Crash Risk Prediction Modeling Based on the Traffic Conflict Technique and a Microscopic Simulation for Freeway Interchange Merging Areas
Abstract
:1. Introduction
2. Methodology
2.1. Time to Collision (TTC) Calculation
2.1.1. The Rear-End Conflict
- —Rear-end conflict value, s;
- —The largest slope of Relative Distance occurred time, s;
- —The virtual collision moment, s.
2.1.2. The Lane-Change Conflict
- —Lane-change conflict value, s;
- —Avoidance behavior generation time, s;
- —Vehicle A length, m;
- —Vehicle B length, m;
- —Vehicle A speed at , m/s;
- —Vehicle B speed at , m/s;
- —Travel distance of vehicle A from avoidance behavior generation site to trajectory cross-point, m;
- —Travel distance of vehicle B from avoidance behavior generation site to trajectory cross-point, m;
- —Travel time of vehicle A from avoidance behavior generation site to trajectory cross-point, s;
- —Travel time of vehicle B from avoidance behavior generation site to trajectory cross-point, s.
2.1.3. TTC Threshold Calculation
Severity Classification
TTC Value Calculation
TTC Threshold Calculation
2.2. HCRI Calculation
- —Hourly conflict risk indexes;
- —The number of serious lane-change conflicts;
- —The number of general lane-change conflicts;
- —The number of serious rear-end conflicts;
- —The number of general rear-end conflicts.
2.3. Model Prototype
- —Hourly conflict risk indexes;
- —Independent variable coefficient;
- —Some independent variable;
- —Ramp traffic volume, veh/h;
- —Outer lane traffic volume, veh/h;
- —Acceleration lane length, m;
- —Ramp percent heavy vehicles, %;
- —Outer lane percent heavy vehicles, %;
- —Ramp design speed, km/h.
- —Constant term.
3. Data Collection
3.1. Field Data
3.1.1. Observer Training
3.1.2. Data Processing
The Rear-End Conflict
The Lane-Change Conflict
TTC Threshold Calculation
3.2. Simulation Data
3.2.1. Calibration and Validation
Part 1
Part 2
Part 3
3.2.2. Simulation Design
The Range of Variables
Design of Orthogonal Test Table
Independent Variable Correlation
Data Analysis
4. Model
4.1. Establishment of the Model
- HCRI—Hourly conflict risk indexes;
- —Ramp traffic volume, veh/h;
- —Acceleration lane length, m.
4.2. Model Validation
5. Conclusions
- (1)
- The threshold of serious and general lane-change conflicts lies between 0–2.3 s and 2.3–4.2 s, respectively; the threshold of serious and general rear-end conflicts lies between 0–2.8 s and 2.8–4.7 s, respectively.
- (2)
- The field data was used to calibrate and verify the simulation model. The traffic conflict is 12.032%, which meets the requirements. The fitting degree of the HCRI model is 0.620. The HCRI model can be used as an effective complement to the method of the traffic conflict technique.
- (3)
- The MAPE of the verified model was 25.91%. More models on the HCRI index can be established in the future.
- (4)
- This paper reports the explorative effort on developing a new traffic conflict model using HCRI as an evaluation index. Such a study bears a lot of potential for engineering applications and safety evaluation.
Acknowledgments
Author Contributions
Conflicts of Interest
References
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Total No. | Accident Type | Total Loss | Average Loss | Weight |
---|---|---|---|---|
92 | Rear-end | 820,000 | 8913.04 | 0.54 |
90 | Lane-change | 675,000 | 7500.00 | 0.46 |
Conflict Type | Rear-End Conflict | Lane-Change Conflict | ||
---|---|---|---|---|
Serious (S) | General (G) | Serious (S) | General (G) | |
TTC average value | 2.4 | 3.9 | 1.8 | 3.3 |
Severity Weight | 0.62 | 0.38 | 0.65 | 0.35 |
Conflict Type | Rear End | Lane-Change | ||
---|---|---|---|---|
Serious Conflict | General Conflict | Serious Conflict | General Conflict | |
Threshold (TTC/s) | 0–2.8 | 2.8–4.7 | 0–2.3 | 2.3–4.2 |
Validation Sets | Travel Time | The Number of Conflicts | ||||
---|---|---|---|---|---|---|
Observed | Simulated | Observed | Simulated | |||
1 | 11.4 | 11.2 | 1.754% | 72 | 65 | 9.722% |
2 | 10.3 | 10.5 | 1.942% | 94 | 85 | 9.574% |
3 | 10.8 | 11 | 1.852% | 35 | 41 | 17.143% |
4 | 9.6 | 10.1 | 5.208% | 35 | 40 | 14.286% |
5 | 10.1 | 10.6 | 4.950% | 53 | 58 | 9.434% |
Average | 10.44 | 10.68 | 3.141% | 57.8 | 57.8 | 12.032% |
No. | X1 (veh/h) | X2 (veh/h) | X3 (m) | X4 (%) | X5 (%) | X6 (km/h) |
---|---|---|---|---|---|---|
Mean | 865 | 1250 | 180 | 0.07 | 0.26 | 62.54 |
Std. deviation | 155 | 245 | 45 | 0.02 | 0.13 | 13.25 |
No. | X1 (veh/h) | X2 (veh/h) | X3 (m) | X4 (%) | X5 (%) | X6 (km/h) |
---|---|---|---|---|---|---|
1 | 500 | 1000 | 150 | 0.02 | 0.05 | 40 |
2 | 600 | 1100 | 180 | 0.04 | 0.10 | 48 |
3 | 700 | 1200 | 210 | 0.06 | 0.20 | 56 |
4 | 800 | 1300 | 240 | 0.08 | 0.30 | 64 |
5 | 900 | 1400 | 270 | 0.10 | 0.40 | 72 |
6 | 1000 | 1500 | 300 | 0.12 | 0.50 | 80 |
Variable | X1 | X2 | X3 | X4 | X5 | X6 |
---|---|---|---|---|---|---|
X1 | 1.0000 | |||||
X2 | −0.0397 | 1.0000 | ||||
X3 | 0.0000 | −0.0079 | 1.0000 | |||
X4 | −0.0000 | 0.0238 | 0.0000 | 1.0000 | ||
X5 | −0.0000 | 0.0241 | −0.0000 | −0.0000 | 1.0000 | |
X6 | 0.0000 | −0.0397 | 0.0000 | 0.0000 | 0.0000 | 1.0000 |
Evalution Index | Maximum | Minimum | Mean | Std. Deviation |
---|---|---|---|---|
HCRI | 147.953 | 3.095 | 71.137 | 35.980 |
HCR | 0.329 | 0.008 | 0.162 | 0.079 |
Variable | HCR | HCRI | ||||
---|---|---|---|---|---|---|
Coef. | Std. Err. | p > |t| | Coef. | Std. Err. | p > |t| | |
X1 | 0.000227 | 0.000030 | 0.000 | 0.120002 | 0.012565 | 0.000 |
X2 | −0.000026 | 0.000030 | 0.396 | 0.016022 | 0.012587 | 0.206 |
X3 | 0.000838 | 0.000100 | 0.000 | 0.381452 | 0.041851 | 0.000 |
X4 | −0.090874 | 0.150695 | 0.548 | −49.579750 | 62.791880 | 0.432 |
X5 | 0.060689 | 0.032330 | 0.063 | 23.210860 | 13.471470 | 0.088 |
X6 | −0.000608 | 0.000377 | 0.110 | −0.215238 | 0.157059 | 0.174 |
_cons | −0.137401 | 0.057390 | 0.019 | −114.403800 | 23.913310 | 0.000 |
R-squared | 0.5450 | 0.620 | ||||
Root MSE | 0.05348 | 22.283 |
HCRI | Removing X2, X4, X6 | Removing X2, X4, X6, X5 | ||||
---|---|---|---|---|---|---|
Coef. | Std. Err. | p > |t| | Coef. | Std. Err. | p > |t| | |
X1 | 0.119367 | 0.012628 | 0.000 | 0.119366 | 0.012750 | 0.000 |
X3 | 0.381029 | 0.042094 | 0.000 | 0.381029 | 0.042501 | 0.000 |
X5 | 23.625440 | 13.54627 | 0.084 | |||
_cons | −110.2217 | 14.01081 | 0.000 | −104.1185 | 13.69801 | 0.000 |
R-squared | 0.6156 | 0.6081 | ||||
MSE | 22.413 | 22.63 |
Validation Dataset | Maximum | Minimum | Mean | Std. Deviation | RMSE | MAPE |
---|---|---|---|---|---|---|
Field HCRI | 225.70 | 29.28 | 106.08 | 46.90 | 38.27 | 25.91% |
Predicted HCRI | 129.56 | 24.66 | 78.25 | 27.11 |
© 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Li, S.; Xiang, Q.; Ma, Y.; Gu, X.; Li, H. Crash Risk Prediction Modeling Based on the Traffic Conflict Technique and a Microscopic Simulation for Freeway Interchange Merging Areas. Int. J. Environ. Res. Public Health 2016, 13, 1157. https://doi.org/10.3390/ijerph13111157
Li S, Xiang Q, Ma Y, Gu X, Li H. Crash Risk Prediction Modeling Based on the Traffic Conflict Technique and a Microscopic Simulation for Freeway Interchange Merging Areas. International Journal of Environmental Research and Public Health. 2016; 13(11):1157. https://doi.org/10.3390/ijerph13111157
Chicago/Turabian StyleLi, Shen, Qiaojun Xiang, Yongfeng Ma, Xin Gu, and Han Li. 2016. "Crash Risk Prediction Modeling Based on the Traffic Conflict Technique and a Microscopic Simulation for Freeway Interchange Merging Areas" International Journal of Environmental Research and Public Health 13, no. 11: 1157. https://doi.org/10.3390/ijerph13111157
APA StyleLi, S., Xiang, Q., Ma, Y., Gu, X., & Li, H. (2016). Crash Risk Prediction Modeling Based on the Traffic Conflict Technique and a Microscopic Simulation for Freeway Interchange Merging Areas. International Journal of Environmental Research and Public Health, 13(11), 1157. https://doi.org/10.3390/ijerph13111157