Challenging the insight toolkit for modelling …...Title Challenging the insight toolkit for...
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Challenging the insight toolkit for modelling tomorrow’s world November 2016
Transcript of Challenging the insight toolkit for modelling …...Title Challenging the insight toolkit for...
Challenging the insight toolkit for modelling tomorrow’s world
November 2016
© Copyright 2016 TRL Ltd
Approaches to modelling
Traffic modelling
Driving simulation
Virtual validation2
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Platooning - SARTRE
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Platooning – modelling impact
0%
1%
2%
3%
4%
5%
6%
7%
0 10 20 30 40 50
Pe
rce
nta
ge in
cre
ase
in c
apac
ity
Percentage HGVs in Road Trains
Carriageway
Lane 1
Lane 2
Lane 3
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5%
10%
15%
20%
25%
30%
35%
40%
45%
0 5 10 15 20
Pe
rce
nta
ge in
cre
ase
in c
apac
ity
Percentage Cars in Road Trains
Carriageway
Lane 1
Lane 2
Lane 3
Increase in capacity (5 HGVs) Increase in capacity (HGV + 5 cars)
Harwood, N., & Reed, N. (2014, October). Modelling the impact of platooning on motorway capacity. In Road Transport Information and Control Conference 2014 (RTIC 2014) (pp. 1-6). IET.
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Platooning - modelling
Useful insights from basic modelling
But…
Brute force manipulation of modelling software
No ability to:
form stable vehicle platoons
investigate platoon formation
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Simulator validation
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Diels, C., Robbins, R., & Reed, N. (2012). Behavioural validation of the TRL driving simulator DigiCar: phase 1: speed choice. In International Conference on Driver Behaviour and Training, 5th, 2011, Paris, France.
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Positioning
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Acceleration and deceleration
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Diels, C., Robbins, R., & Reed, N. (2012). Behavioural validation of the TRL driving simulator DigiCar: phase 1: speed choice. In International Conference on Driver Behaviour and Training, 5th, 2011, Paris, France.
© Copyright 2016 TRL Ltd
Cruising speed
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Diels, C., Robbins, R., & Reed, N. (2012). Behavioural validation of the TRL driving simulator DigiCar: phase 1: speed choice. In International Conference on Driver Behaviour and Training, 5th, 2011, Paris, France.
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Braking profile
10Brake pedal application (0-1)
Dec
eler
atio
n (
ms-2
)
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Automated vehicles
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Google operating >50 vehicles in CA, TX, AZ, WA
Collecting >20k miles of automated driving data per month (and many more in simulation)
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Shuttle driving through LIDAR environment
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Challenging the insight toolkit
Flexibility
Sophistication
Validation13
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Thank you
Presented by Professor Nick ReedTRL Academy Director
Month YYYYTel: +44 1344 770046
Email: [email protected]
