valeo motorbike detection

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January 13 th , 2014 I 1 January 13th, 2015 i-Mobility forum Motorbike detection on urban motorways Philippe Gougeon Valeo Comfort & Driving Assistance

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Page 1: VALEO Motorbike Detection

January 13th, 2014 I 1

January 13th, 2015

i-Mobility forum Motorbike detection on urban motorways

Philippe Gougeon

Valeo Comfort & Driving Assistance

Page 2: VALEO Motorbike Detection

January 13th, 2014 I 2

Motorbike detection on urban motorways

Accidentology in FRA

Situation on urban motorways

Human factors

Detection by Radar

Detection by camera

C2X communications

Conclusions

Page 3: VALEO Motorbike Detection

January 13th, 2014 I 3

Motorbike detection

Accidentology – France 2013

Killed People

Killed People %

Traffic %

Injured People

Injured People %

6- Victims per road user

categories

24% 31%

2%

Killed and injured %

vs traffic %

Page 4: VALEO Motorbike Detection

January 13th, 2014 I 4

Motorbike detection

Situation on urban motorways (Paris)

Page 5: VALEO Motorbike Detection

January 13th, 2014 I 5

Motorbike detection

Human factors

Motorbike = freedom

Motorbike = saves commuting time

Motorbike = no need to find parking location

Many PTW users are not ‘bikers’

Mixed traffic: experienced users share the road with new comers or foreigners

Driving rules are transgressed

Implicit & unwritten driving rules are widely used

Page 6: VALEO Motorbike Detection

January 13th, 2014 I 6

Motorbike detection by Radar

Test Drive Evaluation

Used Sensor: Valeo MBH radars, 24GHz narrow band

City traffic in Paris ( motorbikes are often shadowed by following cars)

113 motorbikes used for analysis

0,00

20,00

40,00

60,00

80,00

100,00

120,00

0 10 20 30 40 50 60 70 80 90range [m]

Probability that a motorbike was detected at min range [%]

Page 7: VALEO Motorbike Detection

January 13th, 2014 I 9

Results from Radar Classification Algorithm

Class Truck Class Car Class Motorbike

act. Truck 94.51% 5.28% 0.21%

act. Car 2.89% 92.79% 4.32%

act. Motorbike 0% 1.91% 98.09%

Fast moving targets on German motorway

Confusion matrix

Performance of the algorithm is compared with the manual classification to generate the following confusion matrix

Compared was a 3 hours long test drive on German motorways where the probability of finding a motorbike is low

Page 8: VALEO Motorbike Detection

January 13th, 2014 I 10

Motorbike detection by camera

Learning algorithm for day time

Lighting identification at night time

Issue with classification

Issue with distance and speed estimation

Issue with salience now that Daytime running lamps are mandatory on cars and motorbikes

[V.Carvallo, Ifsttar-LEPSIS]

Page 9: VALEO Motorbike Detection

January 13th, 2014 I 11

Motorbike detection by C2X communication

Requires On-Board Unit and antenna on Motorbikes, and accurate GPS

WiFi 802.11p is recommended, Visible Light Communication may be investigated

Standard data transfer protocols: Communication Awareness Messages (ETSI TS 102637-2)

=> SafeVRU H2020-2014 proposal

[V.Carvallo, Ifsttar-LEPSIS]

ITS On-Board Unit for PTW

Page 10: VALEO Motorbike Detection

January 13th, 2014 I 12

Motorbike detection on urban motorways

Conclusions

Small business volumes for EU motorbike sales => adaptation of standard solutions from vehicle detection

Sensor fusion is necessary on vehicles for PTW detection

New ADAS functions on vehicles will integrate the base equipments:

Blind spot and Lane Change Assist Radars

Sensor cocoon for Overtaking Maneuvers and Intersection Assist

Cameras for e-Mirrors

C2X communication

Page 11: VALEO Motorbike Detection

January 13th, 2014 I 13

i-Mobility forum

Valeo contact :

Philippe Gougeon

Valeo Comfort & Driving Assistance

Director, Collaborative Research Projects

[email protected]

Tel : +33 (0)1 49 42 38 35

Mob: +33 (0)6 1 14 41 82

Page 12: VALEO Motorbike Detection

January 13th, 2014 I 14