The paper describes a novel approach to modelling traffic light control in SUMO with control logic configured in xml inputs. It shows also, that this approach allows for high fidelity replication of a real-world traffic controller by comparing original and simulated switching behavior when confronted with the same traffic situations. The approach could process from a traffic engineer with limited programming knowledge.

The high levels of air contamination and presence of different pollutants are a large problem in most of the cities in which road transport is the primary source of emissions.The governments of more than 100 countries are adopting different policies and strategies to help reduce and mitigate their global emissions. In terms of road transport, reductions in emissions could be achieved by replacing conventional vehicle technologies or by changing the travel patterns of individuals using a private vehicle as their primary means of transportation. However, accurately quantifying the emissions related to the urban traffic from multiple possible scenarios is a very complicated task, even when appropriate tools made for this purpose are available. Here we apply a scientifically rigorous protocol to accurately estimate greenhouse and other polluting gases. We describe the methodological steps we followed to analyse the vast quantities of data available from different heterogeneous sources. This data can aid decision-makers in planning better strategies for urban transportation. We used the origin-destination matrices already available for Valencia city (Spain), as well as historical information for their street induction-loops and the phases and times of their traffic light system as our input data for the traffic model. Rather than a brute-force algorithm, we used a fast-convergence Lagrangian algorithm model which deals with that vast quantities of information. Based on the elements mentioned above together with the statistics about the types of vehicles in the city by simulations the urban mobility city's traffic was reconstructed at different times to quantify the emissions produced with a high spatial and temporal resolution.

Vehicular Ad Hoc Networks (VANETs) are expected to be the next big step towards safer road transport, supporting applications to exchange information between vehicles. To develop novel applications for this area a high number of tests, considering all traffic situations, are demanded. However, it is unfeasible to reproduce these tests in real life, by the fact that any failure on the applications would cause severe impacts on transport system safety and could risk human lives. Thus, this paper presents the concept, model, and validation for InTAS, a realistic traffic scenario for Ingolstadt. InTAS’ road topology accurately represents Ingolstadt’s real road map. Elements such as buildings, bus stops, and traffic lights were added to the map. Twenty traffic lights systems were simulated according to the real program deployed on the traffic lights. Traffic demand was modeled based on the activitygen method, considering demographic data and real-traffic information. The city’s public transport system was also simulated accordingly to bus time-tables and their routes. The simulation step was implemented considering the best value for device.rerouting.probability, which was defined by evaluating InTAS’ output and real traffic data. The scenario was validated by comparing real-traffic data from 24 measurement points with InTAS’ simulation results.