Traffic congestion: Reconstruction with Kerner's three-phase theory
The traffic flow models ASDA and FOTO based on Kerner Boris three-phase traffic theory, can detect traffic congestion on highways and track in time and space ( Fig. 1).
PHOTO ( Forecasting of traffic objects) recognizes and tracks the areas of synchronized traffic in time and space. ASDA ( Automatic storage dynamics analysis: Automatic Tracking of Moving Jams ) recognizes and pursues moving traffic. The ASDA / FOTO models are designed for online applications, and work online without any changes of the model parameters under different weather conditions and road infrastructure and other traffic flow parameters ( proportion of trucks, etc.)
General
Road traffic is either jammed or free. Transport takes place here in time and space instead, that is, he is a temporal- spatial process. Nevertheless, traffic is usually measured directly only in some places, eg with measuring loops, video equipment, vehicle data or data from mobile phones. For an efficient traffic control and other intelligent transport systems a time-space detect traffic incidents is necessary, especially in all places in the road network, in which no direct measurements are available.
First, the ASDA / FOTO models recognize in accordance with the measured properties of traffic disruptions, the two phases of traffic synchronized traffic (S) and wide moving jam ( J) in the measured data. One of these properties, use the ASDA / FOTO models for recognition of the respective transport phase is as follows: in phase J are both speed and traffic flow is very low ( Fig. 2 ( cf) ). In contrast, the traffic flow can be in an area of the synchronized traffic be similar to those of free traffic (Fig. 2 (d, f) ), even if the speed relative to the free traffic is significantly reduced ( Fig. 2 ( c, e) ).
After detecting the phase S PHOTO pursues the model, the two fronts of synchronized traffic, over time ( Fig. 3). After the detection of the phase J is the ASDA model follows the two fronts of wide moving jams ( Fig. 3). This persecution takes place also between the positions of measuring points when the fronts of the transport phase could not be measured directly.
In other words, the models ASDA and FOTO say the positions of the jam fronts over time ahead regardless of the local measuring points. By ASDA / FOTO a merger and / or resolution of either or both transport phases J and S can be predicted between individual measurement points.
ASDA / FOTO for local measurements
Approach cumulative traffic flows in PHOTO
While the downstream front of the synchronized traffic is mostly stationary ( see Figure 2 (a, b ) ), the upstream front, delayed on the vehicles in the synchronized traffic, move against the direction of travel can.
In measured traffic data, the speed of the upstream front of the synchronized movement of the traffic variables within the synchronized traffic and in free circulation depends further upstream.
A good agreement with measured data is achieved when the time dependence of the upstream front of the synchronized traffic in PHOTO is determined by a so-called cumulative traffic flow approach:
In this case correspond and [ veh / h] the respective traffic flows upstream and downstream of the upstream front of the synchronized traffic, is a model parameter [ m / veh ], and is the number of lanes.
Two approaches to congestion following in ASDA
There are two basic approaches to congestion following with ASDA:
Use of the shockwave- Stokes formula
The current speed v ( jam ) the front of a wide moving jam is determined by the Stokes' formula of 1848:
,
With and as traffic flow and density upstream ( and downstream) of traffic jams. In ( 2) no relationship, in particular no fundamental diagram between the traffic flows, and traffic densities were adopted: the values are determined from measured data independently.
Use of a characteristic velocity
If downstream of a wide moving jams no measured data are available with which the above formula ( 2) could be used, with
Worked using as the characteristic velocity of the downstream jam front of the Kerner phase property [J]. This means that after a recognition of the downstream jam front of a wide moving jams at the time gives the position of:
The characteristic velocity is shown in Figure 4. Two slow moving traffic pass successively through a stretch while maintaining the mean velocity of the downstream jam front. In contrast to the mean velocity of the downstream front of a wide moving jam, the speed of the upstream front of traffic flow and density depends on traffic upstream from the jam. The use of formula (4) can therefore lead to a larger error in the estimate of the mean speed of the upstream front of the jam.
On the basis of many measured data on German motorways, a value was determined by. Even if the mean velocity is independent of the transport variables in front of a wide moving jam, the value is influenced by the percentage of trucks, weather, driver behavior, etc.. As a result, the value varies for different data from several years in the field.
On-line applications from ASDA / FOTO in traffic centers
ASDA / FOTO is now used permanently in the Hessen Traffic Centre at 1200 km of motorway. Since April 2004, data from about 2500 detectors automatically with ASDA / FOTO be analyzed. The resulting spatio-temporal traffic patterns are shown as Figure 5 in a distance-time graph. In 2007, the ASDA / FOTO applied online system in North Rhine -Westphalia (NRW). The raw data were transferred to the WDR, the public service broadcaster of NRW, based in Cologne, which radiates traffic information to end users through the broadcast channel RDS. The application processed relevant parts of the overall network in NRW with 1900 km in length with the use of more than 1000 detectors. In addition, since 2009 ASDA / FOTO is also used online in northern Bavaria.
Mean traffic flow characteristics and travel times
In addition to the time-space detect traffic incidents ( Figure 1 and Figure 5), ASDA / FOTO offers other medium parameters for the transport phases S and J. This allows the estimation of travel times on road sections or along a vehicle travel (see examples of vehicle trajectories 1-4 in Figure 5).
ASDA / FOTO for moving data from measurements
ASDA / FOTO can also be used for the reconstruction of traffic patterns on the basis of data from moving sources (eg, vehicles, mobile devices). First ASDA / FOTO recognizes the state and phase transitions along the travel of a vehicle: each of these transition points is connected to a front that separates two phases of traffic from each other. If these transition points are localized, ASDA / FOTO follows the areas of synchronized traffic and wide moving jams. In this pursuit ASDA / FOTO models use the measured properties of the phases J and S, which have been described above (see Figure 2 and Figure 4).