Influential Factors and Determination Method of Unconventional Outside Left-Turn Lanes Based on a BP Neural Network
To reduce the delay caused by the interweaving and parallel driving of multiple left-turn vehicles and through vehicles upstream of the intersection entrance, the influencing factors and determination methods of unconventional left-turn lanes are studied in right-hand traffic (RHT) countries. For co...
Ausführliche Beschreibung
Autor*in: |
Yi Cao [verfasserIn] Dandan Jiang [verfasserIn] Xuetong Li [verfasserIn] |
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Format: |
E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2022 |
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Übergeordnetes Werk: |
In: Applied Sciences - MDPI AG, 2012, 12(2022), 12, p 6026 |
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Übergeordnetes Werk: |
volume:12 ; year:2022 ; number:12, p 6026 |
Links: |
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DOI / URN: |
10.3390/app12126026 |
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Katalog-ID: |
DOAJ042726719 |
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520 | |a To reduce the delay caused by the interweaving and parallel driving of multiple left-turn vehicles and through vehicles upstream of the intersection entrance, the influencing factors and determination methods of unconventional left-turn lanes are studied in right-hand traffic (RHT) countries. For countries driving right, left-turn lanes are usually on the inside of roads. However, when there are a large number of vehicles turning left in the outer lane of the upstream section of the intersection, these vehicles will be forced to pass many consecutive parallel lanes and then enter the left-turn lane. During this process, many traffic conflicts will occur between left-turning vehicles and going-straight vehicles, which will lead to longer traffic delays. To reduce traffic conflicts and delays caused by problems mentioned before, a scheme of setting left-turn lanes abroad is proposed, and major influencing factors and judgment methods of such a scheme are also studied. With the help of traffic simulation software VISSIM, the simulation model of intersection entrance with a different number of through lanes, length of weaving section and left turn inner and outer lanes is established. By inputting different numbers of entry through vehicles and left-turning vehicles in the outer lane, the delay data under different geometric and traffic conditions are obtained for simulation analysis. With the help of MATLAB software, this paper analyzes the influence of the length of the weaving area and the number of left-turning vehicles on the delay of inside and outside left-turning lanes under the condition of a different number of straight vehicles, as well as the variation law between them. By inputting parameters such as the length of the weaving area and the number of lanes, go-straight vehicles and left-turning vehicles into the system of VISSIM, a BP neural network model is constructed and trained. When investigating the entrances of four intersections, the BP neural network model is used to analyze and calculate the traffic delay and determine the setting scheme of the inside or outside of the left-turn lane. Through experiments and further studies, a phenomenon was found: When more vehicles chose to turn left or go straight in the outside lane, the length of the weaving area will become shorter, and the delay reduction effect of the unconventional left-turn lane will more obvious. The specific location of the left-turn lane should be determined by the constructed BP neural network model through the comparative analysis of delay, and the judgment results are in good agreement with the realistic scheme. | ||
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10.3390/app12126026 doi (DE-627)DOAJ042726719 (DE-599)DOAJ40197e9c663e4ddfada3bf3f353ea9f8 DE-627 ger DE-627 rakwb eng TA1-2040 QH301-705.5 QC1-999 QD1-999 Yi Cao verfasserin aut Influential Factors and Determination Method of Unconventional Outside Left-Turn Lanes Based on a BP Neural Network 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier To reduce the delay caused by the interweaving and parallel driving of multiple left-turn vehicles and through vehicles upstream of the intersection entrance, the influencing factors and determination methods of unconventional left-turn lanes are studied in right-hand traffic (RHT) countries. For countries driving right, left-turn lanes are usually on the inside of roads. However, when there are a large number of vehicles turning left in the outer lane of the upstream section of the intersection, these vehicles will be forced to pass many consecutive parallel lanes and then enter the left-turn lane. During this process, many traffic conflicts will occur between left-turning vehicles and going-straight vehicles, which will lead to longer traffic delays. To reduce traffic conflicts and delays caused by problems mentioned before, a scheme of setting left-turn lanes abroad is proposed, and major influencing factors and judgment methods of such a scheme are also studied. With the help of traffic simulation software VISSIM, the simulation model of intersection entrance with a different number of through lanes, length of weaving section and left turn inner and outer lanes is established. By inputting different numbers of entry through vehicles and left-turning vehicles in the outer lane, the delay data under different geometric and traffic conditions are obtained for simulation analysis. With the help of MATLAB software, this paper analyzes the influence of the length of the weaving area and the number of left-turning vehicles on the delay of inside and outside left-turning lanes under the condition of a different number of straight vehicles, as well as the variation law between them. By inputting parameters such as the length of the weaving area and the number of lanes, go-straight vehicles and left-turning vehicles into the system of VISSIM, a BP neural network model is constructed and trained. When investigating the entrances of four intersections, the BP neural network model is used to analyze and calculate the traffic delay and determine the setting scheme of the inside or outside of the left-turn lane. Through experiments and further studies, a phenomenon was found: When more vehicles chose to turn left or go straight in the outside lane, the length of the weaving area will become shorter, and the delay reduction effect of the unconventional left-turn lane will more obvious. The specific location of the left-turn lane should be determined by the constructed BP neural network model through the comparative analysis of delay, and the judgment results are in good agreement with the realistic scheme. traffic engineering route optimization genetic algorithm feeder bus station transfer Technology T Engineering (General). Civil engineering (General) Biology (General) Physics Chemistry Dandan Jiang verfasserin aut Xuetong Li verfasserin aut In Applied Sciences MDPI AG, 2012 12(2022), 12, p 6026 (DE-627)737287640 (DE-600)2704225-X 20763417 nnns volume:12 year:2022 number:12, p 6026 https://doi.org/10.3390/app12126026 kostenfrei https://doaj.org/article/40197e9c663e4ddfada3bf3f353ea9f8 kostenfrei https://www.mdpi.com/2076-3417/12/12/6026 kostenfrei https://doaj.org/toc/2076-3417 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2022 12, p 6026 |
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10.3390/app12126026 doi (DE-627)DOAJ042726719 (DE-599)DOAJ40197e9c663e4ddfada3bf3f353ea9f8 DE-627 ger DE-627 rakwb eng TA1-2040 QH301-705.5 QC1-999 QD1-999 Yi Cao verfasserin aut Influential Factors and Determination Method of Unconventional Outside Left-Turn Lanes Based on a BP Neural Network 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier To reduce the delay caused by the interweaving and parallel driving of multiple left-turn vehicles and through vehicles upstream of the intersection entrance, the influencing factors and determination methods of unconventional left-turn lanes are studied in right-hand traffic (RHT) countries. For countries driving right, left-turn lanes are usually on the inside of roads. However, when there are a large number of vehicles turning left in the outer lane of the upstream section of the intersection, these vehicles will be forced to pass many consecutive parallel lanes and then enter the left-turn lane. During this process, many traffic conflicts will occur between left-turning vehicles and going-straight vehicles, which will lead to longer traffic delays. To reduce traffic conflicts and delays caused by problems mentioned before, a scheme of setting left-turn lanes abroad is proposed, and major influencing factors and judgment methods of such a scheme are also studied. With the help of traffic simulation software VISSIM, the simulation model of intersection entrance with a different number of through lanes, length of weaving section and left turn inner and outer lanes is established. By inputting different numbers of entry through vehicles and left-turning vehicles in the outer lane, the delay data under different geometric and traffic conditions are obtained for simulation analysis. With the help of MATLAB software, this paper analyzes the influence of the length of the weaving area and the number of left-turning vehicles on the delay of inside and outside left-turning lanes under the condition of a different number of straight vehicles, as well as the variation law between them. By inputting parameters such as the length of the weaving area and the number of lanes, go-straight vehicles and left-turning vehicles into the system of VISSIM, a BP neural network model is constructed and trained. When investigating the entrances of four intersections, the BP neural network model is used to analyze and calculate the traffic delay and determine the setting scheme of the inside or outside of the left-turn lane. Through experiments and further studies, a phenomenon was found: When more vehicles chose to turn left or go straight in the outside lane, the length of the weaving area will become shorter, and the delay reduction effect of the unconventional left-turn lane will more obvious. The specific location of the left-turn lane should be determined by the constructed BP neural network model through the comparative analysis of delay, and the judgment results are in good agreement with the realistic scheme. traffic engineering route optimization genetic algorithm feeder bus station transfer Technology T Engineering (General). Civil engineering (General) Biology (General) Physics Chemistry Dandan Jiang verfasserin aut Xuetong Li verfasserin aut In Applied Sciences MDPI AG, 2012 12(2022), 12, p 6026 (DE-627)737287640 (DE-600)2704225-X 20763417 nnns volume:12 year:2022 number:12, p 6026 https://doi.org/10.3390/app12126026 kostenfrei https://doaj.org/article/40197e9c663e4ddfada3bf3f353ea9f8 kostenfrei https://www.mdpi.com/2076-3417/12/12/6026 kostenfrei https://doaj.org/toc/2076-3417 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2022 12, p 6026 |
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10.3390/app12126026 doi (DE-627)DOAJ042726719 (DE-599)DOAJ40197e9c663e4ddfada3bf3f353ea9f8 DE-627 ger DE-627 rakwb eng TA1-2040 QH301-705.5 QC1-999 QD1-999 Yi Cao verfasserin aut Influential Factors and Determination Method of Unconventional Outside Left-Turn Lanes Based on a BP Neural Network 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier To reduce the delay caused by the interweaving and parallel driving of multiple left-turn vehicles and through vehicles upstream of the intersection entrance, the influencing factors and determination methods of unconventional left-turn lanes are studied in right-hand traffic (RHT) countries. For countries driving right, left-turn lanes are usually on the inside of roads. However, when there are a large number of vehicles turning left in the outer lane of the upstream section of the intersection, these vehicles will be forced to pass many consecutive parallel lanes and then enter the left-turn lane. During this process, many traffic conflicts will occur between left-turning vehicles and going-straight vehicles, which will lead to longer traffic delays. To reduce traffic conflicts and delays caused by problems mentioned before, a scheme of setting left-turn lanes abroad is proposed, and major influencing factors and judgment methods of such a scheme are also studied. With the help of traffic simulation software VISSIM, the simulation model of intersection entrance with a different number of through lanes, length of weaving section and left turn inner and outer lanes is established. By inputting different numbers of entry through vehicles and left-turning vehicles in the outer lane, the delay data under different geometric and traffic conditions are obtained for simulation analysis. With the help of MATLAB software, this paper analyzes the influence of the length of the weaving area and the number of left-turning vehicles on the delay of inside and outside left-turning lanes under the condition of a different number of straight vehicles, as well as the variation law between them. By inputting parameters such as the length of the weaving area and the number of lanes, go-straight vehicles and left-turning vehicles into the system of VISSIM, a BP neural network model is constructed and trained. When investigating the entrances of four intersections, the BP neural network model is used to analyze and calculate the traffic delay and determine the setting scheme of the inside or outside of the left-turn lane. Through experiments and further studies, a phenomenon was found: When more vehicles chose to turn left or go straight in the outside lane, the length of the weaving area will become shorter, and the delay reduction effect of the unconventional left-turn lane will more obvious. The specific location of the left-turn lane should be determined by the constructed BP neural network model through the comparative analysis of delay, and the judgment results are in good agreement with the realistic scheme. traffic engineering route optimization genetic algorithm feeder bus station transfer Technology T Engineering (General). Civil engineering (General) Biology (General) Physics Chemistry Dandan Jiang verfasserin aut Xuetong Li verfasserin aut In Applied Sciences MDPI AG, 2012 12(2022), 12, p 6026 (DE-627)737287640 (DE-600)2704225-X 20763417 nnns volume:12 year:2022 number:12, p 6026 https://doi.org/10.3390/app12126026 kostenfrei https://doaj.org/article/40197e9c663e4ddfada3bf3f353ea9f8 kostenfrei https://www.mdpi.com/2076-3417/12/12/6026 kostenfrei https://doaj.org/toc/2076-3417 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2022 12, p 6026 |
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10.3390/app12126026 doi (DE-627)DOAJ042726719 (DE-599)DOAJ40197e9c663e4ddfada3bf3f353ea9f8 DE-627 ger DE-627 rakwb eng TA1-2040 QH301-705.5 QC1-999 QD1-999 Yi Cao verfasserin aut Influential Factors and Determination Method of Unconventional Outside Left-Turn Lanes Based on a BP Neural Network 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier To reduce the delay caused by the interweaving and parallel driving of multiple left-turn vehicles and through vehicles upstream of the intersection entrance, the influencing factors and determination methods of unconventional left-turn lanes are studied in right-hand traffic (RHT) countries. For countries driving right, left-turn lanes are usually on the inside of roads. However, when there are a large number of vehicles turning left in the outer lane of the upstream section of the intersection, these vehicles will be forced to pass many consecutive parallel lanes and then enter the left-turn lane. During this process, many traffic conflicts will occur between left-turning vehicles and going-straight vehicles, which will lead to longer traffic delays. To reduce traffic conflicts and delays caused by problems mentioned before, a scheme of setting left-turn lanes abroad is proposed, and major influencing factors and judgment methods of such a scheme are also studied. With the help of traffic simulation software VISSIM, the simulation model of intersection entrance with a different number of through lanes, length of weaving section and left turn inner and outer lanes is established. By inputting different numbers of entry through vehicles and left-turning vehicles in the outer lane, the delay data under different geometric and traffic conditions are obtained for simulation analysis. With the help of MATLAB software, this paper analyzes the influence of the length of the weaving area and the number of left-turning vehicles on the delay of inside and outside left-turning lanes under the condition of a different number of straight vehicles, as well as the variation law between them. By inputting parameters such as the length of the weaving area and the number of lanes, go-straight vehicles and left-turning vehicles into the system of VISSIM, a BP neural network model is constructed and trained. When investigating the entrances of four intersections, the BP neural network model is used to analyze and calculate the traffic delay and determine the setting scheme of the inside or outside of the left-turn lane. Through experiments and further studies, a phenomenon was found: When more vehicles chose to turn left or go straight in the outside lane, the length of the weaving area will become shorter, and the delay reduction effect of the unconventional left-turn lane will more obvious. The specific location of the left-turn lane should be determined by the constructed BP neural network model through the comparative analysis of delay, and the judgment results are in good agreement with the realistic scheme. traffic engineering route optimization genetic algorithm feeder bus station transfer Technology T Engineering (General). Civil engineering (General) Biology (General) Physics Chemistry Dandan Jiang verfasserin aut Xuetong Li verfasserin aut In Applied Sciences MDPI AG, 2012 12(2022), 12, p 6026 (DE-627)737287640 (DE-600)2704225-X 20763417 nnns volume:12 year:2022 number:12, p 6026 https://doi.org/10.3390/app12126026 kostenfrei https://doaj.org/article/40197e9c663e4ddfada3bf3f353ea9f8 kostenfrei https://www.mdpi.com/2076-3417/12/12/6026 kostenfrei https://doaj.org/toc/2076-3417 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2022 12, p 6026 |
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Influential Factors and Determination Method of Unconventional Outside Left-Turn Lanes Based on a BP Neural Network |
abstract |
To reduce the delay caused by the interweaving and parallel driving of multiple left-turn vehicles and through vehicles upstream of the intersection entrance, the influencing factors and determination methods of unconventional left-turn lanes are studied in right-hand traffic (RHT) countries. For countries driving right, left-turn lanes are usually on the inside of roads. However, when there are a large number of vehicles turning left in the outer lane of the upstream section of the intersection, these vehicles will be forced to pass many consecutive parallel lanes and then enter the left-turn lane. During this process, many traffic conflicts will occur between left-turning vehicles and going-straight vehicles, which will lead to longer traffic delays. To reduce traffic conflicts and delays caused by problems mentioned before, a scheme of setting left-turn lanes abroad is proposed, and major influencing factors and judgment methods of such a scheme are also studied. With the help of traffic simulation software VISSIM, the simulation model of intersection entrance with a different number of through lanes, length of weaving section and left turn inner and outer lanes is established. By inputting different numbers of entry through vehicles and left-turning vehicles in the outer lane, the delay data under different geometric and traffic conditions are obtained for simulation analysis. With the help of MATLAB software, this paper analyzes the influence of the length of the weaving area and the number of left-turning vehicles on the delay of inside and outside left-turning lanes under the condition of a different number of straight vehicles, as well as the variation law between them. By inputting parameters such as the length of the weaving area and the number of lanes, go-straight vehicles and left-turning vehicles into the system of VISSIM, a BP neural network model is constructed and trained. When investigating the entrances of four intersections, the BP neural network model is used to analyze and calculate the traffic delay and determine the setting scheme of the inside or outside of the left-turn lane. Through experiments and further studies, a phenomenon was found: When more vehicles chose to turn left or go straight in the outside lane, the length of the weaving area will become shorter, and the delay reduction effect of the unconventional left-turn lane will more obvious. The specific location of the left-turn lane should be determined by the constructed BP neural network model through the comparative analysis of delay, and the judgment results are in good agreement with the realistic scheme. |
abstractGer |
To reduce the delay caused by the interweaving and parallel driving of multiple left-turn vehicles and through vehicles upstream of the intersection entrance, the influencing factors and determination methods of unconventional left-turn lanes are studied in right-hand traffic (RHT) countries. For countries driving right, left-turn lanes are usually on the inside of roads. However, when there are a large number of vehicles turning left in the outer lane of the upstream section of the intersection, these vehicles will be forced to pass many consecutive parallel lanes and then enter the left-turn lane. During this process, many traffic conflicts will occur between left-turning vehicles and going-straight vehicles, which will lead to longer traffic delays. To reduce traffic conflicts and delays caused by problems mentioned before, a scheme of setting left-turn lanes abroad is proposed, and major influencing factors and judgment methods of such a scheme are also studied. With the help of traffic simulation software VISSIM, the simulation model of intersection entrance with a different number of through lanes, length of weaving section and left turn inner and outer lanes is established. By inputting different numbers of entry through vehicles and left-turning vehicles in the outer lane, the delay data under different geometric and traffic conditions are obtained for simulation analysis. With the help of MATLAB software, this paper analyzes the influence of the length of the weaving area and the number of left-turning vehicles on the delay of inside and outside left-turning lanes under the condition of a different number of straight vehicles, as well as the variation law between them. By inputting parameters such as the length of the weaving area and the number of lanes, go-straight vehicles and left-turning vehicles into the system of VISSIM, a BP neural network model is constructed and trained. When investigating the entrances of four intersections, the BP neural network model is used to analyze and calculate the traffic delay and determine the setting scheme of the inside or outside of the left-turn lane. Through experiments and further studies, a phenomenon was found: When more vehicles chose to turn left or go straight in the outside lane, the length of the weaving area will become shorter, and the delay reduction effect of the unconventional left-turn lane will more obvious. The specific location of the left-turn lane should be determined by the constructed BP neural network model through the comparative analysis of delay, and the judgment results are in good agreement with the realistic scheme. |
abstract_unstemmed |
To reduce the delay caused by the interweaving and parallel driving of multiple left-turn vehicles and through vehicles upstream of the intersection entrance, the influencing factors and determination methods of unconventional left-turn lanes are studied in right-hand traffic (RHT) countries. For countries driving right, left-turn lanes are usually on the inside of roads. However, when there are a large number of vehicles turning left in the outer lane of the upstream section of the intersection, these vehicles will be forced to pass many consecutive parallel lanes and then enter the left-turn lane. During this process, many traffic conflicts will occur between left-turning vehicles and going-straight vehicles, which will lead to longer traffic delays. To reduce traffic conflicts and delays caused by problems mentioned before, a scheme of setting left-turn lanes abroad is proposed, and major influencing factors and judgment methods of such a scheme are also studied. With the help of traffic simulation software VISSIM, the simulation model of intersection entrance with a different number of through lanes, length of weaving section and left turn inner and outer lanes is established. By inputting different numbers of entry through vehicles and left-turning vehicles in the outer lane, the delay data under different geometric and traffic conditions are obtained for simulation analysis. With the help of MATLAB software, this paper analyzes the influence of the length of the weaving area and the number of left-turning vehicles on the delay of inside and outside left-turning lanes under the condition of a different number of straight vehicles, as well as the variation law between them. By inputting parameters such as the length of the weaving area and the number of lanes, go-straight vehicles and left-turning vehicles into the system of VISSIM, a BP neural network model is constructed and trained. When investigating the entrances of four intersections, the BP neural network model is used to analyze and calculate the traffic delay and determine the setting scheme of the inside or outside of the left-turn lane. Through experiments and further studies, a phenomenon was found: When more vehicles chose to turn left or go straight in the outside lane, the length of the weaving area will become shorter, and the delay reduction effect of the unconventional left-turn lane will more obvious. The specific location of the left-turn lane should be determined by the constructed BP neural network model through the comparative analysis of delay, and the judgment results are in good agreement with the realistic scheme. |
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container_issue |
12, p 6026 |
title_short |
Influential Factors and Determination Method of Unconventional Outside Left-Turn Lanes Based on a BP Neural Network |
url |
https://doi.org/10.3390/app12126026 https://doaj.org/article/40197e9c663e4ddfada3bf3f353ea9f8 https://www.mdpi.com/2076-3417/12/12/6026 https://doaj.org/toc/2076-3417 |
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Dandan Jiang Xuetong Li |
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