GB2421828A

GB2421828A - Traffic hazard management system for a vehicle, that sends and receives data from sensors and other vehicles relating to the traffic hazards

Info

Publication number: GB2421828A
Application number: GB0428321A
Authority: GB
Inventors: Yedidia Emanuel Meshulam
Original assignee: Individual
Current assignee: Individual
Priority date: 2004-12-29
Filing date: 2004-12-29
Publication date: 2006-07-05
Also published as: GB0428321D0

Abstract

The disclosed traffic hazard management system uses a hazard management processor (HMP) on a vehicle to process data obtained from several sources of information. The sources of information include vehicle significant volatile data sources, such as vehicle related data, eg speed or tyre pressure, extra vehicular data eg weather or other environmental data, and driver or passenger related data. The sources also include vehicle independent autonomous data sources eg, geographic data and traffic updates. A wireless communication system sends and receives the data from other vehicles and networks such as the internet. The HMP is able to send signals for controlling the vehicle and alerting the driver when required. The independent data may be physically loaded and comprise navigation data such as road infrastructure. The geographic data may be displayed on a digital compound map and the location obtained using a GPS receiver.

Description

242 1828

SYSTEM FOR MANAGING TRAFFIC HAZARDS

FIELD OF 1'IfF INVENTION

The present invention is in the general field of traffic control in streets and highways.

More specifically the invention relates to systems for managing travel risk in land vehicles.

BACKGROUND OF THE INVENTION

Traveling in streets and highways is a risky event. Car accidents occur between a vehicle and one to a plurality of vehicles, a vehicle and a pedestrian, and between vehicles and solid objects at the vicinity of the road.

The causes for road accidents are numerous and are subject to study as well as to controversy. Road accidents occur on poorly designed maintained roads as well as on well designed and careMly maintained roads. The quality of driving is one important factor which determines the probability of the occurrence of accidents and their severity. Even a proficient driver may be subjected at times to the influence of fatigue drowsiness, or may otherwise behave carelessly such as when talking, eating or listening to music. Another factor that is considered as detennining the probability of accidents occurring is the distance between vehicles traveling in the same lane on the road. The higher the speed of travel is, the larger the distance of bringing the vehicle to halt from the starting point. However, the ability of a driver to not only automatically monitor the distance of vehicle on the back is limited. Moreover, the ability of a driver to increase the distance from a vehicle at the back is severely limited. For a driver sensing an alarming decrease in distance there is not much left to do apart from increasing own velocity or moving to a different lane, which actions are quite risky.

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BRIEF DESCRIPTION OF THE DRAWINGS

Fig. 1 is a logical block diagram describing the categories of data feeding the hazard processor of the invention; Fig. 2A is a logical block diagram describing sources of significant volatile risk conditions; Fig. 2B is a logical block diagram describing sources of autonomous data relating to traffic hazards; Fig. 3 is a logical block diagram describing sources of information feeding the hazard risk processor in example 1.

Fig. 4A is a schematic description of a simple derivation of a hazard threshold from one hazard factor input; Fig. 4B is a schematic description of a derivation of a hazard threshold from one hazard thctor input with the intervention of a second one; Fig. 4C is a schematic description of a derivation of a hazard threshold from one hazard factor input with the intervention of a second one; Fig. 4D is a schematic description of a derivation of two hazard thresholds from two hazard factors, with mutual intervention; Fig. 5 is a schematic description of the wiring connections of an I-IMP dividing input and output contributions.

DETAILED DESCRIPTION OF tHE PRESENT INVENTION

The system of the invention aims at diminishing the probability of the occurrence of road accidents and their detrimental effect by putting to use preventive measures that dynamically monitor changes in risks on the road. Further, the system of the invention furnishes alert signals to the driver or even interferes with the driving in order to bring the risk to a minimum.

The hazard management processor (HMP) of the invention accepts data and issues signals to a variety of devices. As described schematically in Fig. 1 to which reference is now made, two general categories of data streams are utilized by HMP 20 of the vehicle, utilizing the system of the invention. The vehicle significant volatile conditions data stream (VSVCDS) 22 relates to all the data obtained by continuously measuring appliances associated with the vehicle, that help define the factors that potentially have an effect on the vehicle with respect to the safety * . S.. S * . S S I S 5 * S S S 555 *** * * S. S S * * . S. S S S *S * * S S.. * 5 S S of the passengers. The other stream of data relates to vehicle independent and autonomously supplied data stream (VIASIS) 24 received in a preferred embodiment of the invention, online by the vehicle or are loaded physically onto an updatable memory connected to the HMP 20. As the input data is processed by HMP 20, outgoing signals may be formed that can be categorized in two categories, each containing a group of items, namely the control signals group 26 and the alert signal group 28.

The sources of information that feed into the HMP the relevant data are, as mentioned above, either derived from sources respective of the volatile conditions associated with the vehicle or its environment, or are derived from an autonomous source. The significant volatile conditions as described schematically in Fig. 2k to which reference is now made, are derived and interpreted from outputs of respective appliances that measure each some physical quantity correlated with a risk factor. A non exclusive list of such factors includes vehicle related class of ictors 40, which includes inter alia speed and mechanical aspects of the vehicle, class 42, which includes environmental related risk factors such as visibility and temperature. Class 44 is another class of risk factors which relates to extra - vehicular impact (collision) factors which are non mappable by any service provider. This list includes inter aba other mobile elements on or about the road, pedestrians, and small non mobile elements such as road blocks, and fallen trees. Class 46 relates to passenger related risk factors such as safety belt usage, drowsiness of driver, and extreme conditions that amy interfere with the driving (noise volume, heat, cold).

The vehicle - independent and autonomously supplied data source 24 described schematically in Fig. 2B, to which reference is now made, is loaded periodically onto an updatable memoty of the vehicle. Another option is that such data is obtained on - line from one or more remote providers by means of a wireless communications link. Both options may co - exist.

Several classes of information sources contribute to this data categoiy. Class 50 contributes available digital maps expressing the geographical location of roads, bridges, parking lots and sites of interest in terms of geographical coordinates. Class 52 contributes information concerning roads and associated infrastructure, typically road classification, traflic signs, bridges and traffic lights.

Class 54 relates to on - line data relating to traffic condition updates. Class 56 relates to navigation means available through satellites, aerial or earth - bound means. The details afforded hereinabove with respect to the various classes of information categorized in the bounds of the categories defined, express only a portion of the available and possibly futuristic information services.

* I *S% * - * I. * * * S S eS* * I 5 * * S S - * * I S 50 5 - S I.. I S S The HMP assesses hazard thresholds (HT) of as many aspects of the traveling associated a variables and constantly calculates a hazard status for the vehicle. Consequently it further takes action when one or more hazard threshold is met. Two types of response signals are issued. Control signals are issued by the HMP, directly or indirectly, effecting an appliance associated with the vehicle. For example, a sensor associated with the vehicle senses a drop in light level, and as result the lIMP turns on the main light circuit of the vehicle by issuing a control signal to a switch closing the circuit. Some examples are given below to explain the implementation of preferred systems Example I: A vehicle travels on a road under certain conditions. As can be seen in Fig. 3 to which reference is now made, the HMP 20 of the vehicle receives information from three sources. Source 60 is a road wetness sensor, source 62 is a vehicle velocity sensor (such as a speedometer) and sensor 64 is a radar constantly measuring the distance between the vehicle.

Cruise conditions are constantly monitored, and assuming that the HMP calculates the momentaiy hazard status, and if no HT is surpassed, no outwardly directed signals will be issued. When rain begins to fall, the road wetness sensor 60 sends information that is interpreted as a wetness parameter typically by a signal processing circuit that in turn feeds data into the HMP. The lIMP receives the new wetness parameter and calculates a new momentaiy hazard status. If a certain hazard threshold is surpassed, the HMP may issue an alert signal, such as "reduce speed" alert or may even reduce the speed by automatically decreasing the fuel flow into the engine. The three sensors mentioned hereinabove, are all of the VSVCDS 22 data source. Source 66 however falls in the categoiy of(VIASIS) 24. The signal issued by source 66 determines the velocity of the vehicle as dictated by the limits imposed by the authorities.

From the example elaborated above, it can be generalized as follows. The explanations are made with reference to schematic Figs 4A - D. The lIMP calculates the HT related to each information source s as influenced by other factors. For a single hazard factor 80, as described schematically in Fig. 4A the HMP 20 calculates a HT level 82. In Fig. 4B the Hazard factor 80 contributes information to HMP 20 but in addition, hazard factor 84 contributes independent data to the lIMP. A new HT is calculated for hazard factor 80 which may be different than the HT 82 calculated without the input associated with hazard factor 84. Further, in Fig. 4C the HMP produces not only a HT for hazard factor 80, but also a HT 88 associated with Hazard factor 84.

Finally, in Fig. 4D, The two HTs produced by the lIMP are interdependent to some extent, so that * I ISa * - * I S * * * S - * S S S - * .* * S II * S a. a. a S I * 5* * * * *5* I * * S Hi' 90, is influenced by the inflow information regarding hazard factor 84, and HT 92 is influenced by the inflow of information regarding hazard factor 80. Thus, the HTs produced by the HMP are all potentially transient and their values may constantly change.

Example 2: A vehicle travels on a road under daylight conditions. As the time goes by, the light diminishes and the sensor that senses the amount of daylight send signals which are preprocessed and fed into the HIvlP as data indicating of sub-threshold light (VSVCDS class 42 risk). The HMP activates the headlights of the vehicle, or alternatively sounds an alert signal. As the driver becomes tired, he or she may become drowsy, and a sleep detector (VSVCDS class 46 risk) signals the HMP of the event. The HMP signals the driver by issuing a sound or an electric shock, waking him/ her up. The vehicle approaches a pedestrian road crossing and at specific distance from a categoty 52 alerts is received by a receiver in the vehicle which sends a signal to the HMP, in which it is processed, alerting the driver of the upcoming hazard.

Example 3: One of the most prominent risk ictors in road driving is the short distance between vehicles moving in the same direction. In accordance with the present invention, a vehicle employing the system of the invention typically implements hazard threshold assessment as described next. Car a employing the system of the invention, measures the distance to a vehicle b at the rear. Concomitantly, car a also measures its own velocity. Based on the distance measured between the two vehicles and the velocity, the HMP can calculate the momentary HT (hazard threshold). In a more complicated example, the velocities of the car a and vehicle b are not constant, so that the distance between both vehicles is changeable. Thus car a monitors the distance to vehicle b constantly, and based on the knowledge of its own speed, the HMP can calculate not only the velocity of vehicle b, but also its acceleration. Depending on the rate of sampling of both distance and own velocity, the momentary change in distance can be calculated.

In case that the HMP produced a hazard signal (i.e. the HT was surpassed), several alternative responses can be employed. A typical option is both warning the driver and passengers of car a, and in parallel warning the driver of vehicle b. Warning the driver of vehicle b can be done in one of several ways. One approach is that of a connection made between subscribers of mobile public communications system, namely cellular, wireless internet and satellite telephony systems. The cellular telephony network has inherent information regarding the location of a subscriber, and the more advanced the networks are, the more precisely the location is known. Thus, it is possible that the cellular personal identification provides a cue as to the identity of a specific vehicle having

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S S *SS S S * . * * * :. ..* * * S * S S * * * * S S. S * * . . . * . . S * . S.. * * cellular connection. Thus even without having any pnor knowledge of the identity of an alien vehicle it is possible with some degree of probability to have contact with alien car providing that the cellular service complies with the request of a certain car A subscriber identified by the cellular service to determine the identity of an alien vehicle driving behind. Wireless internet technologies may also provide connection between vehicles. Localised networks offer another possibility for communicating between adjacent vehicles. Presently, the low power, short distance wireless communications networks such as "Bluetooth" and "ZigBee" (IEEE 802.15.4 standard) can provide reliable wireless connectivity over short ranges. If the authorities were to enforce connectivity of travelling vehicles, the results of communicative interaction between adjacent vehicles would increase the effectiveness. At this stage, a typical exemplaiy wiring scheme of the connections of the HMP can be illustrated. In Fig. 5 to which reference is now made, the input contributing inputs to HMP 20 are described. Wireless communications 120 contribute data from independent information providers, adjacent vehicles, authorities. Input contribution 122 relates to a memory including potentially information from independent providers such as mapping companies, authorities and others. The memory is updatable for example by way of wireless update or by physically downloading data into a memory connected with the HMP. Appliances (typically sensors) contribute information usually originating in the vehicle or its vicinity. On the output side, wireless communications 124, not necessarily the same as for the input side, contribute infonnationto other vehicles, independent providers, authorities or other agents. Some information may be directed to display device 126 in the vehicle to be used by the driver or other passengers or both. A typical example is a map depicting the position of the vehicle on the map. Audio signal generator or loudspeaker 128 issues typically announcements or voiced warnings. Control signal generator 130 is an output contributed by the HMP that directly intervenes with the way the vehicle or parts of it function, without necessarily consulting the driver.

Example 4: Another frequently accused factor in the occurrence of road accidents is the condition of the tires. The degree of inflation is an important factor governing the road grip and the wear of the tires. In an embodiment of the invention, the vehicle employing the system of the invention uses has both a sensor for monitoring the pressure in side the wheels, and a pumping apparatus that can both inflate and deflate the wheels. Thus, the lIMP receives sampled data concerning the inflation of the wheels. This data can be reconciled with different data received, for example the velocity of travel, road wetness and temperature to issue HT for the wheels. This transient HT allows the HMP to constantly keep the level of inflation of the wheels such that the

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In example 5, the use of navigating systems is described in conjunction with other sorts of infonnation obtained, for maldng road travel a safer task. The Accurate to very accurate navigation system are known and publicly available. The OPS system of navigation satellites is free for use and provides accuracy within the range of tens of meters, if unobstructed. Differential GPS (dOPS) which uses a mobile GPS receiver and a static reference receiver may provide accuracies within the range of centimeters. In accordance with the present invention, a vehicle busing the system of the invention, receives navigation information from a navigation system, such that the memory of the HMP is always updated and the cunent location of the vehicle is always shown on an electronic map. Such a map is optionally presented on a display screen in the vehicle.

Concomitantly, other information is received by the HtvIP, both from sources relating to condition of the vehicle, and from independent sources, in addition to the navigation information. The independent information in this example is publicly broadcasted geographical distribution of road elements. Thus information regarding road signs, blocks, borders, bridges, crossings and the like.

All this information is registered to the map of the HMP and since the navigation fix is constantly registered to the map, there is a constant geographical relationship between the traveling vehicle and the road elements. The constantly updating of road element information allows the HMP to assess traffic code violations by the vehicle and by other vehicles. Thus, if for example the vehicle travels in a limited speed section and surpasses that limit. The HMP, getting speed information from the speed monitor, would issue an alert to the driver. If the driver is listening to music at too loud a volume, an obstruction to the heaiing and responsiveness is expected, and to that extent a noise sensor inside the vehicle is disposed, for feeding noise information to the HMP. The noise assessment by the HMP may result in noise reduction, rendering the driver and passengers more receptive to alerts. The information presented regarding road elements also helps in assessing collision risks. If a road bather exists separating between opposite lanes of the same road, the HMP may omit, at such sections of the road the possibility of head to head collision.

To emphasize the importance of the integration of a plurality of mapping inputs and optionally with the implementation of navigation means as a travel risk reduction scheme, the following example 5 is given next. A vehicle traveling in an urban environment, uploads to the I-IMP an official digital map of the of the city, including the coordinates of roads, traffic signs, * * *** * * * S S S S ** 555 * S * S * * * S S S * S. S S S * * S * S S ** . S *5. * S traffic lights, and the speed limits associated with certain sections of the roads. A parking lot map issued by a proprietor of the parking lots in that area is superimposed on the official map, by matching coordinates. A compound map is then formed. The navigation signals are constantly being interpreted as dynamic location of the vehicle on the compound map. The driver who wishes to find a parking place is directed towards parking lots by audio signals. On the other hand, the navigation means, if accurate enough can be used calculate the speed (dividing distances traveled by time) and the HMP can warn the driver of passing speed limit. Also while the driver is struggling to find a parking, the I-IMP may issue alerts as to one way roads, and other prohibitions.

Also, concomitantly, the vehicle get updates relating to hazards relating to the traffic. The constant updating and instruction issuance are extremely beneficial to taxi drivers and bus drivers who must pay attention to more factors than ordinary drivers.

Another significant contribution of the system of the invention to the safety of driving is the ability to forecast hazards or impediments to travel in extended time frames. Information provided online by a wireless communications link about traffic hazards, traffic jams and accidents, is received and used by the HMP that calculate time of arrival into a hazardous site. A first vehicle, traveling in a certain direction and at certain velocity that employs the system of the invention, can calculate its location and speed based on navigation data. The data of speed and location can be transmitted and can further be used by a second vehicle to calculate the probability of future coffision with the first vehicle.

As most modern cars utilize processors for the control and function of various appliances as well as for the reporting of status of various subsystems to driver, the linking of such processors to the HMP is recommended. In some embodiments, the HMP may be integrated in to a processor of the vehicle or vice versa. S *

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Claims

A system for managing traffic hazards of a vehicle comprising: * a hazard management processor (JHIMP) for processing data relating to traffic hazards; * sources of information feeding said lIMP wherein said sources are categorized as vehicle significant volatile conditions data sources; * sources of information feeding said lIMP wherein said sources are categorized as vehicle independent autonomous data sources; * a communications system for wirelessly communicating with sources of data, and * a communications system for communicating with other vehicles, wherein said processor is capable of sending signals for controlling the travel of said vehicle and of sending alert signals to a driver of said vehicle.
2. A system for managing traffic hazards of a vehicle as in claim I wherein said vehicle significant volatile conditions comprise at least vehicle related risks.
3. A system for managing traffic hazards of a vehicle as in claim I wherein said vehicle significant volatile conditions comprise at least environmental conditions associated risks.
4. A system for managing traffic hazards of a vehicle as in claim 1 wherein said vehicle significant volatile conditions comprise at least extra vehicular associated risks.
5. A system for managing traffic hazards of a vehicle as in claim 1 wherein said vehicle significant volatile conditions comprise at least passenger related risk.
6. A system for managing traffic hazards of a vehicle as in claim 2 wherein said vehicle related risks comprise at least the degree of wheel inflation.

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7. A system for managing traffic hazards of a vehicle as in claim 1 wherein said vehicle independent autonomous data are physically loaded into a memory of said HMP.
8. A system for managing traffic hazards of a vehicle as in claim 1 wherein said vehicle independent autonomous data sources communicate with said HMP by wireless communications link.
9. A system for managing traffic hazards of a vehicle as in claim 1 wherein said vehicle independent autonomous data sources comprise at least geographical information.
10. A system for managing traffic hazards of a vehicle as in claim 1 wherein said vehicle independent autonomous data sources comprise at least road system associated infrastructure information.
11. A system for managing traffic hazards of a vehicle as in claim 1 wherein said vehicle independent autonomous data sources comprise at least traffic updates.
12. A system for managing traffic hazards of a vehicle as in claim 1 wherein said vehicle independent autonomous data sources further comprise at least one navigation system.
13. A system for managing traffic hazards of a vehicle as in claim 9 wherein said geographical information further comprise at least one digital map.
14. A system for managing traffic hazards of a vehicle as in claim 13 and wherein said map is compound.
15. A method for managing the hazard level of a vehicle wherein a hazard management processor (HMP) receives streams of data relating to significant * S **. * S..

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volatile conditions of the vehicle and to vehicle - independent and autonomously supplied data stream, and wherein said HMP constantly calculates the volatile hazard status of said vehicle, and wherein said HMP receives warning from other vehicles at the vicinity of said vehicle over wireless communications.
16. A method for managing the hazard level of road travel as in claim 15 and wherein the location and the velocity of said vehicle is measured by reference to a navigation system.
17. A method for managing the hazard level of road travel as in claim 15 and wherein said vehicle independent and autonomously supplied data is obtained by a wireless communication link.
18. A method for managing the hazard level of road travel as in claim 17 and wherein said vehicle independent and autonomously supplied data is obtained on - line.
19. A method for managing the hazard level of a vehicle wherein a hazard management processor (HMP) receives streams of data relating to significant volatile conditions of the vehicle and to vehicle independent and autonomously supplied data stream, and wherein said HN'IP constantly calculates the volatile hazard status of said vehicle, and wherein hazards and impediments to travel are forecasted.

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