  Pollution in urban centres is becoming a major societal problem. While
pollution is a concern for all urban dwellers, cyclists are one of the most
exposed groups due to their proximity to vehicle tailpipes. Consequently, new
solutions are required to help protect citizens, especially cyclists, from the
harmful effects of exhaust-gas emissions. In this context, hybrid vehicles
(HVs) offer new actuation possibilities that can be exploited in this
direction. More specifically, such vehicles when working together as a group,
have the ability to dynamically lower the emissions in a given area, thus
benefiting citizens, whilst still giving the vehicle owner the flexibility of
using an Internal Combustion Engine (ICE). This paper aims to develop an
algorithm, that can be deployed in such vehicles, whereby geofences (virtual
geographic boundaries) are used to specify areas of low pollution around
cyclists. The emissions level inside the geofence is controlled via a coin
tossing algorithm to switch the HV motor into, and out of, electric mode, in a
manner that is in some sense optimal. The optimality criterion is based on how
polluting vehicles inside the geofence are, and the expected density of
cyclists near each vehicle. The algorithm is triggered once a vehicle detects a
cyclist. Implementations are presented, both in simulation, and in a real
vehicle, and the system is tested using a Hardware-In-the-Loop (HIL) platform
(video provided).
