Transcript NXP Semiconductors - uCAN

Maurice Geraets
Senior Director New Business NXP Automotive
Eric-Mark Huitema
IBM Smarter Transportation Leader
We Connect the Car and bring CAN data to the Cloud
This real time in-car data delivers valuable information
Real Time
Traffic Info
Smart phone
navigation
apps for
road users
Dynamic
Maximum
Speed
Driving style
&‘black box’
info for fleet
managers
In-Car
CAN data
Traffic & road
condition info
for road
authorities
Speed real time
Braking real time
Real time Rain, 08:45
Real time Rain, 09:15
Real time Rain, 10:15
Real time Rain, 11:15
Cloud dashboard available for 95% of existing car types
We have gathered 1.8 Billion data points …
We use data to deliver valuable information !
Real Time
Traffic Info
Smart phone
navigation
apps for
road users
Dynamic
Maximum
Speed
Driving style
&‘black box’
info for fleet
managers
In-Car
CAN data
Traffic & road
condition info
for road
authorities
… leading to 48.000 ‘events’
Road authorities: (RWS) benefit from road surface info
Rijkswaterstaat and TU/E have concluded that
in-car data can provide info on road surface
Public: Smart phone apps can display relevant events
Nokia’s real time traffic
Rijkswaterstaat dynamic max speed
Events generated from CAN data, e.g.:
• Fog, heavy rain
• Road assistance car on rescue lane
• Harsh braking – more accurate traffic jam info
Fleet manager: incident analytics
Accurate in car data is available for analytics of specific situations:
In December 2012, in a dark evening an accident occurred between
a scooter and a taxi.
According to the scooter driver the taxi suddenly made a unexpected U-Turn
without paying attention to the traffic and without using the turn indicator lights.
According to the Taxi driver he stopped the taxi at the roadside and carefully
turned the taxi while using his turn indicator.
An investigation was conducted using SMART-In-Car taxi data.
It clearly showed on a per second basis what the situation actually was.
It indicated the taxi driver’s statement was fully correct based on detailed
signals from the car which were stored in the Cloud.
Fortunately the scooter driver was not injured, and after being confronted with
the data, acknowledged he was speeding, did not have his lights on and was
not paying attention.
Proffessional Drivers: Cibatax drivers
have really improved driving style and
lowered fuel consumption
Mercedes Sprinter
fuel consumption
Mercedes E class
Overall Rel
Improve
Urban Rel
Improve
Urban
Absolute
driving style score
Urban Abs
Improve
Cibatax drivers have really improved driving style
In our zero measurement the most seen urban driving style score was 6.9
(on scale of 0 - 10)
After stimulating the taxi drivers to improve their driving style, the most seen urban
score improved with 10% (to 7.6)
Those who scored in the zero measurement below 6 in urban areas,
improved their average driving style score in the competition with 6%
The 10 drivers who showed the highest urban improvement
have on average improved their score with over 18%
On Mercedes E Class car we monitored fuel consumption from the CAN bus
– Almost 75% of these cars showed reduced fuel consumption in urban areas
– The average of these reductions in fuel consumption was close to 5%
Extrapolating to all passenger cars in The Netherlands this would save yearly
730 Million tons CO2 emission and 800 Million Euro fuel costs
Effective driving style improvement for taxi drivers:
– Shows better results in urban environments than on high ways
– Can be best achieved with direct driver feedback
– Really pays of in emissions and fuel savings
SMART-In-Car start generated Worldwide Interest
Innovation Requires Great Partners Collaborating Well
state of art chip technology
to understands CAN ‘dialects’
client server software to transfer data to the cloud
data connectivity
cloud based data analytics and visualization
floating car data, maps
road surface friction algorithm and driving style qualification
smartphone app
use case development and exploration
>40 road side assistance vehicles
>120 taxi’s
data for road surface and traffic analytics