Exploring credentials of Wi-Fi sensors as a complementary transport data: An Indian experience

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Abstract

This study investigates the performance of Wi-Fi sensors positioned at varying lateral and vertical positions on data collection efficiency under prevailing traffic conditions in India. Investigation revealed that penetration rate (a measure of performance of sensor) is significantly influenced by height and lateral position of the sensor. Time gap (time-headway) between successive detection for varying height and the lateral position was modelled using statistical distribution to investigate, how height and lateral positions of sensor influences its performance. It was observed that the variation in time headway causes variation in the number of detections and hence, affects the performance of the sensor. A new performance measure named time-to-detection was developed from the observed distribution of headways and it was observed that time-to-detection is significantly influenced by the sensor location. Further, in addition to lateral and vertical positions, stream speed was also observed to have a significant effect on the sensor performance. Field observed headway and headway values computed using sensor data were thereafter correlated to optimise the sensor location in terms of its vertical and lateral positions. Based on the headway distribution analysis, the study recommends installing a Wi-Fi sensor mainly at ground level along the median to capture temporal variations in traffic parameters more effectively.

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Gore, N., Arkatkar, S., Joshi, G., & Bhaskar, A. (2019). Exploring credentials of Wi-Fi sensors as a complementary transport data: An Indian experience. IET Intelligent Transport Systems, 13(12), 1860–1869. https://doi.org/10.1049/iet-its.2019.0251

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