Nguyen, Huynh Duc (2020)
Capacity Analysis of Signalised Intersections in Motorcycle Dependent Cities.
Technische Universität Darmstadt
doi: 10.25534/tuprints-00011474
Dissertation, Erstveröffentlichung
Kurzbeschreibung (Abstract)
The capacity of a traffic stream is one of the most significant parts of traffic performance analysis. Particularly, capacity analysis of signalised intersections has been studied in developed countries where the primary transportation mode is the private car usage. In some developing countries, however, there are several distinctive traffic flow characteristics in contrast with those in developed countries such as 80% of traffic composition being motorcycles, which is leading to the term ‘Motorcycle Dependent City (MDC)’. Moreover, motorcycle driving behaviour in MDCs is entirely different from four-wheeled vehicle driving behaviour in car dependent cities. Therefore, we cannot use models defined for car traffic in developed countries to analyse performances of motorcycle traffic and to evaluate the capacities of signalised intersections in developing countries such as Vietnam. This research focuses on proposing suitable models which can explain the specific characteristics of traffic streams in MDCs and the intersection capacities in different traffic situations. This goal can be divided into objectives: finding factors that affect the capacity of signalised intersections significantly; proposing a suitable capacity calculation method; developing a capacity calculation guideline for signalised intersections in MDCs. However, the research area of this study is limited to the concept of MDCs in which the motorcycle occupies a high share in traffic composition. The comprehensive literature review on the capacity of signalised intersections is conducted in both, car dependent cities and motorcycle dependent cities, to understand the calculation method throughout various countries. Several methods and manuals in car traffic-based conditions such as German Highway Capacity Manual (HBS) (FGSV, 2015), American Highway Capacity Manual (HCM) (TRB 2010), Indonesia Highway Capacity Manual 1997 (IHCM 1997), Malaysia Highway Capacity Manual 2011 (MHCM 2011) and the Manual on Traffic Signal Control in 2006 (JSTE 2006) are introduced. Besides, some models from researched projects in MDCs are mentioned to indicate the difference in traffic situations between these cities and others. Basically, the capacity of signalised intersections includes two main components: the saturation flow rate and the effective green ratio. The saturation flow rate would be calculated by the base saturation flow rate and is adjusted by some influencing factors. Depending on the characteristics of each location and the selected method, the saturation flow rate analysis process may differ from car traffic-based flow to motorcycle traffic-based flow. In this study, the saturation flow rate models would also follow the common concept of previous studies. The base saturation flow rate will be investigated, and the motorcycle unit will be used as the basic unit. Then some main adjustment factor will be applied for the model such as approach width, vehicle type, turning activities, etc. On the other hand, the effective green ratio shows the correlation between the effective green time and the cycle time. In car traffic-based flow, the effective green time has been proved to be 1 s higher than the displayed green time. However, in MDCs, this outcome is still a controversial question and is needed to be evaluated because of its unique traffic characteristics. The traffic characteristics at signalised intersections in MDCs are analysed to figure out how they affect the intersection capacity. The traffic characteristics are categorised into several factors: vehicle characteristics, volume characteristics, speed characteristics, lane allocation characteristics, traffic signal systems, and driver behaviour. From the literature review and the traffic characteristics which are mentioned, the overall capacity model for MDCs is built up as the combination of the saturation flow rate model, the effective green time model, and the intergreen time model. The normal capacity and the maximum capacity are estimated depending on the different effective green times. Besides the proposed theoretical models, field observations are also conducted in Ho Chi Minh City, Vietnam for the model calibration process. The contents and the researching results of each model can be summarised as follows: studies. • The saturation flow rate is estimated by the motorcycle saturation flow rate and adjustment factors. In the model, the term ‘normalised saturation flow rate’ which is defined as the saturation flow rate passing over one-meter approach width is introduced. Observation results showed that the normalised saturation flow rate was calculated at 3,058 mcu/(h*m) when the green time was higher or equal to 16 s. That rate was estimated at 3,178 mcu/(h*m) when the green time was lower than 16 s. • Motorcycle equivalent unit (MCU) is chosen as a basic unit to apply the conversion of heterogeneous streams to homogeneous motorcycle streams. The MCU values may vary depending on the share of passenger cars in the flow. The MCU value changes from 5.5 to 6.8 corresponding with the car share value of 5% to 100%. The recommended MCU values for cars, middle heavy vehicles and heavy vehicles for normal calculation are 6, 9 and 14.4, respectively. • Besides the adjustment factor for the approach width, the adjustment factors for vehicle types and turning movements are considered as the main affecting factors of the saturation flow rate model. The numerical results indicated that the impact of vehicle type was the primary factor and contributed to reducing the approach capacity significantly. As regards the effect of turning movements, different turning types have different effects on the approach capacity. Right-turning motorcycles do not influence the discharge flow rate because they are assigned to run on the right side of the flow. Right-turning cars, however, affect the through-flow significantly because of their left-side position. Left-turning motorcycles interfere through-discharging cars and left-turning cars, and they would reduce the discharging speed of through-vehicles. • The effective green time model applies a method to count the number of motorcycles passing the stop line during certain time periods. Two models are classified: model 1 when the rule ‘no red-light running’ is strictly obeyed and model 2 when the rule ‘no red-light running’ is ignored. In the first model, the effective green time was proven to be equal to the displayed green time. In the second model, the effective green time was estimated to be equal to the displayed green time plus 2 s. • The intergreen time model in MDCs applies the German method with some modifications. The crossing time was recommended to be equal to the amber time which is set up at 3 s for most cases. The clearing time was increased by the addition of the interaction time between clearing through-vehicles and clearing opposing left-turning movements. The interaction time depends on vehicle types at each stream and was suggested as 1 s. The entering time was calculated by the entering distance which was defined from the middle point of the stop line to the centre of the conflict area between the entering route and the clearing route, and the entering speed was observed as 5 m/s. • The normal capacity and the maximum capacity are estimated depending on the different effective green times. The normal capacity is presented along with the rule ‘no red-light running’ which drivers must obey. Besides, the maximum capacity is given along with weak acceptance of the rule ‘no red-light running’ which is ignored by many drivers, in practice. In this thesis, the normal capacity is recommended for the capacity analysis. The maximum capacity is considered as an adaption to the current traffic situation while the illegal driving behaviour could not be controlled. After proposing the comprehensive capacity model of signalised intersections, a procedure for application of that model and a sample calculation are introduced. The procedure for application is presented as a guideline which depicts step by step capacity calculation at signalised intersections in MDCs for operational and planning purposes. Finally, this research concludes with recommendations, limitations, and further studies.
Typ des Eintrags: | Dissertation | ||||
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Erschienen: | 2020 | ||||
Autor(en): | Nguyen, Huynh Duc | ||||
Art des Eintrags: | Erstveröffentlichung | ||||
Titel: | Capacity Analysis of Signalised Intersections in Motorcycle Dependent Cities | ||||
Sprache: | Englisch | ||||
Referenten: | Boltze, Prof. Dr. Manfred ; Nakamura, Prof. Dr. Hideki | ||||
Publikationsjahr: | 2020 | ||||
Ort: | Darmstadt | ||||
Datum der mündlichen Prüfung: | 11 Februar 2019 | ||||
DOI: | 10.25534/tuprints-00011474 | ||||
URL / URN: | https://tuprints.ulb.tu-darmstadt.de/11474 | ||||
Kurzbeschreibung (Abstract): | The capacity of a traffic stream is one of the most significant parts of traffic performance analysis. Particularly, capacity analysis of signalised intersections has been studied in developed countries where the primary transportation mode is the private car usage. In some developing countries, however, there are several distinctive traffic flow characteristics in contrast with those in developed countries such as 80% of traffic composition being motorcycles, which is leading to the term ‘Motorcycle Dependent City (MDC)’. Moreover, motorcycle driving behaviour in MDCs is entirely different from four-wheeled vehicle driving behaviour in car dependent cities. Therefore, we cannot use models defined for car traffic in developed countries to analyse performances of motorcycle traffic and to evaluate the capacities of signalised intersections in developing countries such as Vietnam. This research focuses on proposing suitable models which can explain the specific characteristics of traffic streams in MDCs and the intersection capacities in different traffic situations. This goal can be divided into objectives: finding factors that affect the capacity of signalised intersections significantly; proposing a suitable capacity calculation method; developing a capacity calculation guideline for signalised intersections in MDCs. However, the research area of this study is limited to the concept of MDCs in which the motorcycle occupies a high share in traffic composition. The comprehensive literature review on the capacity of signalised intersections is conducted in both, car dependent cities and motorcycle dependent cities, to understand the calculation method throughout various countries. Several methods and manuals in car traffic-based conditions such as German Highway Capacity Manual (HBS) (FGSV, 2015), American Highway Capacity Manual (HCM) (TRB 2010), Indonesia Highway Capacity Manual 1997 (IHCM 1997), Malaysia Highway Capacity Manual 2011 (MHCM 2011) and the Manual on Traffic Signal Control in 2006 (JSTE 2006) are introduced. Besides, some models from researched projects in MDCs are mentioned to indicate the difference in traffic situations between these cities and others. Basically, the capacity of signalised intersections includes two main components: the saturation flow rate and the effective green ratio. The saturation flow rate would be calculated by the base saturation flow rate and is adjusted by some influencing factors. Depending on the characteristics of each location and the selected method, the saturation flow rate analysis process may differ from car traffic-based flow to motorcycle traffic-based flow. In this study, the saturation flow rate models would also follow the common concept of previous studies. The base saturation flow rate will be investigated, and the motorcycle unit will be used as the basic unit. Then some main adjustment factor will be applied for the model such as approach width, vehicle type, turning activities, etc. On the other hand, the effective green ratio shows the correlation between the effective green time and the cycle time. In car traffic-based flow, the effective green time has been proved to be 1 s higher than the displayed green time. However, in MDCs, this outcome is still a controversial question and is needed to be evaluated because of its unique traffic characteristics. The traffic characteristics at signalised intersections in MDCs are analysed to figure out how they affect the intersection capacity. The traffic characteristics are categorised into several factors: vehicle characteristics, volume characteristics, speed characteristics, lane allocation characteristics, traffic signal systems, and driver behaviour. From the literature review and the traffic characteristics which are mentioned, the overall capacity model for MDCs is built up as the combination of the saturation flow rate model, the effective green time model, and the intergreen time model. The normal capacity and the maximum capacity are estimated depending on the different effective green times. Besides the proposed theoretical models, field observations are also conducted in Ho Chi Minh City, Vietnam for the model calibration process. The contents and the researching results of each model can be summarised as follows: studies. • The saturation flow rate is estimated by the motorcycle saturation flow rate and adjustment factors. In the model, the term ‘normalised saturation flow rate’ which is defined as the saturation flow rate passing over one-meter approach width is introduced. Observation results showed that the normalised saturation flow rate was calculated at 3,058 mcu/(h*m) when the green time was higher or equal to 16 s. That rate was estimated at 3,178 mcu/(h*m) when the green time was lower than 16 s. • Motorcycle equivalent unit (MCU) is chosen as a basic unit to apply the conversion of heterogeneous streams to homogeneous motorcycle streams. The MCU values may vary depending on the share of passenger cars in the flow. The MCU value changes from 5.5 to 6.8 corresponding with the car share value of 5% to 100%. The recommended MCU values for cars, middle heavy vehicles and heavy vehicles for normal calculation are 6, 9 and 14.4, respectively. • Besides the adjustment factor for the approach width, the adjustment factors for vehicle types and turning movements are considered as the main affecting factors of the saturation flow rate model. The numerical results indicated that the impact of vehicle type was the primary factor and contributed to reducing the approach capacity significantly. As regards the effect of turning movements, different turning types have different effects on the approach capacity. Right-turning motorcycles do not influence the discharge flow rate because they are assigned to run on the right side of the flow. Right-turning cars, however, affect the through-flow significantly because of their left-side position. Left-turning motorcycles interfere through-discharging cars and left-turning cars, and they would reduce the discharging speed of through-vehicles. • The effective green time model applies a method to count the number of motorcycles passing the stop line during certain time periods. Two models are classified: model 1 when the rule ‘no red-light running’ is strictly obeyed and model 2 when the rule ‘no red-light running’ is ignored. In the first model, the effective green time was proven to be equal to the displayed green time. In the second model, the effective green time was estimated to be equal to the displayed green time plus 2 s. • The intergreen time model in MDCs applies the German method with some modifications. The crossing time was recommended to be equal to the amber time which is set up at 3 s for most cases. The clearing time was increased by the addition of the interaction time between clearing through-vehicles and clearing opposing left-turning movements. The interaction time depends on vehicle types at each stream and was suggested as 1 s. The entering time was calculated by the entering distance which was defined from the middle point of the stop line to the centre of the conflict area between the entering route and the clearing route, and the entering speed was observed as 5 m/s. • The normal capacity and the maximum capacity are estimated depending on the different effective green times. The normal capacity is presented along with the rule ‘no red-light running’ which drivers must obey. Besides, the maximum capacity is given along with weak acceptance of the rule ‘no red-light running’ which is ignored by many drivers, in practice. In this thesis, the normal capacity is recommended for the capacity analysis. The maximum capacity is considered as an adaption to the current traffic situation while the illegal driving behaviour could not be controlled. After proposing the comprehensive capacity model of signalised intersections, a procedure for application of that model and a sample calculation are introduced. The procedure for application is presented as a guideline which depicts step by step capacity calculation at signalised intersections in MDCs for operational and planning purposes. Finally, this research concludes with recommendations, limitations, and further studies. |
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URN: | urn:nbn:de:tuda-tuprints-114745 | ||||
Sachgruppe der Dewey Dezimalklassifikatin (DDC): | 600 Technik, Medizin, angewandte Wissenschaften > 600 Technik | ||||
Fachbereich(e)/-gebiet(e): | 13 Fachbereich Bau- und Umweltingenieurwissenschaften 13 Fachbereich Bau- und Umweltingenieurwissenschaften > Verbund Institute für Verkehr 13 Fachbereich Bau- und Umweltingenieurwissenschaften > Verbund Institute für Verkehr > Institut für Verkehrsplanung und Verkehrstechnik |
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Hinterlegungsdatum: | 08 Mär 2020 20:55 | ||||
Letzte Änderung: | 08 Mär 2020 20:55 | ||||
PPN: | |||||
Referenten: | Boltze, Prof. Dr. Manfred ; Nakamura, Prof. Dr. Hideki | ||||
Datum der mündlichen Prüfung / Verteidigung / mdl. Prüfung: | 11 Februar 2019 | ||||
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