Using mobile phone signaling to analyze the impact of driving restriction on travel modes

To analyze the quantitative impact of urban car tail number restriction policies on residents' travel modes, a method sharing rate evaluation system based on mobile signaling data is proposed for the implementation of car tail number restriction policies. Firstly, based on the judgment conditions of parking time, speed mutation degree and time window, the identification algorithm of travel start and end points and sub chain segmentation points is optimized; then, after five groups of cross validation, the expert survey method and Closed-Random Forest Classifier are used to determine the optimal feature set and feature weight of the trip sharing rate identification covering nine indexes, such as the maximum travel speed and the repetition rate of the rail transit network. Finally, taking the Gaussian function as the kernel function, the multi classification Support Vector Machine model of the trip sharing rate is established, and the super parameter optimization algorithm of the kernel function is optimized. The results show that the classification accuracy<i>P<sub>c</sub></i>, recall rate<i>R<sub>c</sub></i>, <i>F</i><sub>1</sub>score, and ACC value were 0.976, 0.983, 0.979, and 0.981, respectively. The ablation experiment found that the expert survey method contributed 5.4 percentage points more to the algorithm improvement than the closed random forest algorithm. The trip sharing rates of walking, vehicle and public bus in the central urban area of Chongqing in 2021 are reduced by 0.3%, 0.4% and 0.3% respectively compared with those before the restriction. The restriction of key channels of bridge and tunnel in mountain city can effectively inhibit vehicle driving, and the rail transit trip sharing rate is increased by 1.3%, which has become the main alternative for restricted citizens. However, under the condition of no-purchase restriction, the inhibition effect of restriction on vehicle driving can only continue for 12 to 15 months, so it is necessary to introduce measures to strengthen restrictions.

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Publication Details

Published
2025-06-16
DOI
https://doi.org/10.1117/12.3059269
Primary Topic
Transportation Planning and Optimization
Type
article
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article

Using mobile phone signaling to analyze the impact of driving restriction on travel modes

Xiaoyang Zhang, Lei Zhang, Tao Xu, Wenjing Zhou et al.
Transportation Planning and Optimization
article

Using mobile phone signaling to analyze the impact of driving restriction on travel modes

Xiaoyang Zhang, Lei Zhang, Tao Xu, Wenjing Zhou, Longchun Cheng
article en

Abstract

To analyze the quantitative impact of urban car tail number restriction policies on residents' travel modes, a method sharing rate evaluation system based on mobile signaling data is proposed for the implementation of car tail number restriction policies. Firstly, based on the judgment conditions of parking time, speed mutation degree and time window, the identification algorithm of travel start and end points and sub chain segmentation points is optimized; then, after five groups of cross validation, the expert survey method and Closed-Random Forest Classifier are used to determine the optimal feature set and feature weight of the trip sharing rate identification covering nine indexes, such as the maximum travel speed and the repetition rate of the rail transit network. Finally, taking the Gaussian function as the kernel function, the multi classification Support Vector Machine model of the trip sharing rate is established, and the super parameter optimization algorithm of the kernel function is optimized. The results show that the classification accuracy<i>P<sub>c</sub></i>, recall rate<i>R<sub>c</sub></i>, <i>F</i><sub>1</sub>score, and ACC value were 0.976, 0.983, 0.979, and 0.981, respectively. The ablation experiment found that the expert survey method contributed 5.4 percentage points more to the algorithm improvement than the closed random forest algorithm. The trip sharing rates of walking, vehicle and public bus in the central urban area of Chongqing in 2021 are reduced by 0.3%, 0.4% and 0.3% respectively compared with those before the restriction. The restriction of key channels of bridge and tunnel in mountain city can effectively inhibit vehicle driving, and the rail transit trip sharing rate is increased by 1.3%, which has become the main alternative for restricted citizens. However, under the condition of no-purchase restriction, the inhibition effect of restriction on vehicle driving can only continue for 12 to 15 months, so it is necessary to introduce measures to strengthen restrictions.

China Design Group (China) (CN), China Coal Technology and Engineering Group Corp (China) (CN), Chongqing Jiaotong University (CN)
Reduced inequalities
Openalex Percentile: Top 85%
Transportation Planning and Optimization
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