Logit-Based Analysis of Drivers’ Crossing Behavior at Unsignalized Intersections in China
Objective: This study aims to investigate the crossing behavior of straight-moving drivers when they encounter other straight-moving drivers at unsignalized intersections in China. Background: In China, when two vehicle drivers encounter at an unsignalized intersection, neither driver completely sto...
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Veröffentlicht in: | Human factors 2015-11, Vol.57 (7), p.1101-1114 |
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creator | Lu, Guangquan Liu, Miaomiao Wang, Yunpeng Wan, Huasen Tian, Daxin |
description | Objective:
This study aims to investigate the crossing behavior of straight-moving drivers when they encounter other straight-moving drivers at unsignalized intersections in China.
Background:
In China, when two vehicle drivers encounter at an unsignalized intersection, neither driver completely stops his or her vehicle in most cases. Instead, one driver gradually approaches the intersection and dynamically decides to either yield or preempt by gaming with the other vehicle. This process increases the probability of accidents.
Method:
A total of 305 crossing cases were collected at an unsignalized intersection in Kunming City. Motion parameters were extracted from the video detection program designed by our research group. Based on a logistic regression method, we analyzed decision making moment of straight-moving drivers under crossing conditions, established crossing behavior models, and identified the main factors that affected drivers’ decisions. In all, 68 cases observed at a separate intersection were used to validate the established models.
Results:
For crossing processes at unsignalized intersections in China, straight-moving drivers from the right side completed preemptive/yielding decisions at 1.3 s before reaching the crossing point. However, the majority of straight-moving drivers from the left side completed decisions at 1.1 s before reaching the crossing point. The most important parameter that influenced the drivers’ decisions was the difference between the speeds of the two vehicles.
Conclusion:
An effective method for preventing traffic conflict between two straight-moving drivers is to control the speeds of the vehicles before they enter the intersection.
Application:
This study explores crossing behavior of straight-moving drivers and provides significant insights for controlling driver behavior. |
doi_str_mv | 10.1177/0018720815592097 |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_1770380579</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sage_id>10.1177_0018720815592097</sage_id><sourcerecordid>1722424039</sourcerecordid><originalsourceid>FETCH-LOGICAL-c446t-7484ec46e0b7f1aad0519422f0703057a540174717a6f6d14ffc31f2a39ba89f3</originalsourceid><addsrcrecordid>eNqNkb1OwzAURi0EoqWwMyFLLCyBex0nTsa2_FWqxEInhshN7NZVmxQ7rVQmXoPX40lwaEEICYnJwz3fufL9CDlFuEQU4goAE8EgwShKGaRij7Qx4iJIMMF90m7GQTNvkSPnZgAQp2F0SFosxhBiIdrkaVhNTB30pFMF7ZZyvnHG0UrTa2vWyrr31zfat5VzppzQnprKtakslTUdlc5MPG9efHBQ1p5VeW2q0lFT0v7UlPKYHGg5d-pk93bI6PbmsX8fDB_uBv3uMMg5j-tA8ISrnMcKxkKjlAVEmHLGNAgIIRIy4oCCCxQy1nGBXOs8RM1kmI5lkuqwQy623qWtnlfK1dnCuFzN57JU1cpl_lIQJt6U_gNljDMOYYOe_0Jn1cr6H39SXpkygZ6CLZU3R7JKZ0trFtJuMoSs6Sj73ZGPnO3Eq_FCFd-Br1I8EGwBJyfqx9a_hB_1nJd4</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1727709271</pqid></control><display><type>article</type><title>Logit-Based Analysis of Drivers’ Crossing Behavior at Unsignalized Intersections in China</title><source>MEDLINE</source><source>SAGE Complete A-Z List</source><creator>Lu, Guangquan ; Liu, Miaomiao ; Wang, Yunpeng ; Wan, Huasen ; Tian, Daxin</creator><creatorcontrib>Lu, Guangquan ; Liu, Miaomiao ; Wang, Yunpeng ; Wan, Huasen ; Tian, Daxin</creatorcontrib><description>Objective:
This study aims to investigate the crossing behavior of straight-moving drivers when they encounter other straight-moving drivers at unsignalized intersections in China.
Background:
In China, when two vehicle drivers encounter at an unsignalized intersection, neither driver completely stops his or her vehicle in most cases. Instead, one driver gradually approaches the intersection and dynamically decides to either yield or preempt by gaming with the other vehicle. This process increases the probability of accidents.
Method:
A total of 305 crossing cases were collected at an unsignalized intersection in Kunming City. Motion parameters were extracted from the video detection program designed by our research group. Based on a logistic regression method, we analyzed decision making moment of straight-moving drivers under crossing conditions, established crossing behavior models, and identified the main factors that affected drivers’ decisions. In all, 68 cases observed at a separate intersection were used to validate the established models.
Results:
For crossing processes at unsignalized intersections in China, straight-moving drivers from the right side completed preemptive/yielding decisions at 1.3 s before reaching the crossing point. However, the majority of straight-moving drivers from the left side completed decisions at 1.1 s before reaching the crossing point. The most important parameter that influenced the drivers’ decisions was the difference between the speeds of the two vehicles.
Conclusion:
An effective method for preventing traffic conflict between two straight-moving drivers is to control the speeds of the vehicles before they enter the intersection.
Application:
This study explores crossing behavior of straight-moving drivers and provides significant insights for controlling driver behavior.</description><identifier>ISSN: 0018-7208</identifier><identifier>EISSN: 1547-8181</identifier><identifier>DOI: 10.1177/0018720815592097</identifier><identifier>PMID: 26130677</identifier><identifier>CODEN: HUFAA6</identifier><language>eng</language><publisher>Los Angeles, CA: SAGE Publications</publisher><subject>Accidents, Traffic ; Automobile drivers ; Automobile Driving - statistics & numerical data ; Behavior ; China ; China - epidemiology ; Decision Making ; Encounters ; Human factors ; Humans ; Intersections ; Logistic Models ; Mathematical models ; Models, Theoretical ; Preempting ; Regression ; Regression analysis ; Reproducibility of Results ; Space life sciences ; Vehicles ; Velocity</subject><ispartof>Human factors, 2015-11, Vol.57 (7), p.1101-1114</ispartof><rights>2015, Human Factors and Ergonomics Society</rights><rights>2015, Human Factors and Ergonomics Society.</rights><rights>Copyright Human Factors and Ergonomics Society Nov 2015</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c446t-7484ec46e0b7f1aad0519422f0703057a540174717a6f6d14ffc31f2a39ba89f3</citedby><cites>FETCH-LOGICAL-c446t-7484ec46e0b7f1aad0519422f0703057a540174717a6f6d14ffc31f2a39ba89f3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://journals.sagepub.com/doi/pdf/10.1177/0018720815592097$$EPDF$$P50$$Gsage$$H</linktopdf><linktohtml>$$Uhttps://journals.sagepub.com/doi/10.1177/0018720815592097$$EHTML$$P50$$Gsage$$H</linktohtml><link.rule.ids>314,780,784,21819,27924,27925,43621,43622</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/26130677$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Lu, Guangquan</creatorcontrib><creatorcontrib>Liu, Miaomiao</creatorcontrib><creatorcontrib>Wang, Yunpeng</creatorcontrib><creatorcontrib>Wan, Huasen</creatorcontrib><creatorcontrib>Tian, Daxin</creatorcontrib><title>Logit-Based Analysis of Drivers’ Crossing Behavior at Unsignalized Intersections in China</title><title>Human factors</title><addtitle>Hum Factors</addtitle><description>Objective:
This study aims to investigate the crossing behavior of straight-moving drivers when they encounter other straight-moving drivers at unsignalized intersections in China.
Background:
In China, when two vehicle drivers encounter at an unsignalized intersection, neither driver completely stops his or her vehicle in most cases. Instead, one driver gradually approaches the intersection and dynamically decides to either yield or preempt by gaming with the other vehicle. This process increases the probability of accidents.
Method:
A total of 305 crossing cases were collected at an unsignalized intersection in Kunming City. Motion parameters were extracted from the video detection program designed by our research group. Based on a logistic regression method, we analyzed decision making moment of straight-moving drivers under crossing conditions, established crossing behavior models, and identified the main factors that affected drivers’ decisions. In all, 68 cases observed at a separate intersection were used to validate the established models.
Results:
For crossing processes at unsignalized intersections in China, straight-moving drivers from the right side completed preemptive/yielding decisions at 1.3 s before reaching the crossing point. However, the majority of straight-moving drivers from the left side completed decisions at 1.1 s before reaching the crossing point. The most important parameter that influenced the drivers’ decisions was the difference between the speeds of the two vehicles.
Conclusion:
An effective method for preventing traffic conflict between two straight-moving drivers is to control the speeds of the vehicles before they enter the intersection.
Application:
This study explores crossing behavior of straight-moving drivers and provides significant insights for controlling driver behavior.</description><subject>Accidents, Traffic</subject><subject>Automobile drivers</subject><subject>Automobile Driving - statistics & numerical data</subject><subject>Behavior</subject><subject>China</subject><subject>China - epidemiology</subject><subject>Decision Making</subject><subject>Encounters</subject><subject>Human factors</subject><subject>Humans</subject><subject>Intersections</subject><subject>Logistic Models</subject><subject>Mathematical models</subject><subject>Models, Theoretical</subject><subject>Preempting</subject><subject>Regression</subject><subject>Regression analysis</subject><subject>Reproducibility of Results</subject><subject>Space life sciences</subject><subject>Vehicles</subject><subject>Velocity</subject><issn>0018-7208</issn><issn>1547-8181</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqNkb1OwzAURi0EoqWwMyFLLCyBex0nTsa2_FWqxEInhshN7NZVmxQ7rVQmXoPX40lwaEEICYnJwz3fufL9CDlFuEQU4goAE8EgwShKGaRij7Qx4iJIMMF90m7GQTNvkSPnZgAQp2F0SFosxhBiIdrkaVhNTB30pFMF7ZZyvnHG0UrTa2vWyrr31zfat5VzppzQnprKtakslTUdlc5MPG9efHBQ1p5VeW2q0lFT0v7UlPKYHGg5d-pk93bI6PbmsX8fDB_uBv3uMMg5j-tA8ISrnMcKxkKjlAVEmHLGNAgIIRIy4oCCCxQy1nGBXOs8RM1kmI5lkuqwQy623qWtnlfK1dnCuFzN57JU1cpl_lIQJt6U_gNljDMOYYOe_0Jn1cr6H39SXpkygZ6CLZU3R7JKZ0trFtJuMoSs6Sj73ZGPnO3Eq_FCFd-Br1I8EGwBJyfqx9a_hB_1nJd4</recordid><startdate>20151101</startdate><enddate>20151101</enddate><creator>Lu, Guangquan</creator><creator>Liu, Miaomiao</creator><creator>Wang, Yunpeng</creator><creator>Wan, Huasen</creator><creator>Tian, Daxin</creator><general>SAGE Publications</general><general>Human Factors and Ergonomics Society</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QF</scope><scope>7QQ</scope><scope>7SC</scope><scope>7SE</scope><scope>7SP</scope><scope>7SR</scope><scope>7T2</scope><scope>7TA</scope><scope>7TB</scope><scope>7TK</scope><scope>7U5</scope><scope>8BQ</scope><scope>8FD</scope><scope>C1K</scope><scope>F28</scope><scope>FR3</scope><scope>H8D</scope><scope>H8G</scope><scope>JG9</scope><scope>JQ2</scope><scope>K9.</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>7X8</scope></search><sort><creationdate>20151101</creationdate><title>Logit-Based Analysis of Drivers’ Crossing Behavior at Unsignalized Intersections in China</title><author>Lu, Guangquan ; Liu, Miaomiao ; Wang, Yunpeng ; Wan, Huasen ; Tian, Daxin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c446t-7484ec46e0b7f1aad0519422f0703057a540174717a6f6d14ffc31f2a39ba89f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Accidents, Traffic</topic><topic>Automobile drivers</topic><topic>Automobile Driving - statistics & numerical data</topic><topic>Behavior</topic><topic>China</topic><topic>China - epidemiology</topic><topic>Decision Making</topic><topic>Encounters</topic><topic>Human factors</topic><topic>Humans</topic><topic>Intersections</topic><topic>Logistic Models</topic><topic>Mathematical models</topic><topic>Models, Theoretical</topic><topic>Preempting</topic><topic>Regression</topic><topic>Regression analysis</topic><topic>Reproducibility of Results</topic><topic>Space life sciences</topic><topic>Vehicles</topic><topic>Velocity</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lu, Guangquan</creatorcontrib><creatorcontrib>Liu, Miaomiao</creatorcontrib><creatorcontrib>Wang, Yunpeng</creatorcontrib><creatorcontrib>Wan, Huasen</creatorcontrib><creatorcontrib>Tian, Daxin</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Aluminium Industry Abstracts</collection><collection>Ceramic Abstracts</collection><collection>Computer and Information Systems Abstracts</collection><collection>Corrosion Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>Health and Safety Science Abstracts (Full archive)</collection><collection>Materials Business File</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Neurosciences Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Copper Technical Reference Library</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>MEDLINE - Academic</collection><jtitle>Human factors</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lu, Guangquan</au><au>Liu, Miaomiao</au><au>Wang, Yunpeng</au><au>Wan, Huasen</au><au>Tian, Daxin</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Logit-Based Analysis of Drivers’ Crossing Behavior at Unsignalized Intersections in China</atitle><jtitle>Human factors</jtitle><addtitle>Hum Factors</addtitle><date>2015-11-01</date><risdate>2015</risdate><volume>57</volume><issue>7</issue><spage>1101</spage><epage>1114</epage><pages>1101-1114</pages><issn>0018-7208</issn><eissn>1547-8181</eissn><coden>HUFAA6</coden><abstract>Objective:
This study aims to investigate the crossing behavior of straight-moving drivers when they encounter other straight-moving drivers at unsignalized intersections in China.
Background:
In China, when two vehicle drivers encounter at an unsignalized intersection, neither driver completely stops his or her vehicle in most cases. Instead, one driver gradually approaches the intersection and dynamically decides to either yield or preempt by gaming with the other vehicle. This process increases the probability of accidents.
Method:
A total of 305 crossing cases were collected at an unsignalized intersection in Kunming City. Motion parameters were extracted from the video detection program designed by our research group. Based on a logistic regression method, we analyzed decision making moment of straight-moving drivers under crossing conditions, established crossing behavior models, and identified the main factors that affected drivers’ decisions. In all, 68 cases observed at a separate intersection were used to validate the established models.
Results:
For crossing processes at unsignalized intersections in China, straight-moving drivers from the right side completed preemptive/yielding decisions at 1.3 s before reaching the crossing point. However, the majority of straight-moving drivers from the left side completed decisions at 1.1 s before reaching the crossing point. The most important parameter that influenced the drivers’ decisions was the difference between the speeds of the two vehicles.
Conclusion:
An effective method for preventing traffic conflict between two straight-moving drivers is to control the speeds of the vehicles before they enter the intersection.
Application:
This study explores crossing behavior of straight-moving drivers and provides significant insights for controlling driver behavior.</abstract><cop>Los Angeles, CA</cop><pub>SAGE Publications</pub><pmid>26130677</pmid><doi>10.1177/0018720815592097</doi><tpages>14</tpages></addata></record> |
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language | eng |
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source | MEDLINE; SAGE Complete A-Z List |
subjects | Accidents, Traffic Automobile drivers Automobile Driving - statistics & numerical data Behavior China China - epidemiology Decision Making Encounters Human factors Humans Intersections Logistic Models Mathematical models Models, Theoretical Preempting Regression Regression analysis Reproducibility of Results Space life sciences Vehicles Velocity |
title | Logit-Based Analysis of Drivers’ Crossing Behavior at Unsignalized Intersections in China |
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