Maurice GeraetsSenior Director New Business NXP Automotive

Eric-Mark HuitemaIBM Smarter Transportation Leader

We Connect the Car and bring CAN data to the Cloud

This real time in-car data delivers valuable information

In-CarCAN data

DynamicMaximum

Speed

Real TimeTraffic Info

Smart phonenavigationapps for

road users

Driving style&‘black box’info for fleetmanagers

Traffic & roadcondition info

for roadauthorities

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 …

In-CarCAN data

DynamicMaximum

Speed

Real TimeTraffic Info

Smart phonenavigationapps for

road users

Driving style&‘black box’info for fleetmanagers

Traffic & roadcondition info

for roadauthorities

We use data to deliver valuable information !

… leading to 48.000 ‘events’

Rijkswaterstaat and TU/E have concluded thatin-car data can provide info on road surface

Road authorities: (RWS) benefit from road surface info

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 betweena 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

Urban Absolute

Urban Rel Improve

Overall RelImprove

Urban Abs Improve

Mercedes SprinterMercedes E class

driving style score

fue

l co

nsu

mp

tion

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 improvementhave 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 yearly730 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