Real-time cruising speed design approach for multiline bus systems
In this paper, we focus on controlling multiline buses operated in networks with curbside bus stops. In such networks, both bus bunching and bus queueing, which often result in passenger inconvenience as well as bus waiting delays, are frequently observed during bus operations. To address the advers...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Bian, Bomin [verfasserIn] Zhu, Ning [verfasserIn] Meng, Qiang [verfasserIn] |
|---|
| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2023 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Transportation research / B - Amsterdam [u.a.] : Elsevier, 1979, 170, Seite 1-24 |
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| Übergeordnetes Werk: |
volume:170 ; pages:1-24 |
| DOI / URN: |
10.1016/j.trb.2023.02.003 |
|---|
| Katalog-ID: |
ELV009433546 |
|---|
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| 100 | 1 | |a Bian, Bomin |e verfasserin |0 (orcid)0000-0002-9862-3366 |4 aut | |
| 245 | 1 | 0 | |a Real-time cruising speed design approach for multiline bus systems |
| 264 | 1 | |c 2023 | |
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| 520 | |a In this paper, we focus on controlling multiline buses operated in networks with curbside bus stops. In such networks, both bus bunching and bus queueing, which often result in passenger inconvenience as well as bus waiting delays, are frequently observed during bus operations. To address the adverse influences of these two phenomena, we propose a mixed integer programming (MIP) model to provide guidance on real-time bus cruising speeds based on the real-time state of the whole system. The proposed model can avoid bus bunching by coordinating bus cruising speeds and alleviate bus queueing congestion by restricting the number of bus arrivals at each stop. Specifically, to address bus bunching, the model has a quadratic objective function that minimizes the total expected passenger waiting time; while for bus queueing, the model has big-M and time-indexed constraints that restrict the number of bus arrivals in each time interval of length g based on the waiting capacity Q s of each stop s . Simulation experiments are conducted with different sizes of virtual networks, and the corresponding results show that the proposed model can lead to both a shorter average passenger waiting time and less bus congestion at stops. The improvement with respect to bus waiting delay is more significant: the percentage decrease can reach 46.9%. Moreover, the results of the average computing time show that the control model can be solved before a bus finishes service in most cases, which means decisions can be fed back to drivers in a timely manner; therefore, the proposed model can meet the requirements of real-time control. A sensitivity analysis with respect to parameters Q s and g is also performed. These two parameters are shown to only affect control performance with respect to bus waiting delays at stops, and shorter bus waiting delays can be achieved with relatively small Q s and large g . Further experiments are conducted within a real network, and the experimental results show that our method is suitable for implementation in practice. | ||
| 650 | 4 | |a Multiline buses | |
| 650 | 4 | |a Bus bunching | |
| 650 | 4 | |a Bus queueing | |
| 650 | 4 | |a Real-time cruising speed design | |
| 650 | 4 | |a Curbside bus stop | |
| 700 | 1 | |a Zhu, Ning |e verfasserin |0 (orcid)0000-0001-8560-5946 |4 aut | |
| 700 | 1 | |a Meng, Qiang |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Transportation research / B |d Amsterdam [u.a.] : Elsevier, 1979 |g 170, Seite 1-24 |h Online-Ressource |w (DE-627)306714914 |w (DE-600)1501221-9 |w (DE-576)099210851 |x 1879-2367 |7 nnns |
| 773 | 1 | 8 | |g volume:170 |g pages:1-24 |
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| 936 | b | k | |a 55.80 |j Verkehrswesen |j Transportwesen: Allgemeines |
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10.1016/j.trb.2023.02.003 doi (DE-627)ELV009433546 (ELSEVIER)S0191-2615(23)00016-4 DE-627 ger DE-627 rda eng 380 DE-600 55.80 bkl Bian, Bomin verfasserin (orcid)0000-0002-9862-3366 aut Real-time cruising speed design approach for multiline bus systems 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this paper, we focus on controlling multiline buses operated in networks with curbside bus stops. In such networks, both bus bunching and bus queueing, which often result in passenger inconvenience as well as bus waiting delays, are frequently observed during bus operations. To address the adverse influences of these two phenomena, we propose a mixed integer programming (MIP) model to provide guidance on real-time bus cruising speeds based on the real-time state of the whole system. The proposed model can avoid bus bunching by coordinating bus cruising speeds and alleviate bus queueing congestion by restricting the number of bus arrivals at each stop. Specifically, to address bus bunching, the model has a quadratic objective function that minimizes the total expected passenger waiting time; while for bus queueing, the model has big-M and time-indexed constraints that restrict the number of bus arrivals in each time interval of length g based on the waiting capacity Q s of each stop s . Simulation experiments are conducted with different sizes of virtual networks, and the corresponding results show that the proposed model can lead to both a shorter average passenger waiting time and less bus congestion at stops. The improvement with respect to bus waiting delay is more significant: the percentage decrease can reach 46.9%. Moreover, the results of the average computing time show that the control model can be solved before a bus finishes service in most cases, which means decisions can be fed back to drivers in a timely manner; therefore, the proposed model can meet the requirements of real-time control. A sensitivity analysis with respect to parameters Q s and g is also performed. These two parameters are shown to only affect control performance with respect to bus waiting delays at stops, and shorter bus waiting delays can be achieved with relatively small Q s and large g . Further experiments are conducted within a real network, and the experimental results show that our method is suitable for implementation in practice. Multiline buses Bus bunching Bus queueing Real-time cruising speed design Curbside bus stop Zhu, Ning verfasserin (orcid)0000-0001-8560-5946 aut Meng, Qiang verfasserin aut Enthalten in Transportation research / B Amsterdam [u.a.] : Elsevier, 1979 170, Seite 1-24 Online-Ressource (DE-627)306714914 (DE-600)1501221-9 (DE-576)099210851 1879-2367 nnns volume:170 pages:1-24 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_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_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 55.80 Verkehrswesen Transportwesen: Allgemeines AR 170 1-24 |
| spelling |
10.1016/j.trb.2023.02.003 doi (DE-627)ELV009433546 (ELSEVIER)S0191-2615(23)00016-4 DE-627 ger DE-627 rda eng 380 DE-600 55.80 bkl Bian, Bomin verfasserin (orcid)0000-0002-9862-3366 aut Real-time cruising speed design approach for multiline bus systems 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this paper, we focus on controlling multiline buses operated in networks with curbside bus stops. In such networks, both bus bunching and bus queueing, which often result in passenger inconvenience as well as bus waiting delays, are frequently observed during bus operations. To address the adverse influences of these two phenomena, we propose a mixed integer programming (MIP) model to provide guidance on real-time bus cruising speeds based on the real-time state of the whole system. The proposed model can avoid bus bunching by coordinating bus cruising speeds and alleviate bus queueing congestion by restricting the number of bus arrivals at each stop. Specifically, to address bus bunching, the model has a quadratic objective function that minimizes the total expected passenger waiting time; while for bus queueing, the model has big-M and time-indexed constraints that restrict the number of bus arrivals in each time interval of length g based on the waiting capacity Q s of each stop s . Simulation experiments are conducted with different sizes of virtual networks, and the corresponding results show that the proposed model can lead to both a shorter average passenger waiting time and less bus congestion at stops. The improvement with respect to bus waiting delay is more significant: the percentage decrease can reach 46.9%. Moreover, the results of the average computing time show that the control model can be solved before a bus finishes service in most cases, which means decisions can be fed back to drivers in a timely manner; therefore, the proposed model can meet the requirements of real-time control. A sensitivity analysis with respect to parameters Q s and g is also performed. These two parameters are shown to only affect control performance with respect to bus waiting delays at stops, and shorter bus waiting delays can be achieved with relatively small Q s and large g . Further experiments are conducted within a real network, and the experimental results show that our method is suitable for implementation in practice. Multiline buses Bus bunching Bus queueing Real-time cruising speed design Curbside bus stop Zhu, Ning verfasserin (orcid)0000-0001-8560-5946 aut Meng, Qiang verfasserin aut Enthalten in Transportation research / B Amsterdam [u.a.] : Elsevier, 1979 170, Seite 1-24 Online-Ressource (DE-627)306714914 (DE-600)1501221-9 (DE-576)099210851 1879-2367 nnns volume:170 pages:1-24 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_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_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 55.80 Verkehrswesen Transportwesen: Allgemeines AR 170 1-24 |
| allfields_unstemmed |
10.1016/j.trb.2023.02.003 doi (DE-627)ELV009433546 (ELSEVIER)S0191-2615(23)00016-4 DE-627 ger DE-627 rda eng 380 DE-600 55.80 bkl Bian, Bomin verfasserin (orcid)0000-0002-9862-3366 aut Real-time cruising speed design approach for multiline bus systems 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this paper, we focus on controlling multiline buses operated in networks with curbside bus stops. In such networks, both bus bunching and bus queueing, which often result in passenger inconvenience as well as bus waiting delays, are frequently observed during bus operations. To address the adverse influences of these two phenomena, we propose a mixed integer programming (MIP) model to provide guidance on real-time bus cruising speeds based on the real-time state of the whole system. The proposed model can avoid bus bunching by coordinating bus cruising speeds and alleviate bus queueing congestion by restricting the number of bus arrivals at each stop. Specifically, to address bus bunching, the model has a quadratic objective function that minimizes the total expected passenger waiting time; while for bus queueing, the model has big-M and time-indexed constraints that restrict the number of bus arrivals in each time interval of length g based on the waiting capacity Q s of each stop s . Simulation experiments are conducted with different sizes of virtual networks, and the corresponding results show that the proposed model can lead to both a shorter average passenger waiting time and less bus congestion at stops. The improvement with respect to bus waiting delay is more significant: the percentage decrease can reach 46.9%. Moreover, the results of the average computing time show that the control model can be solved before a bus finishes service in most cases, which means decisions can be fed back to drivers in a timely manner; therefore, the proposed model can meet the requirements of real-time control. A sensitivity analysis with respect to parameters Q s and g is also performed. These two parameters are shown to only affect control performance with respect to bus waiting delays at stops, and shorter bus waiting delays can be achieved with relatively small Q s and large g . Further experiments are conducted within a real network, and the experimental results show that our method is suitable for implementation in practice. Multiline buses Bus bunching Bus queueing Real-time cruising speed design Curbside bus stop Zhu, Ning verfasserin (orcid)0000-0001-8560-5946 aut Meng, Qiang verfasserin aut Enthalten in Transportation research / B Amsterdam [u.a.] : Elsevier, 1979 170, Seite 1-24 Online-Ressource (DE-627)306714914 (DE-600)1501221-9 (DE-576)099210851 1879-2367 nnns volume:170 pages:1-24 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_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_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 55.80 Verkehrswesen Transportwesen: Allgemeines AR 170 1-24 |
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10.1016/j.trb.2023.02.003 doi (DE-627)ELV009433546 (ELSEVIER)S0191-2615(23)00016-4 DE-627 ger DE-627 rda eng 380 DE-600 55.80 bkl Bian, Bomin verfasserin (orcid)0000-0002-9862-3366 aut Real-time cruising speed design approach for multiline bus systems 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this paper, we focus on controlling multiline buses operated in networks with curbside bus stops. In such networks, both bus bunching and bus queueing, which often result in passenger inconvenience as well as bus waiting delays, are frequently observed during bus operations. To address the adverse influences of these two phenomena, we propose a mixed integer programming (MIP) model to provide guidance on real-time bus cruising speeds based on the real-time state of the whole system. The proposed model can avoid bus bunching by coordinating bus cruising speeds and alleviate bus queueing congestion by restricting the number of bus arrivals at each stop. Specifically, to address bus bunching, the model has a quadratic objective function that minimizes the total expected passenger waiting time; while for bus queueing, the model has big-M and time-indexed constraints that restrict the number of bus arrivals in each time interval of length g based on the waiting capacity Q s of each stop s . Simulation experiments are conducted with different sizes of virtual networks, and the corresponding results show that the proposed model can lead to both a shorter average passenger waiting time and less bus congestion at stops. The improvement with respect to bus waiting delay is more significant: the percentage decrease can reach 46.9%. Moreover, the results of the average computing time show that the control model can be solved before a bus finishes service in most cases, which means decisions can be fed back to drivers in a timely manner; therefore, the proposed model can meet the requirements of real-time control. A sensitivity analysis with respect to parameters Q s and g is also performed. These two parameters are shown to only affect control performance with respect to bus waiting delays at stops, and shorter bus waiting delays can be achieved with relatively small Q s and large g . Further experiments are conducted within a real network, and the experimental results show that our method is suitable for implementation in practice. Multiline buses Bus bunching Bus queueing Real-time cruising speed design Curbside bus stop Zhu, Ning verfasserin (orcid)0000-0001-8560-5946 aut Meng, Qiang verfasserin aut Enthalten in Transportation research / B Amsterdam [u.a.] : Elsevier, 1979 170, Seite 1-24 Online-Ressource (DE-627)306714914 (DE-600)1501221-9 (DE-576)099210851 1879-2367 nnns volume:170 pages:1-24 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_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_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 55.80 Verkehrswesen Transportwesen: Allgemeines AR 170 1-24 |
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10.1016/j.trb.2023.02.003 doi (DE-627)ELV009433546 (ELSEVIER)S0191-2615(23)00016-4 DE-627 ger DE-627 rda eng 380 DE-600 55.80 bkl Bian, Bomin verfasserin (orcid)0000-0002-9862-3366 aut Real-time cruising speed design approach for multiline bus systems 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this paper, we focus on controlling multiline buses operated in networks with curbside bus stops. In such networks, both bus bunching and bus queueing, which often result in passenger inconvenience as well as bus waiting delays, are frequently observed during bus operations. To address the adverse influences of these two phenomena, we propose a mixed integer programming (MIP) model to provide guidance on real-time bus cruising speeds based on the real-time state of the whole system. The proposed model can avoid bus bunching by coordinating bus cruising speeds and alleviate bus queueing congestion by restricting the number of bus arrivals at each stop. Specifically, to address bus bunching, the model has a quadratic objective function that minimizes the total expected passenger waiting time; while for bus queueing, the model has big-M and time-indexed constraints that restrict the number of bus arrivals in each time interval of length g based on the waiting capacity Q s of each stop s . Simulation experiments are conducted with different sizes of virtual networks, and the corresponding results show that the proposed model can lead to both a shorter average passenger waiting time and less bus congestion at stops. The improvement with respect to bus waiting delay is more significant: the percentage decrease can reach 46.9%. Moreover, the results of the average computing time show that the control model can be solved before a bus finishes service in most cases, which means decisions can be fed back to drivers in a timely manner; therefore, the proposed model can meet the requirements of real-time control. A sensitivity analysis with respect to parameters Q s and g is also performed. These two parameters are shown to only affect control performance with respect to bus waiting delays at stops, and shorter bus waiting delays can be achieved with relatively small Q s and large g . Further experiments are conducted within a real network, and the experimental results show that our method is suitable for implementation in practice. Multiline buses Bus bunching Bus queueing Real-time cruising speed design Curbside bus stop Zhu, Ning verfasserin (orcid)0000-0001-8560-5946 aut Meng, Qiang verfasserin aut Enthalten in Transportation research / B Amsterdam [u.a.] : Elsevier, 1979 170, Seite 1-24 Online-Ressource (DE-627)306714914 (DE-600)1501221-9 (DE-576)099210851 1879-2367 nnns volume:170 pages:1-24 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_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_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 55.80 Verkehrswesen Transportwesen: Allgemeines AR 170 1-24 |
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Bian, Bomin |
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Bian, Bomin ddc 380 bkl 55.80 misc Multiline buses misc Bus bunching misc Bus queueing misc Real-time cruising speed design misc Curbside bus stop Real-time cruising speed design approach for multiline bus systems |
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380 DE-600 55.80 bkl Real-time cruising speed design approach for multiline bus systems Multiline buses Bus bunching Bus queueing Real-time cruising speed design Curbside bus stop |
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real-time cruising speed design approach for multiline bus systems |
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Real-time cruising speed design approach for multiline bus systems |
| abstract |
In this paper, we focus on controlling multiline buses operated in networks with curbside bus stops. In such networks, both bus bunching and bus queueing, which often result in passenger inconvenience as well as bus waiting delays, are frequently observed during bus operations. To address the adverse influences of these two phenomena, we propose a mixed integer programming (MIP) model to provide guidance on real-time bus cruising speeds based on the real-time state of the whole system. The proposed model can avoid bus bunching by coordinating bus cruising speeds and alleviate bus queueing congestion by restricting the number of bus arrivals at each stop. Specifically, to address bus bunching, the model has a quadratic objective function that minimizes the total expected passenger waiting time; while for bus queueing, the model has big-M and time-indexed constraints that restrict the number of bus arrivals in each time interval of length g based on the waiting capacity Q s of each stop s . Simulation experiments are conducted with different sizes of virtual networks, and the corresponding results show that the proposed model can lead to both a shorter average passenger waiting time and less bus congestion at stops. The improvement with respect to bus waiting delay is more significant: the percentage decrease can reach 46.9%. Moreover, the results of the average computing time show that the control model can be solved before a bus finishes service in most cases, which means decisions can be fed back to drivers in a timely manner; therefore, the proposed model can meet the requirements of real-time control. A sensitivity analysis with respect to parameters Q s and g is also performed. These two parameters are shown to only affect control performance with respect to bus waiting delays at stops, and shorter bus waiting delays can be achieved with relatively small Q s and large g . Further experiments are conducted within a real network, and the experimental results show that our method is suitable for implementation in practice. |
| abstractGer |
In this paper, we focus on controlling multiline buses operated in networks with curbside bus stops. In such networks, both bus bunching and bus queueing, which often result in passenger inconvenience as well as bus waiting delays, are frequently observed during bus operations. To address the adverse influences of these two phenomena, we propose a mixed integer programming (MIP) model to provide guidance on real-time bus cruising speeds based on the real-time state of the whole system. The proposed model can avoid bus bunching by coordinating bus cruising speeds and alleviate bus queueing congestion by restricting the number of bus arrivals at each stop. Specifically, to address bus bunching, the model has a quadratic objective function that minimizes the total expected passenger waiting time; while for bus queueing, the model has big-M and time-indexed constraints that restrict the number of bus arrivals in each time interval of length g based on the waiting capacity Q s of each stop s . Simulation experiments are conducted with different sizes of virtual networks, and the corresponding results show that the proposed model can lead to both a shorter average passenger waiting time and less bus congestion at stops. The improvement with respect to bus waiting delay is more significant: the percentage decrease can reach 46.9%. Moreover, the results of the average computing time show that the control model can be solved before a bus finishes service in most cases, which means decisions can be fed back to drivers in a timely manner; therefore, the proposed model can meet the requirements of real-time control. A sensitivity analysis with respect to parameters Q s and g is also performed. These two parameters are shown to only affect control performance with respect to bus waiting delays at stops, and shorter bus waiting delays can be achieved with relatively small Q s and large g . Further experiments are conducted within a real network, and the experimental results show that our method is suitable for implementation in practice. |
| abstract_unstemmed |
In this paper, we focus on controlling multiline buses operated in networks with curbside bus stops. In such networks, both bus bunching and bus queueing, which often result in passenger inconvenience as well as bus waiting delays, are frequently observed during bus operations. To address the adverse influences of these two phenomena, we propose a mixed integer programming (MIP) model to provide guidance on real-time bus cruising speeds based on the real-time state of the whole system. The proposed model can avoid bus bunching by coordinating bus cruising speeds and alleviate bus queueing congestion by restricting the number of bus arrivals at each stop. Specifically, to address bus bunching, the model has a quadratic objective function that minimizes the total expected passenger waiting time; while for bus queueing, the model has big-M and time-indexed constraints that restrict the number of bus arrivals in each time interval of length g based on the waiting capacity Q s of each stop s . Simulation experiments are conducted with different sizes of virtual networks, and the corresponding results show that the proposed model can lead to both a shorter average passenger waiting time and less bus congestion at stops. The improvement with respect to bus waiting delay is more significant: the percentage decrease can reach 46.9%. Moreover, the results of the average computing time show that the control model can be solved before a bus finishes service in most cases, which means decisions can be fed back to drivers in a timely manner; therefore, the proposed model can meet the requirements of real-time control. A sensitivity analysis with respect to parameters Q s and g is also performed. These two parameters are shown to only affect control performance with respect to bus waiting delays at stops, and shorter bus waiting delays can be achieved with relatively small Q s and large g . Further experiments are conducted within a real network, and the experimental results show that our method is suitable for implementation in practice. |
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|
| score |
7.400401 |