# On the Use of the Multi-Agent Environment for Mobility Applications
## 2 Environment as a Spatio-Temporal Reference
### Space-Time Environment in Mobility Simulation  
Transportation systems are becoming progressively complex as they are increasingly composed of intelligent and mobile entities. Travellers equipped with mobile devices and vehicles with connection capabilities allow passengers and vehicles to adapt their behaviour with up-to-date information. However, without control, the massive dissemination of information via billboards, radio announcements and individual guidance can have adverse effects and create new traffic concentrations and disruptions. Indeed, with this generalisation of real-time traveller information, the behaviour of modern transportation networks becomes more difficult to analyse and predict. It is then essential to properly observe these effects to consider the adequate methods to face them. To this end, we developed a multi-agent simulation platform that represents travellers, drivers, and public transportation vehicles and makes them move realistically on a multimodal transportation network. To allow travellers to receive only the disruption information relevant to them, the spatio-temporal network model described above is integrated into the simulation platform. In the following, we briefly introduce the multi-agent simulation platform, called SM4T (Simulator for Multi-agent MultiModal Mobility of Travelers) [13], before presenting our method of disseminating information to relevant travellers with spatio-temporal networks. The multi-agent simulation platform that we designed and implemented allows for the individual representation of travellers moving on a transport network. We enrich it with traveller information capabilities, both at the stops and with personal information directly on the travellers' smartphones. A simulation represents itinerary planners, passengers, public transportation vehicles, and information means in a micro-level and simulate their dynamic movements (cf. Figure 3). The multi-agent system of the simulator is composed of the following entities. We define four types of agents: Public transport vehicle agents (representing buses, metros, tramways, etc. in the system), Connected travellers, which represent the passengers that connect to real-time information sources, Non-connected travellers, that represent the travellers that only have a spatial representation of the network, and Local information agents, that provide real-time information locally on the stations of the network. A planning service is defined and is responsible for calculating the best route for the connected travellers only. It bases its calculation on the latest network status, including the ongoing disruptions (cf. Figure 4). Figure 3: Interface of SM4T. Non-connected travellers base their calculations on a static view of the network. They compute their shortest path based on this view. They wait for vehicles at scheduled stops and do not change their route until they either get stuck in an ongoing disruption (delay or line disconnection) or receive local information (from a Local information agent) about an ongoing disruption. When they receive the information, they infer the new network by applying the changes to their mental-and static-view of the transportation network and calculate a new shortest path based on this representation. On the other hand, Connected travellers have their itineraries monitored by the Planning service. The latter uses the spatio-temporal network model defined earlier, representing the public transportation network, the network topology and the vehicle schedules. Recall that an arc connects two nodes \(n_{1}(t)\) and \(n_{2}(t)\) in \(G(t)\) when there is a vehicle departing from \(n_{1}\) to \(n_{2}\) at \(t\). Otherwise, the arc is absent. The spatiotemporal network is active in this application: the space-time arcs store listeners for traveller agents and inform them when the departure time or travel time changes or when the vehicle cancels its mission.