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Maurice Geraets Senior Director New Business NXP Automotive Eric-Mark Huitema IBM Smarter Transportation Leader.

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Presentation on theme: "Maurice Geraets Senior Director New Business NXP Automotive Eric-Mark Huitema IBM Smarter Transportation Leader."— Presentation transcript:

1 Maurice Geraets Senior Director New Business NXP Automotive Eric-Mark Huitema IBM Smarter Transportation Leader

2 We Connect the Car and bring CAN data to the Cloud

3 This real time in-car data delivers valuable information In-Car CAN data Dynamic Maximum Speed Real Time Traffic Info Smart phone navigation apps for road users Driving style &black box info for fleet managers Traffic & road condition info for road authorities

4 Speed real time

5 Braking real time

6 Real time Rain, 08:45

7 Real time Rain, 09:15

8 Real time Rain, 10:15

9 Real time Rain, 11:15

10 Cloud dashboard available for 95% of existing car types We have gathered 1.8 Billion data points …

11 In-Car CAN data Dynamic Maximum Speed Real Time Traffic Info Smart phone navigation apps for road users Driving style &black box info for fleet managers Traffic & road condition info for road authorities We use data to deliver valuable information ! … leading to events

12 Rijkswaterstaat and TU/E have concluded that in-car data can provide info on road surface Road authorities: (RWS) benefit from road surface info

13 Public: Smart phone apps can display relevant events Nokias 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

14 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 drivers 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.

15 Proffessional Drivers: Cibatax drivers have really improved driving style and lowered fuel consumption Urban Absolute Urban Rel Improve Overall Rel Improve Urban Abs Improve Mercedes Sprinter Mercedes E class driving style score fuel consumption

16 Cibatax drivers have really improved driving style In our zero measurement the most seen urban driving style score was 6.9 (on scale of ) 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

17 SMART-In-Car start generated Worldwide Interest

18 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 taxis data for road surface and traffic analytics


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