Use of Micro-Simulation at Signalised Intersections

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This section discusses the methodology adopted in this research. Six intersections were selected to collect the data for this study. A video recording technique was used for recording the traffic flow in peak traffic flow hours. The recorded data was analysed to evaluate the headways. Signal stop line at each approach was taken as a reference line for the analysis and measurements were taken when the front bumper of the car crosses the stop line. Saturation flow rates were calculated by the headway method. Trends were analysed to examine the queue discharge behaviour and a new model is proposed based on the observed behaviours.

Study Framework

Capacity analysis of a signalised intersection is calculated by determining the saturation flow rate. Determination of saturation flow rate in the field is a cumbersome job and different methods are proposed in literature. Analytical methods, including HCM (2010) and ARR 123 (1981), assume almost identical methodologies in saturation flow rate calculations. HCM (2000) describes direct measurement of prevailing saturation flow rates in Chapter 16, Appendix H. According to HCM (2010), the saturation flow rate represents the maximum rate of flow measured at stop line during the green time. The state of stability is said to be achieved after 10 to 14 s of green time. The direct measurement of saturation flow rate is conducted to cater for the prevailing conditions. The prevailing conditions are those conditions that affect the saturation flow rate due to effect of lane width, traffic composition (heavy vehicles), terrain, and other geometric, control and traffic conditions. In absence of field measurements, a base saturation flow rate is assumed and then saturation flow rate for the prevailing conditions is determined after applying the adjustment factors. The base saturation flow rate is defined as the discharge rate from a standing queue that carries only through passenger cars and is otherwise unaffected by conditions such as grade, parking, and turning vehicles.
The methodology for determining field saturation flow rate in ARR 123 (Akçelik, 1995) divides the green time into three portions. Saturation flow rate is measured after excluding the first 10 seconds of green time. ARR 123 (Akçelik, 1995) recommends a number of cycles to be observed for greater accuracy in calculation of saturation flow rate. This research adopted existing techniques to measure and verifies the generally assumed sustained saturation flow rate theory. Six intersections were identified for collecting data in Auckland city. The selection of these intersections was made according to a number of factors that are discussed in the subsequent sections in detail.*
The methodological frame work for this study is presented in Figure 3.1. The research is split into two phases. The first phase covers the practical aspect in which data is collected to study the queue discharge behaviour at signalised intersections. The objective of this stage is to verify the variability of saturation flow rate and determine the tendencies of queue discharge flow rate with respect to queue position and green time. A pilot study was conducted to observe the field trends. Based on the preliminary verification, a detailed methodology is worked out to conduct the extensive data collection from six intersections in Auckland, New Zealand. A criterion was set for selection of the intersections for data collection. The main concern in the selection of the intersections was to highlight those intersections which are not affected by capacity reducing factors.
The data was collected through the video data collection method as well as SCATS data was requested from the Auckland Council. The main factors considered in data collection include: headway, cycle time, saturation flow rate, and delay. The outcome of this phase helped to establish a framework for model development in the second phase. The second phase reviews all the model development methodologies and revisit the cycle time calculation formulation to incorporate results obtained in phase I.

Data Collection


It is a well-known fact that a number of factors affect saturation flow rate. The HCM (2000), and ARR 123 (Akçelik, 1995) described a number of urban conditions and various geometric and traffic configurations that can cause substantial variability in saturation flows. A description of these conditions is highlighted in Table 3.1. Factors used to modify the saturation flow of a given lane or approach generally include the urban environment; local driver behaviour; parking or transit interference; interaction with priority, opposing or adjacent flows; and limited queuing or discharge space. Some methodologies even consider the impact of weather conditions and green interval. While selecting signalised intersection for this particular study, it is particularly crucial that an ideal or close to ideal situation should be established for data collection. Therefore those approaches at signalised intersections are selected that contained baseline geometric conditions and are not influenced by geometric factors that have been reported to be influential in reducing saturation flow rates. Following factors are considered in selection of the intersections;


While selection process, the approaches that are crossing perpendicular or closeness to perpendicular, are being selected for data collection. The best alignment at grade intersections is believed to be when the intersecting roads meet at right or nearly right angles (Garber and Hoel, 2010).

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The lane configuration factor is taken into account when seeking the ideal intersection and priority is given to intersections with at least one exclusive through lane. Balmoral – Dominion Road intersection and Balmoral – Sandringham Road Intersection have exclusive left turn slip lanes.

Traffic composition

Cars constitute the commonest vehicle type in the Auckland urban area. While selecting an intersection, great care is taken to ensure that those intersections are selected where cars form the maximum percentage of vehicles. This is done in order to study the real field situation with minimum conversions.

Bunching Effects

One of the most important factors in analysis of isolated signalised intersections is the effect of a nearby intersection if it is closely spaced. This effect is very important as it can reduce the saturation flow rate substantially. This factor is also considered and the approaches that are likely to produce the bunching effect are simply crossed out.
Other factors that could affect saturation flow including bus blockage, parking, pedestrian and bicycles activity.
The selection of intersections is intended to minimize factors that can affect the saturation flow rate. The intersections are highlighted with minimum disturbance in terms of bus blockage, parking, pedestrians, bicycle activity and other factors.

Field Surveys

The control for cameras were planned to setup at the green area, and recording were to be done in the morning peak hours from 6:55AM to 9:00AM and in the evening peak hours from 3:55PM to 6:00PM. All the safety procedures of University of Auckland and Auckland Council were adopted during the data collection activity. Permission for conducting data collection activity was acquired from Auckland Council. Recorded data is stored in a hard drive and is analysed later for saturation flow and delay calculations.

Data Matrix

Six intersections selected have four approaches each which make the total number of approaches 24. Table 3.2 below shows the calculated data matrix for proposed data collection on six intersections. Out of these 24 approaches, four approaches were crossed out for data collection due to different reasons. At Balmoral – Dominion Road intersection, the south and north approach have parking, commercial activity and bunching effect due to pedestrian signals respectively. On St. Lukes – New North Road intersection, the south approach has no exclusive through lane, so this approach was crossed out for data collection. The northern approach at Great South Road – South Eastern Highway intersection has a curve which can affect the saturation flow rate. This approach was also excluded from the data collection.

Safety Aspects

Sufficient safety arrangements were made to ensure the safety of the people and equipment during data collection activity. The University of Auckland policy for safety was followed during collection of data. Safety and operational aspects of traffic were carefully monitored. At the mounting and dismounting of camera assemblies at intersections, all measures were adopted to avoid interference with the traffic.

1.1 Background
1.2 Problem Statement
1.3 Research Objectives
1.4 Research Contributions
1.5 Scope of the Research
1.6 Organization of the Dissertation
2.1 Characterisation of Traffic Flow at Signalised Intersections
2.2 Headway
2.3 Traffic Signal Operations
2.4 Saturation Flow Rate
2.5 Variations in Saturation Flow Rate
2.6 Exiting Models for Saturation Headway
2.7 Capacity and Degree of Saturation
2.8 Cycle Time Formulation
2.9 Delay
2.10 Delay Models
2.11 Queue Process at Signalised Intersection
2.12 SCATS System
2.13 Use of Micro-Simulation at Signalised Intersections
2.14 Gene Expression Programming
3.1 Study Framework
3.2 Data Collection
3.3 Selected Intersections for Data Collection
3.4 Field Observations
3.5 Microscopic and Micro-Analytical Analysis
3.6 Modelling the Observed Queue Discharge Behaviour
3.7 Equipment Preparation
3.8 Site Set-up
4.1 Pilot Study
4.2 Detailed Data Collection
4.3 Data Analysis
5.1 Introduction
5.2 Saturation Flow Rate
5.3 Micro-Simulation and Capacity of Signalised Intersections
5.4 Data Collection
5.5 Data Analysis and Results
5.6 Conclusions
6.1 Introduction
6.2 Traffic Operations at Pre-Timed Signalised Intersection
6.3 Gene Expression Programming
6.4 Field Observation
6.5 Data Analysis and Results
6.6 Concluding Remarks
7.1 Introduction
7.2 Model Implementation
7.3 Concluding Remarks
8.1 Introduction
8.2 Delay Models
8.3 Traffic Observations in Auckland
8.4 Model Formulation
8.5 Model Validation
8.6 Discussion
8.7 Concluding Remarks
9.1 Introduction
9.3 Gene Expression Programming
9.5 Model Validation
9.6 Concluding Remarks
10.1 Summary
10.2 Verification of Saturation Flow Rate
10.3 Development of Queue Discharge Models
10.4 Model Implementation
10.5 Development of Car-following Model for Signalised Intersections
10.6 Recommendations for Future Research

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