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Estimation of the change in the parameters of traffic in the organization of the bus lane
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Transportation Research Procedia 00 (2018) 000–000 Transportation Research Procedia 00 (2018) 000–000
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ScienceDirect Transportation Research Procedia 36 (2018) 166–172 www.elsevier.com/locate/procedia
Thirteenth International Conference on Organization and Traffic Safety Management in Large Thirteenth International Conference on Organization and Traffic Safety Management in Large Cities (SPbOTSIC 2018) Cities (SPbOTSIC 2018)
Estimation of the change in the parameters of traffic in the Estimation of the change in the parameters organization of the bus lane of traffic in the organization of the bus lane Alexey Fadyushin*, Dmitrii Zakharov, Dmitrii Karmanov Alexey Fadyushin*, Dmitrii Zakharov, Dmitrii Karmanov Industrial University of Tyumen, 38 Volodarskogo St., 625000, Tyumen, Russia Industrial University of Tyumen, 38 Volodarskogo St., 625000, Tyumen, Russia
Abstract Abstract The article deals with the issues of improving the quality of public transport services through implementation of the concept of public transport manyofcities, when the this quality conceptofispublic implemented, attention is paid to change ofconcept traffic for The article dealspriority. with theInissues improving transportinsufficient services through implementation of the of individual transport. Choice of optimal allowsistoimplemented, ensure high speed of public transport traffic and reduce negative public transport priority. In many cities,traffic whenpattern this concept insufficient attention is paid to change of traffic for effect for individual transport introducing a busallows lane without expanding theofroadway. The purpose this research is to individual transport. Choice of when optimal traffic pattern to ensure high speed public transport trafficofand reduce negative determine traffic parameters in introducing a bus lane and minimize deterioration of road traffic for individual transport. effect for individual transport when introducing a bus lane without expanding the roadway. The purpose of this research isThe to results of simulation of roadintraffic in a street road section with a bus lane traffic have been obtained. transport. Based on The the determine traffic parameters introducing a busand lane andnetwork minimize deterioration of road for individual simulation results, theoftotal time calculated fornetwork all passengers both individual and been publicobtained. transport. The on results results of simulation roaddelay traffic in awas street and road section of with a bus lane have Based the confirm theresults, hypothesis thewas bus calculated lane parameters the road parameters.and Dependencies of theThe totalresults delay simulation the that totalchanging delay time for allaffects passengers of traffic both individual public transport. time on the traffic intensity of individual transport and theaffects distance bus parameters. lane end to the stop line of of an the intersection. confirm the road hypothesis that changing the bus lane parameters thefrom roadthe traffic Dependencies total delay time on the road traffic intensity of individual transport and the distance from the bus lane end to the stop line of an intersection. © 2018 The Authors. Published by Elsevier B.V. © 2018 The Authors. by Elsevier B.V. This is an open accessPublished article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) © 2018 The Authors. by Elsevier B.V. This is an open accessPublished article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the scientific committee of the Thirteenth International Conference on Organization and This is an open access article underofthe BY-NC-ND licenseof (https://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility theCC scientific committee the Thirteenth International Conference on Organization and Traffic Safety Management in Large Cities (SPbOTSIC 2018). Peer-review under responsibility of the scientific committee of the Thirteenth International Conference on Organization and Traffic Safety Management in Large Cities (SPbOTSIC 2018). Traffic Safety Management in Large Cities (SPbOTSIC 2018). Keywords:quality of public transport services; public transport; individual transport; total delay time; organization of road traffic; microscopic simulation of roadof traffic. Keywords:quality public transport services; public transport; individual transport; total delay time; organization of road traffic; microscopic simulation of road traffic.
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Corresponding author. Tel.: +0-000-000-0000 ; fax: +0-000-000-0000 . [email protected] Corresponding author. Tel.: +0-000-000-0000 ; fax: +0-000-000-0000 .
* E-mail:
E-mail: [email protected] 2352-1465© 2018 The Authors. Published by Elsevier B.V. This is an open access under the CC by BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)Peer-review under 2352-1465© 2018 Thearticle Authors. Published Elsevier B.V. responsibility the scientific committee the Thirteenth International Conference on Organization and Traffic Safety Management This is an openofaccess article under the CCof BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)Peer-review under in Large Cities (SPbOTSIC 2018). responsibility of the scientific committee of the Thirteenth International Conference on Organization and Traffic Safety Management in Large Cities (SPbOTSIC 2018).
2352-1465 2018 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the scientific committee of the Thirteenth International Conference on Organization and Traffic Safety Management in Large Cities (SPbOTSIC 2018). 10.1016/j.trpro.2018.12.059
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Alexey Fadyushin et al. / Transportation Research Procedia 36 (2018) 166–172 Alexey Fadyushin, Dmitrii Zakharov, Dmitrii Karmanov / Transportation Research Procedia 00 (2018) 000–000
167
1. Introduction Today the state and quality of urban transport systems depends to a large extent on the efficiency and safety of urban public transport as the most important system that ensures the economic development of cities and the population’s social well-being (Abouhassan, 2017, 2018; Al-Mudhaffar et al., 2016;Basbas and Papanikolaou, 2009; Horváth, 2012). In 2015, the United Nations set a target that by 2030 access to “safe, accessible and sustainable transport’ would be available to all (United Nations, 2015). This task ask improving urban public transport systems to realize these aims is not an easy (Currie and De Gruyter, 2018). It is a commonly held belief of the transport research community that urban public transport systems are, by their very nature, more “sustainable” than private car based transport systems due to their relative social, economic and environmental performance (Shen et al., 2018; Venter et al., 2018; Dinesh and Geetam, 1999;Vuchic, 1999; Litman, 2009; Masek et al., 2016). For effective and safe operation of urban transport systems, it is required to ensure the coordinated operation of route transport, with the limitations of urban transport infrastructure being considered (Gorodokin et al., 2017; Kazhaev et al., 2018;Larin and Dosenko, 2014). One of the main tasks faced by the authorities is to provide efficient public transport services. According to the Code SP 42.13330.2011 “Urban Development. Urban and Rural Planning and Development”, time expenditure on transition from places of living to work for 90% of workforce (one way) should not exceed 40 min for cities with population of 1 million people (Priester et al., 2014).Reducing commuting time and thus increasing the quality of public transport services is possible by means of several strategies: development of the existing infrastructure of the street and road network, introduction of intellectual transport systems or implementation of the concept of public transport priority. System approaches to elimination of traffic congestions were described in Solodkijand Gorev (2013); Solodkij and Yenokayev (2017). Efforts ensuring public transport priority provide socioeconomic effect for passengers as well as save funds for the municipal budget. The size of both effects depends on the rate of increase in the traffic speed of public transport in Gorev et al.(2010). Over the last 5 years, Moscow introduced approximately 200 km of bus lanes. By 2015, the total length of bus lanes in Moscow was 241 km. Bus lanes helped to increase the speed of route traffic by 17–30%. In 2014, Moscow city public passenger transport carried 30% more passengers than in 2013. Creation of bus lanes significantly increases efficiency and appeal of route vehicles. However, if in this case route vehicles gain advantages, the road through-put capacity for individual transport decreases in Zyryanov and Mironchuk (2012). Due to the existing high-density development in cities, in most cases it is impossible to expand the available roadway and thus minimize deterioration of road traffic for individual transport. Choice of street and road network sections for assumed creation of priority bus lanes should be thorough and preceded by adequate research and simulation that allow to determine the optimal parameters of traffic organization in Yakimov (2017) and Zhankaziev (2017). Belova (2012) addresses creating a methodology of rationale for bus lane allocation. The purpose of this research is to determine traffic parameters when introducing a bus lane and minimize deterioration of road traffic for individual transport. 2. Study background and methodology In Tyumen, the bus lane in Respubliki Street was created by expanding the roadway. Intersection of Respubliki Street and Kholodilnaya Street has four lanes, one of which was allocated as a bus lane. Due to allocation of the bus lane, there was one lane for direct traffic of individual transport (see Fig. 1). The loading level in direct traffic of individual transport lane increased significantly, traffic congestions appeared. That is why the bus lane in section from Minskaya Street to Kholodilnaya Street was cancelled. The paper considers creation of a bus lane by reducing the number of individual transport lanes from 3 to 2 lanes.
Alexey Fadyushin et al. / Transportation Research Procedia 36 (2018) 166–172 Alexey Fadyushin, Dmitrii Zakharov, Dmitrii Karmanov / Transportation Research Procedia 00 (2018) 000–000
168
3
Fig. 1. Traffic signs in lanes in Respubliki Street between Minskaya Street and Kholodilnaya Street (a) as of 2016; (b) as of 2017.
The object of the study is the traffic process in inhabited localities in section of the street and road network with bus lanes. The subject of research is the change of traffic parameters for different properties of traffic streams and infrastructure parameters for route vehicles. In this article, bus lane parameters mean the distance from the end of a bus lane (traffic sign 5.14.1 “End of bus lane”) to the stop line of an intersection (hereinafter referred to as the length of the lane for all vehicles). The paper lists the following factors: the length of the lane for all vehicles, the traffic intensity of individual transport (hereinafter referred to as IT) and the traffic intensity of public transport (hereinafter referred to as PT). This article considers the length of the lane for all vehicles and the IT traffic intensity. The delay time is an important parameter of road traffic that should be attendedspecifically. The average delay time is a specific parameter for one vehicle present in the street and road network. The number of passengers travelling by IT and PT should be taken into account. The total delay time is the delay times of all passengers travelling in the street and road network section under consideration, for a specific modeof transport. The hypothesis of the study is based on the statement that the parameters of bus lane affect the parameters of IP traffic and PT traffic. It follows from the hypothesis of the study that there are parameters that allow to observe improvement of the IP traffic parameters and slight deterioration of the PT traffic parameters. The multifactor mathematical model of the average delay time for IT and PT when changing the length of the lane for all vehicles, the IT traffic intensity and the PT traffic intensity on an automobile road appears as follows:
tIT t IT о аLall bN IT сN PT
(1)
tPT tPT о аLall bN IT сN PT
(2)
where
tIT
is the average delay time in IT traffic, s;
average IT delay time under optimal conditions, s;
t PT
is the average delay time in PT traffic, s;
t IT о
is the
tPT о is the average PT delay time under optimal conditions, s; а Lall
is the parameter of sensitivity to the value of the length of the lane for all vehicles, s/m;
is the length of the lane
for all vehicles, m; b is the parameter of sensitivity to the value of the IT traffic intensity, s2/m;
N PT
N IT
is the IT
is the PT traffic traffic intensity, veh./h; c is the parameter of sensitivity to the PT traffic intensity, s2/m; intensity, veh./h. The total delay time is the product of the number of passengers in one vehicle, the traffic intensity and the average delay time for each mode of transport individually. The total delay time of a specific mode of transport is calculated according to the following equations:
TIT PT TIT TPT
t IT N IT qIT 3600
t PT N PT qPT 3600
(3)
Alexey Fadyushin, Dmitrii Zakharov, Dmitrii Karmanov / Transportation (2018) 000–000 Alexey Fadyushin et al. / Transportation ResearchResearch ProcediaProcedia 36 (2018)00166–172
4
where
TIT PT
is the sum total delay time for IT and PT, hr;
TIT
is the total delay time for IT, hr;
TPT
average number of passengers in one IT vehicle, passengers/vehicle; the average number of passengers in one PT vehicle, passengers/vehicle.
169
q IT
is the total delay time for PT, hr;
is the
q PT
is
3. Case study and results To evaluate the efficiency of changing the length of the lane for all vehicles, a microscopic traffic simulation was created with the use of PTV Vision VISSIM 8.0 software. When developing the simulation model, a street and road network section with a bus lane was created. A street and road network sectionis one direction of a signal-controlled intersection with three lanes: the left lane is for left-hand turn in additional section, the middle lane is for direct IT traffic, and the right lane is the bus lane. The right lane throughout the distance from the bus lane end to the intersection stop line is also intended for IT traffic (it is for the direct right-hand turn at the intersection). Tables 1–3 show the results of simulation in case of different lengths of the lane for all vehicles, different IT traffic intensities, and the PT traffic intensity of 120 vehicles/hour. Table 1: Change of the total delay time for IT in case of different IT traffic intensities and lengths of the lane for all vehicles. Total delay time for IT, h Traffic intensity IT, veh./h
The length of the lane for all vehicles, m 25
50
75
100
125
1000
131
22.6
18.5
17.7
17.2
1500
430
230
175
139
130
2000
742
557
464
425
391
2500
1092
910
772
717
732
Table 2: Change of the total delay time for PT in case of different IT traffic intensities and lengths of the lane for all vehicles. Total delay time for PT, h Traffic intensity IT, veh./h
The length of the lane for all vehicles, m 25
50
75
100
125
1000
5.4
11.7
16.3
21.9
27.4
1500
6.2
13.9
26.8
39
72.1
2000
6.3
16.1
24.7
37.4
78.3
2500
7.3
13.8
25.1
38.5
81.8
Table 3: Change of the sum total delay time in case of different IT traffic intensities and lengths of the lane for all vehicles. Sum total delay time, h Traffic intensity IT, veh./h
The length of the lane for all vehicles, m 25
50
75
100
125
1000
136
34.3
34.7
39.6
44.6
1500
436
244
201
178
201
2000
748
573
489
463
469
2500
1097
929
797
755
814
Figs. 2–4 show dependencies of the total delay time of IT and PT in case of change of the length of the lane for all vehicles and IT and PT traffic intensities based on the results of microsimulation.
Alexey Fadyushin, Dmitrii Zakharov, Dmitrii Kar Karmanov / Transportation Research Procedia 00 (2018) 000–000 Alexey Fadyushin et al. / Transportation Research Procedia 36 (2018) 166–172
Total delay time, h
170
500 450 400 350 300 250 200 150 100 50 0
y=
5
IT PT Sum
0.051x2
– 9.84x + 637 0.97 R² = 0.9
y = 4770x-0.76 R² = 0.99 y = 0.05x1.48 R² = 0.98 0
20
40 60 80 100 The length of the lane for all vehicles, m
120
140
Fig. 2. Dependency of the total delay time for IT and PT on the length of the lane for all vehicles (in case of the IT traffic intensity of 1500 veh./h).
800-1000 600-800 400-600 200-400 0-200
1200 1000 800 600 400 200 0
2000 25
50
75
100
1000 125
The length of the lane for all vehicles vehicles, m
Traffic intensity IT, veh./h
1000-1200
Total delay time for IT, h
Analysis of the results shows that, as the length of the lane for all vehicles increases from 25 to 125 meter meters, s, the total delay time decreases from 430 to 130 hours for IT and doubles for PT. The sum total delay time has the minimal value, which will be the optimal value of the length of the lane for all vehicles. For this example (with the IT traffic intensity off 1500 veh./h), the optimal length of the lane for all vehicles will be 90 meters.
Fig. 3. Dependency of the total delay time for IT on the length of the lane for all vehicles and on the IT traffic intensity intensity.
In case of the IT traffic intensity of 1000–1500 1500 veh./h, dependency of the total IT delay time on the length of the lane for all vehicles is linear. In case of the IT traffic intensity of 2000 2000-2500 2500 veh./h, change of the total IT delay time is more significant. In case of the minimal length of the llane for all vehicles of 25-50 50 meters, the influence of the IT traffic intensity has a significant impact on the total IT delay time. In case of significant length of the lane for all vehicles (75 meters and more), the influence of the IT traffic intensity has lower impact on the total IT delay time.
Alexey Fadyushin, Dmitrii Zakharov, Dmitrii Karmanov / Transportation Research Procedia 00 (2018) 000–000 Alexey Fadyushin et al. / Transportation Research Procedia 36 (2018) 166–172
80-100 60-80 40-60 20-40 0-20
Total delay time for РT, h
171
100 80 60 40 20
2000
0 25
50
75
100
1000 125
The length of the lane for all vehicles, m
Traffic intensity IT, veh./h
6
Fig. 4. Dependency of the total delay time for PT on the length of the lane for all vehicles and on the IT traffic intensity intensity.
In case of the IT traffic intensity of 1000–1500 1500 veh./h, dependency of the total PT delay time on the length of the lane for all vehicles is linear. In case of the IT traffic intensity of 2000-2500 2500 veh./h, the influence of the length of the lane for all vehicles on the total PT delay time is more significant. In case of the minimal length of the lane for all vehicles of 25-50 50 meters, the influence of the IT traffic intensity has no significant impact on the total PT delay time. In case of the length of the lane for all vehicles of 100 meters and more, the influence of the IT traffic intensity is significant. 4. Discussion and conclusion The obtained results confirm the hypothesis that changing the distance from the bus lane end to the intersection stop-line affects the road traffic parameters. Dependency of the total delay timee on the length of the lane for all vehicles is described by an exponential model. As the length of the lane for all vehicles increases, the total delay time decreases by 73% for IT and increases insignificantly for PT. The next task is developing a techni technique que to determine the optimal bus lane parameters with different IT and PT traffic intensities. References Abouhassan, M, 2018. Urban Transport System Analysis. WIT Trans Built Env 176, 57–68, https://doi.org/10.2495/UT170061. Abouhassan, M., 2017. Urban Transport System Analysis XXIII 176, 57 57–68. https://doi.org/10.2495/UT170061. Al-Mudhaffar, A., Nissan A., Bang, K., 2016. Bus stop and bus terminal capacity Transp Transportation Research Procedia 14, 1762–1771. 1771. https://doi.org/10.1016/j.trpro.2016.05.142. Basbas, S., Papanikolaou, A., 2009. Evaluation of a sustainable urban transport system through the use of the transecon methodology. International Journal of Sustainable Development and Planning 4(1), 18–34. https://doi.org/10.2495/SDP-V4-N1-18-34. ivil Engineers 6 Belova, A.,2012.Technique bases of planning the organization of allocated strips for public transport movement. Bulletin of C Civil (35), 123–129. he sustainability performance of urban public transport and land use in international Currie, G., De Gruyter, C., 2018.Exploring links between the cities. J Transp Land Use11(1), 325–342. https://doi.org/10.5198/jtlu.2018.957. 10.5198/jtlu.2018.957. Dinesh, M. Geetam, T., 1999. Sustainable transport systems: linkages between environmental issues, public transport, non-motorised. Economic nomic and Political Weekly 34(25), 1589–1596. Gorev, A., Popova, O.,Filimonova, A.,2010. Increasing the efficiency of using public transport at the expense of allocated lanes. Motor transport enterprise 8, 10–22. Gorodokin, V., Almetova, Z., Shepelev, V., 2017. Procedure for calculating on on-time time duration of the main cycle of a set of coordinated traffic https://doi.org/10.1016/j.trpro.2017.01.060. lights. Transportation Research Procedia 20, 231–235. https://doi.org/10.1016/j.trpro.2017.01.060 Horváth, B., 2012. A simple method to forecast travel demand in urban public transport Ac Acta Polytechnica Hungarica 9(4), 165–176
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Transportation Research Procedia 00 (2018) 000–000 Transportation Research Procedia 00 (2018) 000–000
Available online at www.sciencedirect.com
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ScienceDirect Transportation Research Procedia 36 (2018) 166–172 www.elsevier.com/locate/procedia
Thirteenth International Conference on Organization and Traffic Safety Management in Large Thirteenth International Conference on Organization and Traffic Safety Management in Large Cities (SPbOTSIC 2018) Cities (SPbOTSIC 2018)
Estimation of the change in the parameters of traffic in the Estimation of the change in the parameters organization of the bus lane of traffic in the organization of the bus lane Alexey Fadyushin*, Dmitrii Zakharov, Dmitrii Karmanov Alexey Fadyushin*, Dmitrii Zakharov, Dmitrii Karmanov Industrial University of Tyumen, 38 Volodarskogo St., 625000, Tyumen, Russia Industrial University of Tyumen, 38 Volodarskogo St., 625000, Tyumen, Russia
Abstract Abstract The article deals with the issues of improving the quality of public transport services through implementation of the concept of public transport manyofcities, when the this quality conceptofispublic implemented, attention is paid to change ofconcept traffic for The article dealspriority. with theInissues improving transportinsufficient services through implementation of the of individual transport. Choice of optimal allowsistoimplemented, ensure high speed of public transport traffic and reduce negative public transport priority. In many cities,traffic whenpattern this concept insufficient attention is paid to change of traffic for effect for individual transport introducing a busallows lane without expanding theofroadway. The purpose this research is to individual transport. Choice of when optimal traffic pattern to ensure high speed public transport trafficofand reduce negative determine traffic parameters in introducing a bus lane and minimize deterioration of road traffic for individual transport. effect for individual transport when introducing a bus lane without expanding the roadway. The purpose of this research isThe to results of simulation of roadintraffic in a street road section with a bus lane traffic have been obtained. transport. Based on The the determine traffic parameters introducing a busand lane andnetwork minimize deterioration of road for individual simulation results, theoftotal time calculated fornetwork all passengers both individual and been publicobtained. transport. The on results results of simulation roaddelay traffic in awas street and road section of with a bus lane have Based the confirm theresults, hypothesis thewas bus calculated lane parameters the road parameters.and Dependencies of theThe totalresults delay simulation the that totalchanging delay time for allaffects passengers of traffic both individual public transport. time on the traffic intensity of individual transport and theaffects distance bus parameters. lane end to the stop line of of an the intersection. confirm the road hypothesis that changing the bus lane parameters thefrom roadthe traffic Dependencies total delay time on the road traffic intensity of individual transport and the distance from the bus lane end to the stop line of an intersection. © 2018 The Authors. Published by Elsevier B.V. © 2018 The Authors. by Elsevier B.V. This is an open accessPublished article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) © 2018 The Authors. by Elsevier B.V. This is an open accessPublished article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the scientific committee of the Thirteenth International Conference on Organization and This is an open access article underofthe BY-NC-ND licenseof (https://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility theCC scientific committee the Thirteenth International Conference on Organization and Traffic Safety Management in Large Cities (SPbOTSIC 2018). Peer-review under responsibility of the scientific committee of the Thirteenth International Conference on Organization and Traffic Safety Management in Large Cities (SPbOTSIC 2018). Traffic Safety Management in Large Cities (SPbOTSIC 2018). Keywords:quality of public transport services; public transport; individual transport; total delay time; organization of road traffic; microscopic simulation of roadof traffic. Keywords:quality public transport services; public transport; individual transport; total delay time; organization of road traffic; microscopic simulation of road traffic.
*
Corresponding author. Tel.: +0-000-000-0000 ; fax: +0-000-000-0000 . [email protected] Corresponding author. Tel.: +0-000-000-0000 ; fax: +0-000-000-0000 .
* E-mail:
E-mail: [email protected] 2352-1465© 2018 The Authors. Published by Elsevier B.V. This is an open access under the CC by BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)Peer-review under 2352-1465© 2018 Thearticle Authors. Published Elsevier B.V. responsibility the scientific committee the Thirteenth International Conference on Organization and Traffic Safety Management This is an openofaccess article under the CCof BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)Peer-review under in Large Cities (SPbOTSIC 2018). responsibility of the scientific committee of the Thirteenth International Conference on Organization and Traffic Safety Management in Large Cities (SPbOTSIC 2018).
2352-1465 2018 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the scientific committee of the Thirteenth International Conference on Organization and Traffic Safety Management in Large Cities (SPbOTSIC 2018). 10.1016/j.trpro.2018.12.059
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Alexey Fadyushin et al. / Transportation Research Procedia 36 (2018) 166–172 Alexey Fadyushin, Dmitrii Zakharov, Dmitrii Karmanov / Transportation Research Procedia 00 (2018) 000–000
167
1. Introduction Today the state and quality of urban transport systems depends to a large extent on the efficiency and safety of urban public transport as the most important system that ensures the economic development of cities and the population’s social well-being (Abouhassan, 2017, 2018; Al-Mudhaffar et al., 2016;Basbas and Papanikolaou, 2009; Horváth, 2012). In 2015, the United Nations set a target that by 2030 access to “safe, accessible and sustainable transport’ would be available to all (United Nations, 2015). This task ask improving urban public transport systems to realize these aims is not an easy (Currie and De Gruyter, 2018). It is a commonly held belief of the transport research community that urban public transport systems are, by their very nature, more “sustainable” than private car based transport systems due to their relative social, economic and environmental performance (Shen et al., 2018; Venter et al., 2018; Dinesh and Geetam, 1999;Vuchic, 1999; Litman, 2009; Masek et al., 2016). For effective and safe operation of urban transport systems, it is required to ensure the coordinated operation of route transport, with the limitations of urban transport infrastructure being considered (Gorodokin et al., 2017; Kazhaev et al., 2018;Larin and Dosenko, 2014). One of the main tasks faced by the authorities is to provide efficient public transport services. According to the Code SP 42.13330.2011 “Urban Development. Urban and Rural Planning and Development”, time expenditure on transition from places of living to work for 90% of workforce (one way) should not exceed 40 min for cities with population of 1 million people (Priester et al., 2014).Reducing commuting time and thus increasing the quality of public transport services is possible by means of several strategies: development of the existing infrastructure of the street and road network, introduction of intellectual transport systems or implementation of the concept of public transport priority. System approaches to elimination of traffic congestions were described in Solodkijand Gorev (2013); Solodkij and Yenokayev (2017). Efforts ensuring public transport priority provide socioeconomic effect for passengers as well as save funds for the municipal budget. The size of both effects depends on the rate of increase in the traffic speed of public transport in Gorev et al.(2010). Over the last 5 years, Moscow introduced approximately 200 km of bus lanes. By 2015, the total length of bus lanes in Moscow was 241 km. Bus lanes helped to increase the speed of route traffic by 17–30%. In 2014, Moscow city public passenger transport carried 30% more passengers than in 2013. Creation of bus lanes significantly increases efficiency and appeal of route vehicles. However, if in this case route vehicles gain advantages, the road through-put capacity for individual transport decreases in Zyryanov and Mironchuk (2012). Due to the existing high-density development in cities, in most cases it is impossible to expand the available roadway and thus minimize deterioration of road traffic for individual transport. Choice of street and road network sections for assumed creation of priority bus lanes should be thorough and preceded by adequate research and simulation that allow to determine the optimal parameters of traffic organization in Yakimov (2017) and Zhankaziev (2017). Belova (2012) addresses creating a methodology of rationale for bus lane allocation. The purpose of this research is to determine traffic parameters when introducing a bus lane and minimize deterioration of road traffic for individual transport. 2. Study background and methodology In Tyumen, the bus lane in Respubliki Street was created by expanding the roadway. Intersection of Respubliki Street and Kholodilnaya Street has four lanes, one of which was allocated as a bus lane. Due to allocation of the bus lane, there was one lane for direct traffic of individual transport (see Fig. 1). The loading level in direct traffic of individual transport lane increased significantly, traffic congestions appeared. That is why the bus lane in section from Minskaya Street to Kholodilnaya Street was cancelled. The paper considers creation of a bus lane by reducing the number of individual transport lanes from 3 to 2 lanes.
Alexey Fadyushin et al. / Transportation Research Procedia 36 (2018) 166–172 Alexey Fadyushin, Dmitrii Zakharov, Dmitrii Karmanov / Transportation Research Procedia 00 (2018) 000–000
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3
Fig. 1. Traffic signs in lanes in Respubliki Street between Minskaya Street and Kholodilnaya Street (a) as of 2016; (b) as of 2017.
The object of the study is the traffic process in inhabited localities in section of the street and road network with bus lanes. The subject of research is the change of traffic parameters for different properties of traffic streams and infrastructure parameters for route vehicles. In this article, bus lane parameters mean the distance from the end of a bus lane (traffic sign 5.14.1 “End of bus lane”) to the stop line of an intersection (hereinafter referred to as the length of the lane for all vehicles). The paper lists the following factors: the length of the lane for all vehicles, the traffic intensity of individual transport (hereinafter referred to as IT) and the traffic intensity of public transport (hereinafter referred to as PT). This article considers the length of the lane for all vehicles and the IT traffic intensity. The delay time is an important parameter of road traffic that should be attendedspecifically. The average delay time is a specific parameter for one vehicle present in the street and road network. The number of passengers travelling by IT and PT should be taken into account. The total delay time is the delay times of all passengers travelling in the street and road network section under consideration, for a specific modeof transport. The hypothesis of the study is based on the statement that the parameters of bus lane affect the parameters of IP traffic and PT traffic. It follows from the hypothesis of the study that there are parameters that allow to observe improvement of the IP traffic parameters and slight deterioration of the PT traffic parameters. The multifactor mathematical model of the average delay time for IT and PT when changing the length of the lane for all vehicles, the IT traffic intensity and the PT traffic intensity on an automobile road appears as follows:
tIT t IT о аLall bN IT сN PT
(1)
tPT tPT о аLall bN IT сN PT
(2)
where
tIT
is the average delay time in IT traffic, s;
average IT delay time under optimal conditions, s;
t PT
is the average delay time in PT traffic, s;
t IT о
is the
tPT о is the average PT delay time under optimal conditions, s; а Lall
is the parameter of sensitivity to the value of the length of the lane for all vehicles, s/m;
is the length of the lane
for all vehicles, m; b is the parameter of sensitivity to the value of the IT traffic intensity, s2/m;
N PT
N IT
is the IT
is the PT traffic traffic intensity, veh./h; c is the parameter of sensitivity to the PT traffic intensity, s2/m; intensity, veh./h. The total delay time is the product of the number of passengers in one vehicle, the traffic intensity and the average delay time for each mode of transport individually. The total delay time of a specific mode of transport is calculated according to the following equations:
TIT PT TIT TPT
t IT N IT qIT 3600
t PT N PT qPT 3600
(3)
Alexey Fadyushin, Dmitrii Zakharov, Dmitrii Karmanov / Transportation (2018) 000–000 Alexey Fadyushin et al. / Transportation ResearchResearch ProcediaProcedia 36 (2018)00166–172
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where
TIT PT
is the sum total delay time for IT and PT, hr;
TIT
is the total delay time for IT, hr;
TPT
average number of passengers in one IT vehicle, passengers/vehicle; the average number of passengers in one PT vehicle, passengers/vehicle.
169
q IT
is the total delay time for PT, hr;
is the
q PT
is
3. Case study and results To evaluate the efficiency of changing the length of the lane for all vehicles, a microscopic traffic simulation was created with the use of PTV Vision VISSIM 8.0 software. When developing the simulation model, a street and road network section with a bus lane was created. A street and road network sectionis one direction of a signal-controlled intersection with three lanes: the left lane is for left-hand turn in additional section, the middle lane is for direct IT traffic, and the right lane is the bus lane. The right lane throughout the distance from the bus lane end to the intersection stop line is also intended for IT traffic (it is for the direct right-hand turn at the intersection). Tables 1–3 show the results of simulation in case of different lengths of the lane for all vehicles, different IT traffic intensities, and the PT traffic intensity of 120 vehicles/hour. Table 1: Change of the total delay time for IT in case of different IT traffic intensities and lengths of the lane for all vehicles. Total delay time for IT, h Traffic intensity IT, veh./h
The length of the lane for all vehicles, m 25
50
75
100
125
1000
131
22.6
18.5
17.7
17.2
1500
430
230
175
139
130
2000
742
557
464
425
391
2500
1092
910
772
717
732
Table 2: Change of the total delay time for PT in case of different IT traffic intensities and lengths of the lane for all vehicles. Total delay time for PT, h Traffic intensity IT, veh./h
The length of the lane for all vehicles, m 25
50
75
100
125
1000
5.4
11.7
16.3
21.9
27.4
1500
6.2
13.9
26.8
39
72.1
2000
6.3
16.1
24.7
37.4
78.3
2500
7.3
13.8
25.1
38.5
81.8
Table 3: Change of the sum total delay time in case of different IT traffic intensities and lengths of the lane for all vehicles. Sum total delay time, h Traffic intensity IT, veh./h
The length of the lane for all vehicles, m 25
50
75
100
125
1000
136
34.3
34.7
39.6
44.6
1500
436
244
201
178
201
2000
748
573
489
463
469
2500
1097
929
797
755
814
Figs. 2–4 show dependencies of the total delay time of IT and PT in case of change of the length of the lane for all vehicles and IT and PT traffic intensities based on the results of microsimulation.
Alexey Fadyushin, Dmitrii Zakharov, Dmitrii Kar Karmanov / Transportation Research Procedia 00 (2018) 000–000 Alexey Fadyushin et al. / Transportation Research Procedia 36 (2018) 166–172
Total delay time, h
170
500 450 400 350 300 250 200 150 100 50 0
y=
5
IT PT Sum
0.051x2
– 9.84x + 637 0.97 R² = 0.9
y = 4770x-0.76 R² = 0.99 y = 0.05x1.48 R² = 0.98 0
20
40 60 80 100 The length of the lane for all vehicles, m
120
140
Fig. 2. Dependency of the total delay time for IT and PT on the length of the lane for all vehicles (in case of the IT traffic intensity of 1500 veh./h).
800-1000 600-800 400-600 200-400 0-200
1200 1000 800 600 400 200 0
2000 25
50
75
100
1000 125
The length of the lane for all vehicles vehicles, m
Traffic intensity IT, veh./h
1000-1200
Total delay time for IT, h
Analysis of the results shows that, as the length of the lane for all vehicles increases from 25 to 125 meter meters, s, the total delay time decreases from 430 to 130 hours for IT and doubles for PT. The sum total delay time has the minimal value, which will be the optimal value of the length of the lane for all vehicles. For this example (with the IT traffic intensity off 1500 veh./h), the optimal length of the lane for all vehicles will be 90 meters.
Fig. 3. Dependency of the total delay time for IT on the length of the lane for all vehicles and on the IT traffic intensity intensity.
In case of the IT traffic intensity of 1000–1500 1500 veh./h, dependency of the total IT delay time on the length of the lane for all vehicles is linear. In case of the IT traffic intensity of 2000 2000-2500 2500 veh./h, change of the total IT delay time is more significant. In case of the minimal length of the llane for all vehicles of 25-50 50 meters, the influence of the IT traffic intensity has a significant impact on the total IT delay time. In case of significant length of the lane for all vehicles (75 meters and more), the influence of the IT traffic intensity has lower impact on the total IT delay time.
Alexey Fadyushin, Dmitrii Zakharov, Dmitrii Karmanov / Transportation Research Procedia 00 (2018) 000–000 Alexey Fadyushin et al. / Transportation Research Procedia 36 (2018) 166–172
80-100 60-80 40-60 20-40 0-20
Total delay time for РT, h
171
100 80 60 40 20
2000
0 25
50
75
100
1000 125
The length of the lane for all vehicles, m
Traffic intensity IT, veh./h
6
Fig. 4. Dependency of the total delay time for PT on the length of the lane for all vehicles and on the IT traffic intensity intensity.
In case of the IT traffic intensity of 1000–1500 1500 veh./h, dependency of the total PT delay time on the length of the lane for all vehicles is linear. In case of the IT traffic intensity of 2000-2500 2500 veh./h, the influence of the length of the lane for all vehicles on the total PT delay time is more significant. In case of the minimal length of the lane for all vehicles of 25-50 50 meters, the influence of the IT traffic intensity has no significant impact on the total PT delay time. In case of the length of the lane for all vehicles of 100 meters and more, the influence of the IT traffic intensity is significant. 4. Discussion and conclusion The obtained results confirm the hypothesis that changing the distance from the bus lane end to the intersection stop-line affects the road traffic parameters. Dependency of the total delay timee on the length of the lane for all vehicles is described by an exponential model. As the length of the lane for all vehicles increases, the total delay time decreases by 73% for IT and increases insignificantly for PT. The next task is developing a techni technique que to determine the optimal bus lane parameters with different IT and PT traffic intensities. References Abouhassan, M, 2018. Urban Transport System Analysis. WIT Trans Built Env 176, 57–68, https://doi.org/10.2495/UT170061. Abouhassan, M., 2017. Urban Transport System Analysis XXIII 176, 57 57–68. https://doi.org/10.2495/UT170061. Al-Mudhaffar, A., Nissan A., Bang, K., 2016. Bus stop and bus terminal capacity Transp Transportation Research Procedia 14, 1762–1771. 1771. https://doi.org/10.1016/j.trpro.2016.05.142. Basbas, S., Papanikolaou, A., 2009. Evaluation of a sustainable urban transport system through the use of the transecon methodology. International Journal of Sustainable Development and Planning 4(1), 18–34. https://doi.org/10.2495/SDP-V4-N1-18-34. ivil Engineers 6 Belova, A.,2012.Technique bases of planning the organization of allocated strips for public transport movement. Bulletin of C Civil (35), 123–129. he sustainability performance of urban public transport and land use in international Currie, G., De Gruyter, C., 2018.Exploring links between the cities. J Transp Land Use11(1), 325–342. https://doi.org/10.5198/jtlu.2018.957. 10.5198/jtlu.2018.957. Dinesh, M. Geetam, T., 1999. Sustainable transport systems: linkages between environmental issues, public transport, non-motorised. Economic nomic and Political Weekly 34(25), 1589–1596. Gorev, A., Popova, O.,Filimonova, A.,2010. Increasing the efficiency of using public transport at the expense of allocated lanes. Motor transport enterprise 8, 10–22. Gorodokin, V., Almetova, Z., Shepelev, V., 2017. Procedure for calculating on on-time time duration of the main cycle of a set of coordinated traffic https://doi.org/10.1016/j.trpro.2017.01.060. lights. Transportation Research Procedia 20, 231–235. https://doi.org/10.1016/j.trpro.2017.01.060 Horváth, B., 2012. A simple method to forecast travel demand in urban public transport Ac Acta Polytechnica Hungarica 9(4), 165–176
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