InTAS - The Ingolstadt Traffic Scenario for SUMO

Authors

DOI:

https://doi.org/10.52825/scp.v1i.102

Keywords:

realistic traffic scenario, traffic modelling, VANET, V2X, SUMO

Abstract

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.

References

Audi AG. Audi vernetzt sich mit ampeln in deutschland. [online], 2019. https://www.audi-mediacenter.com/de/pressemitteilungen/audi-vernetzt-sich-mit-ampeln-in-deutschland-11649, last viewed January 2020.

Thomas Biehle and Klaus Krumbiegel. Triggering Conditions and Data Quality Dangerous Situation. Technical Report Release 1.4.0, CAR 2 CAR Communication Consortium, 09 2019.

Jan Buchholz. Triggering Conditions and Data Quality Exchange of IRCs. Technical Report Release 1.4.0, CAR 2 CAR Communication Consortium, 09 2019.

L. Codeca, R. Frank, and T. Engel. Luxembourg SUMO Traffic (LuST) Scenario: 24 hours of mobility for vehicular networking research. In 2015 IEEE Vehicular Networking Conference (VNC), pages 1–8, Dec 2015.

L. Codeca and Jerome HARRI. Monaco ¨ SUMO traffic (MoST) scenario: A 3d mobility scenario for cooperative its. In SUMO 2018- Simulating Autonomous and Intermodal Transport Systems, volume 2, pages 43–55, 2018.

Edsger W. Dijkstra. A note on two problems in connexion with graphs. Numerische mathematik, 1(1):269–271, 1959

Sebastian Engel. Triggering Conditions and Data Quality Adverse Weather Conditions. Technical Report Release 1.4.0, CAR 2 CAR Communication Consortium, 09 2019.

Sebastian Engel. Triggering Conditions and Data Quality Stationary Vehicle Warning. Technical Report Release 1.4.0, CAR 2 CAR Communication Consortium, 09 2019.

Amt f¨ur Verkehrsmanagement und Geoinformation. Verkehrsentwicklungsplan 2025. [online], 2018. https://www.ingolstadt.de/media/custom/2789_1089_1.PDF?1540885166, last viewed December 2019.

Christian Gawron. An Iterative Algorithm to Determine the Dynamic User Equilibrium in a Traffic Simulation Model. In Proceedings of the 3rd Industrial Simulation Conference 2005, EUROSISETI, pages 285–290, 1998.

Google. Google maps. [online]. https://www.google.com/maps/@48.7621617,11.4349463, 6820m/data=!3m1!1e3, last viewed June 2019.

Stadt Ingolstadt. Kartografie: Statistik und stadtforschung. [online]. https://www.ingolstadt.de/media/custom/2789_150_1_g.JPG?1501493618, last viewed January 2020.

Stadt Ingolstadt. Verkehrspolitische ziele der stadt ingolstadt. [online]. https://www.ingolstadt.de/Rathaus/Verkehr/Verkehrsmanagement/Verkehrsplanung/index.php La=1&object=tx,465.4793.1&kat=&kuo=2&sub=0, last viewed January 2020.

Stadt Ingolstadt. Ingolstadt in zahlen 2018/2019. [online], 2018. https://ingolstadt.de/media/custom/465_1995_1.PDF?1534841095, last viewed September 2019.

Stadt Ingolstadt. Kleinr¨aumige statistiken zum 31.12.2018. [online], 2019. https://www.ingolstadt.de/media/custom/3052_1647_1.PDF?1563171021, last viewed October 2019.

INVG. Ingolst¨adter verkehrsgesellschaft. [online]. https://www.invg.de/, last viewed November 2019.

S Krauß. Microscopic Modeling of Traffic Flow: Investigation of Collision Free Vehicle Dynamics. PhD thesis, DLR-Forschungsbericht, 08 1998.

Pablo Alvarez Lopez, Michael Behrisch, Laura Bieker-Walz, Jakob Erdmann, Yun-Pang Fl¨otter¨od, Robert Hilbrich, Leonhard L¨ucken, Johannes Rummel, Peter Wagner, and Evamarie Wießner. Microscopic Traffic Simulation using SUMO. In The 21st IEEE International Conference on Intelligent Transportation Systems, pages 2575–2582. IEEE, November 2018.

D. McKenney and T. White. Distributed and adaptive traffic signal control within a realistic traffic simulation. In Engineering Applications of Artificial Intelligence, volume 26, pages 574–583, January 2013.

R. Miucic. Introduction. In Connected Vehicles, pages 1–10, 2019.

S. Neumeier, M. H¨opp, and C. Facchi. Yet another driving simulator openrouts3d: The driving simulator for teleoperated driving. In 2019 IEEE International Conference on Connected Vehicles and Expo (ICCVE), pages 1–6, Graz, AUT, Nov 2019.

C. Obermaier, R. Riebl, and C. Facchi. Fully reactive hardware-in-the-loop simulation for vanet devices. In 2018 21st International Conference on Intelligent Transportation Systems (ITSC), pages 3755–3760, Nov 2018.

OpenStreetMap. OpenStreetMap. [online]. https://openstreetmap.org, last viewed June 2019.

Gevas Humberg & Partner. Integriertes verkehrsmodell datenerfassungskonzepte ingolstadt. [online]. https://www.gevasingenieure.de/pdf/REF_VP_Verkehrsmodell_Ingolstadt_IN-VMO02_neu.pdf, last viewed November 2019.

Muhammad Ahsan Qureshi, Rafidah Md. Noor, Azra Shamim, Shamshirband PhD, and KimKwang Raymond Choo. A lightweight radio propagation model for vehicular communication in road tunnels. PLoS ONE, 11, 03 2016.

J. Soares, C. Lobo, Z. Vale, and P. B. de Moura Oliveira. Realistic traffic scenarios using a census methodology: Vila real case study. In 2014 IEEE PES General Meeting

Conference Exposition, pages 1–5, July 2014.

SUMO. Demand/dynamic user assignment. [online], 2020. https://sumo.dlr.de/docs/Demand/Dynamic_User_Assignment.html, last viewed June 2020.

SUMO. Simulation/output/tripinfo. [online], 2020. https://sumo.dlr.de/docs/Simulation/Output/TripInfo.html, last viewed June 2020.

Agrani Swarnkar and Anil Swarnkar. Artificial intelligence based optimization techniques: A review. In Akhtar Kalam, Khaleequr Rehman Niazi, Amit Soni, Shahbaz Ahmed Siddiqui, and Ankit Mundra, editors, Intelligent Computing Techniques for Smart Energy Systems, pages 95–103, Singapore, 2020. Springer Singapore.

H. Tchouankem, T. Zinchenko, and H. Schumacher. Impact of buildings on vehicle-to-vehicle communication at urban intersections. In 2015 12th Annual IEEE Consumer Communications and Networking Conference (CCNC), pages 206–212, Jan 2015.

T. Tielert, M. Killat, H. Hartenstein, R. Luz, S. Hausberger, and T. Benz. The impact of trafficlight-to-vehicle communication on fuel consumption and emissions. In 2010 Internet of Things (IOT), pages 1–8, Nov 2010.

S. Uppoor and M. Fiore. Large-scale urban vehicular mobility for networking research. In 2011 IEEE Vehicular Networking Conference ( VNC), pages 62–69, Nov 2011.

N. Wu, D. Li, and Y. Xi. Distributed weighted balanced control of traffic signals for urban traffic congestion. IEEE Transactions on Intelligent Transportation Systems, 20(10):3710–3720, Oct 2019.

Downloads

Published

2022-07-01

How to Cite

Lobo, S., Neumeier, S., M. G. Fernandez, E., & Facchi, C. (2022). InTAS - The Ingolstadt Traffic Scenario for SUMO. SUMO Conference Proceedings, 1, 73–92. https://doi.org/10.52825/scp.v1i.102

Issue

Section

Conference papers