Identification and Factor Analysis of Traffic Conflicts in the Merge Area of Freeway Work Zone
Abstract
:1. Introduction
2. Data
2.1. Unmanned Aerial Vehicle Data Collection
2.2. Video Data Processing
- (1)
- Vehicle detection
- (2)
- Vehicle tracking
3. Methods
3.1. Avoidant Conflict Identification
3.2. Impact Analysis of Severe Traffic Conflicts
3.2.1. Influencing Factors
Category | Variable | Variable Explanation |
---|---|---|
Traffic flow factors | FMQ | Hourly traffic volume on the freeway, veh/h |
FRQ | Hourly traffic volume on the ramp, veh/h | |
FMvstd | Average speed standard deviation of the freeway traffic, m/s | |
FRvstd | Average speed standard deviation of the ramp traffic, m/s | |
FMV | Average speed of the freeway traffic, m/s | |
FRV | Average speed of the ramp traffic, m/s | |
Road factor | L | Distance between the upstream work zone and the merge area (Figure 5), m |
IFw | Whether there is construction on the outside of the merge area | |
IFc | Whether the length of the acceleration lane in the merge area is compressed (whether it is shorter than before construction) | |
Individual vehicle factor | Ctype | Vehicle type |
V(i) | Average speed of the vehicle, m/s | |
Vstd(i) | Standard deviation of the continuous driving speed of the vehicle, m/s | |
amax(i) | The most unfavorable acceleration of the vehicle (acceleration corresponding to the maximum absolute value of the vehicle acceleration), m/s2 | |
Target variable | yi | Whether there are serious conflicts when the vehicles are driving in the merge area |
3.2.2. Binomial Logistic Model
4. Results and Analysis
4.1. Identification Results of Severe Traffic Conflicts
4.2. Distribution of Traffic Conflicts
- (1)
- Overall vehicle conflict distribution
- (2)
- Conflict distribution at different intervals
4.3. Logistic Model Results
4.3.1. Variable Correlation Analysis
4.3.2. Variable Discretization
4.3.3. Model Result Analysis
4.3.4. Model Validation
5. Conclusions and Discussion
- (1)
- Based on video data of vehicles collected using a UAV, the running tracking information of the vehicles was parsed, conflict states of vehicles in merge areas were studied, and spatial distribution characteristics of traffic conflicts in merge areas were analyzed. This is an effective approach to achieving the goals of traffic conflict research.
- (2)
- From the perspective of the conflict-avoidance driving behaviors of vehicles, the correlations between the serious conflict rate and traffic accident rate were analyzed using the Pearson coefficient method, based on the interval initial velocity and acceleration of the vehicles. The analysis shows that vehicles in the freeway merge areas will have serious traffic conflicts in the following two situations: (Ⅰ) m/s and m/s2; and (Ⅱ) m/s, and m/s2.
- (3)
- From the spatial distribution characteristics of the traffic conflicts and running tracks of vehicles in the merge areas, the percentages of serious traffic conflicts in the first 25 m and last 25 m of the merge area are 32.45% and 34.61%, respectively, i.e., higher than in the other sections. Moreover, the running tracks of vehicles will change significantly in these two intervals.
- (4)
- A binomial logistic model was established by considering the road conditions in the work zone. It was found that the smaller the distance between the upstream work zone and the merge area, the greater the probability of serious traffic conflicts. As the average vehicle speed increases, the probability of serious traffic conflicts initially decreases, and then increases; however, as the hourly traffic volume on the freeway increases, it first increases and then decreases. From the comparison of the OR value of each factor, it is found that when the average vehicle speed is high, the probability of serious conflict is the greatest, at 5.95 times that of the original probability. Large vehicles have the second-largest probability of experiencing serious conflicts, at 4.765 times that of small vehicles.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Collection Time | Including the morning peak from 8:00 to 9:00, the evening peak from 16:00 to 17:00, and the flat peaks from 10:00 to 11:00 and 15:00 to 16:00. |
Collection Site | K176 + 500, K258 + 260 (including 2 merge areas), and K132 + 300 (including 2 merge areas). |
Characteristics of merge area | Merge area (K176 + 500):100 m long and 14 m wide Merge areas (K258 + 260): two merge areas are both 120 m and 15 m wide. Merge areas (K132 + 300): two merge areas are both 150 m and 15 m wide. |
Collected Data Amount | A total of six hours of data were collected; after data sorting, 56,825 frames with complete data were retained. |
Initial Velocity Classification | Initial Velocity (m/s) | Acceleration Classification | Acceleration (m/s2) |
---|---|---|---|
Interval 1 | [7, 13.5) | Interval 1 | [−3.96, −1.57) |
Interval 2 | [13.5, 17.6) | Interval 2 | [−1.57, −0.65) |
Interval 3 | [17.60, 21.10) | Interval 3 | [−0.65, 0.04) |
Interval 4 | [21.10, 24.30) | Interval 4 | [0.04, 0.84) |
Interval 5 | [24.30, 30.30] | Interval 5 | [0.84, 3.15] |
Initial Velocity (m/s) | Acceleration (m/s2) | Pearson Coefficient | Initial Velocity (m/s) | Acceleration (m/s2) | Pearson Coefficient |
---|---|---|---|---|---|
[7,13.5) | [−3.96, −1.57) | 0.812 ** | [13.5, 17.6) | [−3.96, −1.57) | 0.823 ** |
[7,13.5) | [−1.57, −0.65) | 0.877 ** | [13.5, 17.6) | [−1.57, −0.65) | 0.563 |
[7,13.5) | [−0.65, 0.04) | 0.267 | [13.5, 17.6) | [−0.65, 0.04) | 0.532 |
[7,13.5) | [0.04, 0.84) | 0.245 | [13.5, 17.6) | [0.04, 0.84) | 0.573 |
[7,13.5) | [0.84, 3.15] | 0.214 | [13.5, 17.6) | [0.84, 3.15] | 0.861 ** |
[17.60,21.10) | [−3.96, −1.57) | 0.806 ** | [21.10, 24.30) | [−3.96, −1.57) | 0.511 |
[17.60,21.10) | [−1.57, −0.65) | 0.612 | [21.10, 24.30) | [−1.57, −0.65) | 0.643 |
[17.60,21.10) | [−0.65, 0.04) | 0.422 | [21.10, 24.30) | [−0.65, 0.04) | 0.512 |
[17.60,21.10) | [0.04, 0.84) | 0.476 | [21.10, 24.30) | [0.04, 0.84) | 0.332 |
[17.60,21.10) | [0.84, 3.15] | (0.221) | [21.10, 24.30) | [0.84, 3.15] | 0.324 |
[24.30,30.30] | [−3.96, −1.57) | 0.614 | [24.30, 30.30] | [0.04, 0.84) | 0.253 |
[24.30,30.30] | [−1.57, −0.65) | 0.322 | [24.30, 30.30] | [0.84, 3.15] | 0.298 |
[24.30,30.30] | [−0.65, 0.04) | 0.106 |
Number of Vehicles in Serious Conflict (Vehicles) | Number of Vehicles in Non-Serious Conflict (Vehicles) | Total Number of Vehicles (Vehicles) | Proportion of Vehicles in Serious Conflict (%) |
---|---|---|---|
816 | 1552 | 2368 | 34.46 |
Variable | FRQ | FMV | FMvstd | FRvstd | IFc | IFw | L | |
---|---|---|---|---|---|---|---|---|
Hourly traffic on the freeway (FMQ) | Correlation | −0.577 | 0.821 | −0.821 | ||||
significance (two-tailed) | 0.000 | 0.000 | 0.000 | |||||
Hourly traffic volume on the ramp (FRQ) | Correlation | −0.599 | 0.633 | |||||
significance (two-tailed) | 0.000 | 0.000 | ||||||
Average speed of the freeway traffic(FMV) | Correlation | 0.636 | 0.638 | |||||
significance (two-tailed) | 0.000 | 0.000 | ||||||
Standard deviation of the average speed of the freeway traffic (FMvstd) | Correlation | 0.625 | ||||||
significance (two-tailed) | 0.000 | |||||||
Whether the acceleration lane is compressed (IFc) | Correlation | −1.000 | −0.856 | |||||
significance (two-tailed) | 0.000 | 0.000 | ||||||
Whether the roadside is under construction (IFw) | Correlation | 0.856 | ||||||
significance (two-tailed) | 0.000 |
Variable Type | Variable | Discrete Value | Discretization Discriminant |
---|---|---|---|
Individual vehicle variables | Vehicle type | 0 | Small or medium-sized vehicle |
Ctype | 1 | Large vehicle | |
Average speed of an individual vehicle V(i) (m/s) | 1 | [6, 15.5) | |
2 | [15.5, 21.6) | ||
3 | [21.6, 33] | ||
Standard deviation of the average speed of an individual vehicle Vstd(i) (m/s) | 1 | [0, 1.85) | |
2 | [1.85, 5) | ||
3 | [5, 8] | ||
The most unfavorable acceleration of an individual vehicle amax(i) (m/s2) | 1 | [−4.5, −2.3) | |
2 | [−2.3, 0.2) | ||
3 | [0.2, 3] | ||
Traffic flow variables | Hourly traffic on the freeway FMQ (veh/h) | 1 | [820, 900) |
2 | [900, 1000) | ||
3 | [1000, 1120] | ||
Average speed of the freeway traffic FMV (m/s) | 1 | [12, 14) | |
2 | [14, 17) | ||
3 | [17, 21] | ||
Average speed of the ramp traffic FRV (m/s) | 1 | [8, 10) | |
2 | [10, 14) | ||
3 | [14, 18] | ||
Road condition variables | Distance between the upstream work zone and the merge area L | 1 | Small |
2 | Medium | ||
3 | Large | ||
Dependent variables | Whether there is a risk of serious conflict yi | 0 | Non-serious conflict |
1 | Serious conflict |
Variable | β | S.E. | Wald | Degree of Freedom | Significance | Odds Ratio (OR) |
---|---|---|---|---|---|---|
V(i) = 1 | 8.504 | 2 | 0.000 | |||
V(i) = 2 | −0.814 | 0.868 | 0.880 | 1 | 0.048 | 0.443 |
V(i) = 3 | 1.783 | 0.729 | 5.990 | 1 | 0.000 | 5.954 |
FMQ = 1 | 7.210 | 2 | 0.000 | |||
FMQ = 2 | 0.542 | 0.278 | 3.812 | 1 | 0.000 | 1.720 |
FMQ = 3 | −0.221 | 0.113 | 3.854 | 1 | 0.000 | 0.801 |
amax(i) = 1 | 15.607 | 2 | 0.000 | |||
amax(i) = 2 | −3.323 | 0.841 | 15.607 | 1 | 0.000 | 0.036 |
amax(i) = 3 | −20.509 | 798.820 | 0.000 | 1 | 0.998 | 0.000 |
Ctype | 1.561 | 0.734 | 4.531 | 1 | 0.033 | 4.765 |
L = 1 | 4.000 | 2 | 0.000 | |||
L = 2 | −0.029 | 0.022 | 1.803 | 1 | 0.000 | 0.971 |
L = 3 | −0.587 | 0.360 | 2.656 | 1 | 0.000 | 0.556 |
Constant | −3.909 | 0.600 | 42.449 | 1 | 0.000 | 0.020 |
Chi-Square | Degree of Freedom | Significance | |
---|---|---|---|
Step (T) | 4.634 | 1 | 0.031 |
Block | 1101.623 | 11 | 0.000 |
Model | 1101.623 | 11 | 0.000 |
Step (T) | Chi-Square | Degree of Freedom | Significance |
---|---|---|---|
6 | 0.223 | 6 | 1.000 |
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Wang, P.; Zhu, S.; Zhao, X. Identification and Factor Analysis of Traffic Conflicts in the Merge Area of Freeway Work Zone. Sustainability 2023, 15, 11314. https://doi.org/10.3390/su151411314
Wang P, Zhu S, Zhao X. Identification and Factor Analysis of Traffic Conflicts in the Merge Area of Freeway Work Zone. Sustainability. 2023; 15(14):11314. https://doi.org/10.3390/su151411314
Chicago/Turabian StyleWang, Pan, Shunying Zhu, and Xiaoyue Zhao. 2023. "Identification and Factor Analysis of Traffic Conflicts in the Merge Area of Freeway Work Zone" Sustainability 15, no. 14: 11314. https://doi.org/10.3390/su151411314