# Study on Traffic Conflict Prediction Model of Closed Lanes on the Outside of Expressway

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## Abstract

**:**

## 1. Introduction

## 2. Literature Review

## 3. Data Collection and Method

#### 3.1. Data Collection

#### 3.2. Method

## 4. Traffic Characteristic Analysis

#### 4.1. Traffic Volume Characteristics

#### 4.2. Speed Distribution

#### 4.3. Time Headway

#### 4.4. Vehicle Queuing Analysis

## 5. Results

#### 5.1. Traffic Conflict Analysis

#### 5.2. Construction of Traffic Conflict Prediction Model

#### 5.3. Model Validation

## 6. Conclusions

## Author Contributions

## Funding

## Conflicts of Interest

## References

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**Figure 4.**Traffic volume in warning area, upstream transition area and activity area of expressway maintenance operation area.

**Figure 5.**Distribution of speed in each area of expressway maintenance operation area. (

**a**) Warning Area 1; (

**b**) Warning Area 2; (

**c**) Upstream Transition Area; (

**d**) Buffer Area; (

**e**) Activity Area.

**Figure 6.**Time headway distribution in expressway maintenance operation area. (

**a**) Time headway distribution in warning area; (

**b**) time headway distribution in upstream transition area; (

**c**) time headway distribution in buffer area; (

**d**) time headway distribution in activity area.

**Figure 7.**Distribution of traffic conflicts in maintenance operation areas: (

**a**) serious conflict cumulative frequency distribution; (

**b**) non-serious conflict cumulative frequency distribution; (

**c**) traffic conflict frequency distribution.

**Figure 8.**Validation of traffic conflict prediction model: (

**a**) warning area conflict fitting; (

**b**) upstream transition area conflict fitting.

Statistical Analysis | Warning Area 1 | Warning Area 2 | Upstream Transition Area | Buffer Area | Activity Area |
---|---|---|---|---|---|

Mean (km/h) | 90.631 | 68.345 | 60.271 | 36.765 | 60.367 |

Standard error | 1.274 | 0.946 | 0.690 | 0.460 | 0.940 |

Standard deviation | 21.9 | 16.3 | 12.1 | 8.8 | 16.4 |

Sample variance | 487.63 | 274.68 | 149.76 | 77.51 | 299.13 |

Sample capacity | 290 | 320 | 328 | 380 | 352 |

Area | Mean (s) | Standard Deviation | $\mathit{k}$ | Sample Capacity | ${\mathit{\chi}}^{2}$ | Result |
---|---|---|---|---|---|---|

Warning area | 3.51 | 2.14 | 1.06 | 352 | 29 | Conform |

Upstream transition area | 4.13 | 2.96 | 1.59 | 302 | 37 | Conform |

Buffer area | 3.82 | 2.27 | 1.25 | 289 | 24 | Conform |

Activity area | 3.03 | 1.58 | 1.38 | 335 | 22 | Conform |

Traffic Conflict | $\mathbf{Coefficient}\text{}\mathit{\beta}$ | Standard Deviation | $\mathit{z}$ | $\mathit{p}$ | 95% Confidence Interval | |
---|---|---|---|---|---|---|

Traffic flow $\left({x}_{q}\right)$ | 0.00534 | 0.0006792 | 2.31 | 0.025 | 0.002667 | 0.002929 |

Large vehicles penetration rate (${x}_{b}$) | 4.889321 | 1.4588371 | 1.03 | 0.033 | 3.007575 | 6.061398 |

Speed difference (${x}_{v}$) | 0.019611 | 0.0303476 | 2.51 | 0.028 | 0.438721 | 1.156973 |

Time headway (${h}_{t}$) | −0.58312 | 0.6439872 | −1.41 | 0.000 | −4.567334 | −1.356922 |

Undetermined constant | 2.81207 | 1.3790561 | 3.23 | 0.001 | 1.757953 | 7.163752 |

$\alpha $ | 0.28673 | 0.0169789 | - | - | 0.004139 | 0.103357 |

Variable | $\mathbf{Traffic}\text{}\mathbf{Flow}\text{}{\mathit{x}}_{\mathit{q}}\text{}(\mathbf{pcu}/30\text{}\mathbf{min})$ | $\mathbf{Large}\text{}\mathbf{Vehicles}\text{}\mathbf{Penetration}\text{}\mathbf{Rate}\text{}{\mathit{x}}_{\mathit{b}}(\%)$ | $\mathbf{Speed}\text{}\mathbf{Difference}\text{}{\mathit{x}}_{\mathit{v}}\text{}(\mathbf{m}/\mathbf{s})$ | $\mathbf{Time}\text{}\mathbf{headway}\text{}{\mathit{h}}_{\mathit{t}}\text{}\left(\mathbf{s}\right)$ |
---|---|---|---|---|

Warning area | 156 | 19.8 | 9.82 | 4.02 |

upstream transition area | 108 | 26.3 | 5.36 | 3.21 |

Conflict Location | Actual Value | Predicted Value | MAPE |
---|---|---|---|

Warning area | 8.00 | 7.13 | 10.8% |

upstream transition area | 7.00 | 6.65 | 5.0% |

© 2020 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

**MDPI and ACS Style**

Ge, H.; Huang, M.; Lu, Y.; Yang, Y.
Study on Traffic Conflict Prediction Model of Closed Lanes on the Outside of Expressway. *Symmetry* **2020**, *12*, 926.
https://doi.org/10.3390/sym12060926

**AMA Style**

Ge H, Huang M, Lu Y, Yang Y.
Study on Traffic Conflict Prediction Model of Closed Lanes on the Outside of Expressway. *Symmetry*. 2020; 12(6):926.
https://doi.org/10.3390/sym12060926

**Chicago/Turabian Style**

Ge, Huimin, Mingyue Huang, Ying Lu, and Yousen Yang.
2020. "Study on Traffic Conflict Prediction Model of Closed Lanes on the Outside of Expressway" *Symmetry* 12, no. 6: 926.
https://doi.org/10.3390/sym12060926