John Ash

TL;DR: A novel framework for real-time traffic flow parameter estimation from aerial videos is proposed that achieves about 96% and 87% accuracy in estimating average traffic stream speed and vehicle count, respectively and achieves a fast processing speed that enables real- time traffic information estimation.

TL;DR: In this article, the authors investigated the spatial heterogeneity in the sensitivity of parking occupancy to price change using data obtained in downtown San Francisco between 2011 and 2014 and found that there is a significant negative correlation between occupancy change and parking rate change.

TL;DR: The main finding shows that the rankings produced by the NB and GFMNB-2 models for hotspot identification are often quite different, and this was especially noticeable with the Texas dataset.

TL;DR: Estimation results demonstrate the accuracy and effectiveness of the EFNN method through comparison with existing methods including: multiple linear regression (MLR), instantaneous model (IM), linear model (LM), neural network (NN), and cumulative plots (CP).

TL;DR: In this paper, a new accessibility-based methodology addressing travel modes was developed to evaluate transportation network vulnerability under flooding impacts, and a case study based on data from Hillsborough County, Florida, was conducted to verify the established model.