Estimation of Vehicle Speed Based on Asynchronous Data from a Silicon Retina Optical Sensor

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Abstract
This work presents an embedded optical sensory system for traffic monitoring and vehicles speed estimation based on a neuromorphic "silicon-retina" image sensor, and the algorithm developed for processing the asynchronous output data delivered by this sensor. The main purpose of these efforts is to provide a flexible, compact, low-power and low-cost traffic monitoring system which is capable of determining the velocity of passing vehicles simultaneously on multiple lanes. The system and algorithm proposed exploit the unique characteristics of the image sensor with focal-plane analog preprocessing. These features include sparse asynchronous data output with high temporal resolution and low latency, high dynamic range and low power consumption. The system is able to measure velocities of vehicles in the range 20 to 300 km/h on up to four lanes simultaneously, day and night and under variable atmospheric conditions, with a resolution of 1 km/h. Results of vehicle speed measurements taken from a test installation of the system on a four-lane highway are presented and discussed. The accuracy of the speed estimate has been evaluated on the basis of calibrated light-barrier speed measurements. The speed estimation error has a standard deviation of 2.3 km/h and near zero mean

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