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FORM 2
The Patent Act 1970
(39 of 1970)
&
The Patent Rules, 2005
COMPLETE SPECIFICATION
(SEE SECTION 10 AND RULE 13)
TITLE OF THE INVENTION
“System for providing Travel Information using Sensor Devices”
APPLICANTS:
Name Nationality Address
Alcatel Lucent France 54 rue de la Boétie, 75008 Paris, France
The following specification particularly describes and ascertains the nature of this
invention and the manner in which it is to be performed:-
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BACKGROUND
Technical Field
[001] The embodiments herein relate to data processing systems, and, more
particularly, to providing travel information services.
5
Description of the Related Art
[002] In most countries, traffic growth is out-stripping road capacities and the
road infrastructure is not able to cope with rapid economic growth. The roads operate
very close to full capacity during peak hours and as a result, a small perturbation in traffic
10 volume translates to significant traffic jams causing inordinate delays in travel time. This
creates under-utilization of valuable human-hours. Further, road congestion induces
wastage of fuel.
[003]A variety of traffic related information is now available for use in aiding
vehicle operation. Generally, urban road networks are provided with traffic speed sensing
15 devices at strategic locations. These devices detect the speed of passing vehicles, vehicle
types and collects traffic flow rates along specific sections of roadways traveled heavily.
The information can be compiled and broadcasted over Amplitude Modulation (AM)/
Frequency Modulation (FM) radio stations to provide accurate travel-time estimates in
real-time to users. This provides an opportunity to the user to select an alternative route.
20 [004]Currently, Cellular communication or Global Positioning System (GPS)
devices are used to detect location estimates and consequently travel-time estimates of
vehicles. The GPS devices are usually carried within the vehicles. The speed of the
vehicle can then be obtained from the GPS location data provided by the GPS devices at
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different points at different times. Usually location estimates are obtained by
triangulation of the cellular signal obtained by the devices from different base stations.
[005] In another existing solution, sensors are placed on roads at various locations
to provide for travel information system. Sensing devices themselves are quite expensive.
And installation and maintenance of these sensing devices further 5 make the system more
expensive. Furthermore, backhauling of the information adds to the cost of such a system.
Also, placing video-cameras and processing systems with the sensing devices incur
additional cost. The high-cost makes the information solution impractical for large scale
deployment. Further, maintenance and troubleshooting of sensors can be a difficult task
10 as it involves human intervention and possible traffic disruption. The sensory system
suffers poor fault tolerance as the sensors are sparsely placed. A single faulty sensor may
cause the system to wrongly estimate the travel-time information on the road. Also,
placing additional redundant sensors to improve fault-tolerance is not feasible due to high
costs.
15 [006] Furthermore, acquiring GPS information from vehicles and phones involves
privacy issues. Also, obtaining GPS location information from a phone can drain battery
power and may create additional load on the network. GPS devices require line-of-sight
with satellites for transmitting information. Thus implementation of the system would be
an issue in urban areas, as the systems may not work in places with high rise buildings
20 that obstruct the line-of-sight to satellites.
[007]Moreover, use of cellular triangulation systems is not sufficiently accurate to
locate a vehicle on a road segment in an urban area. The phones need to be in active
mode for the service. However, to measure the vehicle accurately in two locations, which
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are considerably far apart, requires the call to last for a sufficiently long duration of time,
which may be very infrequent.
SUMMARY
[008] In view of the foregoing, an embodiment 5 herein provides a method of
providing travel information between a plurality of travel point to users. The method
comprises of a plurality of sensors acquiring information of devices in vehicles, the
plurality of sensors transmitting the information to a server, the server computing travel
information between different points of the plurality of sensors using the information, and
10 the server providing the travel information to the users, on receiving a request for the
travel information from the users. The sensors can detect devices using Bluetooth,
ZigBee, Wireless fidelity (Wi-Fi) or Radio Frequency Identification (RFID) and the
devices in vehicles can also be Bluetooth devices, ZigBee devices, Wireless fidelity (Wi-
Fi) devices or Radio Frequency Identification (RFID) devices. The information acquired
15 by the plurality of sensors comprises detection time of the devices in the vehicles and a
unique identifier of devices in the vehicles. The travel information comprises of at least
one of travel-time estimates and route computation estimates between different road
segments, where the road segment refers to length of road between two successive
sensors. The pluralities of sensors transmit the information of the vehicles to the server
20 over a wireless data link. The method further comprises of writing the travel information
into a data structure, updating periodicity of update interval of the travel information to
the plurality of sensors, reading the travel information from the data structure, refining
the travel estimates by capturing travel-time correlation between different road segments,
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and aggregating the travel estimates. The users can request the server for providing
information of real-time travel estimates between travel points, recommendation for timeof-
day to travel based on congestion level and historical data or traffic behavior over
road-segments on different days. The users can request for the travel information using a
Short Message Service (SMS), electronic mail, or Graphical 5 User Interface (GUI).
[009]Embodiments herein further disclose a system for transmitting traffic
information to a server. The system further comprises of a scanning unit for detecting
devices in vehicles, a storage unit for storing information from the scanning unit, an
uploading unit for periodically uploading the information to the server and a wireless data
10 link for transmitting the information from the uploading unit to the server. The scanning
unit comprises of a power supply unit, an identifier, and a plurality of dongles. The power
supply unit provides power supply through at least one of a plurality of batteries, solar
panel, or power grid connection.
[0010]Embodiments herein further disclose a system for providing travel
15 information between a plurality of travel point to users. The system comprises at least
one means adapted to acquire traffic information from a plurality of sensors, compute
travel information between different road segments, where the road segment refers to
length of road between two successive sensors, provide the travel information to the
users, on receiving a request for the travel information from the users. The system
20 comprises of a means adapted to write the travel information into a data structure, update
periodicity of update interval of the travel information to the plurality of sensors, read the
travel information from the data structure, refine the travel estimates by capturing traveltime
correlation between different the road segments, and aggregate the travel estimates.
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The travel information comprises of travel-time estimates and route computation
estimates between two road segments. The system further comprises a database for
storing real-time records of each road segment, the travel-time estimates, and precomputed
travel-times between different points of an area.
[0011] These and other aspects of the embodiments 5 herein will be better
appreciated and understood when considered in conjunction with the following
description and the accompanying drawings.
BRIEF DESCRIPTION OF THE DRAWINGS
10 [0012] The embodiments herein will be better understood from the following
detailed description with reference to the drawings, in which:
[0013] FIG. 1 is a block diagram illustrating an architecture of a Travel
Information System (TIS) providing real-time travel information to users, in accordance
with the embodiments herein;
15 [0014] FIG. 2 is a block diagram illustrating functional elements of a sensor for
obtaining the vehicle information, in accordance with the embodiments herein;
[0015] FIG. 3 is a block diagram illustrating the functional elements of a server
for computing a vehicle travel-time between two locations, in accordance with the
embodiments herein;
20 [0016]FIG. 4 illustrates a flow chart depicting a method of providing real-time
travel information to users, in accordance with the embodiments herein;
[0017] FIG. 5 illustrates a flowchart depicting a method of aggregating sensory
data, in accordance with the embodiments herein; and
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[0018] FIG. 6 illustrates a flow chart depicting a method of computing travel-time
of vehicles, in accordance with the embodiments herein.
DETAILED DESCRIPTION OF EMBODIMENTS
[0019] The embodiments herein and the various features 5 and advantageous details
thereof are explained more fully with reference to the non-limiting embodiments that are
illustrated in the accompanying drawings and detailed in the following description.
Descriptions of well-known components and processing techniques are omitted so as to
not unnecessarily obscure the embodiments herein. The examples used herein are
10 intended merely to facilitate an understanding of ways in which the embodiments herein
may be practiced and to further enable those of skill in the art to practice the
embodiments herein. Accordingly, the examples should not be construed as limiting the
scope of the embodiments herein.
[0020]The embodiments herein achieve a system and method for providing real15
time travel information to users for enabling users to make decisions on travel route and
travel time. Referring now to the drawings, and more particularly to FIGS. 1 through 6,
where similar reference characters denote corresponding features consistently throughout
the figures, there are shown embodiments.
[0021] The embodiment herein discloses a method of providing an automated
20 Travel Information System (TIS) to users. A plurality of scanning devices is placed along
the road-side. The scanning devices can detect devices present in the vehicles, which are
using Bluetooth, ZigBee, Wi-Fi, Radio frequency Identification (RFID) or any other form
of near field communication. The scanning devices can detect vehicles carrying devices
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capable of near field communication and note down a unique ID of the device and the
time fo detection of the vehicles. As an example, the scanning devices detects vehicles
with Bluetooth devices and note a unique Bluetooth ID of the device. The information is
then transmitted periodically to a server over a wireless data link. The server aggregates
the data from different sensors, cleans the data and writes the 5 data into appropriate data
structure. An engine for travel-time computation reads the data from the data structure
and computes the travel time estimate between two successive sensors. The server refines
travel time estimates using statistical techniques by capturing the travel-time correlation
between different segments of the road. The server then computes travel-time along
10 different routes and provides the travel information to users on request.
[0022]FIG. 1 is a block diagram illustrating a Travel Information System (TIS)
providing real-time travel information to users, in accordance with the embodiments
herein. The device 102 can be any communication device having a radio interface and is
carried by users 101. The device can use Bluetooth, ZigBee, Wi-Fi, RFID or any other
15 form of near field communication as a radio interface. A plurality of sensors 103 are
placed along the side of roads. The sensors 103 can detect devices present in the vehicles,
which are using Bluetooth, ZigBee, Wi-Fi, Radio frequency Identification (RFID) or any
other form of near field communication. The sensors 103 constantly operate in scanning
mode. As vehicles with devices 102 drive past any of the sensors 103, the sensors 103
20 detect the device 102 and record a unique identifier (for example, Media Access Control
Identification Card (MAC ID)) and the time of detection of the device 102. A sensor 103
can simultaneously access a plurality of devices 102 carried by users 101 for recording
traffic information of vehicles. The sensor 103 then periodically transmits the information
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to a backend server 105 through a wireless data link 104. The periodicity of
communication between the sensor 103 and the server 105 depends primarily on
congestion build-up time. The cost of sensors 103 are considerably less which allows
widespread deployment across a wide area. The sensors 103 also aggregate observations
and select convenient update intervals to create minimum load on the 5 wireless data link
104. For instance, the wireless data link 104 can be provided from a direct 3G/WiMAX
connection, local aggregation followed by a 3G/WiMAX connection from aggregator,
RS-232 wireless link, or the like. The server 105 correlates the unique ID observed
between any two sensors 103 to compute the travel time between the points at which the
10 sensors 103 are placed in real time. The real-time travel estimates, route information and
other relevant information is provided to users on request.
[0023]FIG. 2 is a block diagram illustrating the functional elements of a sensor
for obtaining the vehicle information, in accordance with the embodiments herein. A
sensor 103 is a computing device comprising of a scanning unit 201, a storage unit 205,
15 an uploader unit 206 and a wireless data interface 207. The scanning unit 201 comprises
of constant power supply unit 202, unique identifier 203 and a plurality of dongles 204.
The power supply 201 can be through a battery, a solar panel or a connection from power
grid. The identifier 202 uniquely determines the location of the sensors 103 on the road.
The plurality of dongles 204 comprise of a dongle for each near field communication
20 technology used by the sensor 103. For example, a sensor may comprise of a Bluetooth
dongle, a dongle for detecting ZigBee devices, a dongle for detecting Wi-Fi devices and a
dongle for detecting RFID devices. The sensors 103 constantly operate in scanning mode.
As vehicles with devices 102 drive past any one of the sensors 103, sensor 103 detects
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the devices 102 and records the unique identifier (for example, MAC ID of the devices)
102 and the time of detection of the devices 102. The sensors 103 also aggregate
observations and select convenient update intervals to create minimum load on the
wireless data link 104 on reception of an instruction from server 105 to modify update
interval. The sensors 103 store the information collected from the 5 devices and the vehicle
detection time temporarily in the storage unit 205. The uploading unit 206 then
periodically uploads the information to the server 105 through the wireless data
connection 205. The periodicity of transmission of information to the server 105 depends
on the congestion build-up time.
10 [0024]FIG. 3 is a block diagram illustrating the functional elements of a server for
computing a vehicle travel-time between two locations, in accordance with the
embodiments herein. The server 105 is connected to the sensors 103 through the wireless
data link 104. The sensory data aggregator 301 engine receives data from different
sensors 103 periodically and aggregates the sensory data. The sensory data is then passed
15 to a data cleansing engine 302 which cleans the data using suitable data mining
techniques and writes the data into an appropriate data structure. The data cleansing
engine 302 removes extraneous data which includes pedestrians, vehicles moving slowly
for reasons other than congestion, multiple devices detected in a single vehicle and the
like. The data cleansing engine 302 also accounts for removing multiple detections of the
20 same device 102 at the same sensor 103. The sensory data aggregator 301 then updates
the sensors 103 about the periodicity of uploading the traffic data into the server 105. The
travel-time computation engine 303 reads data from a data structure created by sensory
data aggregator 301 and computes an initial travel time estimate on each road segment. A
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road segment is the length of the road between two successive sensors 103. The traveltime
computation engine 303 captures the travel-time correlation between different
segments of the road and uses statistical techniques to refine the travel time estimates.
For instance, in a case where few samples exist in a particular road segment but more
data samples exist in the nearby road-segments, it is possible to 5 define the travel-time
estimate in the road-segment with few samples by capturing the correlation of travel-time
between the segments. The travel-time computation engine 303 creates a moving average
of the travel-time along different road-segments. Further, the travel-time computation
engine 303 computes the travel time along different routes between key points in an area
10 and stores the data in an appropriate data structure in a database 304. The database 304
stores real-time data 305 for each road-segment. The database 304 also stores predicted
travel-time estimates for near-future and pre-computed travel-times between different
clusters in an area. The database 304 also stores extensive archived data 306 about the
travel times required for resolving non-real-time queries, for predicting segment travel
15 times in the near-future based on current travel-time. The database 304 also stores and
updates the time-correlation, stores information about spreading of congestion during
street mishaps and stores and updates information about spatial-correlation. The route
computation engine 307 accepts queries from the query-processing front-end and queries
the database 304 to perform route computation. The route computation engine 307
20 queries either real-time data 305 or archived data 306 based on the query from users 101.
The engine for serving user requests 308 is also responsible for catering to user requests.
The request may be for real-time travel estimates, recommendation for time-of-day to
travel based on current congestion levels and historical data, traffic behavior over road12
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segments on different days and the like. The information request from users may be SMS
based, email based or GUI based.
[0025]FIG. 4 illustrates a flow chart depicting a method of providing real-time
travel information to users, in accordance with the embodiments herein. A default update
interval for sensor and the sensor ID is input (401) to the 5 sensor 103. The sensor 103
operates (402) in scanning mode. The sensor 103 periodically performs a check (403) to
verify if time from last update is greater than the initial update interval. If the time is less
than the update interval, the sensor collects and inputs (401) traffic data at the default
interval. If the time is greater than the update interval, the sensor 103 performs a further
10 check (404) if any instruction to modify the update interval is received from the server
105. If there is an instruction from the server 105, the sensor 103 modifies (405) the
update interval and collects traffic data at the updated interval. The sensor 103 placed
along the road waits (406) for a device 102 to be detected. On detecting a device 102, the
sensor 103 records (407) a unique identifier of the device 102, for example, the MAC ID
15 and the vehicle detection time in a log file. The sensor 103 then sends (408) the log file to
the server 105 at periodic intervals over the wireless data link 104. The sensory data
aggregator 301 collects the data from different sensors, cleans the data and writes (409)
the data into a traffic data structure. The travel-time computation engine 303 reads (410)
the data from the data-structure created by the sensor data aggregator 301 and computes
20 an appropriate travel time estimate on each road-segment. The travel-time computation
engine 303 then uses algorithms to refine (411) the travel-time estimates by capturing
travel-time correlation between different segments of the road. The engine 303 then
computes (412) the travel-time between two points in a coverage area and prepares (413)
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different route computations between the two points by querying the database 304. The
engine then stores the travel data in an appropriate data structure in the database 304. The
server 105 then performs a check (414) to find if any request for travel information has
been received from users 101. If a request is received, the engine for serving user
requests 308 provides (415) the information to the 5 users 101. If no request for
information is received, the system stores the data and waits (416) for a request from
users 101. The request may be for obtaining real-time travel estimates, recommendations
for time-of-day to travel based on congestion level and historical data, traffic behavior
over road-segments on different days and so on. The users 101 can request for
10 information using SMS, email or GUI. The various actions in method 400 may be
performed in the order presented, in a different order or simultaneously. Further, in some
embodiments, some actions listed in FIG. 4 may be omitted.
[0026]FIG. 5 illustrates a flowchart depicting a method of aggregating sensory
data, in accordance with the embodiments herein. The sensory data aggregator 301
15 engine present in the server 105 receives (501) log file containing traffic data from the
sensor 103. The sensory data aggregator 301 performs a check (502) to find if the travel
time computation engine 303 has modified the update interval time for any sensor 103. If
the update interval is modified, then sensory data aggregator 301 notifies (503) the
modified update interval to the sensor 103 for uploading traffic data to the server 105.
20 Further, the sensory data aggregator 301 creates (504) a new log file by inputting the
update interval time to the sensor 103. If the update interval time is not modified, then the
sensor 103 measures (505) the traffic data at the default update interval. On receiving the
traffic data from the sensor 103, the data is cleansed (506) using suitable data mining
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techniques by a data cleansing engine 302. The data cleansing engine 302 removes
extraneous data which includes pedestrians, vehicles moving slowly for reasons other
than congestion, multiple devices from a single vehicle and the like. The data cleansing
engine 302 also accounts for removal of multiple detections of the same device 102 by
the same sensor 103. Further, the data aggregation engine writes 5 (507) the data into an
appropriate data structure. The various actions in method 500 may be performed in the
order presented, in a different order or simultaneously. Further, in some embodiments,
some actions listed in FIG. 5 may be omitted.
[0027]FIG. 6 illustrates a flow chart depicting a method of computing travel-time
10 of vehicles, in accordance with the embodiments herein. The travel-time computation
engine 303 in the server 105 obtains (601) the data from traffic data structure updated by
the sensory data aggregator 301. The travel time computation engine 303 then computes
(602) travel time within a specified update interval for each road segment, where road
segment refers to the length of the road between two successive sensors 103. The travel15
time computation engine 303 then performs a check (603) to find if the update interval
needs to be modified for any sensor 103. If modification of the update interval is
required, then modify the update interval and notify (604) the new update interval to the
sensor 103. If modification of the update interval is not required, then the travel-time
computation engine 303 determines (605) travel-time and route confirmation estimates by
20 capturing travel time correlation between different segments of the coverage area at the
default update interval. Further, the travel-time computation engine 303 computes (606)
travel-time and routing information between two points in the coverage area and saves
the estimates in appropriate data structure in the database 304. The various actions in
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method 600 may be performed in the order presented, in a different order or
simultaneously. Further, in some embodiments, some actions listed in FIG. 6 may be
omitted.
[0028]The embodiment disclosed herein provides accurate prediction of traveltime
for various options between starting point and destination 5 to users. The embodiment
is useful for users to plan a time for a trip and also to find appropriate routes. The
embodiment can be used to plan for complex travel routes. The system can be used to
answer complex queries like, for 10 destination points and each with a deadline, the best
travel route and so on. For example, for a user travelling from a point A to a point Z, the
10 user can request for information on the time required to reach point Z, traffic volume on
the road, best possible routes to point Z etc. The commuter can request for the travel
information by sending an SMS or sending an email or using GUI. The travel-computing
engine in the sever, then reads travel-estimate between each road segment between the
points A to Z. The travel-estimate between each road segment A to C, C to F, and so on is
15 then aggregated to estimate the total travel-time from points A to Z. The server also
computes all possible routes between point A and point Z. On reception of a request from
the user, the server provides information on travel-estimate and routes to the users, which
in turn assists the users to select a route with less traffic congestion, or a short route to
reach point Z. The embodiment further aids city planners to study historical data like
20 traffic-load on a given route at certain hours. Furthermore, the embodiment alerts
authorities when road congestion occurs in a certain part of the city and also allows them
to study real-time and historical data so as to deploy more officials at points of heavy
congestion.
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[0029]The embodiment disclosed herein can be build with a comparatively lower
cost as compared to conventional sensing systems. The sensors exhibit excellent fault
tolerance properties and hence the presence of faulty sensors does not impact the system
performance. The embodiment does not fail to provide continuous travel-time prediction
as few samples lead to larger update interval of the travel-time. The 5 larger interval in turn
may not affect the travel time over a long route significantly. The embodiment combines
data from various sensors to improve the travel-time predictions. This reduces the
maintenance cost as the maintenance cost required for fixing a faulty sensor is
substantially less.
10 [0030]The embodiment herein provides data security to users by using devices
capable of near field communication to obtain vehicle data. The devices are considered
secure as only a unique identifier is accessed and also there is no mapping between the
identifier and the user. The embodiment can be deployed in dense urban environments as
well as highways.
15 [0031]The embodiment disclosed herein provides better estimates for having
more samples for predicting travel-times since devices using a form of near field
communications for example, phones with Bluetooth are extremely prevalent even in
developing nations. For example, a recent study indicates that 95% mobile phones in
India are equipped with Bluetooth.
20 [0032]The embodiment disclosed herein prevents location error as the locations of
the sensors are known precisely. The embodiment herein is stand-alone as it does not
require active support of a wireless service provider and thus have fewer dependencies as
compared to systems using cell-phones as probes. Also, cell-phones as probes require the
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phones to be making calls, thus reducing the potential number of data samples.
[0033]The embodiments disclosed herein can be implemented through at least one
software program running on at least one hardware device and performing network
management functions to control the network elements. The network elements shown in
FIGs. 1, 2 and 3 include blocks which can be at least one 5 of a hardware device, a
software module or a combination of hardware device and software module.
[0034]The embodiment disclosed herein specifies that the travel-information
system can be hosted as a separate entity or in combination with the already existing
elements of the network. Further, there exists similar means compatible to travel-time
10 computation engine for transforming the information acquired from vehicles into
information pertinent to travel related activities for users. Therefore, it is understood that
the scope of the protection is extended to such a program and in addition to a computer
readable means having a message therein, such computer readable storage means contain
program code means for implementation of one or more steps of the method, when the
15 program runs on a backend server or any suitable programmable device. The method is
implemented in a preferred embodiment through or together with a software program
written in e.g. Very high speed integrated circuit Hardware Description Language
(VHDL) or C, C++, Java, or using another programming language, or implemented by
one or more VHDL, C, C++, or Java processes or routines, or several software modules
20 being executed on at least one hardware device. The hardware device can be any kind of
device which can be programmed including e.g. any kind of computer like a server or a
personal computer, an FPGA, a processor, or the like, or any combination thereof, e.g.
one processor and two FPGAs. The device may also include means which could be e.g.
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hardware means like e.g. an ASIC, or a combination of hardware and software means,
e.g. an ASIC and an FPGA, or at least one microprocessor and at least one memory with
software modules located therein. Thus, the means are at least one hardware means
and/or at least one software means. The method embodiments described herein could be
implemented in pure hardware or partly in hardware and partly 5 in software. The device
may also include only software means. Alternatively, the invention may be implemented
on different hardware devices, e.g. using a plurality of CPUs or sensor devices.
10
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CLAIMS
What is claimed is:
1. A method of providing travel information between a plurality of travel points to
users (101), said method comprising steps of
a plurality of sensors (103) acquiring information of 5 devices (102) in vehicles;
said plurality of sensors (103) transmitting said information to a server (105);
said server (105) computing travel information between different points of said
plurality of sensors (103) using said information; and
said server (105) providing said travel information to said users (101), on
10 receiving a request for said travel information from said users (101).
2. The method as claimed in claim 1, wherein said sensors are capable of detecting a
device, said device using atleast one of
Bluetooth;
15 ZigBee;
Wireless Fidelity (Wi-Fi); or
Radio Frequency Identification (RFID).
3. The method as claimed in claim 1, wherein said devices can be a wireless device,
20 chosen from a group consisting of
Bluetooth devices;
ZigBee devices;
Wi-Fi devices; and
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Radio Frequency Identification (RFID) devices.
4. The method as claimed in claim 1, wherein said information acquired by said
plurality of sensors (103) comprises detection time of said devices (102) in said vehicles.
5
5. The method as claimed in claim 1, wherein said information acquired by said
plurality of sensors (103) comprises a unique identifier of said devices (102) in said
vehicles.
10 6. The method as claimed in claim 1, wherein said travel information comprises of at
least one of travel-time estimates and route computation estimates between different road
segments, where said road segment refers to length of road between two successive
sensors (103).
15 7. The method as claimed in claim 1, wherein said plurality of sensors (103) transmit
said information of said vehicles to said server (105) over a wireless data link (104).
8. The method as claimed in claim 1, wherein said method further comprising of
writing (409) said travel information into a data structure; and
20 updating periodicity of update interval of said travel information to said plurality
of sensors (103).
9. The method as claimed in claim 1, wherein said method further comprising of
reading (410) said travel information from said data structure;
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refining (411) said travel estimates by capturing travel-time correlation between
different said road segments; and
aggregating said travel estimates.
10. The method as claimed in claim 1, wherein said users 5 (101) can request said
server (105) for providing travel information comprising at least one of
real-time travel estimates between travel points;
recommendation for time-of-day to travel based on congestion level and historical
data; and
10 traffic behavior over road-segments on different days.
11. The method as claimed in claim 1, wherein said users (101) can request for said
travel information using at least one of
a Short Message Service (SMS);
15 electronic mail; or
Graphical User Interface (GUI).
12. A system for transmitting traffic information to a server (105), said system
comprising of:
20 a scanning unit (201) for detecting devices (102) in vehicles;
a storage unit (205) for storing information from said scanning unit (201); and
an uploading unit (206) for periodically uploading said information to said server
(105).
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13. The system as claimed in claim 11, further comprises a wireless interface (207)
for transmitting said information from said uploading unit (206) to said server (105).
14. The system as claimed in claim 11, wherein said scanning unit uses a wireless
sensor, said wireless sensor is capable of detecting a device, said device 5 using atleast one
of
Bluetooth;
ZigBee;
Wireless Fidelity (Wi-Fi); or
10 Radio Frequency Identification (RFID).
15. The system as claimed in claim 11, wherein said scanning unit (201) comprises of
a power supply unit (202);
15 an identifier (203); and
a plurality of dongles (204).
16. The system as claimed in claim 14, wherein said power supply unit (202) provides
power supply through at least one of
20 a plurality of batteries;
solar panel; or
power grid connection.
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17. A system for providing travel information between a plurality of travel points to
users (101), said system comprising at least one means adapted to
acquire traffic information from a plurality of sensors (103);
compute (412) travel information between different road segments, where said
road segment refers to length of road between two 5 successive sensors (103);
provide (415) said travel information to said users (101), on receiving a request
for said travel information from said users (101).
18. The system as claimed in claim 14, wherein said travel information comprises at
10 least one of travel-time estimates and route computation estimates.
19. The system as claimed in claim 14, wherein said system further comprising at
least one means adapted to
write (409) said travel information into a data structure; and
15 update periodicity of update interval of said travel information to said plurality of
sensors (103).
20. The system as claimed in claim 14, further comprising at least one means adapted
to
20 read (410) said travel information from said data structure;
refine (411) said travel estimates by capturing travel-time correlation between
different said road segments; and
aggregate said travel estimates.
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21. The system as claimed in claim 14, further comprising a database (304) for
storing at least one of
real-time records of each road segment;
said travel-time estimates; and
pre-computed travel-times between di 5 fferent points of an area.
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ABSTRACT
A method of providing real-time travel information to users is disclosed. A
plurality of sensors placed along road-side acquires traffic information from users
equipped with devices capable of using near field communication technology. The traffic
information is transmitted to a server, which computes travel information 5 using statistical
techniques and provides the information to users on request. The method comprises of
acquiring information of devices in vehicles, a plurality of sensors transmitting
information to a server, the server computing travel-estimates between two successive
points of sensors, the server refining travel-estimates by capturing travel-time correlation
10 between different road segments, aggregating travel-estimates, performing route
computation between road segments and providing the travel-estimates and routing
information to users. The traffic information includes the time of detection of vehicles
and a unique Identifier of the device passing the sensors and the information is
transmitted over a wireless data link to server.
15 FIG. 4