Applying Machine Learning to Develop Lane Control Principles for Mixed Traffic
| Autor: | Tien-Pen Hsu, Taiyi Zhang, Ku Lin Wen |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
motorcycle prohibition policy
Computer science Geography Planning and Development Control (management) Decision tree TJ807-830 010501 environmental sciences Management Monitoring Policy and Law Space (commercial competition) TD194-195 01 natural sciences Renewable energy sources Transport engineering 0502 economics and business GE1-350 0105 earth and related environmental sciences 050210 logistics & transportation Environmental effects of industries and plants Renewable Energy Sustainability and the Environment 05 social sciences Random forest Environmental sciences machine learning lane control rule accident prediction before-and-after analysis Control methods |
| Zdroj: | Sustainability, Vol 13, Iss 7656, p 7656 (2021) Sustainability Volume 13 Issue 14 |
| ISSN: | 2071-1050 |
| DOI: | 10.3390/su13147656 |
| Popis: | The mixed traffic environment often has high accident rates. Therefore, many motorcycle-related traffic improvements or control methods are employed in countries with mixed traffic, including slow-traffic lanes, motorcycle two-stage left turn areas, and motorcycle waiting zones. In Taiwan, motorcycles can ride in only the two outermost lanes, including the curb lane and a mixed traffic lane. This study analyzed the new motorcycle-riding space control policy on 27 major arterial roads containing 248 road segments in Taipei by analyzing before-and-after accident data from the years 2012–2018. In this study, the equivalent-property-damage-only (EPDO) method was used to evaluate the severity of crashes before and after the cancelation of the third lane prohibition of motorcycles (TLPM) policy. After EPDO analysis, the random forest analysis method was used to screen the crucial factors in accidents for specific road segments. Finally, a classification and regression tree (CART) was created to predict the accident improvement effects of the road segments with discontinued TLPM in different situations. Furthermore, to provide practical applications, this study integrated the CART results and the needs of traffic authorities to determine four rules for canceling TLPM. In the future, on the accident-prone road segment with TLPM, the inspection of the four rules can provide the authority to decide whether to cancel TLPM to improve the accident or not. |
| Databáze: | OpenAIRE |
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