Analyzing and Optimizing the Emission Impact of Intersection Signal Control in Mixed Traffic
Abstract
:1. Introduction
2. Field Emission Data and Modeling
2.1. Field Emission Data Collection
2.2. Real-Time Vehicle Emission Models
3. Optimization of Signal Control
4. Results
4.1. Case Study Based on Field Data at an Intersection
4.2. Impact of Conversion Factors on Signal Timing of Different Directions in the Case Study
4.3. The Effects of the Proposed Optimization Methods on Intersection Emissions
5. Conclusions
- (1)
- An inlet lane dominated by heavy-duty vehicles experiences an elongation of effective green time with increasing conversion factors, indicating a priority advantage.
- (2)
- Signal control optimization through instantaneous emissions-based conversion factors leads to varying effective green times for the intersection’s four entry lanes. Nevertheless, a trend towards uniformity emerges as the conversion factor grows. High heavy vehicle ratios do not grant unrestricted priority as the factor increases.
- (3)
- After conventional signal control optimization, CO, HC, and NOx emissions decrease for heavy-duty vehicles, and CO and HC emissions drop for light-duty vehicles. However, NOx emissions from light-duty vehicles remain relatively steady.
- (4)
- The improvement in reducing vehicle emissions using signal timing optimization based on vehicle conversion factors is more significant than that based on conventional signal timing optimization.
- (5)
- Slight increases in traffic emissions occur as the vehicle conversion factor surpasses a specific threshold. It results from the considerable presence of light-duty vehicles in the traffic flow. As heavy-duty vehicles gain more right of way, it impacts light-duty vehicle capacity and contributes to the emission rise.
6. Limitations and Future Study
- (1)
- While acknowledging that the peak-hour period represents only a segment of overall traffic flow, our future work will address the impact of signal timing optimization on vehicle emissions during off-peak hours.
- (2)
- Due to resource constraints, the current dataset is limited. Future research can overcome these limitations by expanding both the volume of data and the breadth of the investigation, allowing for a more comprehensive analysis of emissions from medium-sized vehicles, buses, and other vehicle models. While our present empirical analysis predominantly centers on urban road intersections, subsequent studies can extend to urban segments and the entire road network.
- (3)
- Traffic emission research primarily informs the creation of urban traffic management and transportation planning. Subsequent research can use simulation methods and consider emission variations among different vehicle models and road network structures. It can construct an expansive traffic emission network simulation tailored to cities.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Vehicle Parameter | Light-Duty Vehicle | Heavy-Duty Vehicle |
---|---|---|
Brand | Volkswagen | FAW Jie Fang |
Total mass (kg) | 1285 | 15,790 |
Engine displacement (L) | 1.6 | 6.6 |
Fuel type | Petrol | Diesel |
VSP | Light Vehicle | Heavy Vehicle | ||||
---|---|---|---|---|---|---|
Instantaneous Emissions (mg/s) | Instantaneous Emissions (mg/s) | |||||
CO | HC | NOx | CO | HC | NOx | |
(−∞, −30) | 4.27 | 0.77 | 0.15 | 111.84 | 13.71 | 18.59 |
[−30, −28) | 4.45 | 0.51 | 0.12 | 80.24 | 11.18 | 13.54 |
[−28, −26) | 2.54 | 0.54 | 0.13 | 94.52 | 12.85 | 16.35 |
[−26, −24) | 6.84 | 0.59 | 0.26 | 109.95 | 12.48 | 18.15 |
[−24, −22) | 3.55 | 0.52 | 0.12 | 151.02 | 14.56 | 17.33 |
[−22, −20) | 4.06 | 0.61 | 0.36 | 95.26 | 11.70 | 13.52 |
[−20, −18) | 5.00 | 0.54 | 0.15 | 101.07 | 11.09 | 20.80 |
[−18, −16) | 3.42 | 0.59 | 0.16 | 74.38 | 10.20 | 10.54 |
[−16, −14) | 4.92 | 0.57 | 0.27 | 96.28 | 13.19 | 18.99 |
[−14, −12) | 5.20 | 0.69 | 0.10 | 84.54 | 9.93 | 13.82 |
[−12, −10) | 5.00 | 0.71 | 0.12 | 75.72 | 10.84 | 15.86 |
[−10, −8) | 5.56 | 0.58 | 0.19 | 70.21 | 10.33 | 13.37 |
[−8, −6) | 4.85 | 0.66 | 0.15 | 74.99 | 10.65 | 15.16 |
[−6, −4) | 5.23 | 0.74 | 0.15 | 64.76 | 10.29 | 12.77 |
[−4, −2) | 3.84 | 0.59 | 0.08 | 67.64 | 9.19 | 11.51 |
[−2, 0) | 3.22 | 0.56 | 0.10 | 88.04 | 11.46 | 16.06 |
[0, 2) | 2.90 | 0.54 | 0.05 | 56.92 | 8.34 | 9.27 |
[2, 4) | 4.38 | 0.66 | 0.13 | 64.97 | 10.04 | 13.81 |
[4, 6) | 5.57 | 0.68 | 0.18 | 88.80 | 10.50 | 15.94 |
[6, 8) | 7.37 | 0.83 | 0.16 | 92.62 | 10.02 | 12.56 |
[8, 10) | 7.29 | 0.76 | 0.32 | 82.34 | 10.41 | 15.77 |
[10, 12) | 7.48 | 0.71 | 0.23 | 92.52 | 11.10 | 14.55 |
[12, 14) | 7.95 | 0.81 | 0.28 | 87.23 | 11.67 | 15.61 |
[14, 16) | 8.47 | 0.81 | 0.19 | 101.73 | 12.17 | 18.08 |
[16, 18) | 7.18 | 1.07 | 0.22 | 95.29 | 13.08 | 18.34 |
[18, 20) | 7.20 | 0.83 | 0.28 | 126.65 | 12.73 | 16.63 |
[20, 22) | 9.44 | 0.87 | 0.27 | 98.45 | 11.65 | 17.95 |
[22, 24) | 8.87 | 0.96 | 0.27 | 81.50 | 12.25 | 18.01 |
[24, 26) | 9.01 | 0.97 | 0.25 | 84.48 | 12.03 | 18.29 |
[26, 28) | 9.00 | 0.91 | 0.27 | 101.17 | 12.28 | 18.01 |
[28, 30) | 10.88 | 1.40 | 0.44 | 109.67 | 12.23 | 19.53 |
[30, +∞) | 6.77 | 1.51 | 0.27 | 110.06 | 13.62 | 23.34 |
Light-Duty Vehicle (LDV) | Heavy-Duty Vehicle (HDV) | Saturated Traffic Flow | Saturated Flow Rate Ratio | yi | ||
---|---|---|---|---|---|---|
West import | Left | 415 | 21 | 1710 | 0.13 | 0.32 |
Right | 59 | 7 | 1602 | 0.04 | ||
Straight | 737 | 137 | 1512 | 0.19 | ||
East import | Left | 313 | 31 | 1620 | 0.11 | 0.24 |
Right | 231 | 61 | 1440 | 0.20 | ||
Straight | 563 | 72 | 1584 | 0.13 | ||
North import | Left | 253 | 45 | 1512 | 0.20 | 0.51 |
Right and Straight | 757 | 112 | 1566 | 0.31 | ||
South import | Left | 207 | 58 | 1386 | 0.23 | 0.49 |
Right and Straight | 527 | 122 | 1476 | 0.26 |
Conversion Factor of Emissions | Import | Left-Turn Signal Timing (S) | Through Signal Timing (S) |
---|---|---|---|
HDV:LDV = 2:1 | East–West | 29 | 42 |
South–North | 45 | 69 | |
HDV:LDV = 5:1 | East–West | 23 | 48 |
South–North | 55 | 59 | |
HDV:LDV = 10:1 | East–West | 19 | 48 |
South–North | 58 | 61 | |
HDV:LDV = 15:1 | East–West | 16 | 47 |
South–North | 60 | 62 | |
HDV:LDV = 20:1 | East–West | 15 | 47 |
South–North | 61 | 62 | |
HDV:LDV = 25:1 | East–West | 14 | 47 |
South–North | 62 | 62 | |
HDV:LDV = 30:1 | East–West | 13 | 47 |
South–North | 62 | 63 |
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Fan, J.; Najafi, A.; Sarang, J.; Li, T. Analyzing and Optimizing the Emission Impact of Intersection Signal Control in Mixed Traffic. Sustainability 2023, 15, 16118. https://doi.org/10.3390/su152216118
Fan J, Najafi A, Sarang J, Li T. Analyzing and Optimizing the Emission Impact of Intersection Signal Control in Mixed Traffic. Sustainability. 2023; 15(22):16118. https://doi.org/10.3390/su152216118
Chicago/Turabian StyleFan, Jieyu, Arsalan Najafi, Jokhio Sarang, and Tian Li. 2023. "Analyzing and Optimizing the Emission Impact of Intersection Signal Control in Mixed Traffic" Sustainability 15, no. 22: 16118. https://doi.org/10.3390/su152216118