A study on meta-analysis approach for pedestrian-vehicle interaction using LiDAR

Abstract

To analyse the continuous and intricate interaction between pedestrians and vehicles and to safeguard them, high-resolution micro-traffic data is needed. In comparison to other traditional means of data collection, light detection and ranging (LiDAR) technology is gaining popularity since it can deliver this information with less computing effort and is weather-resistant. This article uses LiDAR technology to analyse qualitative and quantitative data related to pedestrian-vehicle interaction. Based on the study selection criteria, a total of 39 studies were included in the qualitative analysis. Based on the availability of the data, four of these studies were then included in the quantitative meta-analysis. Some of the algorithms developed thus far have a 99 percent accuracy rate. The analysis was carried out using the Fisher r-to-z transformed correlation coefficient as the outcome measure. The amount of heterogeneity was estimated using the restricted maximum-likelihood estimator. A random-effects model was fitted to the data. Q = 51.716, p = 0.0001, and I2 = 92.86 percent were the results of the Q test, demonstrating that there is enough heterogeneity amongst the studies. Neither the rank correlation nor the regression test indicated any funnel plot asymmetry. The findings indicate that LiDAR is a suitable technology for studying pedestrian-vehicle interaction. The study results are useful to explore the new technology of LiDAR and its suitability in pedestrian-vehicle interactions.