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Trustworthy Positioning

for Next Generation

Intelligent Transport

Systems

Ahmed El-Mowafy





Contents

Background on ITS and C-ITS

Requirements

Challenges

RAIM

Test and Results

Japan-Australia Quasi-Zenith Satellite System (QZSS) Industrial

Utilisation Workshop, Sydney, 6 Feb. 2018. 2





ITS objectives

Make transportation safer, more efficient and reduce emissions

Efficiency

Safety

Emissions







C-ITS

Source: Austroads, 2010



V2V and V2I





Communication using DSRC. DSRC-based range-rating measurements can enable GNSS/DSRC cooperative positioning.

VANET (Vehicular ad hoc network)

C-ITS

Source: Internet



https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&uact=8&ved=0ahUKEwjO_7-Y9YPZAhUX6mMKHWNBD9gQFggpMAA&url=https://en.wikipedia.org/wiki/Vehicular_ad_hoc_network&usg=AOvVaw1sFoszlPXg2FdP75jOL22z

https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&uact=8&ved=0ahUKEwjO_7-Y9YPZAhUX6mMKHWNBD9gQFggpMAA&url=https://en.wikipedia.org/wiki/Vehicular_ad_hoc_network&usg=AOvVaw1sFoszlPXg2FdP75jOL22z





• Road level (few m)

• Lane-level (< 1m)

• Where-in-lane level (sub-m)

Current systems mainly use SPS (Standard Positioning Service).

SPS gives 1-5 m accuracy - not suitable for lane-level precision.

Use of augmentation techniques, such as SBAS has the potential to

offer the required accuracy.

Most imported C-ITS uses SBAS technology.

Satellite positioning accuracy requirements

More accuracy is

needed







But: Is it only accuracy we are interested in!







Ex: Curtin University Driverless Buss







Accuracy VS Integrity

AL

Accuracy Integrity

Alert to driver/user



PL





Challenges

• Standards? need to be set based on performance requirements.

• Complete map of risks (e.g. collision types, faults, etc.)

and vulnerabilities (system errors, interference, jamming spoofing, etc.)

and identify their probabilities.

• Integration of sensors (GNSS is a main component but not alone)

• Cost

• Communications

• Application dependence.

• Technology.







Example

of NLOS

Urban environment:

• Loss of lock

• Heavy multipath

• Non Line of Sight (NLOS)

• Frequent cycle-slips

Mitigations:

• Multipath mitigation at the antenna

• 3D city-models – ray-tracing algorithms

• SNR monitoring

• Non-Gaussian error models

• VANET CIM concept

Ex: Vulnerabilities due to the work environment

Use 3D city-

models







Characterisation of errors (ex: clock corrections)

PRN16 PRN 29 PRN30

Histograms

Q-Q

CDF







GNSS Positioning Methods

Baseline length

100km 1,000km 10,000km 10km Worldwide

10cm

20cm

40cm

60cm

80cm

1m

PPP

4cm

RTK

Acc

ura

cy

SBAS DGNSS







SBAS

GEO Satellites

SBAS

SBAS

Ionosphere

Troposphere

Reference

stations

Vulnerabilities linked to

hardware, software and

data link with the satellites

• Improved positioning:

sub-m (DGPS L1, L1/L5)

deci-metre (PPP)

• Integrity monitoring: error bounds for PL







Integrity monitoring

Advanced RAIM (ARAIM)

• Fault Detection & Exclusion based on

statistical hypothesis testing

• PLs computation based on estimated

impact of faults on position solution

Determine Protection Levels (PLs) as

safety bounds to positioning errors

• Take into account risk of

anomalies/faults

• PLs must be smaller than the Alert

Limits (ALs) to guarantee availability







For standalone vehicle

Multi-sensor

V2V and V2I .

ARAIM

Multi-sensor integration



AT

CT





Testing Ex.

• Kinematic test in Tokyo (with TUMSAT)

• Trimble RTK (10Hz)

• GPS, GLONASS and BeiDou

• a Bosch-consumer grade MEMS IMU

The heading error of this IMU ranged

from -2o to 5o, can accumulate to 10o

after 30 min if left uncalibrated.

• Speed sensor: s = 5 cm/s

• GNSS-Doppler: s = 10 cm/s.

• Reference : PPK & POS/LV





Testing: challenging environment





Integrity prediction

Along Track Cross Track

Identify critical locations on the map, at

different times of the day

Integrity unavailable: red points (PL>AL)







Actual data: Flow chart of sensor fusion (RTK, IMU, odometer)

Computes heading

from GNSS Doppler

Meets GNSS

heading

Conditions

Yes

Update heading of the

IMU (GNSS & ZUPT)

Computes positions

from Speed of Speed

sensor and IMU

heading

No

Doppler

available

Yes

RTK

available

No

Yes

Computes

positions using

RTK

Yes

Compute velocity from

GNSS Doppler

Compute positions

from GNSS velocity

Meets GNSS

Velocity

Conditions

No

Output position

No



1 2 3





Protection levels

𝑃𝐿𝐴𝑇,𝑖 = 𝐾𝑓𝑎,𝑖

𝜎𝛿𝐴𝑇,𝑖 + 𝐾𝑚𝑑,𝑖 𝜎𝐴𝑇,𝑖 + (cos 𝜃 𝑎1𝑇 𝑆𝑖 × 𝑏𝑜)2+ (sin 𝜃 𝑎2

𝑇 𝑆𝑖 × 𝑏𝑜)2

𝑃𝐿𝐶𝑇,𝑖 = 𝐾𝑓𝑎,𝑖

𝜎𝛿𝐶𝑇,𝑖 + 𝐾𝑚𝑑,𝑖 𝜎𝐶𝑇,𝑖 + (sin 𝜃 𝑎1𝑇 𝑆𝑖 × 𝑏𝑜)2+ (cos 𝜃 𝑎2

𝑇 𝑆𝑖 × 𝑏𝑜)2

𝑃𝐿𝐴𝑇,𝑖 = 𝐾𝑚𝑑,𝑖 𝜎𝐴𝑇,𝑖 + (cos 𝜃 𝑎1𝑇 𝑆

𝑏𝜃𝐼𝑀𝑈

𝑏𝑣)2+ (sin 𝜃 𝑎2

𝑇 𝑆 𝑏𝜃𝐼𝑀𝑈

𝑏𝑣)2

𝑃𝐿𝐶𝑇,𝑖 = 𝐾𝑚𝑑,𝑖 𝜎𝐶𝑇,𝑖 + (sin 𝜃 𝑎1𝑇 𝑆

𝑏𝜃𝐼𝑀𝑈

𝑏𝑣)2+ (cos 𝜃 𝑎2

𝑇 𝑆 𝑏𝜃𝐼𝑀𝑈

𝑏𝑣)2

RTK

IMU+odometre

𝑃𝐿𝐴𝑇,𝑖 = 𝐾𝑚𝑑,𝑖 𝜎𝐴𝑇,𝑖 + (cos 𝜃 𝑎1𝑇 𝑆

𝑏𝑣𝐸

𝑏𝑣𝑁

)2+ (sin 𝜃 𝑎2𝑇 𝑆

𝑏𝑣𝐸

𝑏𝑣𝑁

)2

𝑃𝐿𝐶𝑇,𝑖 = 𝐾𝑚𝑑,𝑖 𝜎𝐶𝑇,𝑖 + (sin 𝜃 𝑎1𝑇 𝑆

𝑏𝑣𝐸

𝑏𝑣𝑁

)2+ (cos 𝜃 𝑎2𝑇 𝑆

𝑏𝑣𝐸

𝑏𝑣𝑁

)2

Doppler



biases





RTK Results

G+R+B

G+B

G+R

G

* b = 1×10-4

AT CT







All sensors

Combined

Doppler

RTK

IMU+odometer

* b = 1×10-4 00.5

11.5

22.5

33.5

44.5

5

174250 174500 174750 175000

PL

& E

rro

r (

m)

Time (sec)

PL_AT (All) err_AT (All)

00.5

11.5

22.5

33.5

44.5

5

174250 174500 174750 175000

PL

& E

rro

r (

m)

Time (sec)

PL_CT (All) err_CT (All)

0

0.1

0.2

0.3

0.4

0.5

174250 174500 174750 175000

PL

& E

rro

r (

m)

Time (sec)

PL_AT (RTK) err_AT (RTK)

0

0.1

0.2

0.3

0.4

0.5

174250 174500 174750 175000

PL

& E

rro

r (

m)

Time (sec)

PL_CT (RTK) err_CT (RTK)

00.5

11.5

22.5

33.5

44.5

5

174250 174500 174750 175000

PL

& E

rro

r (

m)

Time (sec)

PL_AT (Doppler) err_AT (Doppler)

00.5

11.5

22.5

33.5

44.5

5

174250 174500 174750 175000

PL

& E

rro

r (

m)

Time (sec)

PL_CT (Doppler) err_CT (Doppler)

00.5

11.5

22.5

33.5

44.5

5

174250 174500 174750 175000

PL

& E

rro

r (

m)

Time (sec)

PL_AT (IMU+odo) err_AT (IMU+odo)

00.5

11.5

22.5

33.5

44.5

5

174250 174500 174750 175000

PL

& E

rro

r (

m)

Time (sec)

PL_CT (IMU+odo) err_CT (IMU+odo)

AT CT







Summary

ITS / C-ITS might be the norm in the near future.

Real-time safety related applications in ITS/C-ITS require highly

trustworthy positioning: i.e. integrity monitoring.

The technology might not be the problem: cost and interoperability

might be.

Integrity Monitoring (IM) is challenging

IM can be achieved, but which standards? Applications?







Questions

25 Ahmed El-Mowafy

Spatial Sciences

Thank you

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