Quantifying the impact of probe vehicle localisation data errors on signalised junction control

Abstract

This study investigates theoretical signal control algorithms based solely on probe vehicle data. Through development of a simulation system that can model urban signalised junction control using localisation probe data from all vehicles in the local area, improvements in junction operational efficiency that result from the improved input data are demonstrated for both isolated and coordinated junctions. Results from the isolated junction scenario show that the richness of the information contained within probe vehicle data means that control algorithms based just on positions and velocities of vehicles can produce 25% reductions in average delay compared to the current standard control algorithm MOVA. Results from the twin junction scenario confirm the importance of using high-level synchronisation to coordinate closely connected junctions, achieving reductions in average delays (compared to independent control approaches) of up to 40% through a process of weighting the probe vehicle data to reflect prior stage decisions of other parts of the junction. Critical to achieving these benefits, however, is the availability of high localisation accuracy probe data, with results indicating that the levels of accuracy necessary are representative of the typical performance of current in-vehicle global positioning system units, except when those vehicles are operating in urban canyon environments.

An automated signalized junction controller that learns strategies from a human expert

“…This work showed the auctioning agent approach outperforming MOVA in simulations on an isolated T-junction. In Waterson and Box (2011) the auctioning agent system was subjected to a rigorous quantitative stochastic analysis, which characterized the effects of varying the positioning accuracy and the fraction of vehicles equipped with probes.…”

“…The simulation test bed used for the work presented in this paper is described in detail in Box and Waterson (2010a); Waterson and Box (2011). In summarry: it uses S-Paramics microsimulation software to model networks and simulate the movement of individual vehicles through junctions.…”

“…That is the principle coordinated high bid control. Detailed descriptions of this control method applied to specific junctions are given in Waterson and Box (2011).…”

“…A detailed description of agent re-assignment for a similar two junction network model can be found in (Waterson and Box, 2011).…”

“…The method used to model uncertainty has been described in detail in (Waterson and Box, 2011). To summarize: the position estimates from the simulated localization systems are degraded by the addition of Gaussian noise with 1σ ranging between 2 − 32m.…”