VISSIM: 3rd UK USER Group Meeting
(
more info on: http://www.ptv-newcastle.co.uk/UG3/program.htm
Summary of presentations (the programme can be accessed on:
http://www.ptv-newcastle.co.uk/UG3/UGM3_program_outline_0303.htm):
Optimising
Traffic Signals in VISSIM. A Comparison with LINSIG and TRANSYT Models
By
Sonal Ahuja (Mott MacDonald)
Pedestrian
Simulation with VISSIM
Use
of VISSIM for Strategic Highway Modelling
By
Dave Keenan and Stuart McNaughton (Faber Maunsell)
Measurement
of saturation flow and degree of saturation across signal controlled stoplines
in VISSIM
By
Ioannidis Ioannis (Transport for London)
By
Budi Yulianto (TORG, School of Civil Engineering and Geosciences, University of
Newcastle)
By Sonal Ahuja (Mott MacDonald)
Abstract
Traffic
signals are essential traffic management tools in urban conditions. The design of signals has been an evolving
science, driven by the need to make best use of available road space, and
changing policy objectives, moving away from capacity maximisation or delay
minimisation for private vehicles, towards priority operations for public
transport, recognising the passenger numbers transported.
Traditional
design tools to calculate signal timings in the
§ • inaccurate representation of blocking back, the
vertical queuing assumptions underestimating the interactions between closely
spaced junctions
§ • inability to model dynamic changes in demand,
particularly pedestrian demand
§ • poor validation, i.e. fit with observed
conditions
As
an alternative design tool a VISSIM microsimulation
model was set up to assess and design the appropriate signal timings. This involved development of a traffic signal
optimiser that minimises some measure of delay for road traffic whilst
allocating priority to public transport.
Comparative
results show that:
§ • traditional, average flow rate based tools such
as TRANSYT and LINSIG have severe limitations in evaluating congested corridors
§ • microsimulation,
because of its dynamic and disaggregate nature, can produce a much better fit
to observed conditions
§ • the VAP vehicle actuated programming capability
of VISSIM enables us to develop a signal optimiser that will both calculate an
optimum signal design and show its operation in reality.
By Paul Clifford (Babtie)
Abstract
This presentation will set out
current experience with the simulation of pedestrian movements and behaviour
with VISSIM and explore the potential to assist interchange design, both on the
highway and for public transport systems. The integration of highway and
pedestrian networks and the analysis criteria for performance review will be
discussed.
By Dave Keenan and Stuart McNaughton (Faber Maunsell)
Abstract:
The presentation will introduce the use of VISSIM for large-scale and strategic modelling purposes.
Two examples will be discussed:
1. Objective
One Study,
This model covers the motorway network in
2. M1, J.40 Ramp Metering Study
M1 in the vicinity of J.39 – 42 (just south of the M62) suffers from severe congestion in the weekday peak periods due to large volumes of traffic attempting to merge with the mainline flow. Under work commissioned by the Highways Agency FaberMaunsell constructed a three-junction network of the M1 motorway in the area, to examine the potential benefits available from ramp metering of the merge flows. Journey time measurements and the concept of Level of Service categories were used extensively to monitor changes in mainline performance, and compare the benefits available from different methods of metering at three-year intervals through to 2011.
By Serbjeet Singh Kohli
Abstract:
The presentation explains the use of various existing data
sources to develop large VISUM networks. Developing large networks in VISUM, or
as a matter of fact in any other modelling package, is a time consuming
exercise. VISUM provides the flexibility of converting external data sources to
VISUM networks. VISUM offers a unique feature, through the Shapefile
converter and other interfaces, to create the basic network consisting of links
and nodes from GIS information such as landline data, digitised OS maps, Featureline database etc. Further information about the
link types/lengths can also be imported to VISUM in the conversion process. Hence
landline data and digitised OS maps become the basic data source for highway
network building. Public transportation networks can be converted from VIPS
networks to VISUM networks as VIPS has a direct format interface with VISUM. Information
about public transportation lines, routes, timetables etc. can be imported
directly from VIPS into the VISUM network format. Area level zoning information
such as census statistics, land use information and socio-economic data can
also be imported from MAPINFO/GIS database as a separate file. This file can be
appended to the link and node networks by reading the network file additionally
to the VISUM highway network. VISUM can read EMME/2 files therefore information
from the existing EMME/2 models can be imported into VISUM networks. VISUM has
an interface with MS ACCESS, which works as a key in the integration of
different networks.
Mott MacDonald is currently in the process of building a
comprehensive highway and public transportation network for the
The public transportation network has been imported from the
bus network from the existing VIPS model. Since the bus network uses the road
network, for development of PRISM network the bus network had to be merged with
the highway network. The facility of exporting VISUM networks to other
databases like MS ACCESS was used to achieve this. In addition VISUM has the
facility for matching bus routes on the highway network if the bus stops are
merged with the highway network.
This facility was used to generate bus routes in the highway
network. For the rail network, data from existing CENTRO model for
In summary VISUM provides a unique set of interface features that help the development of a network faster. Our experience with the development of a mammoth network for PRISM in a relatively short time has been more successful than conventional methods.
By Ioannidis Ioannis (Transport for
Abstract:
This is a presentation of a subroutine that is based on the SCATS methodology of measuring the degree of saturation and consequently the saturation flow across a signal controlled stopline. The technique relies on the presence of a detector per lane just downstream of every signal stopline.
The subroutine can be adjusted quite easily to monitor as many stoplines and number of detectors as the user requires for every specific junction. A separate copy of it has to be attached to the VAP file that contains the control logic of every signal controlled junction. All the information needed about detector number and signal group (phase) numbers are contained in the VAP file that controls the junction and the saturation flow subroutine, receives the information necessary from there.
Methodology
The degree of saturation according to this technique is the ratio of the time vehicles are occupying a detector plus the total of time headways when vehicles follow each other under saturated conditions over the time the traffic lights are on green or leaving amber.
The time when vehicles are occupying a detector, the number of vehicles as well as the time when traffic lights are green or amber is measured accurately during every single cycle.
The saturated time headway however for each lane is not a variable that can be measured accurately. A value for this headway has to be assumed for each lane which is used at the beginning of the simulation period. At the end of each of the first sets of green the degree of saturation is calculated using the value of saturated time headway assumed initially. If the degree of saturation as a result of this value is above 1.0 then this means that vehicles were travelling closer to each other during the green period just finished than the time headway used for the calculation. As a result a new value of the time headway is now worked out that will be used for the calculation of the degree of saturation at the end of the green in the next cycle. This is done by dividing the part of the green plus amber time when the detectors were not occupied by vehicles by the total number of vehicles that went over the detector in the green and amber period just finished.
This process is repeated until the value of the time headway in each lane stops being decreased and stabilises around a value that represents the actual saturated time headway for the way the geometric characteristics of that lane have been modelled in VISSIM at that point and the vehicle characteristics of the traffic composition using this lane.
From trials using this methodology and this subroutine in VISSIM models it was found that this process takes about 15 minutes of simulated time and then the saturated time headway reaches a stable value. Beyond this point the degree of saturation for each lane or across a stopline can be considered an accurate measure of what is the degree of saturation across each stopline of the junctions that are monitored by this subroutine.
Having determined the degree of saturation the saturation flow for each stopline is calculated from the formula:
Traffic demand v * C
Degree of saturation = ------------------------ = --------------
Traffic capacity S * g’
Where v = traffic demand (veh/hour)
C = cycle length (seconds)
S = saturation flow (veh/hour)
g’ = eff.green (seconds)
By Chris Pownall (MVA)
Abstract:
A traffic model of the centre of Dalkeith has been created on behalf of Midlothian Council, to predict the impact on traffic flow and parking requirements of the redevlopment of the town centre areas. The model includes all key links in the town cnetre area and is capable of representing the performance of streets and junctions under current week-day peak traffic levels.
The model has been used to test a number of proposed traffic management schemes. Most of these involve the diversion of A68 trunk route which currently runs through the town centre onto other routes, in order to reduce traffic levels in the principal shopping areas.
The model will make use of VISSIM's 3D graphics capabilities, to allow stakeholders to see the combined impact of the redevelopment proposals and the associated traffic management measures on the town.
By Budi Yulianto (TORG,
Abstract:
Traffic signal control is commonly used at road intersections to minimise travel time and delay. In time-varying traffic conditions, a fixed time controller becomes inflexible and not efficient. Using fuzzy logic, traffic signal controllers can be made more adaptive to traffic demands. However, most existing applications of fuzzy logic traffic signal controls are based on non-mixed traffic conditions, where they consider the passenger car only and neglect small-size vehicles such as motorcycles.
This paper describes the design and evaluation of an adaptive traffic signal controller based on fuzzy logic for an isolated four-way intersection with specific reference to mixed traffic (including high proportion of motorcycles). The controller is designed to be responsive to real-time traffic demands. The fuzzy controller uses video image processing to capture traffic data such as average occupancy rate (%) and maximum queue length (in metres) from each approach of the intersection. The proposed Fuzzy Logic Signal Controller (FLSC) uses maximum queue lengths and average occupancy rates collected during the previous cycle in order to estimate the number of seconds of green time required by each set of signal groups (stage) during the next cycle.
The effectiveness of the proposed fuzzy logic signal controller was examined and analysed by the simulation program VISSIM. The performance of this controller is compared to an optimised fixed time controller for different traffic conditions on a simulated an isolated four-way intersection. Simulation results showed better performance of the fuzzy logic signal controller when compared to an optimised fixed time controller in terms of the average travel time and the average delay of vehicles, especially under time-varying traffic conditions.
Keyword: Traffic signal control; Fuzzy logic; Mixed traffic; Video image processing; Isolated intersection; Simulation, VISSIM.