn | 2185-0992 |
| language | English |
| last_indexed | 2024-03-08T14:35:16Z |
| publishDate | 2019-01-01 |
| publisher | Society of Automotive Engineers of Japan, Inc. |
| record_format | Article |
| series | International Journal of Automotive Engineering |
| spelling | doaj.art-750514af711b423e9f96ac33ababcd2e2024-01-12T06:25:57ZengSociety of Automotive Engineers of Japan, Inc.International Journal of Automotive Engineering2185-09922019-01-01101263310.20485/jsaeijae.10.1_26Safe and Ecological Speed Profile Planning Algorithm for Autonomous Vehicles Using a Parametric Multiobjective Optimization ProcedureOlivier Orfila0Dominique Gruyer1Karima Hamdi2Sébastien Glaser3IFSTTARIFSTTARIFSTTARQUTThis paper proposes and evaluates an algorithm called Multi-Objective planning based on Simulated Annealing (MOSA) that plans a trajectory (speed profile) for a passenger car on a free, single lane road. This algorithm is relying on a decomposition of the decision space into “chunks” that are optimized separately. Two objectives have been taken into account: travel time and fuel consumption. Optimization constraints are built from safety modelings combining legal speed, curves speed limits and junctions limits. The multi-objective optimization is performed through a linear scalairisation method and the optimization is a parametric optimization based on simulated annealing. The algorithm has been tested on simulated annealing convergence and results show a good convergence under 500 iterations and a small sensitivity to variables initialization. However, sensitivity to core parameters of the simulated annealing (initial temperature and temperature decreasing rate) is very high and some guidelines for the calibration of these parameters are given in this paper. Then, the algorithm has been tested and compared to experimental results and it shows that, even if some drivers can drive the road quicker than the algorithm, they cannot drive with a lower fuel consumption. Furthermore, the algorithm results are better than the most of the experimental results according to the Pareto definition of dominance and global results outperform results from another planning algorithm based on Dijkstra’s algorithm. Future works will concentrate on improving the algorithm to be more reactive to unexpected obstacles and more consistant in the “chunks” transitions.https://www.jstage.jst.go.jp/article/jsaeijae/10/1/10_20194079/_article/-char/ja |
| spellingShingle | Olivier Orfila Dominique Gruyer Karima Hamdi Sébastien Glaser Safe and Ecological Speed Profile Planning Algorithm for Autonomous Vehicles Using a Parametric Multiobjective Optimization Procedure International Journal of Automotive Engineering |
| title | Safe and Ecological Speed Profile Planning Algorithm for Autonomous Vehicles Using a Parametric Multiobjective Optimization Procedure |
| title_full | Safe and Ecological Speed Profile Planning Algorithm for Autonomous Vehicles Using a Parametric Multiobjective Optimization Procedure |
| title_fullStr | Safe and Ecological Speed Profile Planning Algorithm for Autonomous Vehicles Using a Parametric Multiobjective Optimization Procedure |
| title_full_unstemmed | Safe and Ecological Speed Profile Planning Algorithm for Autonomous Vehicles Using a Parametric Multiobjective Optimization Procedure |
| title_short | Safe and Ecological Speed Profile Planning Algorithm for Autonomous Vehicles Using a Parametric Multiobjective Optimization Procedure |
| title_sort | safe and ecological speed profile planning algorithm for autonomous vehicles using a parametric multiobjective optimization procedure |
| url | https://www.jstage.jst.go.jp/article/jsaeijae/10/1/10_20194079/_article/-char/ja |
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