Exploring Travel Time Distribution and Variability Patterns Using Probe Vehicle Data: Case Study in Beijing
Exploring travel time distribution and variability patterns is essential for reliable route choices and sophisticated traffic management and control. State-of-the-art studies tend to treat different types of roads equally, which fails to provide more detailed analysis of travel time characteristics...
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| Format: | Article |
| Language: | English |
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Wiley
2018-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2018/3747632 |
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| author | Peng Chen Rui Tong Guangquan Lu Yunpeng Wang |
| author_facet | Peng Chen Rui Tong Guangquan Lu Yunpeng Wang |
| author_sort | Peng Chen |
| collection | DOAJ |
| description | Exploring travel time distribution and variability patterns is essential for reliable route choices and sophisticated traffic management and control. State-of-the-art studies tend to treat different types of roads equally, which fails to provide more detailed analysis of travel time characteristics for each specific road type. In this study, based on a vast amount of probe vehicle data, 200 links inside the Third Ring Road of Beijing, China, were investigated. Four types of roads were covered including urban expressways, auxiliary roads of urban expressways, major roads, and secondary roads. The day-of-week distributions of unit distance travel time were first analyzed. Kolmogorov-Smirnov test, Anderson-Darling test, and chi-squared test were employed to test the goodness-of-fit of different distributions and the results showed lognormal distribution was best-fitted for different time periods and road types compared with normal, gamma, and Weibull distribution. In addition, four reliability measures, that is, unit distance travel time, coefficient of variation, buffer time index, and punctuality rate, were used to explore the day-of-week travel time variability patterns. The results indicated that urban expressways, auxiliary roads of urban expressways, and major roads have regular and distinct morning and afternoon peaks on weekdays. It is noteworthy that in daytime the travel times on auxiliary roads of urban expressways and major roads share similar variability patterns and appear relatively stable and reliable, while urban expressways have most reliable travel times at night. The results of analysis help enable a better understanding of the volatile travel time characteristics of each road type in urban network. |
| format | Article |
| id | doaj-art-a9ade8086935403b9bdbee393df68afb |
| institution | Kabale University |
| issn | 0197-6729 2042-3195 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-a9ade8086935403b9bdbee393df68afb2025-08-20T03:39:10ZengWileyJournal of Advanced Transportation0197-67292042-31952018-01-01201810.1155/2018/37476323747632Exploring Travel Time Distribution and Variability Patterns Using Probe Vehicle Data: Case Study in BeijingPeng Chen0Rui Tong1Guangquan Lu2Yunpeng Wang3Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control, School of Transportation Science and Engineering, Beihang University, Xue Yuan Road No. 37, Hai Dian District, Beijing 100191, ChinaBeijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control, School of Transportation Science and Engineering, Beihang University, Xue Yuan Road No. 37, Hai Dian District, Beijing 100191, ChinaBeijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control, School of Transportation Science and Engineering, Beihang University, Xue Yuan Road No. 37, Hai Dian District, Beijing 100191, ChinaBeijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control, School of Transportation Science and Engineering, Beihang University, Xue Yuan Road No. 37, Hai Dian District, Beijing 100191, ChinaExploring travel time distribution and variability patterns is essential for reliable route choices and sophisticated traffic management and control. State-of-the-art studies tend to treat different types of roads equally, which fails to provide more detailed analysis of travel time characteristics for each specific road type. In this study, based on a vast amount of probe vehicle data, 200 links inside the Third Ring Road of Beijing, China, were investigated. Four types of roads were covered including urban expressways, auxiliary roads of urban expressways, major roads, and secondary roads. The day-of-week distributions of unit distance travel time were first analyzed. Kolmogorov-Smirnov test, Anderson-Darling test, and chi-squared test were employed to test the goodness-of-fit of different distributions and the results showed lognormal distribution was best-fitted for different time periods and road types compared with normal, gamma, and Weibull distribution. In addition, four reliability measures, that is, unit distance travel time, coefficient of variation, buffer time index, and punctuality rate, were used to explore the day-of-week travel time variability patterns. The results indicated that urban expressways, auxiliary roads of urban expressways, and major roads have regular and distinct morning and afternoon peaks on weekdays. It is noteworthy that in daytime the travel times on auxiliary roads of urban expressways and major roads share similar variability patterns and appear relatively stable and reliable, while urban expressways have most reliable travel times at night. The results of analysis help enable a better understanding of the volatile travel time characteristics of each road type in urban network.http://dx.doi.org/10.1155/2018/3747632 |
| spellingShingle | Peng Chen Rui Tong Guangquan Lu Yunpeng Wang Exploring Travel Time Distribution and Variability Patterns Using Probe Vehicle Data: Case Study in Beijing Journal of Advanced Transportation |
| title | Exploring Travel Time Distribution and Variability Patterns Using Probe Vehicle Data: Case Study in Beijing |
| title_full | Exploring Travel Time Distribution and Variability Patterns Using Probe Vehicle Data: Case Study in Beijing |
| title_fullStr | Exploring Travel Time Distribution and Variability Patterns Using Probe Vehicle Data: Case Study in Beijing |
| title_full_unstemmed | Exploring Travel Time Distribution and Variability Patterns Using Probe Vehicle Data: Case Study in Beijing |
| title_short | Exploring Travel Time Distribution and Variability Patterns Using Probe Vehicle Data: Case Study in Beijing |
| title_sort | exploring travel time distribution and variability patterns using probe vehicle data case study in beijing |
| url | http://dx.doi.org/10.1155/2018/3747632 |
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