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Faculty of Aerospace Engineering

Field of Research
Autonomous driving strategy utilizing the battery capacity to the full extent For a fleet of autonomous vehicle operating in urban environment (e.g. taxis) the amount of time each vehicle can operate before it needs a battery re-chargeis very significant. In order to maximize the operation time many factors can be taken into account when designing driving policy and control algorithms:
  • Designing optimal profiles for braking and accelerating, while implementing the safety requirements (maintaining the safety distance, practicing defensive driving, performing evasive maneuvers)
  • Designing optimal velocity profiles in urban scenarios, taking into account the traffic situation and static constraints (e.g. traffic lights) along the desired route
  • Designing an optimal driving policy: considering lane changing, overtaking, and other maneuvers in terms of saving the battery power
  • Designing an optimal control strategy in traffic jams
  • Computing the expected (most probable) battery usage for driving from start to final destination along different routes, given the current traffic situation
  • Investigating the trade-off between control loops accuracy (e.g. when tracking a desired velocity profile) and battery usage
The resulting driving strategy can be tested in simulation, which can include a model of dynamics of electric vehicle, and its operating environment: a city segment with different traffic scenarios. There is an option to test the developed driving strategy in one the autonomous vehicles currently operating in Mobileye Vision Technologies, Jerusalem.

This position is for MSc and PhD students

Requirements: A good background, or a strong desire to acquire knowledge in dynamic systems, control theory, optimal control, and optimization; experience in Matlab/Python/C++; open mind and enthusiasm.

Start Date: Immediate

Apply to:


Research Fellow Anna Clarke

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