Impact of Pavement Defects on Traffic Operational Performance
Abstract
:1. Introduction
- Specifying the important multi-lane highways in Kafrelsheikh governorate to be the subject of this study (case study).
- Assigning the flow, speed, and density of the chosen roadways’ traffic streams in dry weather and during daylight hours.
- Conducting a field survey to inspect the pavement distresses visually.
- Researching the impact of various pavement distress levels on traffic efficiency.
- Building a statistical model and creating mathematical relationships based on actual data using linear regression to investigate how pavement distresses affect percentile speeds and traffic capacity.
2. Literature Review
3. Methodology
3.1. Road Selection Criteria
3.2. Data Collection Procedures
3.2.1. Traffic Data
3.2.2. Pavement Condition Data
4. Results and Analysis
4.1. Speed Results
4.1.1. Analysis of Vehicle Speed
4.1.2. Normality Test
4.1.3. Descriptive Statistics of Speed Percentiles
4.1.4. Regression Models
4.2. Capacity Results
Capacity Models
5. Conclusions
- By representing the relationship between pavement distresses (in terms of PCI values) and speed percentiles, it is observed that R2 for all fitted lines is more than 0.9, meaning that the relations between the PCI and both V50 and V85 for the three classes of vehicles are consistent. It means that as PCI value decreases (more pavement distresses), the speed decreases, in addition to the relation between traffic capacity and PCI values. It is obvious the more the PCI, the more the capacity.
- In the comparison between the effect of paving defects on both V50 and V85 for light and heavy vehicles, it is deduced that pavement distresses have a significant impact on light vehicles more than heavy ones.
- The ANOVA test was performed to compare and analyze the speed behavior of vehicles for different classes. The necessity to categorize vehicles into multiple groups has been supported by analyses of the mean speeds for various categories of vehicles.
- A 1-sample K–S test was implemented to examine the normal distribution of speed data. It was found that the speed data for most of the section deviated from the normal distribution. This means that poor pavement conditions may have an impact on the behavior of vehicle speeds.
- Using regression analysis, six models were developed to describe the relationships between the percentile speeds (V50 and V85) and three variables, namely PCI, lane width (L), and shoulder width (S). Additionally, one model only was developed to describe the relationship between capacity and the previous three variables.
- For the speed analysis, R2 values for all models were more than 0.9 which reflects the high goodness of models. The results of the best linear regression model showed that the most influential variable on the percentile speeds was the PCI. However, S and L were excluded from the final model due to poor correlation with percentile speeds.
- For the capacity analysis, the R2 value was 0.95, expressing the goodness of the model fit. The most influential variable on capacity was the PCI followed by S then L. A strong positive correlation was found between capacity and the three investigated independent variables (PCI, L, and S).
- According to the conclusions of this study, the relationships of the developed models can be a useful resource for road and traffic practitioners and field engineers to build roads for defined speed or capacity.
- Finally, speed models can be used to estimate speed given the level of pavement distress (PCI), and the capacity model can also be used to estimate the capacity given PCI, S, and L. They can help traffic and pavement engineers justify their decisions regarding maintenance strategies and carry out safety and operational performance analysis and studies on vehicle operating costs. From these models, a practical framework for analysis and correlation can be provided, so that an appropriate speed adjustment warning can be issued for road safety. Additionally, road standards can be set by determining the speed of these roads by knowing the condition of their pavement.
Author Contributions
Funding
Conflicts of Interest
References
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Property | Road Name | ||||
---|---|---|---|---|---|
I-C Highway | K-B Highway | K-T Highway | |||
Link1 | Link2 | Link3 | |||
Length of the road (km) | 132 | 59 | 6 | 10 | 20 |
lane width (m) | 4.4 | 3.5 | 3.5 | 3.5 | 3.5 |
No. of lanes | 3 | 2 | 3 | 2 | 3 |
Speed Limit (Km/hr) | 100 | 90 | 90 | 90 | 90 |
NO. sections | 2 | 9 | 4 | 6 | 2 |
Section No. | No. Vehicle/5 min (Pcu/hr) | Average Speed (km/hr) | ||||
---|---|---|---|---|---|---|
LV | HV | Total | LV | HV | Total | |
1 | 340 | 90 | 430 | 90.74 | 72.76 | 81.75 |
2 | 338 | 66 | 404 | 88.13 | 69.82 | 78.97 |
3 | 339.5 | 56 | 395.5 | 91.10 | 71.31 | 81.20 |
4 | 347 | 97 | 444 | 88.74 | 66.41 | 77.75 |
5 | 388 | 68 | 456 | 90.29 | 72.83 | 81.56 |
6 | 332.5 | 75 | 410.5 | 90.74 | 72.76 | 81.75 |
7 | 324 | 82 | 406 | 85.31 | 61.15 | 73.23 |
8 | 311 | 104 | 415 | 88.61 | 73.12 | 80.86 |
9 | 402.5 | 94 | 496.5 | 78.67 | 63.69 | 71.18 |
10 | 307 | 154 | 588 | 116.83 | 81.22 | 99.02 |
11 | 330 | 168 | 498 | 114.53 | 85.62 | 100.07 |
12 | 403.5 | 142 | 545.5 | 103.93 | 86.12 | 95.02 |
13 | 427.5 | 192 | 619.5 | 98.68 | 78.19 | 88.43 |
14 | 291 | 180 | 471 | 78.00 | 63.94 | 70.97 |
15 | 356 | 190 | 546 | 83.14 | 65.85 | 74.495 |
16 | 387 | 98 | 485 | 80.28 | 53.72 | 67.00 |
17 | 560 | 174 | 716 | 93.43 | 77.97 | 80.7 |
18 | 649.5 | 206 | 855.5 | 94.81 | 67.88 | 81.34 |
19 | 291 | 180 | 471 | 77.79 | 60.10 | 68.94 |
20 | 434 | 142 | 567 | 81.55 | 65.56 | 73.55 |
21 | 332.5 | 78 | 410.5 | 69.06 | 58.58 | 63.82 |
22 | 362.5 | 172 | 534.5 | 99.11 | 76.53 | 87.82 |
23 | 592 | 180 | 772 | 99.55 | 79.75 | 89.65 |
Highway Name | Section No. | Lane Width (m) | Road Width (m) | Shoulder Width Left (m) | Shoulder Width Right (m) | Average Shoulder Width (m) | PCI | |
---|---|---|---|---|---|---|---|---|
K-B highway | 1 | 3.6 | 7.5 | 38 | ||||
2 | 3.6 | 7.3 | 47 | |||||
3 | 3.6 | 7.5 | 44 | |||||
4 | 3.6 | 7.4 | 51 | |||||
5 | 3.6 | 7.3 | 0.5 | 1.5 | 1 | 59 | ||
6 | 3.6 | 7.5 | 57 | |||||
7 | 3.6 | 7.3 | 53 | |||||
8 | 3.6 | 7.5 | 62 | |||||
9 | 3.6 | 7.1 | 43 | |||||
I-C highway | 10 | 4.40 | 13.2 | 1 | 3 | 2 | 94 | |
11 | 98 | |||||||
K-T highway | Link 1 | 12 | 3.3 | 10.0 | 0.5 | 3.5 | 2 | 79 |
13 | 3.3 | 9.8 | 72 | |||||
14 | 3.3 | 10.0 | 0.5 | 4.1 | 2.3 | 40 | ||
15 | 3.3 | 10.0 | 46 | |||||
Link 2 | 16 | 3.6 | 7.5 | 0.7 | 2.3 | 1.5 | 28 | |
17 | 3.6 | 7.5 | 73 | |||||
18 | 3.6 | 7.2 | 80 | |||||
19 | 3.6 | 7.2 | 32 | |||||
20 | 3.6 | 7.5 | 54 | |||||
21 | 3.7 | 8.0 | 0.5 | 3.1 | 1.8 | 23 | ||
Link 3 | 22 | 3.5 | 10.8 | 1.5 | 2.9 | 2.2 | 82 | |
23 | 3.5 | 90 |
NO. Section | Significance | Multiple Comparisons (Significance) | |||
---|---|---|---|---|---|
2 | 0.000 | LV | HV | TOTAL | |
LH | - | 0.000 | 0.035 | ||
HV | 0.000 | - | 0.000 | ||
TOTAL | 0.035 | 0.000 | - |
Section No. | TEST STATIC(D) | Asymp. Sig. (2-Tailed) | PCI | Section No. | TEST STATIC (D) | Asymp. Sig. (2-Tailed) | PCI |
---|---|---|---|---|---|---|---|
1 | 0.382 | 0.000 | 38 | 13 | 0.127 | 0.000 | 72 |
2 | 0.087 | 0.000 | 47 | 14 | 0.055 | 0.048 | 40 |
3 | 0.104 | 0.000 | 44 | 15 | 0.066 | 0.081 | 46 |
4 | 0.100 | 0.000 | 51 | 16 | 0.085 | 0.001 | 28 |
5 | 0.082 | 0.008 | 59 | 17 | 0.056 | 0.200 | 73 |
6 | 0.075 | 0.030 | 57 | 18 | 0.073 | 0.200 | 80 |
7 | 0.060 | 0.200 | 53 | 19 | 0.075 | 0.048 | 32 |
8 | 0.086 | 0.179 | 62 | 20 | 0.056 | 0.066 | 54 |
9 | 0.075 | 0. 022 | 43 | 21 | 0.047 | 0.000 | 23 |
10 | 0.086 | 0.073 | 94 | 22 | 0.058 | 0.028 | 82 |
11 | 0.068 | 0.062 | 98 | 23 | 0.042 | 0.200 | 90 |
12 | 0.084 | 0.001 | 79 |
Section No. | Light Vehicle | Heavy Vehicle | Total Vehicle | |||
---|---|---|---|---|---|---|
V50L | V85L | V50H | V85H | V50T | V85T | |
1 | 75 | 93 | 61 | 69 | 76 | 91 |
2 | 84 | 102 | 62 | 76 | 82 | 97 |
3 | 81 | 94 | 68 | 74 | 80 | 93 |
4 | 88 | 100 | 66 | 84 | 86 | 98 |
5 | 84 | 102 | 66 | 80 | 82 | 101 |
6 | 85 | 108 | 69 | 84 | 84 | 106 |
7 | 82 | 93 | 60 | 72 | 78 | 90 |
8 | 86 | 98 | 72 | 80 | 84 | 94 |
9 | 72 | 94 | 65 | 74 | 70 | 91 |
10 | 109 | 124 | 82 | 97 | 106 | 122 |
11 | 111 | 137 | 85 | 98 | 108 | 127 |
12 | 99 | 116 | 80 | 90 | 97 | 112 |
13 | 91 | 114 | 74 | 85 | 89 | 110 |
14 | 74 | 86 | 60 | 73 | 71 | 84 |
15 | 80 | 90 | 64 | 72 | 75 | 87 |
16 | 70 | 86 | 58 | 71 | 68 | 84 |
17 | 91 | 108 | 74 | 85 | 89 | 106 |
18 | 97 | 114 | 80 | 92 | 94 | 113 |
19 | 74 | 88 | 55 | 67 | 66 | 79 |
20 | 77 | 95 | 63 | 75 | 74 | 90 |
21 | 66 | 78 | 54 | 69 | 64 | 76 |
22 | 95 | 113 | 79 | 93 | 93 | 111 |
23 | 104 | 125 | 81 | 95 | 102 | 117 |
Variable | Min. | MAX. | Avg. | SD | |
---|---|---|---|---|---|
V50 (Km/h) | LV | 66 | 111 | 86 | 12.1 |
HV | 54 | 85 | 68.3 | 9.9 | |
Total | 64 | 108 | 83.4 | 12.5 | |
V85 (Km/h) | LV | 78 | 137 | 102.3 | 14.2 |
HV | 67 | 101 | 81.1 | 10.4 | |
Total | 76 | 127 | 99.1 | 13.9 | |
PCI | 23 | 98 | 60 | 20 |
Model No. | Model | R2 | t (t-Test) | Sig. of (F) | |
---|---|---|---|---|---|
Constant | PCI | ||||
1 | V50L = 52.03+ 0.58 × PCI | 0.94 | 26.05 | 18.00 | 0.000 |
2 | V85L = 63.97+ 0.66 × PCI | 0.92 | 24.40 | 15.75 | |
3 | V50H = 45.37 + 0.40 × PCI | 0.92 | 29.14 | 16.00 | |
4 | V85H = 55.22 + 0.43× PCI | 0.91 | 30.23 | 14.79 | |
5 | V50T = 50.68+ 0.56 × PCI | 0.93 | 23.73 | 16.27 | |
6 | V85T = 62.87 + 0.62 × PCI | 0.92 | 24.56 | 15.21 |
Road Name | Sec No. | Lane Width | Avg. PCI | Avg. V50T | Avg. V85T |
---|---|---|---|---|---|
K-B | 5, 6, 8 | 3.6 | 59 | 83 | 100 |
K-T | 22, 23 | 3.5 | 86 | 97 | 114 |
Time | No. Vehicle/5 min | q Pcu/hr | ATS Km/hr | K Veh/km | ||
---|---|---|---|---|---|---|
LV Pcu | HV Pcu | Total Pcu | ||||
10:00–10:05 | 26 | 14 | 40 | 480 | 98.12 | 4.89 |
10:05–10:10 | 26 | 14 | 40 | 480 | 97.37 | 4.93 |
10:10–10:15 | 35 | 10 | 44.5 | 534 | 95.13 | 5.61 |
10:15–10:20 | 43 | 22 | 65 | 780 | 93.65 | 8.33 |
10:20–10:25 | 38 | 12 | 49.5 | 594 | 95.34 | 6.23 |
10:25–10:30 | 41 | 8 | 48.5 | 582 | 99.06 | 5.88 |
10:30–10:35 | 45 | 18 | 63 | 756 | 96.46 | 7.84 |
10:35–10:40 | 40 | 4 | 44 | 528 | 98.73 | 5.35 |
10:40–10:45 | 30 | 14 | 44 | 528 | 98.98 | 5.33 |
10:45–10:50 | 24 | 14 | 38 | 450 | 93.94 | 4.79 |
10:50–10:55 | 31 | 8 | 38.5 | 462 | 100.28 | 4.61 |
10:55–11:00 | 27 | 4 | 31 | 372 | 91.25 | 4.08 |
Section No. | The Capacity in One Direction (pcu/h) | Section No. | The Capacity in One Direction (pcu/h) |
---|---|---|---|
1 | 614 | 12 | 1048 |
2 | 648 | 13 | 1000 |
3 | 657 | 14 | 942 |
4 | 684 | 15 | 811 |
5 | 730 | 16 | 616 |
6 | 992 | 17 | 1070 |
7 | 741 | 18 | 1047 |
8 | 936 | 19 | 640 |
9 | 629 | 20 | 925 |
10 | 1354 | 21 | 574 |
11 | 1396 | 22 | 1089 |
23 | 1302 |
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Hashim, I.H.; Badawy, R.M.; Heneash, U. Impact of Pavement Defects on Traffic Operational Performance. Sustainability 2023, 15, 8293. https://doi.org/10.3390/su15108293
Hashim IH, Badawy RM, Heneash U. Impact of Pavement Defects on Traffic Operational Performance. Sustainability. 2023; 15(10):8293. https://doi.org/10.3390/su15108293
Chicago/Turabian StyleHashim, Ibrahim H., Rania M. Badawy, and Usama Heneash. 2023. "Impact of Pavement Defects on Traffic Operational Performance" Sustainability 15, no. 10: 8293. https://doi.org/10.3390/su15108293
APA StyleHashim, I. H., Badawy, R. M., & Heneash, U. (2023). Impact of Pavement Defects on Traffic Operational Performance. Sustainability, 15(10), 8293. https://doi.org/10.3390/su15108293