- SIDRA INTERSECTION Network Model
- Example to Demonstrate the Lane-Based Network Model
- What can SIDRA NETWORK Model Do?
A Unique Lane-Based Network Model for Solving Complex Network Design Challenges and Developing Measures to Alleviate Network Congestion
The network model developed for SIDRA INTERSECTION is a lane-based micro-analytical model unlike traditional analytical link-based network models where links represent lane groups in which traffic conditions of individual lanes are aggregated and therefore lost in more aggregated traffic units. An approach-based method is a more extreme case of this where differing conditions of traffic in all approach lanes are aggregated to some assumed average (balanced) condition. Such link-based (lane-group based) and approach-based network models cannot identify backward spread of congestion for closely spaced intersections.
While estimation of individual lane capacities, lane flows and lane queues are important in assessing performance of a single intersection, this becomes even more important in modeling closely spaced intersections. Lane capacities, lane flows and lane queues for downstream and upstream approaches may be highly interdependent in cases of closely spaced intersections, and therefore, a lane-based method is essential for reliable modeling of network performance.
The reasons why a lane-based network model is needed to identify backward spread of congestion for closely spaced intersections include the following:
- upstream lanes will be affected by downstream (exit) lane queues according to the destinations of movements using upstream lanes,
- saturation levels (v/c ratios), therefore queue blockage probabilities of individual lanes on an approach can differ significantly,
- lane under-utilization can exist due to various reasons including differences in number of lanes available to particular movements on upstream and downstream approaches, and
- the balance of upstream and downstream lane flow rates on an internal approach considering lane change implications within a short distance where long queues exist is also an important consideration.
SIDRA INTERSECTION employs a lane-based micro-analytical network model which satisfies these requirements. The basic aspects of this network model are described briefly in this section followed by an example of staggered-T roundabouts.
Two fundamental elements of the lane-based traffic network model developed for, and implemented in, the SIDRA INTERSECTION software are:
- determination of the backward spread of congestion as queues on downstream lanes block upstream lanes, and
- application of capacity constraint to oversaturated upstream lanes for determining exit flow rates, thus limiting the flows entering downstream lanes.
These two elements are highly interactive with opposing effects. A network-wide iterative process is used to find a solution that balances these opposing effects. This process is implemented as follows:
- Intersection turning volumes specified as input and adjusted for Unit Time for Volumes, Peak Flow Factor, Flow Scale and Growth Rate parameters are treated as demand flow rates.
- Differences between upstream and downstream demand flow rates (resulting from differences in input volumes) are treated as midblock inflows (volume gains) and outflows (volume losses).
- Capacity constraint is applied to departures from oversaturated lanes for determining exit (departure) flow rates. Accordingly, the exit flow rate is determined as the smaller of arrival flow rate and capacity.
- For each internal approach, upstream lane flow rates are determined from exit flow rates according to origin-destination characteristics of traffic departing from all upstream lanes.
- For each internal approach, arrival flow rates at downstream locations are determined according to upstream exit flow rates and net inflow rates (midblock inflows and outflows).
- Flow proportions specified as input for Lane Movements (i.e. movements linking each approach lane to each exit lane available) are used for assigning origin - destination movements departing from each approach lane to their exit lanes as well for determining the queue blockage effect of each exit lane on each approach lane at an intersection.
- Queue blockage probabilities are used to adjust (reduce) capacities at upstream intersection lanes according to lane-by-lane queue blockage effects, thus emulating backward spread of congestion.
- Reduced capacities at upstream lanes may cause oversaturation and result in lower exit flows. This will lead to reduced arrival flows at downstream intersection lanes, and queue blockage probabilities will be lower as a result. This would mean less capacity reduction during next iteration. An equilibrium solution is sought subject to various parameters that control iterations.
Output reports highlight the differences between demand flow rates and arrival flow rates to indicate quickly where lane blockage effects exist. Lane blockage probabilities and capacity adjustment values are also included in output.
An example of staggered-T roundabouts (two T-shaped roundabouts placed with 50 m distance between them) is considered to demonstrate the lane-based network model.
The roundabout geometry and volume data as well various other parameter values are shown in Figure 9.1. The example is for driving on the right-hand side of the road as it has been prepared for a paper to be presented at the Canadian ITE (CITE 2013) conference. The paper is available for download:
AKÇELIK, R. (2013). Lane-based micro-analytical model of a roundabout corridor. Paper was presented at the CITE 2013 Annual Meeting, Calgary, Alberta, Canada, 7-10 April 2013.
In this example, the volumes between the two intersections have been matched perfectly in order to make understanding of results easier.
The example given here assumes that only Turning Volumes are known at each intersection (network origin - destination flows are not known). Default settings are used generally (no Lane Movement Flow Proportions, "Set as Dominant" for roundabout lanes or Lane Utilization Ratios are specified).
The network model iterations were carried out until the difference in any lane degree of saturation is less than 1 per cent (Stopping dx = 1% in the Network Data dialog). The results are summarized in Table 9.1. It is seen that:
- capacity constraint applies to Site 2 South approach (degree of saturation > 1.0) and this results in reduced arrival flows at Site 1, South approach (reduced from 1090 veh/h to 1035 veh/h);
- queues on Site 1 South approach lanes block departures from Site 2 South and East approach lanes resulting in applying capacity reductions to those lanes;
- queues on Site 2 North approach lanes indicate small blockage probabilities resulting in a small effect on Site 2 North approach Lane 1 but no effect on Site 2 West approach lanes (no effect on Lane 1 since it exits to North and no effect on Lane 2 since the probability of blockage is less than the tolerance margin of 5 % (user input)).
The example also shows that there are many side-effects of changes in arrival flows due to downstream queue blockages and resulting upstream capacity reductions. For example, changes in circulating flow rates and the lane balance of circulating flows result in roundabout entry lane capacity changes.
Comparison of the results of this analysis with the results when it is assumed that the Network Origin - Destination flows are known in addition to the intersection turning volumes is given in the CITE 2013 conference paper. The paper discusses how well the upstream and downstream lanes flows for internal approaches match under these assumptions.
SIDRA INTERSECTION employs a unique lane-based micro-analytical network model unlike traditional link-based network models where links represent lane groups in which traffic conditions of individual lanes are aggregated and therefore lost in more aggregated traffic units. Such link-based (lane-group based) and approach-based network models cannot identify backward spread of congestion for closely-spaced intersections adequately.
SIDRA INTERSECTION allows you to evaluate the performance of a Network with interactions between component Sites. The SIDRA INTERSECTION network model will:
- allow the user to configure a detailed lane-based Network including signalised and sign-controlled intersections and roundabouts with ease;
- allow user-specified Route definitions for performance reports and displays, and for signal offset calculations;
- provide detailed Network and Route performance estimates in a variety of output reports and displays (including Route travel time and distance);
- determine blockage of upstream lanes by downstream queues;
- estimate capacity reduction of upstream lanes due to lane blockage;
- emulate backward spread of congestion (queue spillback);
- apply capacity constraint to oversaturated upstream lanes to determine exit flow rates and limit the flows entering downstream lanes;
- take into account midblock inflow and outflow rates implied by user input of Site volumes;
- allow the user to control lane movement flow proportions to determine the exit lane use;
- determine midblock lane changes implied by upstream and downstream lane flow rates so that the user can calibrate external approach lane use patterns;
- use a network-wide iterative process to find a solution that balances the opposing effects of lane blockage and capacity constraint;
- determine network cycle time, phase times and signal offsets for coordinated signal systems;
- determine signal timings for Common Control Groups (several signalised intersections operating under a single signal controller);
- use second-by second arrival and departure flow patterns as a function of signal Offsets to model forward movement of signal platoons for coordinated signal Sites including a unique platoon dispersion model;
- apply midblock lane changes when moving second-by second signal platoon patterns between intersections;
- use the extra bunching parameter determined by the program to allow for the effect of upstream signals on gap-acceptance capacity of roundabouts and two-way sign-controlled intersections;
- allow the use of Special Movement Classes to represent Through movements at external approaches which become turning movements at downstream internal approaches, and the dogleg movements between side roads of two closely-spaced intersections; allocate these movements to specific approach lanes according to movement through the network; and track second-by-second signal platoons for these movements separately.