Data processing: vehicles – navigation – and relative location – Navigation – Employing position determining equipment
Reexamination Certificate
1999-05-26
2001-04-10
Gregory, Bernarr E. (Department: 3662)
Data processing: vehicles, navigation, and relative location
Navigation
Employing position determining equipment
C701S117000, C701S200000, C701S207000, C701S208000
Reexamination Certificate
active
06216088
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Field of the Invention
The invention relates to a method for determining travel route data.
2. Discussion of the Prior Art
Methods for determining travel route data, especially within the framework of destination guidance or navigation of a vehicle, are known in principle and have been described in detail, for example, in W/O 89/02142. In this respect, in particular, traffic routes are maintained in a central control station by segment in a digital map, especially in a digital street map, wherein every segment represents a traffic route between two nodes, which can be intersections, junctions or the like, and is described by static or dymamic parameters. The static parameters essentially consist of structual features of the traffic route such as the type of road condition, or state of the road, number of lanes, speed limit and attributes such as curvy, steep ascents and descents. Moreover, it is known to asign stationary sensors to every segment, wherein dynamic parameters such as the quality of vehicles passing a segment per unit of time and their speed are detached by these sensors.
Further, it is known from German reference DE 195 25 291 to receive dynamic traffic data by means of appropriately outfitted test vehicles and to transmit this dynamic traffic data to a central control station.
Further, the dynamic parameters can be supplemented by weather information and temporary restrictions such as construction sites.
Prognoses about future traffic conditions in every segment which form the basis for the navigation of vehicles are derived in a known manner from the static and dynamic data collected in the control station by means of fundamental diagrams.
However, prognoses achieved in this way have the drawback that while a necessary travel time can be determined through a determined navigation along a plurality of segments based on the actual and prognosticated traffic data available in the control station, the navigated vehicle remains bound to the predetermined routing even when unforeseeable, obstructive events occur.
Further, every prognosis based on fundamental data is still inexact because, on principle, up-to-date dynamic parameters are left out of consideration. This effect is amplified in that analytically obtained mathematical relationships between the fundamental data are very complex and therefore very time-consuming with respect to computer processing.
SUMMARY AND DESCRIPTION OF THE INVENTION
Therefore, it is the object of the present invention to provide a method of the generic type mentioned above which can take into account current dynamic parameters and which can nevertheless be managed by simple computational techniques. It will be suitable not only for planning travel routes and for navigation of vehicles along planned travel routes, but can also be used for prognostic activities such as traffic route planning or for evaluating planned travel routes (determining the projected travel time).
Pursuant to this object, and others which will become apparent hereafter, one aspect of the present invention resides in a method for determining travel data in which static and dynamic parameters are stored in a digital map by route section for detected traffic routes. The static parameters include at least structural features of a respective traffic route. The dynamic parameters include at least one guide value and one load function of a respective section of the traffic route. The method further includes deriving the dynamic parameters one time for presetting starting values from the structural features and, from that point on, continuously adapting dynamic parameters to real conditions of the respective sections of the traffic route with ensured availability of dynamic data independent from static parameters. Finally, the travel route data is determined based on the relevant dynamic parameters.
For this purpose, current dynamic data (especially the current possible or average speed in a route section) are preferably obtained by measurements which are received by means of measuring devices arranged in vehicles, wherein the vehicles float along in traffic (floating cars). Also, data from measuring devices installed along the side of the road can be additionally used.
In this way, highly current traffic data are advantageously achieved and the navigation of vehicles built upon this traffic data can be adapted more quickly to the actual traffic data. That means that the reaction time from the occurrence of a traffic-obstructing event, through its detection, to the distribution of navigation information to vehicles moving toward the traffic obstructions is minimal.
Further, there is no processing of highly complex mathematical simulation calculations with predeterminable models based on fundamental data, as they are called, which essentially rely on assumptions relating to structural, i.e., static, parameters which seriously delay reaction time. Rather, through the preferred measurement at the driving object, not only is the specific location of the traffic-obstructing event known, but an obvious cause for the traffic obstruction can also be derived in the same traffic route through multiple measurements with different vehicles outfitted with measuring devices. Both sets of facts make it possible, for example, to respond immediately to the traffic-obstructing event by means of a navigation of vehicles which takes into account the traffic obstruction. Planned travel routes can be realistically evaluated, that is, in particular, relatively dependable predictions can be made about the anticipated travel time, wherein data extrapolated on the basis of current traffic data and/or data taken from an empirical database can be used as input data. The method according to the invention can be put to very good use for purposes of a simulation model, for example, in order to make traffic prognoses for traffic route planning.
REFERENCES:
patent: 4390951 (1983-06-01), Marcy
patent: WO 96/29688 (1996-09-01), None
“Ein Beitrag zur wissenbasierten Modellierung von Entscheidungsprozessen in Verkehrsleit—und Verkehrsinformationssystemen,” by Kamen Danowski; “Automatisierungstechnische Praxis—ATP,” vol. 35, No. 12, Dec. 01, 1993; pp. 677-682.
Albrecht Uwe
Schlottbom Karlheinz
Schulz Werner
Sievers Christel
Cohen & Pontani, Lieberman & Pavane
Gregory Bernarr E.
Mannesmann AG
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