Data processing: vehicles – navigation – and relative location – Vehicle control – guidance – operation – or indication – Traffic analysis or control of surface vehicle
Reexamination Certificate
2002-07-19
2004-11-02
Nguyen, Thu V. (Department: 3661)
Data processing: vehicles, navigation, and relative location
Vehicle control, guidance, operation, or indication
Traffic analysis or control of surface vehicle
Reexamination Certificate
active
06813555
ABSTRACT:
BACKGROUND AND SUMMARY OF THE INVENTION
This application claims the priority of PCT International Application No. PCT/EP00/08329, filed 26 Aug. 2000 and German Patent Document 199 44 075.1, filed 14 Sep. 1999, the disclosure of which is expressly incorporated by reference herein.
The invention is related to a method for monitoring and forecasting traffic conditions in a traffic network (particularly a road network) with effective bottlenecks. As used herein, the phrase “effective bottlenecks” is to be understood to include both bottlenecks in the actual sense, (a reduction in the number of usable lanes), and bottlenecks in the broader sense, such as are caused, for example, by one or more incoming feeder lanes, a bend, a grade, a downgrade, a division of a lane into two or more lanes, one or more exits or a bottleneck moving slowly (by comparison with the average vehicle speed in free traffic), for example owing to a vehicle which is being driven slowly.
Various methods for monitoring and forecasting traffic conditions of this generic type are known, and are of particular interest also for diverse telematics applications in vehicles. One aim of these methods is to obtain, from measured traffic data detected at traffic measuring points, a qualitative description of the traffic state at the respective measuring point and its surroundings. Measuring points in this sense include both those installed in a stationary fashion on the route network, and moveable measuring points such as, for example, sample vehicles moving in the traffic (so-called “floating cars”) or by a measurement of the traffic flow obtained by means of monitoring from deep space, space or the air.
For the purpose of qualitative description of the traffic state, it is known to divide the latter into various phases, for example into a phase of “free traffic”, in which relatively fast vehicles can overtake without a problem, a phase of “synchronized traffic”, in which possibilities for overtaking scarcely exist, but a high traffic intensity still prevails, and a phase of “congestion”, in the case of which the vehicles are virtually stationary and also the traffic intensity drops to very low values. (See, for example, the journal article by B. S. Kerner and H. Rehborn, “Experimental properties of complexity in traffic flow”, Physical Review E 53, R 4275, 1996.) As used herein, “synchronized traffic” is to be understood both as a state in which, because there are scarcely any possibilities of overtaking, all vehicles in different lanes are driven at a very similar, “synchronized” speed, (for example on route sections without approach roads and exits), and a traffic state in which the distribution of speed for the vehicles in different lanes can differ, but there is a tendency for synchronization of the speeds of those vehicles in different lanes which are respectively being driven on an identical route, since there are scarcely any possibilities of overtaking with reference to one driving route.
The phase division is based on the idea of selecting the phases such that each of them corresponds to specific characteristic properties of the traffic flow, making it possible to estimate the temporal and spatial extent of route sections in which the traffic state is in a specific phase. In the journal article by B. S. Kerner, “Experimental Features of Self-Organization in Traffic Flow”, Physical Review Letters, Vol. 81, No. 17, page 3797, so called “pinch regions” (regions of “congested synchronized traffic”) are selected in the phase of “synchronized traffic”, and are subsequently treated specially. These are regions inside synchronized traffic in which it is possible to drive only at very low speeds and in which there is spontaneous formation of short-lived congestion states which can migrate upstream and grow in the process, and which can then possibly lead to a lasting congestion state.
Various methods are already known for monitoring and predicting traffic “congestion points” (frequently called a “moving jam”). See, for example, the automatic congestion dynamics analysis described in German patent document DE 196 47 127 A1, whose content is incorporated herein by reference, and methods known from the literature mentioned there.
In German patent document 198 35 979.9, which is not a prior publication, there is, moreover, a description of the monitoring and forecasting of synchronized traffic, in particular the detection of a phase transition between free and synchronized traffic, and a prediction of the spatial extent of synchronized traffic. This is done by inferring the position of an upstream edge of the latter based on the fact that, at a corresponding upstream measuring point, specific conditions for an induced upstream phase transition from free to synchronized traffic are no longer fulfilled, or widespread congestion has arisen. This method is particularly suitable for detecting the start of a phase of synchronized traffic at an effective bottleneck of the traffic network, and for tracking the temporal development of the synchronized traffic forming upstream of this bottleneck, the downstream edge of which generally remains fixed at the effective bottleneck. An edge fixed at the effective bottleneck is understood in this case as one which remains in the surroundings of this bottleneck. That is, it remains essentially stationary in the surroundings of a stationary effective bottleneck, or moves along essentially synchronously with a moveable effective bottleneck. The location of the effective bottleneck is therefore the one where the downstream edge of the synchronized traffic is momentarily located.
In a related, co-pending German patent application the current traffic conditions are monitored with regard to different state phases, particularly synchronized traffic and a pinch region as well as the phase transition between states of synchronized traffic on the one hand, and free traffic, on the other hand. The future traffic state is predicted on this basis, if required. In particular, this method can be used to estimate the edges of regions of synchronized traffic relatively accurately for current points in time, or to predict future points in time at which such edges are not (or will not be) located at a measuring point, but somewhere between two measuring points. Suitably designed fuzzy logic is preferably used in this case.
In German patent document DE 199 44 077 A1, (not prior art) the current traffic state is monitored with regard to different state phases and, in particular, with regard to synchronized traffic and a pinch region as well as the phase transition between states of synchronized traffic, on the one hand, and free traffic, on the other hand. The future traffic state is predicted on this basis, if required. In particular, this method can be used to estimate the edges of regions of synchronized traffic relatively accurately for current points in time or to predict future points in time at which such edges are not (or will not be) located at a measuring point, but somewhere between two measuring points. A suitably designed fuzzy logic is preferably used in this case.
European patent document EP 0 884 708 A2 discloses a method for predicting traffic conditions in a traffic network having nodes and edges running therebetween. Detection data referring to the current traffic are acquired and transmitted to a control center which uses them to describe the current traffic state on the traffic network in the form of respective traffic phases which represent the state on an edge or an edge section. It predicts the traffic state by calculating at least the movements and future positions of the traffic phases. The phases are described in binary fashion in the form of the phases of “free” and “congested”; in the five phases of “free”, “busy”, “dense”, “sluggish” and “congested”; or by using another number of different phases. For prediction, use is made of phase boundary speeds which, for example, are calculated by linear regression with the aid of current and earlier detection data, or as the quotient of the
Crowell & Moring LLP
Daimler-Chrysler AG
Nguyen Thu V.
LandOfFree
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