MB-team

Smart Vehicles

Alice_MB-2-04 Alice_EYMB_-2-04 poster-12-04

Mercedes-Benz Experience Design: Future of Mobility Concepts in Suburban America

How to stay one step ahead of the competition with new concepts associated with Being Connected: Mobility Concepts and Services (e.g., Carsharing, Ridesharing, On Demand taxi’s, etc)?  Offer customers a holistic approach to mobility – regardless of whether they want to use a car, a bus, a train or some combination.

The objectives of this research are:

  • Perform human-centered design research as to user pain points associated with mobility and staying connected.  
  • Evaluate current concepts and look for gaps and opportunity spaces.
  • Prototype and test promising concepts.

In his role as Senior Manager for Business Innovation in the Research & Development division of Mercedes-Benz North America, Rasheq Zarif seeks to change consumer expectations of the automobile. “I should be able to multi-task safely during my commute. I want a car that will keep up with the times. I want to stay connected while driving.”

Rasheq-12-04Fung MEng Student Team with Sponsor, Rasheq Zarif, Senior Manager for Business Innovation in the Research & Development division of Mercedes-Benz North America

Rasheq Zarif, Senior Manager for Business Innovation in the Research & Development division of Mercedes-Benz North America, Rasheq Zarif seeks to change consumer expectations of the automobile. “I should be able to multi-task safely during my commute. I want a car that will keep up with the times. I want to stay connected while driving.”

Presentations and Publications

  • “Research on Distributed Intelligence: Sensor Fusion and Design Information Environments,” NSF Director Neal Lanes visit to the UC Berkeley campus, Dec. 5, 1996.
  • “Experience Design: Mobility and Staying Connected in a Mercedes-Benz”, Midterm Poster Session, Fung Institute for Engineering Leadership, Dec. 2013.

Press

  • Implementation at Ladera Ranch: Working with former BEST Labber Rasheq Zarif of Mercedes-Benz, Prof. Agogino’s 2013-14 Masters of Engineering Capstone team developed prototype routings and user interfaces for the project, also with estimates of life cycle energy and carbon benefits. Exclusively for Ranch residents, RanchRide is the convenient, easy and eco-friendly way to get where you want to go.

Autonomous Vehicles 

We developed a framework for real time monitoring and diagnosis of automated vehicles in IVHS. This supervisory control methodology is concerned with fault detection, fault isolation, and control reconfiguration of the many sensors, actuators and controllers that are used in the control process. The supervisory control architecture operates at two levels of the AVCS: at the regulation and at the coordination level. Supervisory control activities at the regulation layer deal with validation and fusion of the sensory data, and fault diagnosis of the actuators, sensors, and the vehicle itself. Supervisory control activities at the coordination layer deal with detecting potential hazards, recommending the feasibility of potential maneuvers and making recommendations to avert accidents in emergency situations. The supervisory control activities are achieved through five modules, organized in an hierarchical manner.

Due to the inherent noise of the sensor measurements, the latter are uncertain. Even if several sensors are used, it is not straight forward which sensor to trust or to what degree to trust it. If untreated, the quality of the ride suffers (as demonstrated in this animation) and in the worst case leads to unsafe conditions. Two different approaches for validation and fusion have been investigated: 1.) a probabilistic approach, and 2.) a fuzzy approach. The probabilistic approach is Kalman Filter based and assumes Gaussian noise distributions while the fuzzy approach makes no such assumptions. For fusion, the fuzzy approach uses validation gates which allow the assignment of confidence values to each sensor reading, depending on the sensor characteristics particular to each sensor. Diagnosis of the sensors is performed on-line via fuzzy abductive methods. A ranking scheme calculates fuzzy closeness measures which are used to obtain the most likely failure (if any. Below you can see validated and fused values for longitudinal distance as well as the original sensor values obtained from radar, sonar, and optical sensors.

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See this website for more information.

 

Real-Time Expert Systems: Monitoring, Diagnostics and Supervisory Control (Prior work that forms the foundation for Smart Vehicles research)

Sensor Validation and Fusion for Autonomous Vehicles