on road public transport
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AP-R401-12
AUSTROADS RESEARCH REPORT
The Use of Microsimulation TrafficModels for On-road Public Transport
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The Use of Microsimulation Traffic Models for 0n-road Public Transport
Published March 2012
Austroads Ltd 2012
This work is copyright. Apart from any use as permitted under the Copyright Act 1968,no part may be reproduced by any process without the prior written permission of Austroads.
The Use of Microsimulation Traffic Models for On-road Public Transport
ISBN 978-1-921991-18-9
Austroads Project No. NT1528
Austroads Publication No. APR401-12
Project Manager
Roger Lau, VicRoads
Prepared by
Dr Ian Espada, Wei Minn Wong, Dr James Luk
ARRB Group
Published by Austroads LtdLevel 9, Robell House
287 Elizabeth Street
Sydney NSW 2000 Australia
Phone: +61 2 9264 7088
Fax: +61 2 9264 1657
Email:[email protected]
www.austroads.com.au
Austroads believes this publication to be correct at the time of printing and does not acceptresponsibility for any consequences arising from the use of information herein. Readers should
rely on their own skill and judgement to apply information to particular issues.
mailto:[email protected]:[email protected]:[email protected]:[email protected] -
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About Austroads
Austroads purpose is to:
promote improved Australian and New Zealand transport outcomes provide expert technical input to national policy development on road and road transport
issues
promote improved practice and capability by road agencies.
promote consistency in road and road agency operations.
Austroads membership comprises the six state and two territory road transport and traffic
authorities, the Commonwealth Department of Infrastructure and Transport, the Australian Local
Government Association, and NZ Transport Agency. Austroads is governed by a Board consisting
of the chief executive officer (or an alternative senior executive officer) of each of its elevenmember organisations:
Roads and Maritime Services New South Wales
Roads Corporation Victoria
Department of Transport and Main Roads Queensland
Main Roads Western Australia
Department of Planning, Transport and Infrastructure South Australia
Department of Infrastructure, Energy and Resources Tasmania
Department of Lands and Planning Northern Territory
Department of Territory and Municipal Services Australian Capital Territory
Commonwealth Department of Infrastructure and Transport
Australian Local Government Association
New Zealand Transport Agency.
The success of Austroads is derived from the collaboration of member organisations and others in
the road industry. It aims to be the Australasian leader in providing high quality information, advice
and fostering research in the road transport sector.
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CONTENTS
1 INTRODUCTION ................................................................................................................... 12 MICROSIMULATION MODELLING OF ORPT ...................................................................... 22.1 Selecting the Appropriate Modelling Technique ..................................................................... 22.2 Organising a Microsimulation Study for ORPT Analysis ......................................................... 4
2.2.1 Study Objectives and Project Scoping ...................................................................... 42.2.2 Selecting a Software Platform .................................................................................. 42.2.3 Base Model Development ........................................................................................ 52.2.4 Model Calibration and Validation .............................................................................. 62.2.5 Auditing a Microsimulation Model ............................................................................. 7
3 REVIEW OF SELECTED ORPT PRIORITY SCHEMES ........................................................ 83.1 Set Back Bus Lane (SBBL) .................................................................................................... 93.2 Queue Jump Bus Lane (QJBL) ............................................................................................ 103.3 Signal Priority for Set Back and Queue Jump Bus Lanes ..................................................... 123.4 Bus Priority Scenarios for MSTM Study ............................................................................... 13
3.4.1 Set Back Bus Lane Scenarios ................................................................................ 133.4.2 Queue Jump Bus Lane Scenarios .......................................................................... 14
4 MICROSIMULATION MODELS FOR ORPT ANALYSIS..................................................... 154.1 Base Model .......................................................................................................................... 15
4.1.1 Hypothetical Network ............................................................................................. 154.1.2 Traffic Demand....................................................................................................... 16
4.2
Set Back Bus Lane Models .................................................................................................. 18
4.3 Queue Jump Bus Lane Models ............................................................................................ 195 SIMULATION RESULTS ..................................................................................................... 225.1 Comparison of Selected Bus Priority Schemes .................................................................... 22 5.2 Set Back Bus Lane Model Results ....................................................................................... 295.3 Queue Jump Bus Lane Model Results ................................................................................. 375.4 Summary of Findings ........................................................................................................... 406 CONCLUSION AND RECOMMENDATIONS ...................................................................... 42REFERENCES ............................................................................................................................. 43APPENDIX A LIST OF ABBREVIATIONS ..................................................................... 44APPENDIX B ORPT PRIORITY SCHEMES IN USE ...................................................... 45APPENDIX C CALIBRATION OF SIGNPOSTING PARAMETERS IN SBBL
MODELS .................................................................................................. 47
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TABLES
Table 2.1: Related Austroads documents on MSTM ................................................................. 2Table 2.2: Suitability of four types of modelling techniques to ORPT priority analysis ............... 3Table 2.3: Input data requirements for base model development .............................................. 5Table 2.4: Inputs needed for OPRT microsimulation ................................................................. 6Table 3.1: SBBL design guidelines ......................................................................................... 10Table 3.2: QJBL design guidelines .......................................................................................... 12Table 3.3: SBBL scenarios ...................................................................................................... 13Table 3.4: QJBL scenarios ...................................................................................................... 14Table 4.1: Features of the hypothetical network ...................................................................... 16Table 4.2: Traffic demand ....................................................................................................... 17Table 4.3: SBBL models ......................................................................................................... 19Table 4.4: SBBL traffic signal priority scheme ......................................................................... 19Table 4.5: QJBL signal scheme with no red B signal ............................................................... 20Table 4.6: QJBL signal scheme with red B signal ................................................................... 21
FIGURES
Figure 3.1: Selected ORPT priority schemes ............................................................................. 8Figure 3.2: Set back bus lane ..................................................................................................... 9Figure 3.3: QJBL using a left turn auxiliary lane ....................................................................... 11Figure 3.4: Short distance for merging for bus in a QJBL with no departure-side
merge lane ............................................................................................................. 11Figure 4.1: Hypothetical network .............................................................................................. 15Figure 4.2: SBBL design scenarios .......................................................................................... 18Figure 4.3: QJBL design scenarios .......................................................................................... 20Figure 5.1: Average travel time under various ORPT schemes at 5-min bus
headway................................................................................................................. 24Figure 5.2: Standard deviation of travel time under various ORPT schemes at 5-min
bus headway .......................................................................................................... 25Figure 5.3: Average travel time under various ORPT schemes at 2-min bus
headway................................................................................................................. 26Figure 5.4: Standard deviation of travel time under various ORPT schemes at 2-min
bus headway .......................................................................................................... 27Figure 5.5: Relative performance of ORPT schemes for car and bus travel ............................. 28Figure 5.6: Average travel time under serial SBBL which starts upstream of the
bottleneck section (SBBL-2) and serial SBBL which starts at thebottleneck section (SBBL-4) ................................................................................... 31
Figure 5.7: Average travel time under serial SBBL ending downstream of thebottleneck section (SBBL-1) and serial SBBL ending at the bottlenecksection (SBBL-2) .................................................................................................... 32
Figure 5.8: Average travel time under SBBL which allow (SBBL-1) and do not allow(SBBL-3) through cars on the kerbside lane at the approach-side .......................... 33
Figure 5.9: Average travel time under SBBL-1 with short and long approach-side set .............. 34Figure 5.10: Average travel time under SBBL-2 with short and long approach-side set .............. 35Figure 5.11: Average travel time under SBBL-1 with and without signal priority ......................... 36Figure 5.12: Average travel time for various QJBL scenarios under flexible bus driver
route choice mode .................................................................................................. 38
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Figure 5.13: Average travel time for various QJBL scenarios under restricted driverroute choice mode .................................................................................................. 39
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SUMMARY
Microsimulation traffic modelling (MSTM) is a useful tool for controlled comparative studies foron-road public transport (ORPT) priority treatments. The purpose of this study was to enable amore consistent approach to the application of MSTM to ORPT priority analysis and improvenetwork planning for ORPT. It was also the purpose of this study to better understand ORPTpriority schemes by controlled comparative studies using MSTM.
The study developed an MSTM study framework which included the following steps:
The first step in conducting a study of an ORPT priority scheme is to confirm if modelling isnecessary; and if so, which modelling technique is most appropriate. The MSTM studyframework suggests the following:
Prior to modelling, it has been recommended that preliminary analysis be conductedfirst. Preliminary analysis could include sketch planning and qualitative analysis. The
need for further analysis by modelling was determined based on the outcome of thepreliminary analysis.
The choice set of modelling techniques include: macro-models (e.g. four-step models),micro-models (e.g. SIDRA models), macrosimulation (e.g. TRANSYT models), ormicrosimulation models. The identification of the most appropriate technique would bebased on a structured technical assessment of each modelling technique as it appliesto the nature and scale of the ORPT priority scheme to be examined.
The MSTM study framework then outlines the required tasks for a microsimulation study asfollows:
identification of the study objectives and project scoping
selection of the right software platform for microsimulation development of a base model, including preparation of the data needed to develop the
base model
model calibration and validation
audit of the model output results.
This study looked into four ORPT priority treatments including: full bus lane (FBL), set back buslane (SBBL), queue jump bus lane (QJBL) and no priority (NP). It is noted that QJBL would requirea construction of new road space, which is not required in the other schemes. Additionalconstruction cost for QJBL is ignored in this study but needs to be considered for projectevaluation. Microsimulation experiments were conducted using a hypothetical linear network toexamine the relative performance of the selected ORPT treatments and extract principles in OPRTpriority applications. Note that Findings were as follows:
At undersaturated conditions, there was no benefit from bus priority treatment.
At near-saturated conditions, the following were noted:
When bus headways are long, QJBL and NP resulted in low and reliable bus and cartravel time. When bus headways are short, NP resulted in better bus and car traveltimes than QJBL due to disruptions caused by the frequent activation of the bus onlysignal phase in QJBL. It may be worth considering not providing a bus only phase inQJBL, provided that a departure-side merge lane is present.
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SBBL and FBL also resulted in similarly low and reliable bus travel time but car traveltime was adversely affected due to the reduced road space for cars. Overall travel time(i.e. combining bus and car travellers) in SBBL was better than in FBL.
At oversaturated conditions, the following were noted:
When bus headways are long, QJBL resulted in the lowest and most reliable overalltravel time. When bus headways are short, NP performed better than QJBL due to thesame reason noted in near-saturated conditions.
Bus travel time in QJBL and NP were high and unreliable and may not be adequate forpromoting modal shift towards bus. The good overall travel time performance in QJBLand NP was largely due to lower car travel time than in SBBL or FBL.
Regardless of bus headway, SBBL and FBL resulted in low and reliable bus operationwhich was suitable for promoting buses. However, high and unreliable car travel time inSBBL and FBL deteriorated overall travel time. The poor overall travel time results ofSBBL and FBL in the experiments were overstated because the linear highway network
used in the analysis did not allow cars to re-route. SBBL and FBL could potentiallyhave a better overall travel time result than QJBL or NP if other measures are appliedin conjunction with SBBL and FBL to mitigate their adverse effects on car travel time.Overall travel time performance of SBBL was better than FBL.
The experiments also looked into specific design issues of SBBL and QJBL as well as theapplication of signal priority in conjunction with SBBL and QJBL. For SBBL, the experimentsfocused on the utilisation of the kerbside lane to improve car travel time whilemaintaining/improving bus travel time. The SBBL experiments particularly examined the case of aserial SBBL, which is a continuous application of SBBL along an arterial. Findings were as follows:
Provision of a departure-side set back improved utilisation of the kerbside lane and resultedin lower car travel time while maintaining low bus travel time.
Results on the analysis of the location of the start and end point of a serial SBBL were asfollows:
The start of a serial SBBL can be located just beyond the maximum queue of the firstbottleneck section along a bus route; or further upstream where congestion levelsremain undersaturated. The simulation results indicated that the latter resulted in bettercar and bus travel time. The former induced lane changing and merging which resultedin a bottleneck that impeded buses trying to enter the mid-block bus lane in SBBL.
The end point of a serial SBBL can be located right after the last bottleneck sectionalong a bus route or further downstream of the last bottleneck section. The formerresulted in better car and bus travel time. More road space was allocated to cars
downstream of the bottleneck section by immediately terminating the serial SBBL.
The findings suggest that inbound serial SBBL should start further upstream from thecentral business district (CBD), while outbound serial SBBL should be terminatedcloser to the CBD.
Results on the analysis on the length of the approach-side set back were as follows:
Lengthening the approach-side set back in an SBBL improved overall travel time whenit was the last section of a serial SBBL or if the departure-side set back was sufficientlylong, provided that the approach-side set back can still allow a bus to cross theintersection in one cycle. Extending the approach-side set back increased utilisation of
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the kerbside lane resulting in improved car travel time while maintaining low bus traveltime.
When the departure-side set back was short, extension of the approach-side set backdegraded bus and car travel times due to disruptions caused by the increased number
of cars on the kerbside lane attempting to merge just downstream of the intersection.
The findings suggest that it is ideal to lengthen the approach-side set back butconstrained by the capacity of the departure-side set back as well as by the maximumqueue position of the bus to allow the bus to cross the intersection in one cycle.
For QJBL, the experiments focused on the effect of the departure-side merge lane. It was foundthat provision of a departure-side merge lane in QJBL with no red B signal improved bus traveltime while car travel time was maintained. The departure-side merge lane was more effective whensite conditions constrain buses to use the short bus lane in a QJBL, e.g. when auxiliary lanes arelong or if a bus stop is located at the auxiliary lane. The results suggest that installation ofdeparture-side merge lanes in QJBL should be considered.
Finally, the experiments examined the application of signal priority in conjunction with QJBL andSBBL. When bus headways are long, the application of signal priority for buses in conjunction withSBBL and QJBL resulted in lower bus travel time but higher car travel time. Signal priority wasfound to be more effective in QJBL than in SBBL. Impacts to car operation need to be managedcarefully with the application of signal priority for buses, particularly in SBBL. As mentioned earlier,when bus headways are short, the high frequency of signal priority activations disrupted trafficmovements and degraded both car and bus travel time in QJBL. It is therefore recommended toconsider signal priority in QJBL sites only when bus headways are long.
The findings from the microsimulation experiments have identified principles in the application ofORPT priority. However, it should be noted that the findings in this study are based on the
conditions of the hypothetical network used in the numerical experiments and it may be necessaryto conduct site specific analysis, where appropriate.
There are concerns as to how a particular on-road public transport priority scheme would balancethe various road user needs and how it would align to societal values. It is therefore recommendedto further apply microsimulation and modelling in general, to examine on-road public transportpriority treatments with the aim of refining and expanding the current on-road public transportguidelines for road agencies. Future analysis should also broaden the range of indicators forcomparison, to include throughput, safety, aesthetics, and others, as well as, travel time indicatorsused in this study.
At present, there are only a small number of cases of the application of on-road public transport
priority; thereby there are only a handful of field cases that can be used to improve road agenciesunderstanding of on-road public transport priority treatments. Field testing is expensive andproblems in field tests can potentially be damaging to public acceptance of on-road public transportpriority schemes. Microsimulation studies and modelling provide a relatively inexpensive approachto better understanding the impacts of on-road public transport priority.
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1 INTRODUCTION
Increasing congestion levels on arterials have heightened the conflict in the allocation of roadcapacity to on-road public transport (ORPT) and general traffic. The application of ORPT priority is
increasingly being considered by road agencies, with the intent of improving travel time and traveltime reliability of ORPT while minimising negative impacts on general traffic. ORPT may be appliedunder the context of network operation plans (Wall & Moslih 2010). ORPT priority schemes alsotarget environmental and social objectives by encouraging more people to use public transportmodes and to improve accessibility of people who do not have access to cars. This study focuseson ORPT priority schemes without major civil works (e.g. no road widening) and schemes areapplied through road space allocation.
Microsimulation traffic modelling (MSTM) is a useful tool for controlled comparative studies forORPT treatments. The purpose of this study was to enable a more consistent approach to theapplication of MSTM to ORPT priority analysis and improve network planning for ORPT. It wasalso the purpose of this study to better understand ORPT priority schemes by controlled
comparative studies using MSTM. The specific objectives of the study are as follows:
develop a framework for an MSTM analysis of ORPT priority schemes, including theidentification of the critical variables and data set associated with MSTM analysis for ORPTpriority initiatives
examine the relative performance of ORPT priority schemes using MSTM and extract designprinciples for ORPT priority schemes from the MSTM results.
ORPT includes trams and buses. This study focused on bus operation only and specifically thefollowing four bus priority schemes:
no priority (NP)
full bus lane (FBL)
set back bus lane (SBBL)
queue jump bus lane (QJBL).
Analysis of the selected bus priority schemes was conducted at two levels. The first level ofanalysis was to characterise the impacts and trade-offs in bus and car travel time of the fourselected bus priority treatments, and to provide guidance on the applicability of the selected buspriority treatments. The second level of analysis looked into specific design issues of SBBL andQJBL. Design aspects of SBBL and QJBL examined in this study include: (i) utilisation of thekerbside lane under varying configurations of the SBBL that is applied serially; (ii) utility of thedeparture-side merge lane and red B signal in QJBL; and, (iii) signal priority in conjunction withSBBL and QJBL.
Contents of the report are as follows (see also Appendix A for a list of abbreviations):
framework for a MSTM study of ORPT priority schemes (Section 2)
review of the selected ORPT priority schemes and development of ORPT priority scenariosfor MSTM analysis (Section 3)
description of the MSTM models used in this study (Section 4)
MSTM model results and discussion of findings (Section 5)
conclusions and recommendations (Section 6).
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2 MICROSIMULATION MODELLING OF ORPT
This section lays out a framework for the MSTM of ORPT. The framework provides guidance in thefollowing:
selection of the appropriate modelling technique for ORPT priority analysis (Section 2.1)
organisation of a MSTM analysis for the ORPT study including the identification of data setrequirements (Section 2.2).
Related Austroads documents on MSTM are summarised in Table 2.1.
Table 2.1: Related Austroads documents on MSTM
Document Coverage
The use and application of microsimulation traffic models (Austroads 2006) Use and limitations of MSTM
Organisation of an MSTM study
Microsimulation standards (ARRB 2007) Preparation of MSTM reports Recommended parameters
Guidelines for selecting techniques for the modelling of network operations (Austroads 2010a) Modelling technique selection
2.1 Selecting the Appropriate Modelling Technique
It is important to confirm that microsimulation is the appropriate technique to use; in certain casesmodelling may not be necessary. This section outlines key considerations to the selection of theappropriate modelling technique based on the Guidelines for Selecting Techniques for theModelling of Network Operations(Austroads 2010a).
Modelling is generally resource intensive and may not be the most appropriate approach to anORPT study. It is recommended that preliminary analysis be conducted prior to embarking onmodelling. Preliminary analysis serves to filter out cases that do not require modelling. It also helpsto clarify the role of models, should modelling be required. Preliminary analysis could be conductedby sketch planning or qualitative comparisons, which are explained in the following:
Sketch planning methods generate rough indicators and an enumeration of factors and theirpotential impact on the schemes being examined. An example is the use of bus headways,car volume and other data to check if a particular scheme is warranted or not. ORPT priorityguidelines available in road agencies include this information. Past studies or experiencesare also useful references.
Qualitative comparison of alternatives can also yield meaningful conclusions. Factors toconsider include environmental, social, strategic planning and economic considerations. Areview of advantages and disadvantages can provide a broad assessment of various ORPTtreatments. Qualitative comparison can highlight important factors that are beyond the scopeof models e.g. aesthetics and social impacts.
A decision to do a more rigorous analysis using modelling could then be made under one of thefollowing conditions: (i) preliminary analysis failed to identify the best course of action; (ii) theproject required more rigorous analysis to be approved or broadly accepted; or (iii) there are risksinvolved in getting recommendations wrong and so modelling can provide additional information fordecision making.
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Modelling techniques that can be considered include:
macroscopic analytical models (or macro-model) which include land use models and thefour-step model, e.g. EMME, CUBE and VISSUM models
microscopic analytical models (or micro-model) which include theoretically and empiricallyderived relationships of traffic flow variables, e.g. SIDRA INTERSECTION models
macrosimulation models which simulate traffic movement of platoons or packets of vehicles,e.g. TRANSYT models
microsimulation models which simulate individual vehicle movements, AIMSUN, PARAMICS,and VISSIM models.
A review of the strengths and limitations of each technique as it applies to the project is necessaryto decide which modelling technique is appropriate. Emphasis is given to the techniqueslimitations on critical aspects of the project rather than on an overall assessment of eachtechnique. Possible aspects of an ORPT priority study and the suitability of each modelling
technique are shown in Table 2.2. The most appropriate technique is the technique that is suitableto all important aspects of the ORPT priority study.
Another class of technique is called mesoscopic models, which can be broadly described as acombination of any of the above four techniques (note that meso means middle). Mescoscopictechniques can overcome limitations of a certain technique by integrating it with another techniquethat do not have such limitations. Common examples include four-step/microsimulation models,four-step/micro-models, and macrosimulation/microsimulation models.
Table 2.2: Suitability of four types of modelling techniques to ORPT priority analysis
Nature of ORPT priori ty analysis Suitability of modelling technique
Macro-model Micro-model Macrosimulation Microsimulation
Demand type Land use or person trips
Origin-destination (city-wide)
Origin-destination (small area)
Time varying traffic flow
Hourly traffic flow
Network type Integrated multimodal network
Highway and transit network
Highway network
Geographical
scope
City-wide
Small area or corridor
Isolated site or facility
Temporal
scope
Medium-term to long-term
Short-term
Traveller
response
Destination and mode choice
Route choice
Traffic control Dynamic traffic control
Static traffic control
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Nature of ORPT priori ty analysis Suitability of modelling technique
Macro-model Micro-model Macrosimulation Microsimulation
Performance
measures
Delay
Travel time
Emission and fuel consumption
Others Non-technical audience
Indicates the technique is suitable.
Indicates the technique is partially suitable.
Indicates that the technique has limitations and may not be suitable.
Source: Austroads (2010a).
2.2 Organising a Microsimulation Study for ORPT Analysis
The Austroads project entitled, The Use and Application of Microsimulation Traffic Models(Austroads 2006) laid out a framework for conducting a microsimulation study, which is applicableto the study of ORPT priority. The key steps in undertaking a microsimulation study are as follows:
identifying study objectives and project scoping
selecting the right software platform for microsimulation
developing a base model
calibrating and validating the model
auditing the model output results.
2.2.1 Study Objectives and Project Scoping
It is advisable that the analyst, the project manager and decision maker have a clearunderstanding on what needs to be achieved from the microsimulation analysis. Some importantquestions to ask include:
Why is the analysis needed?
What are the characteristics of the project being analysed?
What questions should the analysis answer?
What are the scenarios (alternatives) to be studied?
Who are the recipients of the results?
Have all stakeholders involved been consulted?
What are the performance indices required to evaluate the scenarios?
What resources are available?
What is the scale of the study both in time and in space?
2.2.2 Selecting a Software Platform
There are a number of microsimulation software packages available. It is important to consider anumber of factors when choosing a software platform for a microsimulation analysis. Theseinclude:
level of expertise within a project team
level of support from the software supplier
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training required to get a base model developed
level of transparency of the package structure and outputs so that meaningful interpretationof model results enable effective decision making
experience in applying a package for different network sizes
suitability of the facilities and parameters in a package to simulate the phenomenon beinginvestigated
sensitivity to the required parameters on specific features to be analysed in proposedscenarios
accuracy of vehicle movement logic such as lane changing and car-following manoeuvres.
2.2.3 Base Model Development
The base model is encoded using a variety of input data. Table 2.3 lists the input data needed formicrosimulation (Austroads 2006):
Table 2.3: Input data requirements for base model development
Category Data
Input network coding data Link length
Number of lanes
Intersection layout
Signal timings
Link (cruise) speed
Public transport lines and stops
Input demand data Origin-destination flows
Link flows and turning percentages
Pedestrian traffic
Bus headways and dwell times
Input data on driver behaviour Gap acceptance
Car-following
Aggressiveness
Awareness
Source: Austroads (2006).
Table 2.4 describes the extent and level of detail of input data needed for the microsimulation ofORPT depending on the scale of the study area, i.e. isolated intersection/site, linear or network(RTA 2009).
In addition to the data inputs in Table 2.4, it may be necessary to develop special programs tosupplement the capability of microsimulation packages. For example, Application ProgrammingInterfaces, or APIs, need to be developed to simulate complex control and optimisation that couldnot be modelled using basic microsimulation software package features.
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Table 2.4: Inputs needed for OPRT microsimulation
Input data Scale of model
Isolated intersection/site Linear Network
Aerial photograph Required Required Required
Drawing file Desirable Desirable Required
(for complex intersections)
GIS file Not required Desirable Desirable
Signal plans Required Required Required
Road speed and classification Required Required Required
Parking and clearways Desirable Required Required
Public transport information, including route,
timetable/headway, and stations and dwell time
Required Required Required
Traffic count information Required Required Required
Queue length information Desirable Required Required
Travel time information Desirable Required Required
Origin-destination information Not required Desirable Required
Source: Adapted from RTA (2009).
Microsimulation models require appropriate parameters in order to run realistically. Austroadsproject no. NS1229, Microsimulation Standards(ARRB 2007) compiled suitable microsimulationparameters for three packages (i.e. AIMSUN, Q-PARAMICS and VISSIM) which are used by roadagencies in Australia. These parameters can be categorised as follows:
global parameters e.g. reaction time, period of simulation, warm-up period
vehicle parameters e.g. vehicle lengths and widths, acceleration and deceleration rates traffic parameters e.g. specification flow profiles (demands), yellow signal time, all-red time
behaviour e.g. speed limit factor and familiarity
assignment techniques e.g. fixed-time or dynamic
visualisation e.g. vehicle colours, projection, road types
statistics and post processing e.g. suppressed demand and level of aggregation.
2.2.4 Model Calibration and Validation
Calibration is the process of changing the parameter values in a model in order to achieve
agreement between simulation results and observed data. Many parameters are often involved in amicrosimulation model. It is a good practice to adopt a calibration strategy. Some preliminaryconsiderations are as follows:
accept default parameters that can be used with confidence
limit calibration to a workable set of parameters
global parameters should be calibrated first, followed by local or site specific parameters
a smaller time step allows higher resolution in calculating vehicle movements and wouldresult in more realistic vehicle movements in the microsimulation models
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allow the model to settle down (e.g. by filling a network with vehicles) before initiatingcalibration; a rule of thumb is to have a warm-up period equal to twice the travel time for avehicle to traverse from one outermost entry point of the network to the furthest destination atfree flow speed
undertake sufficient runs using different seeds for the random number generators based onstatistical tests; at least five to six runs are recommended.
The following four steps are recommended as good practice for calibrating models:
network depiction: check the physical representation of the network
calibrating capacity: adjust global and link-specific parameters to best replicate capacityvalues from field measurements or acceptable historical values
calibrating demand: fine-tuning at the link-specific level such as geometry and speeds (orcosts) so the flows in the model match observed flows at screen lines or cordon lines
calibrating performance: further refinements at the link-specific level so the model can
replicate performance indicators such as travel time, delay or queue lengths measured fromthe field.
The calibrated model is then validated. Validation is the comparison of model output with observeddata independent from the calibration procedure. It is common to collect sufficient input data suchthat a portion of the input data is for calibration and the rest is for validation. The performanceoutputs can be travel time, delay or queue lengths. Because of the randomness of both observedand simulated data, validation should be carried out on a statistical basis.
2.2.5 Auditing a Microsimulation Model
Auditing a model is defined as a process to verify the results of the model. It can be carried out as
a peer review or through the service of a consultant. This process can be by means of thefollowing:
general error checking
sanity check of model outputs
benchmarking MSTM with an analytical model or other means available
statistical analysis and alternative analysis using different scenarios.
Austroads (2006) provided a pro-forma for auditing a microsimulation model.
In summary, this section compiled a framework for a MSTM analysis of ORPT priority schemes.
The framework covered technique selection and organisation of the microsimulation study,including the identification of the critical variables and data set associated with MSTM analysis forORPT priority initiatives.
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3 REVIEW OF SELECTED ORPT PRIORITY SCHEMES
This section reviews the selected ORPT priority schemes and develops the scenarios for theMSTM study. There are a number of ORPT priority schemes that can be considered and
Appendix B lists ORPT priority schemes described in Austroads and road agency documents. Thisstudy focussed on four schemes for buses (Figure 3.1) including the following:
no priority (NP)
full bus lane (FBL)
set back bus lane (SBBL)
queue jump bus lane (QJBL).
Under NP, buses operate in mixed traffic. FBL is an extreme case of allotting the maximum priorityto buses. Under FBL, one lane is dedicated to bus operation. A bus lane enables buses to bypasstraffic queues, usually approaching traffic signals. This will often mean a substantial time saving to
buses and their passengers, possibly offset by some additional delay to the vehicles which havebeen overtaken (DfT 2001). The SBBL and QJBL schemes aim to maintain efficient bus operationswhile minimising negative impacts to cars. SBBL and QJBL are described in Section 3.1 andSection 3.2 respectively. Traffic signal priority application in SBBL and QJBL are described inSection 3.3. Further scenarios for SBBL and QJBL are described in Section 3.4. It is noted thatQJBL would require a construction of new road space, which is not required in the other schemes.The comparison of schemes under uniform road space is not possible. Additional construction costfor QJBL is ignored in this study but needs to be considered for project evaluation.
(a) No priority (NP)
(b) Full bus lane (FBL)
(c) Set back bus lane (SBBL)
(d) Queue jump bus lane (QJBL)
B B
Approach-side set back Departure-side set back
B B
Approach-side set back Departure-side set back
Figure 3.1: Selected ORPT priority schemes
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3.1 Set Back Bus Lane (SBBL)
The SBBL scheme is a mid-block bus or bus-only lane with an approach-side set back and anoptional departure-side set back (Figure 3.2). The purpose of the approach-side set back is toposition the bus close enough to an intersection to allow it to cross the intersection in one cycle.
The approach-side set back also allows the kerbside lane to be used by cars, which can includeleft-turning cars only or left-turning and through cars. The additional lane space for cars couldpotentially increase the throughput of the intersection.
Figure 3.2: Set back bus lane
The departure-side set back facilitates the safe merging of through cars using the kerbside lane.The departure-side set back also prevents queue spillbacks from blocking buses entering themid-block bus lane. The departure-side set back should therefore be short enough to position abus to enter the mid-block bus lane beyond the expected downstream queue.
It is an option in SBBL to have no departure-side set back such that the bus lane immediatelystarts right after the intersection. However, without a departure-side set back, only left-turning carsare allowed to use the kerbside lane on the approach-side.
A SBBL can be applied in isolation at a selected highway section or serially throughout the route ofthe bus across a congested stretch of highway. Figure 3.2 is an example of a serial application of
SBBL.
Guidelines for the design of SBBL are listed in Table 3.1. It states that the approach-side set backlength depends on the level of saturation and the green time. The setback length is based on afactor of 1.0 m to 2.5 m per second of green time for volume-to-capacity ratio (VCR) of anapproach of 70% to 95% respectively. The approach set back would generally be approximately 50to 100 m.
The departure-side set back is set such that entry point to the mid-block bus lane is beyond thepeak hour queue length. If through cars are allowed on the kerbside lane of the upstream section,then the departure set back should also provide sufficient space for safe merging, which isgenerally 50 m to 100 m.
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Table 3.1: SBBL design guidelines
Document Guidelines related to set back bus lane
Bus priority measures: principles and
design (PTA 2004)
In UK, the optimum setback for bus lanes increases when there is an increase in the degreeof saturation and is proportional to the traffic signal green-time.
Approximately 2.5 m per second of green-time at a 95% saturation level at intersection. Approximately 1.0 m per second of green-time at a 70% saturation level.
No set back at a signalised intersection is justified by a bus flow > 120 buses/h.
Bus priority guidelines (VicRoads 2003) For a through lane, determine the maximum set back distance by considering the shortest green
signal time and computing the number of vehicles which pass through during this time. For set
back with short mid-block bus lane, the entry to the bus way should extend beyond the peak hour
queue length.
For a through and left lane, the following needs to be considered:
number of left turning vehicles
volume of pedestrians
impact due to pedestrians on delay for through traffic
merging distance provided before new bus lane downstream of intersection
if it is difficult to prohibit car parking along its entire length of road during peak hours, a partialapproach may be possible.
On-road bus facilities (VicRoads 2010a) Where the headway between buses is less than 24 min, allocate set back lanes on theapproach to an intersection.
3.2 Queue Jump Bus Lane (QJBL)
A QJBL is a short mid-block bus lane ending at the stopline. The QJBL allows the bus to bypassqueues and be positioned at the head of the queue. Traffic signals in QJBL provide additionalpriority for buses by giving a bus phase. In QJBL, bus drivers have the option to use the short buslane or stay on the main line. A QJBL can be set up by any of the following:
constructing a new short section or flaring the lane at an intersection for the exclusive use ofbuses
removing kerbside parking to permit buses to use this section of the carriageway
forcing cars to merge prior to the congestion point so that buses can bypass them
using the left-turn auxiliary lane and a short bus lane at the slip lane island.
This study focussed only on the QJBL using the left-turn auxiliary lane and a short bus lane at theslip lane island (Figure 3.3). Guidelines for QJBL design are in Table 3.2. The length of the left turnauxiliary lane should be longer than the peak hour queue length. When this is not possible, thelane should at least be longer than the queue length at maximum green time. This is approximately
80 m to 100 m. In retrofitting intersections with QJBL, the length of the auxiliary lane may beconstrained by what is already available.
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(a) QJBL with a departure-side
merge lane
(b) QJBL without a departure-side merge lane
Figure 3.3: QJBL using a left turn auxiliary lane
A QJBL may or may not have a departure-side merge lane. The merge lane on the departure-sidefacilitates bus merging into the second lane. The length of the merge lane at the departure-side isdesigned based on acceleration characteristics of buses and sufficient length to find an appropriategap for merging. Guidelines stipulate the length of the merge lane to be approximately 50 to100 m, ideally 100 m. In certain cases, a merge lane is not provided. Without a merge lane, buseswould utilise the space between road sections to change lanes (Figure 3.4). The short distanceavailable means that the bus could not accelerate enough to merge safely. To avoid this situation a
red B signal should be provided. A red B signal requires a bus on the short bus lane to stop at thestopline. The red B signal does not apply to buses that are not on the short bus lane.
Figure 3.4: Short distance for merging for bus in a QJBL with no departure-side merge lane
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Table 3.2: QJBL design guidelines
Document Guidelines related to queue jump lane
On-road public transport (Austroads 2004) Guidelines in USA recommend this for arterial street intersections with:
high-frequency bus service with a maximum average headway of 15 mins
traffic volumes which exceed 500 veh/h in the kerb lane during peak periods
operation level of service of D or worse
acceptable cost and feasible land acquisition.
Tools that impact network performance:
road space allocation tools
(Austroads 2007)
Short priority lanes in inner suburban locations can be effectively applied where the remaining
traffic volume per lane is less than 500 veh/h and bus headway < 5 mins.
Gold Coast Bus/HOV priority study
(TMR 2005)
Guidelines in Gold Coast (QLD) justify its use at intersections when:
level of service is D or worse
number of buses per peak hour in peak direction 15 buses/hr.
Bus priority guidelines (VicRoads 2003) For queue jump lanes sharing with left-hand turn traffic:
length of the left turn slip lane needs to be reviewed
optimum length longer than the peak hour queue length if optimum length is not feasible, the lane should be longer than the maximum green time
queue length
buses will need a departure-side lane of sufficient length to accelerate to an appropriate speed(50 m to reach 45 km/h) and then undertake a merge over an appropriate distance(approximately 50 m at 45 km/h).
Brisbane HOV arterial roads study
(TMR 2001)
Potential application:
intersection approach with recurring severe peak period congestion
adequate right-of-way for additional approach lane
where mid-block kerbside demands preclude continuous priority lane
part of kerbside priority lane system
peak period conversion of general purpose turn lane (restrict or redirect general purpose turns
during peaks) typically bus-only but could function effectively as transit lane
in conjunction with signal priority.
3.3 Signal Priority for Set Back and Queue Jump Bus Lanes
SBBL and QJBL are considered as road space allocation schemes because they provide prioritythrough spatial means. Bus priority can be enhanced by providing traffic signal priority (TSP).Signal priority provides temporal priority to bus operations. Commonly used signal priority methodsinclude (VicRoads 2003):
bus signal phases provided at various points in the cycle
bus early start phase where a bus phase is provided before the through-green signal when abus is detected
extended green time to allow on-coming buses to pass through an intersection beforeterminating the green phase.
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3.4 Bus Priority Scenarios for MSTM Study
An Austroads project workshop was held on December 2010 to discuss ORPT priority scenariosand provide the direction for the specific scenarios to be analysed in this study. The following taskswere defined:
Assess the impacts and trade-offs in bus and car travel time of the four selected bus prioritytreatments to provide guidance on the applicability of the selected bus priority treatments.
Analyse the utilisation of the kerbside lane under varying configurations of the SBBL that isapplied serially, with the aim to increase car utilisation of the kerbside lane in order toimprove car travel time while maintaining/improving bus travel time. To maximise kerbsidelane utilisation, the following can be considered:
shortening the bus lane by locating the start point of the serial SBBL close to or at thefirst bottleneck section and/or terminating the serial SBBL just after the last bottlenecksection
providing a sufficient departure-side set back to allow and encourage through cars toutilise the kerbside lane made available by the approach-side set back
lengthening the approach-side set back to increase the number of cars that can passthrough the intersection while ensuring that buses can pass through the intersection inone cycle.
Assess the provision of a departure-side merge lane and red B signal in QJBL and its effecton car and bus travel time.
Examine the application of signal priority in conjunction with SBBL and QJBL.
3.4.1 Set Back Bus Lane Scenarios
Four SBBL scenarios, described in Table 3.3, were set up to examine the utilisation of the kerbsidelane and the application of signal priority.
Table 3.3: SBBL scenarios
ID Start and end point of the serial SBBL Car use of the approach-side kerbside lane anddeparture-side set back
Start point of the serial SBBL End point of the serial SBBL
SBBL-1 Upstream of the first bottleneck At the next section after last
bottleneck section
Left turn and through Merging space on the
departure-side is available
SBBL-2 Upstream of the first bottleneck At the last bottleneck section Left turn and through Merging space on the
departure-side is available
SBBL-3 Upstream of the first bottleneck At the next section after last
bottleneck section
Left turn only No merging space on the
departure-side
SBBL-4 Just after the maximum queue
length at the first bottleneck
section
At the last bottleneck section Left turn and through Merging space on the
departure-side is available
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Five numerical experiments were designed as follows:
comparison of SBBL-2 and SBBL-4 to examine the start point of the serial SBBL
comparison of SBBL-1 and SBBL-2 to examine the end point of the serial SBBL
comparison of SBBL-1 and SBBL-3 to investigate through car movement along the kerbsidelane by providing or not providing a merging space on the departure side
comparison of SBBL-1 and SBBL-2 with short and long approach-side setbacks to examinethe applicability of a long approach-side set back
comparison of SBBL-1 with and without signal priority to investigate the effectiveness ofincorporating signal priority with SBBL.
3.4.2 Queue Jump Bus Lane Scenarios
Two QJBL scenarios, described in Table 3.4, were analysed to examine the effect of thedeparture-side merge lane on car and bus travel time and the application of signal priority in
conjunction with QJBL. Note that the absence of a departure-side merge lane mandates theoperation of a red B signal.
Table 3.4: QJBL scenarios
ID Lay out and red B signal Signal priori ty option
Departure-side merge lane Red B signal
QJBL-1 Yes No Full, i.e. bus phase is provided at the earliest possible opportunity
Limited, i.e. bus phase is provided only at a certain time during the cycle
QJBL-2 No Yes Full
Limited
Two numerical experiments were designed as follows:
comparison of QJBL-1 and QJBL-2 to investigate the effect of the departure-side merge lane
comparison of QJBL-1 and QJBL-2 under full and limited signal priority to investigate theeffectiveness of incorporating signal priority with QJBL.
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4 MICROSIMULATION MODELS FOR ORPT ANALYSIS
This section describes the microsimulation models used in this study to analyse various aspects ofORPT priority treatments described in Section 3. Section 4.1 describes the base model.
Section 4.2 and Section 4.3 describe details of the SBBL models and QJBL model respectively.
AIMSUN (www.aimsun.com/site/) was selected as the software platform for this study. Theselection was based on cost and familiarity of the ARRB team with developing applicationprogramming interfaces (APIs) in AIMSUN.
4.1 Base Model
The approach of the MSTM experiments was to simplify the model scenarios as much as possible.Factors that can be considered as non-essential to the objective of the enquiry were minimised oreliminated. The rationale for removing non-essential factors was to highlight the differences inperformance of the schemes to be tested and to isolate the reason for the difference.
4.1.1 Hypothetical Network
A hypothetical network was utilised. The network is shown in Figure 4.1 and its features aredescribed in Table 4.1. A linear network comprising of two intersections was adopted. One busroute passes through the network with headway of two or five minutes and a dwell time of 30 s ateach bus stop. A simple hypothetical network was utilised to minimise variability in themicrosimulation results to heighten differences for comparative analyses. A realistic case studywould be inherently more complex and the microsimulation results would have higher variance andtherefore more simulation runs would be required for comparative analyses.
The source links are A1 Street, B Street and C Street. The source links of the hypothetical networkwere lengthened such that there were no vehicles waiting out at any time during the simulationperiod. Waiting out vehicles are vehicles that could not enter the network when long queues reachthe source node. Waiting out vehicles are not included in the computation of travel time and by nothaving waiting out vehicles, travel time indicators become more comparable. A network withlengthened source links however dilutes the differences in performance between schemes.Therefore more weight should be given on the ranking of performance indicators rather than thescale of differences.
1
2 3
4
56
A1 Street A2 Street A3 Street
B Street C StreetBus stop 1 Bus stop 2
1
2 3
4
56
A1 Street A2 Street A3 Street
B Street C StreetBus stop 1 Bus stop 2
Figure 4.1: Hypothetical network
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Table 4.1: Features of the hypothetical network
Item Description
A1, A2 & A3 Street A1 Street length: 5900 m (source link)
A2 Street & A3 Street length: 350 m
1 direction, 3 lanes Left slip lane: 50 m
Speed limit: 70 km/h
B & C Street B & C Street (source link) length: 5700 m
B & C Street (sink link) length: 600 m
1 direction, 2 lanes
Speed limit: 70 km/h
Traffic signal The traffic signals utilised two phases. Phase A includes through movement on A Street, and left turn movement ontoB or C Street where applicable. Phase B includes through and right turn movement for B or C Street.
A fixed-time setting was utilised assuming a cycle time of 90 s. Yellow is set at 4 s and all red at 2 s. Cycle time higherthan 90 s up to 120 s were tested and did not alter the conclusions of the study.
Phase splits were adjusted depending on the scheme utilised.
20 s offset between signals was also set to facilitate traffic progression. Signal priority for buses is optional.
Microsimulation parameters recommended in Austroads project no. NS1229 MicrosimulationStandards(ARRB 2007) were adopted in this study. The guidelines were not specific on the settingof signposting in AIMSUN. Signposting provides warning to drivers on lane changes and mergebehaviour. Signposting affected the performance of SBBL schemes and was calibrated for themodels used in this study (Appendix C).
4.1.2 Traffic Demand
The rate of input demand was uniform over one hour. Demand was set to zero after one hour ofsimulation. The simulation period was then extended by 1.5 h such that all vehicles have exited thenetwork. Moreover, a warm-up period of 15 min was used.
The comparison of ORPT priority schemes was undertaken under various input traffic volumes. A15% left turn was assigned to A Street traffic volume. A 25% right turn was assigned to B Streetand C Street traffic volume. Vehicles turning left from A1 Street and A2 Street are compensated byright turning traffic volume from B Street and C Street, such that the traffic demand on A1 Street,A2 Street and A3 Street are the same. Table 4.2 details the demand assumed for the comparativeanalysis.
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Table 4.2: Traffic demand
No. Total inputdemand, veh/h
Congestionlevel
Volume by sourcenode(2), veh/h
A1 Street volume, veh/h A2 Street volume(3), veh/h B Street volume, veh/h C Street volume, veh/h
1 5 6 L(1) T All L T All R T All R T All
1 7150 Oversaturated
conditions
3300 1925 1925 495 2805 3300 495 2805 3300 495 1430 1925 495 1430 1925
2 6500 3000 1750 1750 450 2550 3000 450 2550 3000 450 1300 1750 450 1300 1750
3 5850 Near-saturated
conditions
2700 1575 1575 405 2295 2700 405 2295 2700 405 1170 1575 405 1170 1575
4 5200 2400 1400 1400 360 2040 2400 360 2040 2400 360 1040 1400 360 1040 1400
5 4550 Undersaturated
conditions
2100 1225 1225 315 1785 2100 315 1785 2100 315 910 1225 315 910 1225
6 3900 1800 1050 1050 270 1530 1800 270 1530 1800 270 780 1050 270 780 1050
1 L = left turn, T = through, R = right turn.2 Refer to network below.3 Includes right turn traffic from B Street and through traffic from A1 Street.
1
2 3
4
56
A1 Street A2 Street A3 Street
B Street C StreetBus stop 1 Bus stop 2
1
2 3
4
56
A1 Street A2 Street A3 Street
B Street C StreetBus stop 1 Bus stop 2
(Repeated from Figure 4.1).
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4.2 Set Back Bus Lane Models
Four SBBL models were developed based on the four scenarios described in Section 3.4.1. TheSBBL models are illustrated in Figure 4.2 and are described in Table 4.3.
A1 Street A2 Street A3 Street
B Street C Street
(a) SBBL-1
(b) SBBL-2
(c) SBBL-3
A1 Street A2 Street A3 Street
B Street C Street
A1 Street A2 Street A3 Street
B Street C Street
(d) SBBL-4
A1 Street A2 Street A3 Street
B Street C Street
A1 Street A2 Street A3 Street
B Street C Street
(a) SBBL-1
(b) SBBL-2
(c) SBBL-3
A1 Street A2 Street A3 Street
B Street C Street
A1 Street A2 Street A3 Street
B Street C Street
(d) SBBL-4
A1 Street A2 Street A3 Street
B Street C Street
Figure 4.2: SBBL design scenarios
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Table 4.3: SBBL models
ID Start and end point of the serial SBBL Car use of the approach-side kerbside lane anddeparture-side set back
Start point of the serial SBBL End point of the serial SBBL
SBBL-1 At the source node, i.e. node 1 100 m upstream from the
stopline at A2 Street
Left turn and through
Departure-side set back of 80 m at A2 Street
SBBL-2 At the source node, i.e. node 1 100 m upstream from thestopline at A1 Street
Left turn and through
Departure-side set back is not applicable
SBBL-3 At the source node, i.e. node 1 100 m upstream from thestopline at A2 Street
Left turn only
No departure-side set back at A2 Street
SBBL-4 250 m upstream from the stopline at A1 Street
100 m upstream from thestopline at A1 Street
Left turn and through
Departure-side set back is not applicable
SBBL-1 and SBBL-2 were used to test the effect of increasing the approach-side set back. For thispurpose, SBBL-1 and SBBL-2 with approach-side setbacks of 100 m and 150 m were set up.
To simulate signal priority in the models, detectors were placed at the end of the bus lane. Buseswere equipped with special transponders which can be detected by the detectors. Bus detectionwould trigger changes in the signals to give priority to the bus. Changes in the signals depend onthe state of the traffic signal when the bus is detected and are detailed in Table 4.4. APIs weredeveloped to apply the various signal priority actions. It is noted that the use of transponders wereonly for the purpose of modelling in AIMSUN and different technologies may be used in practice.
Table 4.4: SBBL traffic signal priority scheme
Condition when bus is detected at the end of the SBBL Actions(1)
More than 10 s before phase A terminates
(i.e. early in phase A)
Do-nothing
Bus can pass through
Less than 10 s left before phase A terminates
(i.e. late in phase A)
Extend phase A
Call phase B with adjusted(2) phase time
Within the first 30 s of phase B
(i.e. before minimum green has been given to phase B)
Terminate phase B after minimum green of 30 s
Call phase A with adjusted phase time
After 30 s of phase B
(i.e. after minimum green has been given to phase B)
Terminate phase B immediately
Call phase A with adjusted phase time
1 Normal operation ensues after the last action.2 Phase time adjustment was based on maintaining the offset between the two traffic signals.
4.3 Queue Jump Bus Lane ModelsTwo QJBL models were developed based on the two scenarios described in Section 3.4.2. TheQJBL models are illustrated in (Figure 4.3) and are as follows:
QJBL-1: with departure-side merge lane
QJBL-2: without a departure-side merge lane.
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A1 Street A2 Street A3 Street
B Street C Street
(a) QJBL-1
(b) QJBL-2
A1 Street A2 Street A3 Street
B Street C Street
Figure 4.3: QJBL design scenarios
The left turn auxiliary lanes were extended from 50 m in the base model to 100 m in the QJBLmodels to reduce the possibility of queues blocking entry to the short bus lane. The length of thedeparture-side merge lane, when provided, was set to 80 m (Table 3.2).
Limited and full signal priority modes were considered in this study. Under limited signal priority,
the traffic signals in the QJBL models call a bus phase when a bus is detected in the short bus lanebefore phase A. Practice in signal priority for buses tend not to use phase termination (source:e-mail from RTA, dated 1 August 2011). Under full signal priority, the bus phase is called at theearliest possible opportunity whenever a bus is detected in the short bus lane. Traffic signals willchange depending on the state of the traffic signal when the bus is detected, as described inTable 4.5 in the case of no red B signal and Table 4.6 in the case with red B signal. APIs weredeveloped to operate the signal priority in the MSTM models.
Table 4.5: QJBL signal scheme with no red B signal
Condition when bus is detected at the short bus lane Actions(1)(2) Level of signal priority
Full Limited
Phase A Do-nothing (i.e. bus can pass through) Active Off
During the first 30 s of phase B
(i.e. before minimum green has been given to phase B)
Terminate phase B after minimum green of 30 s Call bus phase Call phase A with adjusted phase time
Active Off
After 30 s of phase B
(i.e. after minimum green has been given to phase B)
Terminate phase B immediately (only for full signalpriority)
Wait for phase B to terminate (only for limited signalpriority)
Call bus phase Call phase A with adjusted phase time
Active Active
1 Normal operation ensues after the last action.2 Phase time adjustment was based on maintaining the proper cycle time.
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Table 4.6: QJBL signal scheme with red B signal
Condition when bus is detected at the short bus lane Actions(1) Level of signal prior ity
Full Limited
During the first 32 s of phase A
(i.e. before minimum green has been given to phase A)
Terminate phase A after minimum green of 32 s
Call bus phase
Call phase B with adjusted(2) phase time
Active Off
After 32 s of phase A
(i.e. after minimum green has been given to phase A)
Terminate phase A immediately
Call bus phase
Call phase B with adjusted phase time
Active Off
During the first 30 s of phase B
(i.e. before minimum green has been given to phase B)
Terminate phase B after minimum green of 30 s
Call bus phase
Call phase A with adjusted phase time
Active Off
After 30 s of phase B
(i.e. after minimum green has been given to phase B)
Terminate phase B immediately (only for full signalpriority)
Wait for phase B to terminate (only for limited signalpriority)
Call bus only phase
Call phase A with adjusted phase time
Active Active
1 Normal operation ensues after the last action.2 Phase time adjustment was based on maintaining the proper cycle time.
As previously noted, bus drivers have the option to use the short bus lane or stay on the main linein QJBL. Two bus driver route choice modes were considered as follows:
The flexible mode assumes that the bus drivers have perfect knowledge of the traffic signalswhich allow them to rationally choose between staying on the main line or to use the shortbus lane to minimise bus travel time.
The restricted mode assumes that the bus driver uses the short bus lane all the time.
The modelling of the restricted mode is straightforward. Modelling the flexible mode required theuse of APIs. A decision point was defined upstream of the intersection, approximately 100 m fromthe stop line. Once a bus passes the decision point, a selection is made to either route the busthrough the short bus lane or to allow it to stay on the main line. The selection was based on whichroute will reduce the time to cross the intersection. The selection logic is as follows:
If the bus arrives at the decision point 6 s before phase A terminates, the bus will stay on themain line, i.e. the bus can pass through.
In all other conditions the bus will use the short bus lane.
In AIMSUN, public transport lines could not be modified during simulation. The choice of busdrivers to use the short bus lane or stay on the main line could not be modelled conventionally. Itwas therefore necessary to model buses in the QJBL models as general traffic. Vehicle dimensionsand operational characteristics of buses are maintained. Modelling buses as general traffic makesit possible to manipulate the choice of road section to use by API. Bus stops were alsoprogrammed using API, by assigning road sections where buses stop akin to roadside parking.
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5 SIMULATION RESULTS
This section presents the results and findings of the MSTM comparatives studies. Section 5.1compares the performance of the four selected bus priority schemes. Section 5.2 and Section 5.3
presents the results of the comparison of sub-cases for SBBL and QJBL respectively. Section 5.4is a summary of the results and findings.
The comparisons were based on average travel time and standard deviation of travel time. InAIMSUN, travel time is defined as the average time it takes a vehicle to travel from the origin to thedestination and is expressed in terms of s/km. This is the mean of all individual vehicles travel time(exit time - entrance time). Person travel time is the weighted travel time of cars and buses,assuming occupancy of 1.2 persons per car and 20 persons per bus. The mean of five simulationrepetitions was sufficient for comparison between schemes.
5.1 Comparison of Selected Bus Priority Schemes
This section compares the relative performance of the selected bus priority schemes including NP,FBL, SBBL and QJBL. SBBL-1 (described in Section 4.2) and QJBL-1 (described in Section 4.3)were selected as the representative schemes for SBBL and QJBL for the analysis in this section.The performance indicators of the bus priority schemes are illustrated as follows:
5-min bus headway: average travel time in Figure 5.1 and standard deviation of travel time inFigure 5.2
2-min bus headway: average travel time in Figure 5.3 and standard deviation of travel time inFigure 5.4.
Average travel time and standard deviation of travel time was calculated separately for car and busas well as for people. People or overall travel time and standard deviation of travel time combines
car and bus travellers. In certain cases, e.g. Figure 5.2, car and people travel time indicatorsappear very similar because majority of the traveller count are car travellers.
The comparison of the four schemes can be depicted as Figure 5.5. The x-axis and y-axis ofFigure 5.5 depicts the average travel time for bus and car respectively when bus headways areand short. Schemes are located in the chart depending on their relative performance. Schemesthat are closer to the origin (i.e. x = 0 and y = 0) have relatively good performance resulting in lowcar and bus travel time. It is often the case that schemes would involve varying trade-offs in carand bus travel time. Findings were as follows:
At undersaturated conditions, there was no benefit from bus priority treatment.
At near-saturated conditions, the following were noted:
When bus headways are long, QJBL and NP resulted in low and reliable bus and cartravel time. When bus headways are short, NP resulted in better bus and car traveltimes than QJBL due to disruptions caused by the frequent activation of the bus onlysignal phase in QJBL. It may be worth considering not providing a bus only phase inQJBL, provided that a departure-side merge lane is present.
SBBL and FBL also resulted in similarly low and reliable bus travel time but car traveltime was adversely affected due to the reduced road space for cars. Overall travel time(i.e. combining bus and car travellers) in SBBL was better than in FBL.
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At oversaturated conditions, the following were noted:
When bus headways are long, QJBL resulted in the lowest and most reliable overalltravel time. When bus headways are short, NP performed better than QJBL due to thesame reason noted in near-saturated conditions.
Bus travel time in QJBL and NP were high and unreliable and may not be adequate forpromoting modal shift towards bus. The good overall travel time performance in QJBLand NP was largely due to lower car travel time than in SBBL or FBL.
Regardless of bus headway, SBBL and FBL resulted in low and reliable bus operationwhich was suitable for promoting buses. However, high and unreliable car travel time inSBBL and FBL deteriorated overall travel time. The poor overall travel time results ofSBBL and FBL in the experiments were overstated because the linear highway networkused in the analysis did not allow cars to re-route. SBBL and FBL could potentiallyhave a better overall travel time result than QJBL or NP if other measures are appliedin conjunction with SBBL and FBL to mitigate their adverse effects on car travel time.Overall travel time performance of SBBL was better than FBL.
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(a) Car
(b) Bus
(c) People
0
50
100
150
200
250
3000 4000 5000 6000 7000 8000
Averagetraveltime,
s/km
Total traffic demand, veh/h
NP
FBL
SBBL1
QJBL1
0
20
40
60
80
100
120
140
160
3000 4000 5000 6000 7000 8000
Averagetraveltime,
s/km
Total traffic demand, veh/h
NP
FBL
SBBL1
QJBL1
0
50
100
150
200
250
3000 4000 5000 6000 7000 8000
Averagetrave
ltime,
s/km
Total traffic demand, veh/h
NP
FBL
SBBL1
QJBL1
Figure 5.1: Average travel time under various ORPT schemes at 5-min bus headway
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(a) Car
(b) Bus
(c) People
0
20
40
60
80
100
120
3000 4000 5000 6000 7000 8000
Standarddeviationoftrave
ltime,
s/km
Total traffic demand, veh/h
NP
FBL
SBBL1
QJBL1
0
5
10
15
20
25
30
35
40
3000 4000 5000 6000 7000 8000
Stand
arddeviationoftraveltime,
s/km
Total traffic demand, veh/h
NP
FBL
SBBL1
QJBL1
0
20
40
60
80
100
120
3000 4000 5000 6000 7000 8000
Standarddeviationo
ftraveltime,
s/km
Total traffic demand, veh/h
NP
FBL
SBBL1
QJBL1
Figure 5.2: Standard deviation of travel time under various ORPT schemes at 5-min bus headway
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(a) Car
(b) Bus
(c) People
0
50
100
150
200
250
3000 4000 5000 6000 7000 8000Total traffic demand, veh/h
Averagetraveltime,
s/km
NP
FBL
SBBL1QJBL1
0
20
40
60
80
100
120
140
160
180
3000 4000 5000 6000 7000 8000Total traffic demand, veh/h
Averagetraveltime,
s/km
NP
FBL
SBBL1
QJBL1
0
50
100
150
200
250
3000 4000 5000 6000 7000 8000Total traffic demand, veh/h
Averagetrav
eltime,
s/km
NP
FBL
SBBL1
QJBL1
Figure 5.3: Average travel time under various ORPT schemes at 2-min bus headway
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(a) Car
(b) Bus
(c) People
0
20
40
60
80
100
120
3000 4000 5000 6000 7000 8000Total traffic demand, veh/h
Standarddeviationoftrave
ltime,
s/km
NP
FBL
SBBL1
QJBL1
0
10
20
30
40
50
60
3000 4000 5000 6000 7000 8000Total traffic demand, veh/h
Standarddeviationoftraveltime,
s/km
NP
FBL
SBBL1
QJBL1
0
20
40
60
80
100
120
3000 4000 5000 6000 7000 8000Total traffic demand, veh/h
Standarddeviation
oftraveltime,
s/km
NP
FBL
SBBL1
QJBL1
Figure 5.4: Standard deviation of travel time under various ORPT schemes at 2-min bus headway
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NP: No priority
FBL: Full bus lane
SBBL: Set back bus lane
QJBL: Queue jump bus lane
Long bus headways
Short bus headways
Figure 5.5: Relative performance of ORPT schemes for car and bus travel
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5.2 Set Back Bus Lane Model Results
This section examines the SBBL scheme in the following aspects:
utilisation of the kerbside lane under varying configurations of the SBBL that is applied
serially travel time benefits of signal priority in SBBL.
Five numerical experiments with 5-min bus headway were conducted and the results are illustratedas follows:
comparison of SBBL-2 and SBBL-4 to examine the start point of the SBBL (Figure 5.6)
comparison of SBBL-1 and SBBL-2 to examine the end point of the serial SBBL (Figure 5.7)
comparison of SBBL-1 and SBBL-3 to investigate allowing through cars on the kerbside laneby providing or not providing merging space on the departure-side (Figure 5.8)
comparison of SBBL-1 and SBBL-2 with short and long approach-side setbacks to examinethe applicability of a long approach-side set back (Figure 5.9 and Figure 5.10)
comparison of SBBL-1 with and without signal priority to investigate the effectiveness ofincorporating signal priority with SBBL (Figure 5.11).
Findings were as follows:
Results on the analysis of provision of a departure-side set back were as follows:
Bus travel time was low in the case of the SBBL with a departure-side set back (i.e.SBBL-1) than in the case of the SBBL without a departure-side set back (i.e. SBBL-3),although bus travel time in SBBL-1 was slightly higher than in SBBL-3.
SBBL-1 allowed through cars to use the kerbside lane and thereby more cars wereable to pass through the intersection per cycle, resulting in lower car travel time than inSBBL-3.
The MSTM results therefore suggest that providing a departure-side set back on serialSBBL is recommendable.
Results on the analysis of the location of the start and end point of a serial SBBL were asfollows:
The start of a serial SBBL can be located just beyond the maximum queue of the firstbottleneck section along a bus route (SBBL-4); or further upstream where congestionlevels remain undersaturated (SBBL-2). The following were noted:
The serial SBBL which started at the bottleneck section just beyond themaximum queue length resulted in high bus travel time at near-saturated andoversaturated conditions. The SBBL which started further upstream beyond theinfluence of the bottleneck section (i.e. SBBL-2) resulted in low and reliable bustravel time. There was no appreciable difference in terms of car travel timebetween the two scenarios.
The mid-block bus lane in the case of SBBL-4 created a point where the roadwaycross-section changed, which induced lane changing manoeuvres in cars. Thisresulted in a drop in capacity at this particular point and caused delays for cars,particularly cars on the kerbside lane at near-saturated and oversaturatedconditions. Buses which primarily use the kerbside lane to access the mid-blockbus lanes and stations were slowed down considerably as well.
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The selection of the starting point of a serial SBBL is therefore critical to theperformance of the SBBL. The MSTM results suggest that a serial SBBL shouldbe started at a section further upstream of the bottleneck section where thecongestion levels are low enough to avoid or minimise problems that would arisefrom the change in roadway cross-section. It is insufficient to start the serialSBBL just beyond the maximum queue length of the first bottleneck section.
The findings suggest that inbound serial SBBL should start further upstream fromthe central business district (CBD) where congestion levels tend to be lower.
The end point of a serial SBBL can be located right after the last bottleneck sectionalong a bus route (SBBL-2) or further downstream of the last bottleneck section(SBBL-1). The following were noted:
SBBL-2 resulted in better travel time for cars and buses than in SBBL-1).
The traffic volume entering the section downstream of a bottleneck was regulatedby capacity constraints of the bottleneck. The section downstream of the
bottleneck section therefore did not require a mid-block bus lane to maintainreliable bus operation. Furthermore, it proved advantageous to allocate moreroad space to cars instead of extending the mid-block bus lane beyond what isrequired for bus operation.
The MSTM results suggest that a serial SBBL should end right after the lastbottleneck road section to maximise road allocation for cars while maintaininggood bus operation.
Results on the analysis on the length of the approach-side set back were as follows:
Lengthening the approach-side set back had different effects depending on thepresence of a downstream SBBL. If there was no downstream SBBL (i.e. SBBL-2)longer set back resulted in improved car travel time due to increased utilisation of thekerbside lane. Bus travel time increased beca