Developing and Field Testing a Green Light Optimal Speed Advisory System for Buses
2.1. B-GLOSA System
2.2. GLOSA for Buses
3. Case Study
3.1. Test Environment
- Scenario 1 (S1)—Uninformed drive:
- Scenario 2 (S2)—Informed drive with the provision of signal timing information:
- Scenario 3 (S3)—Informed drive with recommended speed (B-GLOSA):
3.2. Experimental Design and Statistical Analysis
3.3. Quantitative Performance Analysis
- A fuel consumption model for diesel buses was used in the proposed system to compute instantaneous fuel consumption rates, because this model is easy to calibrate using easy-to-access bus data.
- The vehicle dynamics model, fuel consumption model, signal timings, and vehicle speed and distance relationship are used to construct an optimization problem.
- A moving-horizon dynamic program and an A-star algorithm is used to solve the optimization problem and calculate the energy-optimized vehicle trajectory to assist buses to proceed through signalized intersections efficiently. The proposed B-GLOSA system was implemented and field tested to validate the real-world benefits. The test results and the recommendations for future research are summarized below.
- The Virginia Smart Road test facility was used to conduct the field test using 30 participants. A split-split-plot experimental design was used to test the developed B-GLOSA system for different impact factors of road grades and red indication offsets, and statistical analysis was conducted to demonstrate that the fuel consumption performances were significantly different among three test scenarios.
- The quantitative analysis of the test results demonstrated that the proposed B-GLOSA system can greatly smooth the bus trajectory while traversing a signalized intersection, and simultaneously save fuel consumption and travel times.
- Compared to the uninformed drive, the test results demonstrated that the B-GLOSA can efficiently reduce fuel consumption by 22.1% and simultaneously reduce vehicle travel times by 6.1%.
- In future research, the B-GLOSA system will be tested within a microscopic simulation environment to quantify he network-level impact for various traffic conditions and heterogeneous traffic including LDVs and buses.
Institutional Review Board Statement
Informed Consent Statement
Conflicts of Interest
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|Response Variable||Source||DF||DFDen||F Ratio||p Value|
|Direction||Red Offset (Sec)||Scenario 1 FC (Liter)||Scenario 2 FC (Liter)||Scenario 3 FC (Liter)||Difference between S2 and S1 (%)||Difference between S3 and S1 (%)|
|Scenario 1 TT (Sec)||Scenario 2 TT (Sec)||Scenario 3 TT (Sec)||Difference|
between S2 and S1 (%)
between S3 and S1 (%)
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Chen, H.; Rakha, H.A. Developing and Field Testing a Green Light Optimal Speed Advisory System for Buses. Energies 2022, 15, 1491. https://doi.org/10.3390/en15041491
Chen H, Rakha HA. Developing and Field Testing a Green Light Optimal Speed Advisory System for Buses. Energies. 2022; 15(4):1491. https://doi.org/10.3390/en15041491Chicago/Turabian Style
Chen, Hao, and Hesham A. Rakha. 2022. "Developing and Field Testing a Green Light Optimal Speed Advisory System for Buses" Energies 15, no. 4: 1491. https://doi.org/10.3390/en15041491