Volume No. 8 Issue No.: 3A Page No.: 705-716 Jan-Mar 2014

 

REDUCTION OF VEHICULAR POLLUTION THROUGH FUEL ECONOMY IMPROVEMENT WITH THE USE OF AUTONOMOUS SELF-DRIVING PASSENGER CARS

 

Suresh P.* and Manivannan P. V.

Department of Mechanical Engineering, Indian Institute of Technology, Madras, Chennai, Tamil Nadu (INDIA)

 

Received on : October 23, 2013

 

ABSTRACT

 

With ever increasing traffic density in highways, optimal driving of a road vehicle can result in smooth traffic flow, reduced fuel consumption and tail pipe emissions, thus reducing the overall carbon footprint of the vehicle. This paper presents the performance of two types of longitudinal control algorithms, classical PID and Artificial Intelligence based Fuzzy Logic Control (AIFLC) algorithms developed to control a self driving passenger car. The membership functions of the fuzzy logic controller have been tuned using Adaptive Neuro-Fuzzy Inference System (ANFIS). Integral Square Time Error (ISTE) performance criteria have been used for optimizing the controllers. The simulation results for an autonomous vehicle driven with the proposed controllers are presented. Also, the performance of the proposed controllers was compared with simulation results obtained for the same vehicle driven by a human driver model available in the literature. The simulation results show an improvement in fuel economy with the use of automatic control as compared to human control, which results in reduced tail-pipe emissions.

 

Keywords : Self driving Car, PID, Fuzzy Logic Control, Adaptive Neuro-Fuzzy Inference System (ANFIS), Dynamic Human Driver Behavior Model, Fuel economy

 

 

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