Assessing the likelihood of secondary crashes on freeways with Adaptive Signal Control System deployed on alternate routes
Introduction: Reducing the likelihood of freeway secondary crashes will provide significant safety, operational and environmental benefits. This paper presents a method for assessing the likelihood of freeway secondary crashes with Adaptive Signal Control Systems (ASCS) deployed on alternate routes...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Salek, M Sabbir [verfasserIn] Jin, Weimin [verfasserIn] Khan, Sakib Mahmud [verfasserIn] Chowdhury, Mashrur [verfasserIn] Gerard, Patrick [verfasserIn] Basnet, Saurabh Bikram [verfasserIn] Torkjazi, Mohammad [verfasserIn] Huynh, Nathan [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2020 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Journal of safety research - Amsterdam [u.a.] : Elsevier Science, 1982, 76, Seite 314-326 |
|---|---|
| Übergeordnetes Werk: |
volume:76 ; pages:314-326 |
| DOI / URN: |
10.1016/j.jsr.2020.12.020 |
|---|
| Katalog-ID: |
ELV005620082 |
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| 100 | 1 | |a Salek, M Sabbir |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Assessing the likelihood of secondary crashes on freeways with Adaptive Signal Control System deployed on alternate routes |
| 264 | 1 | |c 2020 | |
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| 337 | |a Computermedien |b c |2 rdamedia | ||
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| 520 | |a Introduction: Reducing the likelihood of freeway secondary crashes will provide significant safety, operational and environmental benefits. This paper presents a method for assessing the likelihood of freeway secondary crashes with Adaptive Signal Control Systems (ASCS) deployed on alternate routes that are typically used by diverted freeway traffic to avoid any delay or congestion due to a freeway primary crash. Method: The method includes four steps: (1) identification of secondary crashes, (2) verification of alternate routes, (3) assessment of the likelihood of secondary crashes for freeways with ASCS deployed on alternate routes and non-ASCS (i.e. pre-timed, semi- or fully-actuated) alternate routes, and (4) investigation of unobserved heterogeneity of the likelihood of freeway secondary crashes. Four freeway sections (i.e., two with ASCS deployed on alternate routes and two non-ASCS alternate routes) in South Carolina are considered. Results and Conclusions: Findings from the logistic regression modeling reveal significant reduction in the likelihood of secondary crashes for one freeway section (i.e., Charleston I-26 E) with ASCS deployed on alternate route. Other factors such as rear-end crash, dark or limited light, peak period, and annual average daily traffic contribute to the likelihood of freeway secondary crashes. Furthermore, random-parameter logistic regression model results for Charleston I-26 E reveal that unobserved heterogeneity of ASCS effect exists across the observations and ASCS are associated with the reduction of the likelihood of freeway secondary crashes for 84% of the observations (i.e., primary crashes). Location of the primary crash on the freeway is observed to affect the benefit of ASCS toward freeway secondary crash reduction as the primary crash’s location determines how many upstream freeway vehicles will be able to take the alternate route. Practical Applications: Based on the findings, it is recommended that the South Carolina Department of Transportation (SCDOT) considers deploying ASCS on alternate routes parallel to freeway sections where high percentages of secondary crashes are found. | ||
| 650 | 4 | |a Secondary crash | |
| 650 | 4 | |a Adaptive Signal Control Systems | |
| 650 | 4 | |a Crash Likelihood Estimation | |
| 650 | 4 | |a Logistic regression model | |
| 650 | 4 | |a Unobserved heterogeneity | |
| 700 | 1 | |a Jin, Weimin |e verfasserin |0 (orcid)0000-0003-0148-6834 |4 aut | |
| 700 | 1 | |a Khan, Sakib Mahmud |e verfasserin |4 aut | |
| 700 | 1 | |a Chowdhury, Mashrur |e verfasserin |4 aut | |
| 700 | 1 | |a Gerard, Patrick |e verfasserin |0 (orcid)0000-0003-3710-6055 |4 aut | |
| 700 | 1 | |a Basnet, Saurabh Bikram |e verfasserin |4 aut | |
| 700 | 1 | |a Torkjazi, Mohammad |e verfasserin |0 (orcid)0000-0002-2445-6024 |4 aut | |
| 700 | 1 | |a Huynh, Nathan |e verfasserin |0 (orcid)0000-0002-4605-5651 |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Journal of safety research |d Amsterdam [u.a.] : Elsevier Science, 1982 |g 76, Seite 314-326 |h Online-Ressource |w (DE-627)320527220 |w (DE-600)2015321-1 |w (DE-576)259484849 |x 1879-1247 |7 nnns |
| 773 | 1 | 8 | |g volume:76 |g pages:314-326 |
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10.1016/j.jsr.2020.12.020 doi (DE-627)ELV005620082 (ELSEVIER)S0022-4375(20)30170-5 DE-627 ger DE-627 rda eng 690 DE-600 50.17 bkl 55.80 bkl 44.80 bkl Salek, M Sabbir verfasserin aut Assessing the likelihood of secondary crashes on freeways with Adaptive Signal Control System deployed on alternate routes 2020 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Introduction: Reducing the likelihood of freeway secondary crashes will provide significant safety, operational and environmental benefits. This paper presents a method for assessing the likelihood of freeway secondary crashes with Adaptive Signal Control Systems (ASCS) deployed on alternate routes that are typically used by diverted freeway traffic to avoid any delay or congestion due to a freeway primary crash. Method: The method includes four steps: (1) identification of secondary crashes, (2) verification of alternate routes, (3) assessment of the likelihood of secondary crashes for freeways with ASCS deployed on alternate routes and non-ASCS (i.e. pre-timed, semi- or fully-actuated) alternate routes, and (4) investigation of unobserved heterogeneity of the likelihood of freeway secondary crashes. Four freeway sections (i.e., two with ASCS deployed on alternate routes and two non-ASCS alternate routes) in South Carolina are considered. Results and Conclusions: Findings from the logistic regression modeling reveal significant reduction in the likelihood of secondary crashes for one freeway section (i.e., Charleston I-26 E) with ASCS deployed on alternate route. Other factors such as rear-end crash, dark or limited light, peak period, and annual average daily traffic contribute to the likelihood of freeway secondary crashes. Furthermore, random-parameter logistic regression model results for Charleston I-26 E reveal that unobserved heterogeneity of ASCS effect exists across the observations and ASCS are associated with the reduction of the likelihood of freeway secondary crashes for 84% of the observations (i.e., primary crashes). Location of the primary crash on the freeway is observed to affect the benefit of ASCS toward freeway secondary crash reduction as the primary crash’s location determines how many upstream freeway vehicles will be able to take the alternate route. Practical Applications: Based on the findings, it is recommended that the South Carolina Department of Transportation (SCDOT) considers deploying ASCS on alternate routes parallel to freeway sections where high percentages of secondary crashes are found. Secondary crash Adaptive Signal Control Systems Crash Likelihood Estimation Logistic regression model Unobserved heterogeneity Jin, Weimin verfasserin (orcid)0000-0003-0148-6834 aut Khan, Sakib Mahmud verfasserin aut Chowdhury, Mashrur verfasserin aut Gerard, Patrick verfasserin (orcid)0000-0003-3710-6055 aut Basnet, Saurabh Bikram verfasserin aut Torkjazi, Mohammad verfasserin (orcid)0000-0002-2445-6024 aut Huynh, Nathan verfasserin (orcid)0000-0002-4605-5651 aut Enthalten in Journal of safety research Amsterdam [u.a.] : Elsevier Science, 1982 76, Seite 314-326 Online-Ressource (DE-627)320527220 (DE-600)2015321-1 (DE-576)259484849 1879-1247 nnns volume:76 pages:314-326 GBV_USEFLAG_U SYSFLAG_U GBV_ELV GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 50.17 Sicherheitstechnik 55.80 Verkehrswesen Transportwesen: Allgemeines 44.80 Unfallmedizin Notfallmedizin AR 76 314-326 |
| spelling |
10.1016/j.jsr.2020.12.020 doi (DE-627)ELV005620082 (ELSEVIER)S0022-4375(20)30170-5 DE-627 ger DE-627 rda eng 690 DE-600 50.17 bkl 55.80 bkl 44.80 bkl Salek, M Sabbir verfasserin aut Assessing the likelihood of secondary crashes on freeways with Adaptive Signal Control System deployed on alternate routes 2020 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Introduction: Reducing the likelihood of freeway secondary crashes will provide significant safety, operational and environmental benefits. This paper presents a method for assessing the likelihood of freeway secondary crashes with Adaptive Signal Control Systems (ASCS) deployed on alternate routes that are typically used by diverted freeway traffic to avoid any delay or congestion due to a freeway primary crash. Method: The method includes four steps: (1) identification of secondary crashes, (2) verification of alternate routes, (3) assessment of the likelihood of secondary crashes for freeways with ASCS deployed on alternate routes and non-ASCS (i.e. pre-timed, semi- or fully-actuated) alternate routes, and (4) investigation of unobserved heterogeneity of the likelihood of freeway secondary crashes. Four freeway sections (i.e., two with ASCS deployed on alternate routes and two non-ASCS alternate routes) in South Carolina are considered. Results and Conclusions: Findings from the logistic regression modeling reveal significant reduction in the likelihood of secondary crashes for one freeway section (i.e., Charleston I-26 E) with ASCS deployed on alternate route. Other factors such as rear-end crash, dark or limited light, peak period, and annual average daily traffic contribute to the likelihood of freeway secondary crashes. Furthermore, random-parameter logistic regression model results for Charleston I-26 E reveal that unobserved heterogeneity of ASCS effect exists across the observations and ASCS are associated with the reduction of the likelihood of freeway secondary crashes for 84% of the observations (i.e., primary crashes). Location of the primary crash on the freeway is observed to affect the benefit of ASCS toward freeway secondary crash reduction as the primary crash’s location determines how many upstream freeway vehicles will be able to take the alternate route. Practical Applications: Based on the findings, it is recommended that the South Carolina Department of Transportation (SCDOT) considers deploying ASCS on alternate routes parallel to freeway sections where high percentages of secondary crashes are found. Secondary crash Adaptive Signal Control Systems Crash Likelihood Estimation Logistic regression model Unobserved heterogeneity Jin, Weimin verfasserin (orcid)0000-0003-0148-6834 aut Khan, Sakib Mahmud verfasserin aut Chowdhury, Mashrur verfasserin aut Gerard, Patrick verfasserin (orcid)0000-0003-3710-6055 aut Basnet, Saurabh Bikram verfasserin aut Torkjazi, Mohammad verfasserin (orcid)0000-0002-2445-6024 aut Huynh, Nathan verfasserin (orcid)0000-0002-4605-5651 aut Enthalten in Journal of safety research Amsterdam [u.a.] : Elsevier Science, 1982 76, Seite 314-326 Online-Ressource (DE-627)320527220 (DE-600)2015321-1 (DE-576)259484849 1879-1247 nnns volume:76 pages:314-326 GBV_USEFLAG_U SYSFLAG_U GBV_ELV GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 50.17 Sicherheitstechnik 55.80 Verkehrswesen Transportwesen: Allgemeines 44.80 Unfallmedizin Notfallmedizin AR 76 314-326 |
| allfields_unstemmed |
10.1016/j.jsr.2020.12.020 doi (DE-627)ELV005620082 (ELSEVIER)S0022-4375(20)30170-5 DE-627 ger DE-627 rda eng 690 DE-600 50.17 bkl 55.80 bkl 44.80 bkl Salek, M Sabbir verfasserin aut Assessing the likelihood of secondary crashes on freeways with Adaptive Signal Control System deployed on alternate routes 2020 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Introduction: Reducing the likelihood of freeway secondary crashes will provide significant safety, operational and environmental benefits. This paper presents a method for assessing the likelihood of freeway secondary crashes with Adaptive Signal Control Systems (ASCS) deployed on alternate routes that are typically used by diverted freeway traffic to avoid any delay or congestion due to a freeway primary crash. Method: The method includes four steps: (1) identification of secondary crashes, (2) verification of alternate routes, (3) assessment of the likelihood of secondary crashes for freeways with ASCS deployed on alternate routes and non-ASCS (i.e. pre-timed, semi- or fully-actuated) alternate routes, and (4) investigation of unobserved heterogeneity of the likelihood of freeway secondary crashes. Four freeway sections (i.e., two with ASCS deployed on alternate routes and two non-ASCS alternate routes) in South Carolina are considered. Results and Conclusions: Findings from the logistic regression modeling reveal significant reduction in the likelihood of secondary crashes for one freeway section (i.e., Charleston I-26 E) with ASCS deployed on alternate route. Other factors such as rear-end crash, dark or limited light, peak period, and annual average daily traffic contribute to the likelihood of freeway secondary crashes. Furthermore, random-parameter logistic regression model results for Charleston I-26 E reveal that unobserved heterogeneity of ASCS effect exists across the observations and ASCS are associated with the reduction of the likelihood of freeway secondary crashes for 84% of the observations (i.e., primary crashes). Location of the primary crash on the freeway is observed to affect the benefit of ASCS toward freeway secondary crash reduction as the primary crash’s location determines how many upstream freeway vehicles will be able to take the alternate route. Practical Applications: Based on the findings, it is recommended that the South Carolina Department of Transportation (SCDOT) considers deploying ASCS on alternate routes parallel to freeway sections where high percentages of secondary crashes are found. Secondary crash Adaptive Signal Control Systems Crash Likelihood Estimation Logistic regression model Unobserved heterogeneity Jin, Weimin verfasserin (orcid)0000-0003-0148-6834 aut Khan, Sakib Mahmud verfasserin aut Chowdhury, Mashrur verfasserin aut Gerard, Patrick verfasserin (orcid)0000-0003-3710-6055 aut Basnet, Saurabh Bikram verfasserin aut Torkjazi, Mohammad verfasserin (orcid)0000-0002-2445-6024 aut Huynh, Nathan verfasserin (orcid)0000-0002-4605-5651 aut Enthalten in Journal of safety research Amsterdam [u.a.] : Elsevier Science, 1982 76, Seite 314-326 Online-Ressource (DE-627)320527220 (DE-600)2015321-1 (DE-576)259484849 1879-1247 nnns volume:76 pages:314-326 GBV_USEFLAG_U SYSFLAG_U GBV_ELV GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 50.17 Sicherheitstechnik 55.80 Verkehrswesen Transportwesen: Allgemeines 44.80 Unfallmedizin Notfallmedizin AR 76 314-326 |
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10.1016/j.jsr.2020.12.020 doi (DE-627)ELV005620082 (ELSEVIER)S0022-4375(20)30170-5 DE-627 ger DE-627 rda eng 690 DE-600 50.17 bkl 55.80 bkl 44.80 bkl Salek, M Sabbir verfasserin aut Assessing the likelihood of secondary crashes on freeways with Adaptive Signal Control System deployed on alternate routes 2020 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Introduction: Reducing the likelihood of freeway secondary crashes will provide significant safety, operational and environmental benefits. This paper presents a method for assessing the likelihood of freeway secondary crashes with Adaptive Signal Control Systems (ASCS) deployed on alternate routes that are typically used by diverted freeway traffic to avoid any delay or congestion due to a freeway primary crash. Method: The method includes four steps: (1) identification of secondary crashes, (2) verification of alternate routes, (3) assessment of the likelihood of secondary crashes for freeways with ASCS deployed on alternate routes and non-ASCS (i.e. pre-timed, semi- or fully-actuated) alternate routes, and (4) investigation of unobserved heterogeneity of the likelihood of freeway secondary crashes. Four freeway sections (i.e., two with ASCS deployed on alternate routes and two non-ASCS alternate routes) in South Carolina are considered. Results and Conclusions: Findings from the logistic regression modeling reveal significant reduction in the likelihood of secondary crashes for one freeway section (i.e., Charleston I-26 E) with ASCS deployed on alternate route. Other factors such as rear-end crash, dark or limited light, peak period, and annual average daily traffic contribute to the likelihood of freeway secondary crashes. Furthermore, random-parameter logistic regression model results for Charleston I-26 E reveal that unobserved heterogeneity of ASCS effect exists across the observations and ASCS are associated with the reduction of the likelihood of freeway secondary crashes for 84% of the observations (i.e., primary crashes). Location of the primary crash on the freeway is observed to affect the benefit of ASCS toward freeway secondary crash reduction as the primary crash’s location determines how many upstream freeway vehicles will be able to take the alternate route. Practical Applications: Based on the findings, it is recommended that the South Carolina Department of Transportation (SCDOT) considers deploying ASCS on alternate routes parallel to freeway sections where high percentages of secondary crashes are found. Secondary crash Adaptive Signal Control Systems Crash Likelihood Estimation Logistic regression model Unobserved heterogeneity Jin, Weimin verfasserin (orcid)0000-0003-0148-6834 aut Khan, Sakib Mahmud verfasserin aut Chowdhury, Mashrur verfasserin aut Gerard, Patrick verfasserin (orcid)0000-0003-3710-6055 aut Basnet, Saurabh Bikram verfasserin aut Torkjazi, Mohammad verfasserin (orcid)0000-0002-2445-6024 aut Huynh, Nathan verfasserin (orcid)0000-0002-4605-5651 aut Enthalten in Journal of safety research Amsterdam [u.a.] : Elsevier Science, 1982 76, Seite 314-326 Online-Ressource (DE-627)320527220 (DE-600)2015321-1 (DE-576)259484849 1879-1247 nnns volume:76 pages:314-326 GBV_USEFLAG_U SYSFLAG_U GBV_ELV GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 50.17 Sicherheitstechnik 55.80 Verkehrswesen Transportwesen: Allgemeines 44.80 Unfallmedizin Notfallmedizin AR 76 314-326 |
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10.1016/j.jsr.2020.12.020 doi (DE-627)ELV005620082 (ELSEVIER)S0022-4375(20)30170-5 DE-627 ger DE-627 rda eng 690 DE-600 50.17 bkl 55.80 bkl 44.80 bkl Salek, M Sabbir verfasserin aut Assessing the likelihood of secondary crashes on freeways with Adaptive Signal Control System deployed on alternate routes 2020 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Introduction: Reducing the likelihood of freeway secondary crashes will provide significant safety, operational and environmental benefits. This paper presents a method for assessing the likelihood of freeway secondary crashes with Adaptive Signal Control Systems (ASCS) deployed on alternate routes that are typically used by diverted freeway traffic to avoid any delay or congestion due to a freeway primary crash. Method: The method includes four steps: (1) identification of secondary crashes, (2) verification of alternate routes, (3) assessment of the likelihood of secondary crashes for freeways with ASCS deployed on alternate routes and non-ASCS (i.e. pre-timed, semi- or fully-actuated) alternate routes, and (4) investigation of unobserved heterogeneity of the likelihood of freeway secondary crashes. Four freeway sections (i.e., two with ASCS deployed on alternate routes and two non-ASCS alternate routes) in South Carolina are considered. Results and Conclusions: Findings from the logistic regression modeling reveal significant reduction in the likelihood of secondary crashes for one freeway section (i.e., Charleston I-26 E) with ASCS deployed on alternate route. Other factors such as rear-end crash, dark or limited light, peak period, and annual average daily traffic contribute to the likelihood of freeway secondary crashes. Furthermore, random-parameter logistic regression model results for Charleston I-26 E reveal that unobserved heterogeneity of ASCS effect exists across the observations and ASCS are associated with the reduction of the likelihood of freeway secondary crashes for 84% of the observations (i.e., primary crashes). Location of the primary crash on the freeway is observed to affect the benefit of ASCS toward freeway secondary crash reduction as the primary crash’s location determines how many upstream freeway vehicles will be able to take the alternate route. Practical Applications: Based on the findings, it is recommended that the South Carolina Department of Transportation (SCDOT) considers deploying ASCS on alternate routes parallel to freeway sections where high percentages of secondary crashes are found. Secondary crash Adaptive Signal Control Systems Crash Likelihood Estimation Logistic regression model Unobserved heterogeneity Jin, Weimin verfasserin (orcid)0000-0003-0148-6834 aut Khan, Sakib Mahmud verfasserin aut Chowdhury, Mashrur verfasserin aut Gerard, Patrick verfasserin (orcid)0000-0003-3710-6055 aut Basnet, Saurabh Bikram verfasserin aut Torkjazi, Mohammad verfasserin (orcid)0000-0002-2445-6024 aut Huynh, Nathan verfasserin (orcid)0000-0002-4605-5651 aut Enthalten in Journal of safety research Amsterdam [u.a.] : Elsevier Science, 1982 76, Seite 314-326 Online-Ressource (DE-627)320527220 (DE-600)2015321-1 (DE-576)259484849 1879-1247 nnns volume:76 pages:314-326 GBV_USEFLAG_U SYSFLAG_U GBV_ELV GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 50.17 Sicherheitstechnik 55.80 Verkehrswesen Transportwesen: Allgemeines 44.80 Unfallmedizin Notfallmedizin AR 76 314-326 |
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Salek, M Sabbir @@aut@@ Jin, Weimin @@aut@@ Khan, Sakib Mahmud @@aut@@ Chowdhury, Mashrur @@aut@@ Gerard, Patrick @@aut@@ Basnet, Saurabh Bikram @@aut@@ Torkjazi, Mohammad @@aut@@ Huynh, Nathan @@aut@@ |
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Salek, M Sabbir |
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690 DE-600 50.17 bkl 55.80 bkl 44.80 bkl Assessing the likelihood of secondary crashes on freeways with Adaptive Signal Control System deployed on alternate routes Secondary crash Adaptive Signal Control Systems Crash Likelihood Estimation Logistic regression model Unobserved heterogeneity |
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Assessing the likelihood of secondary crashes on freeways with Adaptive Signal Control System deployed on alternate routes |
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Salek, M Sabbir Jin, Weimin Khan, Sakib Mahmud Chowdhury, Mashrur Gerard, Patrick Basnet, Saurabh Bikram Torkjazi, Mohammad Huynh, Nathan |
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assessing the likelihood of secondary crashes on freeways with adaptive signal control system deployed on alternate routes |
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Assessing the likelihood of secondary crashes on freeways with Adaptive Signal Control System deployed on alternate routes |
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Introduction: Reducing the likelihood of freeway secondary crashes will provide significant safety, operational and environmental benefits. This paper presents a method for assessing the likelihood of freeway secondary crashes with Adaptive Signal Control Systems (ASCS) deployed on alternate routes that are typically used by diverted freeway traffic to avoid any delay or congestion due to a freeway primary crash. Method: The method includes four steps: (1) identification of secondary crashes, (2) verification of alternate routes, (3) assessment of the likelihood of secondary crashes for freeways with ASCS deployed on alternate routes and non-ASCS (i.e. pre-timed, semi- or fully-actuated) alternate routes, and (4) investigation of unobserved heterogeneity of the likelihood of freeway secondary crashes. Four freeway sections (i.e., two with ASCS deployed on alternate routes and two non-ASCS alternate routes) in South Carolina are considered. Results and Conclusions: Findings from the logistic regression modeling reveal significant reduction in the likelihood of secondary crashes for one freeway section (i.e., Charleston I-26 E) with ASCS deployed on alternate route. Other factors such as rear-end crash, dark or limited light, peak period, and annual average daily traffic contribute to the likelihood of freeway secondary crashes. Furthermore, random-parameter logistic regression model results for Charleston I-26 E reveal that unobserved heterogeneity of ASCS effect exists across the observations and ASCS are associated with the reduction of the likelihood of freeway secondary crashes for 84% of the observations (i.e., primary crashes). Location of the primary crash on the freeway is observed to affect the benefit of ASCS toward freeway secondary crash reduction as the primary crash’s location determines how many upstream freeway vehicles will be able to take the alternate route. Practical Applications: Based on the findings, it is recommended that the South Carolina Department of Transportation (SCDOT) considers deploying ASCS on alternate routes parallel to freeway sections where high percentages of secondary crashes are found. |
| abstractGer |
Introduction: Reducing the likelihood of freeway secondary crashes will provide significant safety, operational and environmental benefits. This paper presents a method for assessing the likelihood of freeway secondary crashes with Adaptive Signal Control Systems (ASCS) deployed on alternate routes that are typically used by diverted freeway traffic to avoid any delay or congestion due to a freeway primary crash. Method: The method includes four steps: (1) identification of secondary crashes, (2) verification of alternate routes, (3) assessment of the likelihood of secondary crashes for freeways with ASCS deployed on alternate routes and non-ASCS (i.e. pre-timed, semi- or fully-actuated) alternate routes, and (4) investigation of unobserved heterogeneity of the likelihood of freeway secondary crashes. Four freeway sections (i.e., two with ASCS deployed on alternate routes and two non-ASCS alternate routes) in South Carolina are considered. Results and Conclusions: Findings from the logistic regression modeling reveal significant reduction in the likelihood of secondary crashes for one freeway section (i.e., Charleston I-26 E) with ASCS deployed on alternate route. Other factors such as rear-end crash, dark or limited light, peak period, and annual average daily traffic contribute to the likelihood of freeway secondary crashes. Furthermore, random-parameter logistic regression model results for Charleston I-26 E reveal that unobserved heterogeneity of ASCS effect exists across the observations and ASCS are associated with the reduction of the likelihood of freeway secondary crashes for 84% of the observations (i.e., primary crashes). Location of the primary crash on the freeway is observed to affect the benefit of ASCS toward freeway secondary crash reduction as the primary crash’s location determines how many upstream freeway vehicles will be able to take the alternate route. Practical Applications: Based on the findings, it is recommended that the South Carolina Department of Transportation (SCDOT) considers deploying ASCS on alternate routes parallel to freeway sections where high percentages of secondary crashes are found. |
| abstract_unstemmed |
Introduction: Reducing the likelihood of freeway secondary crashes will provide significant safety, operational and environmental benefits. This paper presents a method for assessing the likelihood of freeway secondary crashes with Adaptive Signal Control Systems (ASCS) deployed on alternate routes that are typically used by diverted freeway traffic to avoid any delay or congestion due to a freeway primary crash. Method: The method includes four steps: (1) identification of secondary crashes, (2) verification of alternate routes, (3) assessment of the likelihood of secondary crashes for freeways with ASCS deployed on alternate routes and non-ASCS (i.e. pre-timed, semi- or fully-actuated) alternate routes, and (4) investigation of unobserved heterogeneity of the likelihood of freeway secondary crashes. Four freeway sections (i.e., two with ASCS deployed on alternate routes and two non-ASCS alternate routes) in South Carolina are considered. Results and Conclusions: Findings from the logistic regression modeling reveal significant reduction in the likelihood of secondary crashes for one freeway section (i.e., Charleston I-26 E) with ASCS deployed on alternate route. Other factors such as rear-end crash, dark or limited light, peak period, and annual average daily traffic contribute to the likelihood of freeway secondary crashes. Furthermore, random-parameter logistic regression model results for Charleston I-26 E reveal that unobserved heterogeneity of ASCS effect exists across the observations and ASCS are associated with the reduction of the likelihood of freeway secondary crashes for 84% of the observations (i.e., primary crashes). Location of the primary crash on the freeway is observed to affect the benefit of ASCS toward freeway secondary crash reduction as the primary crash’s location determines how many upstream freeway vehicles will be able to take the alternate route. Practical Applications: Based on the findings, it is recommended that the South Carolina Department of Transportation (SCDOT) considers deploying ASCS on alternate routes parallel to freeway sections where high percentages of secondary crashes are found. |
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Results and Conclusions: Findings from the logistic regression modeling reveal significant reduction in the likelihood of secondary crashes for one freeway section (i.e., Charleston I-26 E) with ASCS deployed on alternate route. Other factors such as rear-end crash, dark or limited light, peak period, and annual average daily traffic contribute to the likelihood of freeway secondary crashes. Furthermore, random-parameter logistic regression model results for Charleston I-26 E reveal that unobserved heterogeneity of ASCS effect exists across the observations and ASCS are associated with the reduction of the likelihood of freeway secondary crashes for 84% of the observations (i.e., primary crashes). Location of the primary crash on the freeway is observed to affect the benefit of ASCS toward freeway secondary crash reduction as the primary crash’s location determines how many upstream freeway vehicles will be able to take the alternate route. Practical Applications: Based on the findings, it is recommended that the South Carolina Department of Transportation (SCDOT) considers deploying ASCS on alternate routes parallel to freeway sections where high percentages of secondary crashes are found.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Secondary crash</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Adaptive Signal Control Systems</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Crash Likelihood Estimation</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Logistic regression model</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Unobserved heterogeneity</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Jin, Weimin</subfield><subfield code="e">verfasserin</subfield><subfield code="0">(orcid)0000-0003-0148-6834</subfield><subfield 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