Characterising Green Light Optimal Speed Advisory Trajectories for Platoon-Based Optimization

In recent years considerable attention has been given to Green Light Optimal Speed Advisory (GLOSA) systems in the literature. These systems typically compute a single speed for a vehicle in the range between minimum and maximum values. The goal is to optimise for a particular objective, whether it be minimisation of emissions (for environmental reasons), fuel usage or delay. This paper generalises the advice given to vehicles, by optimising primarily for delay over the entire trajectory instead of suggesting an individual speed, regardless of initial conditions. An algorithm is developed primarily to minimise delay and secondarily to reduce fuel usage (and emissions) by conserving kinetic energy as much as possible. The evidence of the importance of taking a platoon-based approach is presented. As will be shown, the effectiveness of GLOSA systems is heavily reliant on correctly identifying the leading vehicle that is given trajectory advice. A “time loop” technique is proposed which allows accurate identification even when there are complex interactions between preceding vehicles.