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Kotani, K., Sun, W., Kitani, T., Shibata, N., Yasumoto, K., Ito, M.:Inter-Vehicle Communication Protocol for Cooperatively Capturing and Sharing Intersection Video, Proc. of 2nd IEEE Intelligent Vehicular Communications System Workshop (IVCS'10), (CD-ROM), Jan. 9th, 2010. DOI:10.1109/CCNC.2010.5421635 (Jan. 2010). http://www.aist-nara.ac.jp/~sunweihua/papers-fullversion/I-10-01-02.pdf For accident prevention at intersections, it is useful for drivers to grasp the position of vehicles in blind spots. This can be achieved without infrastructure if some vehicles passing near the intersection capture and share live video of the intersection through inter-vehicle communications. However, such video streaming requires a congestion control mechanism. In this paper, aiming to let a driver grasp the situation at an intersection, we propose a method to select vehicles that send a video in order to generate a live bird’s-eye-view video of the intersection. In our method, each vehicle at an intersection exchanges information with others, such as the sub-areas of the intersection it captures, the quality of its video, and its position and speed. Based on the exchanged information, each vehicle autonomously judges whether it should send its video or not. Through simulation with a QualNet simulator, we confirm that our method achieves a good video arrival rate and video quality sufficient for practical use.
Citation preview
Kazuya Kotani†1, Weihua Sun†1, Tomoya Kitani†2,
Naoki Shibata†3, Keiichi Yasumoto†1, Minoru Ito†1
†1 Nara Institute of Science and Technology (NAIST), Japan†2 Shizuoka University, Japan
†3 Shiga University, Japan
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Inter-Vehicle Communication Protocol forCooperatively Capturing andSharing Intersection Video
(revised slides)
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Goal: Allow drivers to grasp vehicle positionsin blind spots at intersections
Overview
Proposed Method• Vehicles shoot videos from onboard cameras• Each vehicle decides if it should send its video wirelessly
• according to available bandwidth, etc.• Each vehicle receives videos from multiple vehicles and
compose them into a Bird's Eye View Video (BEVV)• In order to reduce latency, It does not use multi-hop
communication
1. Background
2. Related Work
3. Proposed Method
4. Experimental Results
5. Conclusion
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Outline
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We propose a system that allows drivers to seevehicle positions in blind spots in an intuitive way
Intersection43.9 %
Local Street26.8 %
Vehicles in blind spots
[1] ITS: “Ministry of Land, Infrastructure, Transport and Tourism,”http://www.mlit.go.jp/road/ITS/.
Background
City area74.8 %
43.9% of traffic accidents happen at◦ intersections in city area[1]
They are collisions between◦ vehicle and vehicle◦ vehicle and pedestrian
Most of these are caused by
1. Background
2. Related work
3. Proposed method
4. Experimental results
5. Conclusion
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Outline
DSSS(Driving Safety Support Systems) project [2]◦ Gathers other vehicles’ position with inter-vehicle comm.◦ Vehicles without communication devices are not displayed◦ Positions are not accurate because of GPS positioning error
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[3] Ota et al. : ``Visual Reconstruction of an Intersection by Integrating Cameras on Multiple Vehicles,’’ Proc. on Machine Vision Applications (MVA2007), pp.335–338(2007).
[2] Honda Motor Co., Ltd.: “Honda Technology,” http://www.honda.co.jp/news/2009/4090219.html?from=rss.
Method to compose a birds-eye-view video(BEVV)[3]
◦ Multiple videos are taken from multiple cars from different angles◦ Videos can be composed into one BEVV◦ The method includes no mechanism for exchanging videos
Related Work
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IEEE802.11b, 200 Kbps
1 2 3 4 5 6 7 8 9 100
102030405060708090
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Number of Vehicles
Pa
ck
et
Arr
ive
d R
ati
o
[%]
Problems with this method• Vehicle density can be too high• Wireless bandwidth is not insufficient
We need to carefully select vehicles that send videos to save wireless bandwidth
Problem with a straightforward approach forexchanging captured video
1. Vehicles broadcast request messages before turning right at intersection2. All vehicles in intersection capture and send videos wirelessly3. Vehicles receive videos and compose BEVV
The straightforward method
Objectvie◦Drivers need high quality view of the blind spots
Approach◦Assign priority to each vehicle for sending video◦The following vehicles are assigned high priorities
Vehicles that can capture the requested areas Vehicles that can capture high quality videos
◦Vehicles send out the captured video according to their priorities
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Key Idea for Selecting Vehicles
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1. Background
2. Related work
3. Proposed method
4. Experimental results
5. Conclusion
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Outline
We assume that it is possible to compose a BEVV from videos taken from any different angles
We conducted preliminary experiment with scaled down model of intersection
convert
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compose
Assumptions
Captured on camera
Converted video frame
Multiple video frames
Bird’s eye view frame
An intersection is divided into rectangular cells◦ Each cell is defined by its geographical position◦ Each vehicle knows which cell it is located◦ Each vehicle know cells that can be captured by its camera
Finer position can be determined by visually analyzing captured video[4]
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Requesting vehicle
[4] Alberto et al. : `` Multi-Resolution Vehicle Detection using Artificial Vision,’’ Proc. on IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV’04), pp.310–314(2004).
Dividing Intersection into Cells
Request cells
Vehicles have the following equipment◦ On-board camera◦ Car navigation system with GPS◦ Wireless LAN communication device◦ On-board computer
On-board computer can sense the state of indicator (going straight, turning left or right)
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Assumptions on Vehicle
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1. All vehicles periodically exchange Hello Message
2. Requesting vehicle broadcasts Request Message
3. Each vehicle which received Request Message calculates all vehicles’ Priority
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0
00
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0
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4. Each vehicle decides if it should send video frames
Requesting vehicle
How Proposed Method Works
There are two phases in the proposed method
Information Exchange Phase◦ Vehicles exchange messages to get the information from
the surrounding vehicles
Vehicle Selection Phase◦ Videos are sent utilizing available bandwidth as much as
possible◦ Priority is calculated in this phase
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Two phases in the proposed method
Goal : Each vehicle knows other vehicles’ information
Vehicles close to an intersection exchange the following messages
Hello Message◦ All vehicles inform their own status to other vehicles
position, speed, capturing cells, video quality, number of video frames already sent
Request Message◦ Requesting vehicle sends requested cells to other vehicles
items of Hello Message, requested cells◦ When a vehicle receives a Request Message, it transits to Vehicle
Selection Phase
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Information Exchange Phase
Goal : Making vehicles send videos utilizing available bandwidth as much as possible
Vehicles need to know the usage of communication bandwidth◦ The usage of communication bandwidth is defined by the ratio
of
To decide if each vehicle should send videos◦ Calculate the priority based on the following items
Requested cells that can be captured by the camera on vehicle Video quality for each cell
◦ Priority is the weighted sum of these values
Preliminary experiment We conducted preliminary experiment to determine these weights 16
Vehicle Selection Phase
Number of actually received video framesNumber of video frames informed in Hello messages
Deciding if each vehicle sends video Each vehicle calculates priorities of vehicles
independently◦ Usually, the results of calculations are almost same
For each direction, the vehicle with the highest priority decides to send the video
◦ For each direction, usually the car closest to the center of intersection starts sending video
◦ Then, the cars following the first car sends their videos in turn
◦ The priority is dynamically changed according to the positions of moving vehicle
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Vehicle Selection Phase(contd.)
1. Background
2. Related work
3. Proposed method
4. Experimental results
5. Conclusion
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Outline
Goal◦ To see if the proposed method can select vehicles that capture
requested cells in high quality
Evaluation criteria1. The number of video frames covering each cell in requested cells2. The number of video frames covering requested cells from each
driving direction3. The priority of video frame received by request vehicle
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Experimental Evaluation
We used QualNet[5]
◦ Created terrain data to imitate actual intersection in Kyoto, Japan
◦ Requesting vehicle goes into intersection ⇒ turns to the right
◦ The number of requesting vehicle is one
Transmitting bit rate: 200 [Kbps]
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Settings
Simulation parameters
Packet parameters
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item value
The number of vehicles 60
Requested cells 3 cells
Wireless LAN standard IEEE802.11b
Vehicle density Dense, Middle, Sparse
Carrying rate of equipments 100%, 60%, 30%
Packet name Packet sizeTransmission
interval
Hello Message 300[byte] 0.5[s]
Request Message 300[byte] 0.5[s]
Video frame 1666[byte] 0.067[s]
Parameter setting of experiment
We compared the following methods for selecting vehicles to send their videos i. Proposed method
ii. All vehicles
All vehicles near intersection send video
iii. Vehicles closest to the center of intersection
The vehicle closest to the center of intersection from each
driving direction sends video
Measured evaluation criteria with these three methods
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Comparison of Three Methods
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Request vehicle
Request cells
green1
green2
red2
red1
1 2
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Evaluation experimentDriving directions and request cells
In order to see vehicles in blind spot by video, video quality of at least 10[fps] in average is necessary
RNF is the minimum number of received frames that satisfies the above condition for each cell◦ Simulation time and RNF value in each density setting are
below
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Required Number of Frames (RNF)
Vehicle density Dense Middle Sparse
Simulation time 35[s] 58[s] 88[s]
RNF(each direction) 350[frame] 580[frame] 880[frame]
RNF(each cell) 1400[frame]
2400[frame]
3520[frame]
×4 (driving directions)
In Dense setting with 100% carrying rate◦ Proposed method achieves RNF on all request cells◦ All vehicles doesn’t achieves RNF on any cells◦ Vehicles near the center achieves RNF on two cells
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Number of video frames (Request cells) 1/3
call1 cell2 cell30
500
1000
1500
2000
2500
3000
Proposed methodAll vehiclesVehicles near the centerRNF
Request cells
Nu
mb
er
of
Re
ce
ive
d F
ram
es
In Dense Middle and Sparse setting with 100% carrying rate◦ Proposed method sends more frames than any other method
regardless of vehicle density
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Number of video frames (Request cells) 2/3
call1 cell2 cell30
500
1000
1500
2000
2500
3000
Request cells
Nu
mb
er
of
Re
ce
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d F
ram
es
cell1 cell2 cell30
500
1000
1500
2000
2500
3000
3500
4000
4500
5000
Request cells
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mb
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of
Re
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ive
d F
ram
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cell1 cell2 cell30
1000
2000
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4000
5000
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7000
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Proposed method
All vehicles
Vehicles near the cen-ter
RNF
Request cells
Nu
mb
er
of
Re
ce
ive
d F
ram
e
Dense Middle Sparse
In Dense setting, with 100, 60, 30% carrying ratio◦ Proposed method provides more frames than other methods ◦ Request cells achieving RNF decreases as carrying rate decreases
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Number of video frames (Request cells) 3/3
call1 cell2 cell30
500
1000
1500
2000
2500
3000
Request cells
Nu
mb
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of
Re
ce
ive
d F
ram
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call1 cell2 cell30
500
1000
1500
2000
2500
3000
Request cells
Nu
mb
er
of
Re
ce
ive
d F
ram
e
call1 cell2 cell30
500
1000
1500
2000
2500
3000
Proposed method
All vehicles
Vehicles near the cen-ter
RNF
Request cells
Nu
mb
er
of
Re
ce
ive
d F
ram
e
100% 60% 30%
In Dense setting with 100% carrying rate◦ Proposed method achieves RNF from all directions◦ Other methods achieve RNF from one or two directions
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Number of video frames (Driving direction)
green1 green2 red1 red20
200
400
600
800
1000
1200
1400
1600
1800
Proposed methodAll vehiclesVehicles near the centerRNF
Driving Direction
Nu
mb
er
of
Re
cie
ve
d F
ram
e
In Dense setting with 100% carrying rate◦ There are more high priority frames by proposed method than other
methods
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24~30 18~24 12~18 6~12 0~60
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Proposed method 100%All vehicles 100%Vehicles near the center 100%
Priority
Cu
mm
ula
tive
Den
sity
of
Frm
ae[%
]
Effective in Dense setting with 60% or more carrying rate More efficient than other methods in all environments
Conclusions of experiment results about proposed method
PriorityCumulative distribution function (CDF) graph
Proposed method can make BEVV which contains request cells in high quality
Vehicle selection method◦ For creating a bird's eye view video by letting selected
vehicles efficiently capture and exchange video◦ It assigns priorities to send videos to other vehicles◦ Vehicle with higher priority sends videos within the
available communication bandwidth Results
◦ Proposed method is especially effective in the dense setting with 60% or more arrival rate
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Conclusion
Kotani, K., Sun, W., Kitani, T., Shibata, N., Yasumoto, K., Ito, M.:Inter-Vehicle Communication Protocol for Cooperatively Capturing and Sharing Intersection Video, Proc. of 2nd IEEE Intelligent Vehicular Communications System Workshop (IVCS'10), (CD-ROM), Jan. 9th, 2010.
DOI:10.1109/CCNC.2010.5421635 [ PDF ]
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