Abstract
The precise calibration of acceleration and deceleration parameters is crucial for improving the accuracy of operating speed prediction and analysis tools at tunnel entrances. Therefore, acceleration and deceleration data of passenger car captured from 20 drivers at 30 tunnel entrances were collected from 200 m outside to 200 m inside the tunnel portal and averaged across four study zones. The results show that, first, the distribution of deceleration rates based on speed differs from that of acceleration rates based on speed in all zones. Second, significant differences in the probability density distribution of deceleration were found between each zone ( p < 0.001 ), but differences in acceleration could not be found between any zones ( p > 0.05 ). Third, the feature values (breakpoints) of the acceleration/deceleration cumulative frequency curves were located near the 95th percentile, differing from the traditional 85th percentile found with the extant model. The feature values of acceleration in the four zones coincided at 0.5 m/s2 and those of deceleration were 0.93, 0.85, 0.70, and 0.47 m/s2 under zones 1–4, respectively. This study provides accurate feature values of acceleration and deceleration for modelling an updated tunnel entrance operating speed prediction model.
Highlights
Operating speed consistency analysis remains an important method for freeway safety evaluation. e core of this method is a common operating speed prediction model that is used to obtain continuous operating speed profiles worldwide. is method examines the differences between vehicle operating speeds and road design speeds per adjacent road segments
Most versions of the common model have two common characteristics. ey are applied to specific road segment types, and the road segments almost always depend on single or multiple geometric elements
Speed data were synchronously recorded alongside acceleration/deceleration data at the same frequency, and the real-time driving position was recorded using the video recorder. en, the position curves were obtained by calculating the product of speed over time, and the positions of acceleration and deceleration were determined by synchronizing the video recorder and the onboard diagnostic (OBD) sensor data
Summary
Received 4 February 2021; Revised 18 May 2021; Accepted 17 July 2021; Published 24 July 2021. E precise calibration of acceleration and deceleration parameters is crucial for improving the accuracy of operating speed prediction and analysis tools at tunnel entrances. E results show that, first, the distribution of deceleration rates based on speed differs from that of acceleration rates based on speed in all zones. Ird, the feature values (breakpoints) of the acceleration/deceleration cumulative frequency curves were located near the 95th percentile, differing from the traditional 85th percentile found with the extant model. E feature values of acceleration in the four zones coincided at 0.5 m/ s2 and those of deceleration were 0.93, 0.85, 0.70, and 0.47 m/s2 under zones 1–4, respectively. Is study provides accurate feature values of acceleration and deceleration for modelling an updated tunnel entrance operating speed prediction model Significant differences in the probability density distribution of deceleration were found between each zone (p < 0.001), but differences in acceleration could not be found between any zones (p > 0.05). ird, the feature values (breakpoints) of the acceleration/deceleration cumulative frequency curves were located near the 95th percentile, differing from the traditional 85th percentile found with the extant model. e feature values of acceleration in the four zones coincided at 0.5 m/ s2 and those of deceleration were 0.93, 0.85, 0.70, and 0.47 m/s2 under zones 1–4, respectively. is study provides accurate feature values of acceleration and deceleration for modelling an updated tunnel entrance operating speed prediction model
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