Engineering Design Synthesis of Sensor and Control Systems for Intelligent Vehicles

A smart car that assists driving must give warnings in dangerous situations, override the driver to avoid collisions, and help reach the intended destination as quickly as possible. Unfortunately, satisfying these requirements without limiting the decisional autonomy of the individual driver becomes an extremely hard problem to solve with traditional engineering methods. Biologically-inspired techniques such as Evolutionary Computation and Swarm Intelligence provide promising new ways to tackle the design and control problems of a traffic system.

Team and Collaborators

  • Yizhen Zhang

Sponsors and Research Period

NSF via CNSE under Grant EEC-9402726



Evolutionary engineering design synthesis of on-board traffic monitoring sensors

Y. Zhang; E. K. Antonsson; A. Martinoli 

Research In Engineering Design. 2008. Vol. 19, num. 2-3, p. 113-125. DOI : 10.1007/s00163-008-0047-0.


Evolving Neural Controllers for Collective Robotic Inspection

Y. Zhang; E. K. Antonsson; A. Martinoli 

2006. 9th Online World Conference on Soft Computing in Industrial Applications (WSC9). p. 721-733. DOI : 10.1007/3-540-31662-0_55.


Evolutionary Design of a Collective Sensory System

Y. Zhang; A. Martinoli; E. K. Antonsson 

2003.  p. 283-290.

Evolution of Sensory Configurations for Intelligent Vehicles

Y. Zhang; A. Martinoli; E. K. Antonsson; R. Olney 

2003.  p. 351-356. DOI : 10.1109/IVS.2003.1212935.

Evolving Engineering Design Trade-Offs

E. K. Antonsson; Y. Zhang; A. Martinoli 

2003. 15th International Conference on Design Theory and Methodology, Chicago, Illinois, USA, September 2–6, 2003. p. 819-827. DOI : 10.1115/DETC2003/DTM-48676.


Towards Evolutionary Design of Intelligent Transportation Systems

A. Martinoli; Y. Zhang; P. Prakash; E. K. Antonsson; R. Olney