Gap acceptance for left turns from the major road at unsignalized intersections
This paper attempts to identify factors that may influence the gap acceptance behavior of drivers who turn left from the major road at unsignalized intersections. Drivers’ accepted and rejected gaps as well as their age and gender were collected at six unsignalized intersections with both two and fo...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Vilnius Gediminas Technical University
2017-07-01
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| Series: | Transport |
| Subjects: | |
| Online Access: | https://journals.vgtu.lt/index.php/Transport/article/view/856 |
| _version_ | 1818876957951000576 |
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| author | Hongmei Zhou John N. Ivan Per E. Gårder Nalini Ravishanker |
| author_facet | Hongmei Zhou John N. Ivan Per E. Gårder Nalini Ravishanker |
| author_sort | Hongmei Zhou |
| collection | DOAJ |
| description | This paper attempts to identify factors that may influence the gap acceptance behavior of drivers who turn left from the major road at unsignalized intersections. Drivers’ accepted and rejected gaps as well as their age and gender were collected at six unsignalized intersections with both two and four lanes on the major road, with and without the presence of a Left-Turn Lane (LTL), and with both high and low Speed Limits (SLs). Whether or not a driver accepts a given gap was considered as a binary decision and correlated logit models were used to estimate the probability of accepting a gap. Models with different factors were tested and the best model was selected by the quasi-likelihood information criterion. The gap duration, the number of rejected gaps, the mean and total time interval of the rejected gaps and the gender of the driver were all significant in explaining the variation of the gap acceptance probability, whereas the number of lanes of the major road, the presence of LTL, the SL and the driver’s age category were not. Gap acceptance probability functions were determined based on the best model, including both the factors of the number of rejected gaps and the mean time interval of the rejected gaps. As the values of these two factors increase, the probability of accepting a given gap rises up. The developed model can be further applied in practice to improve the analysis of traffic operations and capacity at unsignalized intersections.
First published online: 10 Jul 2014 |
| first_indexed | 2024-12-19T13:50:39Z |
| format | Article |
| id | doaj.art-afbae5e9b92d41418c6a2e5406d910e7 |
| institution | Directory Open Access Journal |
| issn | 1648-4142 1648-3480 |
| language | English |
| last_indexed | 2024-12-19T13:50:39Z |
| publishDate | 2017-07-01 |
| publisher | Vilnius Gediminas Technical University |
| record_format | Article |
| series | Transport |
| spelling | doaj.art-afbae5e9b92d41418c6a2e5406d910e72022-12-21T20:18:45ZengVilnius Gediminas Technical UniversityTransport1648-41421648-34802017-07-0132310.3846/16484142.2014.933445Gap acceptance for left turns from the major road at unsignalized intersectionsHongmei Zhou0John N. Ivan1Per E. Gårder2Nalini Ravishanker3College of Transportation & Logistics, Dalian University of Technology, ChinaDept of Civil and Environmental Engineering, University of Connecticut, United StatesDept of Civil and Environmental Engineering, University of Maine, United StatesDept of Statistics, University of Connecticut, United StatesThis paper attempts to identify factors that may influence the gap acceptance behavior of drivers who turn left from the major road at unsignalized intersections. Drivers’ accepted and rejected gaps as well as their age and gender were collected at six unsignalized intersections with both two and four lanes on the major road, with and without the presence of a Left-Turn Lane (LTL), and with both high and low Speed Limits (SLs). Whether or not a driver accepts a given gap was considered as a binary decision and correlated logit models were used to estimate the probability of accepting a gap. Models with different factors were tested and the best model was selected by the quasi-likelihood information criterion. The gap duration, the number of rejected gaps, the mean and total time interval of the rejected gaps and the gender of the driver were all significant in explaining the variation of the gap acceptance probability, whereas the number of lanes of the major road, the presence of LTL, the SL and the driver’s age category were not. Gap acceptance probability functions were determined based on the best model, including both the factors of the number of rejected gaps and the mean time interval of the rejected gaps. As the values of these two factors increase, the probability of accepting a given gap rises up. The developed model can be further applied in practice to improve the analysis of traffic operations and capacity at unsignalized intersections. First published online: 10 Jul 2014https://journals.vgtu.lt/index.php/Transport/article/view/856unsignalized intersectionleft turn; gap acceptancecorrelated logit modeltraffic operations |
| spellingShingle | Hongmei Zhou John N. Ivan Per E. Gårder Nalini Ravishanker Gap acceptance for left turns from the major road at unsignalized intersections Transport unsignalized intersection left turn; gap acceptance correlated logit model traffic operations |
| title | Gap acceptance for left turns from the major road at unsignalized intersections |
| title_full | Gap acceptance for left turns from the major road at unsignalized intersections |
| title_fullStr | Gap acceptance for left turns from the major road at unsignalized intersections |
| title_full_unstemmed | Gap acceptance for left turns from the major road at unsignalized intersections |
| title_short | Gap acceptance for left turns from the major road at unsignalized intersections |
| title_sort | gap acceptance for left turns from the major road at unsignalized intersections |
| topic | unsignalized intersection left turn; gap acceptance correlated logit model traffic operations |
| url | https://journals.vgtu.lt/index.php/Transport/article/view/856 |
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