WO2011110903A1 - Système et procédé pour l'amélioration de communications dans des réseaux véhiculaires ad hoc - Google Patents

Système et procédé pour l'amélioration de communications dans des réseaux véhiculaires ad hoc Download PDF

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Publication number
WO2011110903A1
WO2011110903A1 PCT/IB2010/055197 IB2010055197W WO2011110903A1 WO 2011110903 A1 WO2011110903 A1 WO 2011110903A1 IB 2010055197 W IB2010055197 W IB 2010055197W WO 2011110903 A1 WO2011110903 A1 WO 2011110903A1
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WO
WIPO (PCT)
Prior art keywords
vehicle
tile
intersection
vehicles
tiles
Prior art date
Application number
PCT/IB2010/055197
Other languages
English (en)
Inventor
Onn Haran
Tal Azogui
Original Assignee
Onn Haran
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Onn Haran filed Critical Onn Haran
Publication of WO2011110903A1 publication Critical patent/WO2011110903A1/fr

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Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W64/00—Locating users or terminals or network equipment for network management purposes, e.g. mobility management
    • G—PHYSICS
    • G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
    • G09B29/00—Maps; Plans; Charts; Diagrams, e.g. route diagram
    • G—PHYSICS
    • G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
    • G09B29/00—Maps; Plans; Charts; Diagrams, e.g. route diagram
    • G09B29/10—Map spot or coordinate position indicators; Map reading aids
    • G09B29/106—Map spot or coordinate position indicators; Map reading aids using electronic means
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/16—Anti-collision systems
    • G08G1/161—Decentralised systems, e.g. inter-vehicle communication
    • G08G1/162—Decentralised systems, e.g. inter-vehicle communication event-triggered
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W74/00—Wireless channel access, e.g. scheduled or random access
    • H04W74/08—Non-scheduled or contention based access, e.g. random access, ALOHA, CSMA [Carrier Sense Multiple Access]
    • H04W74/0808—Non-scheduled or contention based access, e.g. random access, ALOHA, CSMA [Carrier Sense Multiple Access] using carrier sensing, e.g. as in CSMA
    • H04W74/0816—Non-scheduled or contention based access, e.g. random access, ALOHA, CSMA [Carrier Sense Multiple Access] using carrier sensing, e.g. as in CSMA carrier sensing with collision avoidance
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W84/00—Network topologies
    • H04W84/18—Self-organising networks, e.g. ad-hoc networks or sensor networks

Definitions

  • Embodiments of the invention relate to vehicular communications and communication networks and in particular to real time vehicle-to-vehicle and vehicle-to-infrastructure ad-hoc communications.
  • a vehicle is equipped with radio frequency (RF) transmission and reception capabilities
  • the IEEE802.11p standard provides a common platform for communication. All vehicles equipped with communication equipment transmit periodically their location information in packets called "beacons”.
  • Beacons the IEEE802.11p protocol cannot guarantee communications performance in a congested environment, since the deterministic arrival of beacons is not guaranteed. This leads to various problems, for example lost safety messages. Lost safety messages translate into increased safety message "blind time", which diminishes the safety benefit of such communications.
  • a hidden node is caused by imbalance between a detection area (where a device can sense the wireless medium and realize that other transmission is taking place) and an interference area (where a device transmission can interfere with that of other devices).
  • the worst hidden node scenario exists in an obstructed intersection, where vehicles on different roads cannot sense each other and are therefore highly likely to transmit concurrently. Any concurrent transmission will cause packet drop at the center of the intersection.
  • Vehicles on straight roads may use a power control algorithm to reduce power and decrease interferences.
  • PCT/IB2009/051111 discloses a scheme for a driven vehicle to exchange Request-To-Send (RTS) / Clear-To-Send (CTS) messages with the pivot vehicle in order to prevent transmissions of nearby vehicles. This exchange significantly reduces the hidden node effect.
  • RTS Request-To-Send
  • CTS Clear-To-Send
  • the self learning scheme should be able to cope with various environments, including intersections of varying sizes and different number of connecting roads, complex interchanges with various shapes and heights, parking lots, etc.
  • the scheme should also be able to overcome Global Positioning System (GPS) errors that bias a local map learned based on GPS.
  • GPS Global Positioning System
  • Embodiments of the invention provide systems and methods to reliably detect an intersection in a vehicular environment.
  • the reliable detection of an intersection is essential in a number of applications, for example to adjust transmission power and rate, to mitigate problems which may impact communications in an ad-hoc vehicular network, or to deal with other safety applications.
  • the detection of an intersection is done under various scenarios without relying on any external database.
  • the learning is done while requiring low processing power and while mitigating potential effects of GPS errors.
  • Embodiments of the invention use a coarse map having tiles, at least some of the tiles having moving vehicles placed therein, each moving vehicles having an associated heading.
  • the map is handled at a driven vehicle.
  • the driven vehicle uses solely the coarse map, without assistance from any external database, to detect an intersection.
  • the detected intersection may then be used in various applications mentioned above. For example, it may be used to improve communications and mitigate a hidden node effect.
  • a method which includes the steps of providing a coarse map having tiles, placing moving vehicles in at least some of the tiles, and using the coarse map with the placed vehicles to detect an intersection.
  • the vehicle placement operation occurs by matching the coordinates of a vehicle with the index (coordinates) of a tile.
  • a system which includes a coarse map having a plurality of tiles and centered at a driven vehicle, at least some of the tiles including moving vehicles placed therein, and a search engine operative to identify an intersection based solely on the coarse map and vehicles placed thereon.
  • the system further includes a learning engine operative to place moving vehicles in tiles and a memory management engine operative to dynamically shift the coarse map following vehicle movement.
  • the system further includes a vehicle database used by the learning engine to ensure that a vehicle is placed only once in a given tile.
  • a method which includes the steps of: at a driven vehicle, providing a coarse map having tiles with a tile dimension larger than a given parameter value, some tiles having vehicles placed therein, using solely the coarse map to detect an intersection, and performing a communication exchange with a pivot vehicle located in the intersection to improve the communications.
  • FIG. 1 shows an exemplary coarse map used in embodiments of the invention
  • FIG. 2 shows an embodiment of a method of the invention used to learn an intersection
  • FIG. 3 shows schematically, in a block diagram, an embodiment of a system of the invention which enables the learning of the intersection using a method as in FIG. 2;
  • FIG. 4 describes in more detail the operation of the learning engine
  • FIG. 5 shows schematically the format of a map database
  • FIG. 6 describes in more detail the operation of the search engine
  • FIG. 7 describes in more detail the operation the memory management engine
  • FIG. 8A shows an exemplary geographical map with locations of four vehicles on two crossing roads
  • FIG. 8B shows a coarse map overlapping the geographical map of FIG. 8A, as well as an intersection learned using an embodiment of a method of the invention.
  • Embodiments of the invention provide and use a coarse map centered at a driven vehicle (i.e. the vehicle in which all the processing involved in detection of the intersection occurs).
  • FIG. 1 shows an exemplary such coarse map 102, superimposed on a driven vehicle 104. All other vehicles are called “processed" vehicles.
  • a driven vehicle is also a processed vehicle when the GPS issues it a new reading.
  • Map 102 includes a plurality of tiles 106. At least some tiles have moving vehicles with associated headings placed therein (not shown). Also shown are two roadways 108 and 110, intersecting at an intersection 112.
  • tile defines the basic element of the coarse map.
  • the tiles are rectangular and identical in size (area).
  • the tiles are squares. In such embodiments, their area may range between ca. 4*4m and ca. 32*32m.
  • the area of a tile may be ca. 8*8m. In other embodiments, the area of a tile may be ca.l6*16m.
  • Map 102 covers an area surrounding the driven vehicle. In some embodiments, this area covers about 512*512 meters (i.e. 4096 tiles of 8*8m or 1024 tiles of 16*16m tiles). In other embodiments, the map and/or tile areas may be of other dimensions.
  • Map 102 is "coarse" in the sense that a length parameter of a tile (e.g. a square side) is intentionally larger than a typical GPS reading error, a typical lane width or a typical vehicle movement between GPS readings.
  • a length parameter of a tile e.g. a square side
  • the coarse map tile concept disclosed herein decreases the accuracy on purpose.
  • a major resulting benefit is a smaller memory footprint, since information is stored only per tile, while a smaller number of tiles need to be stored per given area.
  • GPS location information is made available at a vehicle periodically (e.g. every 1 second).
  • the GPS information may be received directly from the vehicle GPS system or transmitted to the vehicle from other vehicles.
  • each vehicle is placed in a tile of the coarse map in step 200.
  • a historical vehicle count is maintained for each tile.
  • the coarse map (with the vehicles placed in it) is then used to detect a next intersection in step 202.
  • step 204 once an intersection is detected a vehicle at the center of intersection is selected to be a pivot vehicle.
  • the driven vehicle performs an RTS/CTS exchange with the pivot vehicle before broadcast transmission to prevent other vehicles in proximity of the intersection from transmitting. This exchange can be done for example as described in PCT/IB2009/051111.
  • the process results in significant improvement of the reception probability of vehicles around the intersection, effectively solving the hidden node problem.
  • FIG. 3 shows schematically, in a block diagram, an embodiment of a system of the invention, marked 300.
  • System 300 includes coarse map 102, the information of which is stored in a map database (see FIG. 5), a learning engine 302, a vehicle database 304, a memory management engine 306 and a search engine 308.
  • components 102, 302, 304, 306 and 308 are implemented in software (SW).
  • SW software
  • the SW components and code associated therewith are stored on a computer readable medium and processed in a processor included in a vehicle computer (not shown).
  • Learning engine 302 is used to position each vehicle in a "current" tile of coarse map 102.
  • "current tile” means a tile on which a vehicle is placed at present.
  • Learning engine 302 accesses vehicle database 304 to ensure that a processed vehicle is placed only once on a given tile of the coarse map.
  • Map database 102 counts all vehicles located on a tile at present and historically, as long as that particular tile is in the coarse map.
  • Memory management engine 306 is used to dynamically shift the coarse map, following the driven vehicle movement. The coarse map is "dynamic' in the sense that it changes with the driven vehicle movement, with some tiles being removed and other tiles being added.
  • Search engine 308 is used to find the next intersection.
  • step 400 each tile is indexed (is assigned X, Y coordinates relative to the driven vehicle coordinates). Note that the driven vehicle is placed in the center tile, while all other vehicles are placed in tiles around the center tile. In some cases, a vehicle may have two consecutive GPS readings that place it in non-contiguous tiles. Tiles located between these non-contiguous tiles are referred to as "skipped tiles" and marked as if the vehicle had been placed inside them.
  • the tile size is set to 8*8 meters or 16*16 meters. This simplifies the division into location (in meters) and effectively performs a simple shift (e.g. of an operator on a binary number) instead.
  • a check is performed to determine if an indexed tile is within the coarse map. The check therefore also determines if a vehicle placed in this tile is inside the map. If no, then operation ends in step 422. If yes (vehicle is inside map) then operation continues from step 406, which checks, using vehicle database 304, if the vehicle was placed in the past in the current tile. The purpose of this check is to avoid false identification of the existence of an intersection based on a stopped vehicle.
  • a vehicle stopped at a certain location should not receive higher weight than a fast moving vehicle (in the sense of being counted more than once). If yes (vehicle was placed before in this tile), the operation ends. If no, operation continues from step 408, where the vehicle is marked in the vehicle database as inserted in the current tile.
  • a count of vehicles is maintained for each tile. This count represents all vehicle placed in a given tile over the period in which the given tile is in (part of) the coarse map. All vehicles counted in a tile are used in the detection of an intersection, see step 416. Note that the count includes "historically" placed vehicles. Therefore, some of the vehicles in a count associated with a current tile may not be physically anymore in the current tile.
  • Some road elements such as bridges impose a three-dimensional view of the map.
  • the identification of an intersection applies to a certain road level. For example, an intersection below a bridge does not imply that an intersection exists on the bridge.
  • the map database defines "layers" in the Z (height) direction, where each layer is a road with a different height. In most cases, only a single layer will be learned. A layer is created automatically when roads exist at different heights.
  • the Z-axis of the vehicle is compared with the Z-axis of all known layers for each tile. If one of the layers is close enough (exemplarily less than 1 meter apart) to the vehicle Z-axis, then the closest existing layer is selected in step 412.
  • the Z-axis of the existing layer may be slightly adjusted to overcome measurement errors in the Z-axis of the processed vehicle. If none of the known layers is close enough, a new layer is created in step 414. The Z-axis of this new layer is taken to be the processed vehicle Z-axis. In both cases, operation continues from step 416. In this step, heading information is added to each counted vehicle in the tile. In an embodiment, the vehicle heading granularity is set to 30 degrees. Other granularities ("quantizations") of headings may be used too. In step 418, vehicle information is added in skipped tiles.
  • step 420 tiles adjacent to the current tile are considered as well for vehicle placement, to overcome potential GPS errors that may lead to wrong placement. That is, a vehicle in the current tile is placed with a fractional count (lower weight) in each adjacent tile. This is effective in signaled intersections, for example when vehicles wait at a "Stop” line and do not cross the intersection. The weighting "smears" the map and helps to detect an intersection even when vehicles are slightly apart.
  • FIG. 5 An exemplary format of a map database is described in FIG. 5.
  • Each row represents a different layer, i.e. a different Z-axis value.
  • the typical number of rows is 1, but it goes higher in bridges.
  • Layer operation is essential for two reasons: a) a RF link between vehicles on roads of different heights is less reliable than selecting a vehicle on the same height between vehicles on a given road at the same height; and b) different layers may require different behavior, as one layer may have an intersection, while the other does not. For example, assume a bridge is placed over an intersection. In this case, vehicles on the layer without the intersection (e.g. the bridge layer) should ignore the intersection in the lower layer.
  • the map database stores the number of vehicles observed for each heading. The maximal number of vehicles per heading may be saturated to limit storage (for example to 255 in order to fit one byte).
  • the operation of search engine (308) is described in FIG. 6.
  • the operation begins in step 600 upon arrival of a GPS update, typically once a second.
  • An intersection search is always performed, even when the next intersection is defined, because an intersection may be discovered between the driven vehicle location and a next intersection which has been found in a previous run of the algorithm.
  • the intersection search is based on tracking the currently driven road until an intersection is detected, or until the tracking distance reaches a threshold.
  • the operation is performed tile by tile.
  • the next tile in the direction of the driven vehicle heading is selected in step 602.
  • this tile is checked for vehicles with different headings. The check is over all counted vehicles and their respective headings.
  • the check in is designed to mitigate errors by applying two conditions: the first condition requires a minimal number of vehicles at each heading to avoid intersection identification by a single misplaced reading and to avoid detection of minor intersections (such as an exit for a vehicle from a small garage). When the number of vehicles is low, the congestion probability is low and the intersection can be ignored.
  • the second condition requires a. separation greater than a threshold between the various headings to overcome GPS heading errors, but smaller than 180 degrees to avoid selection of opposite roads as intersection. For example and assuming heading granularity of 30 degrees, if vehicles in a given tile are found only at headings of 0 and 30 degrees, then an intersection is probably not found since these vehicles could be maneuvering vehicles or vehicles having heading quantization errors.
  • step 606 the intersection found in step 606 can be used for the CTS/RTS coordination process as described in PCT/IB 2009/051111.
  • step 608 the number of searched tiles is checked. If the number of searched tiles exceeds a threshold and an intersection has not been found, then operation is terminated in step 610. Otherwise, the search continues from step 602.
  • step 702 the current tile in which the driven vehicle is placed is compared with a prior tile which contained the driven vehicle. If the tile has not changed, then operation ends in step 708. If the tile has changed, in step 704, memory management erases tiles (and therefore "releases memory”) in the direction opposite to the movement direction.
  • the driven vehicle moves north
  • tiles at the south edge of the coarse map are erased.
  • its vehicle count is also erased.
  • the memory is then reallocated to tiles in the direction of advancement, i.e. new tiles are added in step 706.
  • tiles are allocated at the north edge of map.
  • pointer manipulations can be used instead of release and reallocation of the memory.
  • FIG. 8A shows a geographical map with two roads 808 and 809 with locations of four vehicles 800, 802, 804 and 806. Vehicles 800 and 802 are northbound on road 809 and vehicles 804 and 806 are westbound on road 808.
  • FIG. 8B shows tiles of a coarse map, lanes and a found intersection. The tiles are numbered (indexed) with sequential numbers from 830 to 860. Not all these numbers are mentioned below, to simplify the description. Some tile numbers are skipped. The tiles are not perfectly aligned to the map, i.e. edges of some tiles do not overlap the side of a road. Furthermore, a road may have an angle shift, not shown here for clarity reason.
  • the northbound vehicles (800 and 802) outline a lane 812. Tiles adjacent to tiles on which vehicles are placed are handled as well, as described above. Lanes 810 and 814 are also outlined, since adjacent tiles (832, 840, 848, 856 and 836, 844, 850, 858) are filled with fractional vehicle counts. That is, vehicles are counted on those tiles, but with lower weight, for example as "half a vehicle”. Then, the vehicle count in the adjacent tiles is not zero, but 50% of the vehicle counts in current tiles. Similarly, a lane 822 is outlined by the westbound vehicles (804 and 806) and a lower vehicle count is found in lanes 820 and 824 crossing adjacent tiles (838-844 and 854-860).
  • intersection location is the crossing of lanes 814 and 822, i.e. tile 850.
  • the nine tiles marked as 840-844, 848-852, 856-860 are likely to be considered an intersection as well if the number of vehicles is high.
  • Another potential intersection decision may involve the five tiles composed of center tile 850 and one adjacent tile in each direction. This result is the closest to the actual intersection shape.
  • Computer executable instructions implementing embodiments of the invention can be distributed to users on a computer-readable medium and are often copied onto a hard disk or other storage medium. When such a program of instructions is to be executed, it is usually loaded into the random access memory of the computer, thereby configuring the computer to act in accordance with the techniques disclosed herein. All these operations are well known to those skilled in the art and thus are not further described herein.
  • the term "computer-readable medium” encompasses distribution media, intermediate storage media, execution memory of a computer, and any other medium or device capable of storing for later reading by a computer a computer program implementing the present invention.

Abstract

L'invention porte sur des procédés et des systèmes pour l'amélioration des communications dans des réseaux véhiculaires ad hoc, lesquels procédés et systèmes utilisent une carte grossière ayant des pavés, au moins certains des pavés ayant des véhicules mobiles placés dans ceux-ci, chaque véhicule mobile ayant un libellé associé. La carte grossière est formée dans et centrée au niveau d'un véhicule conduit, qui l'utilise uniquement pour détecter une intersection. En cas de problème de nœuds cachés au niveau de l'intersection détectée, le véhicule conduit peut prendre une action appropriée pour pallier le problème. L'action peut comprendre un échange demande d'émission (RTS)/prêt à émettre (CTS) avec un véhicule pivot localisé dans l'intersection.
PCT/IB2010/055197 2010-03-07 2010-11-16 Système et procédé pour l'amélioration de communications dans des réseaux véhiculaires ad hoc WO2011110903A1 (fr)

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US31133310P 2010-03-07 2010-03-07
US61/311,333 2010-03-07

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