Load Generators for Automatic Simulation of Urban Fleets

Abstract

To ensure cities sustainability, we must deal with, among other challenges, traffic congestion, and its associated carbon emissions. We can approach such a problem from two perspectives: the transition to electric vehicles, which implies the need for charging station infrastructure, and the optimization of traffic flow. However, cities are complex systems, so it is helpful to test changes on them in controlled environments like the ones provided by simulators. In our work, we use Sim-Fleet, an agent-based fleet simulator. Nevertheless, SimFleet does not provide tools for easily setting up big experiments, neither to simulate the realistic movement of its agents inside a city. Aiming to solve that, we enhanced SimFleet introducing two fully configurable generators that automatize the creation of experiments. First, the charging stations generator, which allocates a given amount of charging stations following a certain distribution, enabling to simulate how transports would charge and compare distributions. Second, the load generator, which populates the experiment with a given number of agents of a given type, introducing them dynamically in the simulation, and assigns them a movement that can be either random or based on real city data. The generators proved to be useful for comparing different distributions of charging stations as well as different agent behaviors over the same complex setup.

Infrastructure for the Enhancement of Urban Fleet Simulation

“…To solve such issue, we propose two so-called generators [12], programs which, given a series of parameters, fill or create a new simulation scenario, leaving it ready for execution. Besides that, the generators would obtain more realistic simulations and agent distributions, being able to use cadastral, traffic, and Twitter information to obtain more accurate scenarios.…”

Introduction of emerging mobility services in rural areas through the use of mobile network data combined with activity‐based travel demand modelling

“…The use of data‐driven approaches and simulation to inform operation of commercial DRT services is less common compared to qualitative methods, capturing views of specific segments of the population [9–14].…”

Charging stations and mobility data generators for agent-based simulations

“…In this work, we propose different ways to generate more realistic data as input for agent-based simulation experimentation, extending a previous work presented in [5]. More specifically, we focus the processes of generating more realistic data on two problems: the generation of possible locations for electric vehicle charging stations, and the generation of realistic movements of entities in a city to have an appropriate representation of its traffic flow.…”