Can priors be trusted? Learning to anticipate roadworks

Abstract

Abstract-This paper addresses the question of how much a previously obtained map of a road environment should be trusted for vehicle localisation, during autonomous driving, by assessing the probability that roadworks are being traversed. We compare two formulations of a roadwork prior: one based on Gaussian Process (GP) Classification and the other a more conventional Hidden Markov Model (HMM) in order to model correlations between nearby parts of a vehicle trajectory. Importantly, our formulation allows this prior to be updated efficiently and repeatedly to gain an ever more accurate model of the environment over time. In the absence of, or in addition to, any in-situ observations, information from dedicated web resources can readily be incorporated into the framework. We evaluate our model using real data from an autonomous car and show that although the GP and HMM are roughly commensurate in terms of mapping roadworks, the GP provides a more powerful representation and lower prediction error. Our method allows us to truly map and anticipate roadworks on urban roads.

The future of employment: How susceptible are jobs to computerisation?

“…However, the big data approach can answer this by storing records from the last time snow fell, against which the vehicle's current environment can be compared (Churchill and Newman, 2012). ml approaches have also been developed to identify unprecedented changes to a particular piece of the road network, such as roadworks (Mathibela, et al, 2012). This emerging technology will affect a variety of logistics jobs.…”

Vision-Based Work Zone Safety Alert System in a Connected Vehicle Environment

“…This approach then identifies work zone signs and utilizes them to indicate the starting and ending point of a work zone road segment. Mathibela et al ( 18 ) also identify traffic signs and traffic cones. This method employs the detection findings as characteristics to calculate the likelihood that the vehicle is in a work zone.…”