Optimizing of Traffic-Signal Timing Based on the FCIC-PI—A Surrogate Measure for Fuel Consumption
Optimizing signal timing improves sustainability metrics (e.g., fuel consumption or “FC”). Historically, traffic agencies have retimed signal timing to improve mobility measures (e.g., delays). However, optimizing signals to reduce delays does not necessarily mitigate sustainability measures. Hence,...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-05-01
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| Series: | Future Transportation |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2673-7590/3/2/39 |
| _version_ | 1797594728563212288 |
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| author | Suhaib Alshayeb Aleksandar Stevanovic Jelka Stevanovic Nemanja Dobrota |
| author_facet | Suhaib Alshayeb Aleksandar Stevanovic Jelka Stevanovic Nemanja Dobrota |
| author_sort | Suhaib Alshayeb |
| collection | DOAJ |
| description | Optimizing signal timing improves sustainability metrics (e.g., fuel consumption or “FC”). Historically, traffic agencies have retimed signal timing to improve mobility measures (e.g., delays). However, optimizing signals to reduce delays does not necessarily mitigate sustainability measures. Hence, this study introduces an approach that integrates a newly derived surrogate measure for FC, traffic microsimulation software, and a stochastic genetic algorithm. This approach optimizes signal timing to reduce the surrogate measure and reduce sustainability metrics. This study also evaluated the impact of heavy vehicles’ presence in a fleet on signal timing and FC savings. A 13-intersection arterial on Washington Street in the Chicago metro area served as a case study. Optimized signal timing delivered solutions that balanced both sustainability and mobility. The estimated excess FC savings ranged between 8 and 12% under moderate operating conditions, with no heavy vehicles, compared to the initial signal timing. The savings reached up to ~14% when many heavy vehicles existed on the side streets. Most of the improvements came without worsening traffic-mobility efficiency, which shows the possibility of a fair tradeoff between mobility and sustainability. All optimization scenarios showed that a slightly longer cycle length than the one implemented in the field is required to reduce FC. |
| first_indexed | 2024-03-11T02:26:19Z |
| format | Article |
| id | doaj.art-5448fb8b4cb44f78b1711f7dcb80f3ed |
| institution | Directory Open Access Journal |
| issn | 2673-7590 |
| language | English |
| last_indexed | 2024-03-11T02:26:19Z |
| publishDate | 2023-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Future Transportation |
| spelling | doaj.art-5448fb8b4cb44f78b1711f7dcb80f3ed2023-11-18T10:30:59ZengMDPI AGFuture Transportation2673-75902023-05-013266368310.3390/futuretransp3020039Optimizing of Traffic-Signal Timing Based on the FCIC-PI—A Surrogate Measure for Fuel ConsumptionSuhaib Alshayeb0Aleksandar Stevanovic1Jelka Stevanovic2Nemanja Dobrota3CHA Consulting, 8935 NW 35th Ln, Doral, FL 33172, USADepartment of Civil & Environmental Engineering, Swanson School of Engineering, University of Pittsburgh, 341A Benedum Hall, 3700 O’Hara Street Pittsburgh, Pittsburgh, PA 15261, USAPrincipal—Retime LLC, 225 Valley Park Dr, Pittsburgh, PA 15216, USAKittelson & Associates, Inc., 100 M St SE #910, Washington, DC 20003, USAOptimizing signal timing improves sustainability metrics (e.g., fuel consumption or “FC”). Historically, traffic agencies have retimed signal timing to improve mobility measures (e.g., delays). However, optimizing signals to reduce delays does not necessarily mitigate sustainability measures. Hence, this study introduces an approach that integrates a newly derived surrogate measure for FC, traffic microsimulation software, and a stochastic genetic algorithm. This approach optimizes signal timing to reduce the surrogate measure and reduce sustainability metrics. This study also evaluated the impact of heavy vehicles’ presence in a fleet on signal timing and FC savings. A 13-intersection arterial on Washington Street in the Chicago metro area served as a case study. Optimized signal timing delivered solutions that balanced both sustainability and mobility. The estimated excess FC savings ranged between 8 and 12% under moderate operating conditions, with no heavy vehicles, compared to the initial signal timing. The savings reached up to ~14% when many heavy vehicles existed on the side streets. Most of the improvements came without worsening traffic-mobility efficiency, which shows the possibility of a fair tradeoff between mobility and sustainability. All optimization scenarios showed that a slightly longer cycle length than the one implemented in the field is required to reduce FC.https://www.mdpi.com/2673-7590/3/2/39signal-timing optimizationfuel consumptionemissionssurrogate measurePerformance Index |
| spellingShingle | Suhaib Alshayeb Aleksandar Stevanovic Jelka Stevanovic Nemanja Dobrota Optimizing of Traffic-Signal Timing Based on the FCIC-PI—A Surrogate Measure for Fuel Consumption Future Transportation signal-timing optimization fuel consumption emissions surrogate measure Performance Index |
| title | Optimizing of Traffic-Signal Timing Based on the FCIC-PI—A Surrogate Measure for Fuel Consumption |
| title_full | Optimizing of Traffic-Signal Timing Based on the FCIC-PI—A Surrogate Measure for Fuel Consumption |
| title_fullStr | Optimizing of Traffic-Signal Timing Based on the FCIC-PI—A Surrogate Measure for Fuel Consumption |
| title_full_unstemmed | Optimizing of Traffic-Signal Timing Based on the FCIC-PI—A Surrogate Measure for Fuel Consumption |
| title_short | Optimizing of Traffic-Signal Timing Based on the FCIC-PI—A Surrogate Measure for Fuel Consumption |
| title_sort | optimizing of traffic signal timing based on the fcic pi a surrogate measure for fuel consumption |
| topic | signal-timing optimization fuel consumption emissions surrogate measure Performance Index |
| url | https://www.mdpi.com/2673-7590/3/2/39 |
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