A Method for Pedestrian Position Estimation using

Inter-Vehicle Communication

Yuta Sawa , Tomoya Kitani †, Naoki Shibata†† Keiichi Yasumoto , Minoru Ito

Nara Institute of Science and Technology †Shizuoka University, ††Shiga University

04/12/2023 1Autonet 2008

Outline• Drivers do not notice pedestrians in blind spots• By exchanging information of pedestrian positions

among cars using inter-vehicle communication, drivers can notice pedestrians in the blind spot

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Contents• Background• Assumptions• Proposed method• Experiments• Conclusion

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Background• The total number of fatal traffic accidents is decreasing

in Japan[1]

However, the percentage of the number of traffic accidents where a pedestrian is killed or injured has been increasing

Some car manufacturing companies are developing mechanisms to detect pedestrians

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[1]National Police Agency, Japan: “Police White Paper”, http://www.npa.go.jp/hakusyo/index.htm

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Total Traffic Accident Fatalities Number

Percentage of pedestrians

Pedestrian’s Traffic Accident Fatalities Number

Related Work• Some of these mechanisms employ:

sensors installed on a car The problem with this method is

the dead angle of the sensors

• In other mechanisms, devices carried by pedestrians and cars send their positions to another kind of device installed on crosswalks [4,6]

This method requires extra costs for installing the devices on crosswalks

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○

×

Related Work• Many car companies and researchers are studying

techniques for creating a vehicle safety system using inter-vehicle communication [5]

• This method …. can solve the dead angle problem achieves accurate detection does not need any extra costs for

installing devices on crosswalks

• No detailed implementation methodor protocol is provided

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Our Goals• To achieve an avoid collision system with

pedestrians estimate pedestrian’s position until the car

reaches within the stopping distance estimate pedestrian’s location as accurately as

possible estimate with no extra costs for installing the

devices on crosswalks

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Contents• Background• Assumptions• Proposed method• Experiments• Conclusion

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Assumptions for Cars and Pedestrians

• Assumptions for Pedestrians Each pedestrian has a beacon device A unique ID is assigned to each beacon device

• Assumptions for Cars Each car is equipped with….

• a directional antenna capable of receiving beacon signals and estimating their directions

• a GPS receiver• a computer with a certain amount of storage and accurate clock

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Assumptions for Communication• Time interval

beacon signals and packets are tb [s] and tc [s]

• Beacon signals Beacon signals propagates in the area

with radius rb [m] centered at its sender All cars in the area can receive the beacon

signal when there is no radio interference

• Packets Each packet sent by a car propagates in

the area with radius rc [m] All cars in the area can receive the packet

when there is no radio interference

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rb

rc

Assumptions for Directional Antenna

• Directional antenna When receiving the pedestrian’s beacon signal,

it can estimate the direction and distance from the pedestrian

• Error An error in the measured direction

and distance follows normal distributions

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Contents• Background• Assumptions• Proposed method• Experiments• Conclusion

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Algorithm for Detecting Pedestrians

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Construct a packet with unique beacon ID and

beacon sequence number

When a car receives the beacon signals, it estimates the pedestrian’s position according to measured beacon signal

When a car receives the packet, it composes the information of the estimation with the existent one of the same pedestrian

Time interval for sending beacon signals and packets are tb [s] and tc [s]

Construct a packet with the information of the estimation

The car improves the estimation of the pedestrian

Constraint of Detecting Pedestrians

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If a driver notices a pedestrian in dangerous situation

This car is forced to run several ten meters since the driver decides to brake until the braking gets effective

Stopping Distance

Pedestrian’s position must be informed to the driver until the car reaches within the stopping distance

Pedestrian’s Existence Probability Map

• Pedestrian’s Existence Probability Map From assumption, cars can calculate the error probability

of angle and distance by the measured angle and distance We divide the target space in a road map into grids Cars calculate each grid probabilistic index for the central

point of the grid by using the error probability

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Composing Multiple Probability Maps

• The measurement data has to satisfy the following condition

All cars receive the same beacon with the same ID transmitted at the same time

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Contents• Background• Assumptions• Proposed method• Experiments• Conclusion

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Experiments• Evaluation Items

Number of Received PacketsTo evaluate the estimation accuracy, we measured how many packets car receivesuntil the car reaches within the stopping distance

Estimation Accuracy of Pedestrian’s Locationwe measured the radius of the smallest circle which contains all cells of the grid with over 90% existence probability

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Parameter of Experiments• We have used QualNet Simulator• Parameters

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Number of Cars in the east-west direction varies among 2, 4, 6, 8

Number of Cars in the north-south direction varies among 2, 4, 6, 8, 10

Moving Speed of All Cars 12 m/sStopping Distance 22 m Physical Layer Protocol 802.11b Radio Propagation Range 100 m Interval of Beacon and packet Broadcasting 0.2 sec

Size of Pedestrian’s Beacon 100 byte Size of packet 150 byte

The Target Area : Crosswalks located at Shijo-Kawaramachi in Central Kyoto ( 142 m× 142 m )

12 m/s

22 m

Result -Number of Received Packets

• Evaluate the number of received packets We measured the number of beacons successfully received

until the car reaches within the stopping distance

• For all conditions Each car was able to receive more

than 14 packets until the car reacheswithin the stopping distance

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This result shows that the number of packets is sufficient for estimating the position of the pedestrian

Result -Accuracy of Pedestrian Position

• Evaluate estimation accuracy of pedestrian’s location We measured the area which contains all cells of the grid

with over 90% existence probability The variance of distance error : 10, 20, 30 [m] The variance of angle error : 6 [deg]

• When there is only one car

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::

Result -Accuracy of Pedestrian Position

• When there are 8 cars

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These results show that the accuracyof estimation is improved as the number of cars exchanging information increases

×6

Result -Accuracy of Pedestrian Position

• We measured the radius of the smallest circle which contains all cells of the grid with over 90% existence probability

• When the variance of distance error : 10 [m]

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Only one car ： 18.33 [m]Eight cars ： 3.74 [m]

This result shows that estimation accuracy is reasonable to estimate the pedestrian’s moving direction

Conclusion• We presented a method for pedestrian position

estimation using inter-vehicle communication We confirmed that cars can detect a pedestrian

until the driving car reaches within the stopping distance

• Future work Evaluating each pedestrian’s accident risk for each driver Filtering out low accident risk Detecting a series of pedestrian’s position for a time

interval

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Sawa, Y., Kitani, T., Shibata, N., Yasumoto, K., Ito, M.: A Method for Pedestrian Position Estimation using Inter-Vehicle Communication, Proc. of the 3rd IEEE Workshop on Automotive Networking and Applications (AutoNet 2008), pp. 1 – 6.

DOI:10.1109/GLOCOMW.2008.ECP.57  [ PDF ]