Research on Short-term Prediction Model of Freeway Operation Situation
Based on the traffic flow data and accident data of Beijing-Tianjin-Tanggu freeway, the security situation short-term prediction model was established in the paper. Firstly, we established the risk prediction database, and developed the pre-analysis software of basic data; secondly, the traffic flow...
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| Format: | Article |
| Language: | English |
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EDP Sciences
2017-01-01
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| Series: | MATEC Web of Conferences |
| Online Access: | https://doi.org/10.1051/matecconf/201712402004 |
| _version_ | 1819174005236563968 |
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| author | Zhang Xiaodan |
| author_facet | Zhang Xiaodan |
| author_sort | Zhang Xiaodan |
| collection | DOAJ |
| description | Based on the traffic flow data and accident data of Beijing-Tianjin-Tanggu freeway, the security situation short-term prediction model was established in the paper. Firstly, we established the risk prediction database, and developed the pre-analysis software of basic data; secondly, the traffic flow data between 10 to 15 minutes prior to the time of accident were aggregated at 5-minute level, and the volume, speed, occupancy as well as their statistical parameters were selected; finally, based on the correlation analysis results of parameter s, the multi-parameters Logistic regression model was established. The results indicate, the change of traffic flow parameters and their statistics can effectively predict the possibility of accident, in which the average value of speed of small car, the standard deviation of volume of large car and the average value of volume difference between large car and small car at 5-minute level have a significant impact on the risk of accident. |
| first_indexed | 2024-12-22T20:32:05Z |
| format | Article |
| id | doaj.art-618fedb59b474d1ab60895a685e8ed82 |
| institution | Directory Open Access Journal |
| issn | 2261-236X |
| language | English |
| last_indexed | 2024-12-22T20:32:05Z |
| publishDate | 2017-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | MATEC Web of Conferences |
| spelling | doaj.art-618fedb59b474d1ab60895a685e8ed822022-12-21T18:13:34ZengEDP SciencesMATEC Web of Conferences2261-236X2017-01-011240200410.1051/matecconf/201712402004matecconf_ictte2017_02004Research on Short-term Prediction Model of Freeway Operation SituationZhang XiaodanBased on the traffic flow data and accident data of Beijing-Tianjin-Tanggu freeway, the security situation short-term prediction model was established in the paper. Firstly, we established the risk prediction database, and developed the pre-analysis software of basic data; secondly, the traffic flow data between 10 to 15 minutes prior to the time of accident were aggregated at 5-minute level, and the volume, speed, occupancy as well as their statistical parameters were selected; finally, based on the correlation analysis results of parameter s, the multi-parameters Logistic regression model was established. The results indicate, the change of traffic flow parameters and their statistics can effectively predict the possibility of accident, in which the average value of speed of small car, the standard deviation of volume of large car and the average value of volume difference between large car and small car at 5-minute level have a significant impact on the risk of accident.https://doi.org/10.1051/matecconf/201712402004 |
| spellingShingle | Zhang Xiaodan Research on Short-term Prediction Model of Freeway Operation Situation MATEC Web of Conferences |
| title | Research on Short-term Prediction Model of Freeway Operation Situation |
| title_full | Research on Short-term Prediction Model of Freeway Operation Situation |
| title_fullStr | Research on Short-term Prediction Model of Freeway Operation Situation |
| title_full_unstemmed | Research on Short-term Prediction Model of Freeway Operation Situation |
| title_short | Research on Short-term Prediction Model of Freeway Operation Situation |
| title_sort | research on short term prediction model of freeway operation situation |
| url | https://doi.org/10.1051/matecconf/201712402004 |
| work_keys_str_mv | AT zhangxiaodan researchonshorttermpredictionmodeloffreewayoperationsituation |