Proceedings

Conference Proceedings: https://www.tib-op.org/ojs/index.php/scp/issue/view/5
DOI: https://doi.org/10.52825/scp.v2i

Sessions and Presentations

Tutorial • Video • Tutorial files
Ask us anything • Q&A Transcript
Keynote: Ride-hailing and ride-pooling: State of the art, future research directions, and the role of traffic simulation - Klaus Bogenberger • Video

Session 1: V2X

Cooperative traffic light control - considering cyclists with the aid of V2I - Maik Halbach and Kim Jannik Eggers • Video
A Study of Applying Eco-Driving Speed Advisory System on Transit Signal Priority - Hsuan Chih Wang • Video - Paper
Modeling Cellular Network Infrastructure in SUMO - Anupama Hegde, Ringo Stahl, Silas Lobo and Andreas Festag • Video - Paper

Session 2: Tools

The YASE Framework: Holistic Scenario Modeling with Behavior Trees - Max Paul Bauer • Video
Intelligent traffic management for emergency vehicles with a simulation case study - Laura Bieker-Walz, Michael Behrisch and Ronald Nippold • Video
Can SUMO be used to simulate 2+1 roads? - Filip Kristofersson, Ella Calais, Johan Olstam and Viktor Bernhardsson • Video

Session 3: ITS

The use of SUMO within the Transportation GeoXchange (TGX) platform - Arif K. Rafiq, Jeffrey Kirchner, Juliano Kersting, David Stajan and Andrea Zagar • Video
Simulation of Demand Responsive Transport using a dynamic scheduling tool with SUMO - Maria Giuliana Armellini • Video - Paper
Traffic Simulation Environment Based on Sumo Software - Xuhong Li, Liyong Zheng, Bin Su, Xu Guo, Yonggang Hao, Wenjing Li and Xuhong Li

Session 4: Autonomous Vehicles

Scenario Analysis for shared autonomous driving fleets with SUMO - Emanuel Reichsöllner and Andreas Rößler • Video
Traffic Simulation of Automated Shuttles in Linköping University Campus - Rihanna Gebrehiwot, Johan Olstam and Yun-Pang Flötteröd • Video
Simulating automated vehicles in high capacity networks - Joerg Schweizer, Federico Rupi and Cristian Poliziani • Video
Investigation of the effect of autonomous vehicles (AV) on the capacity of an urban transport network - Ronald Nippold, Peter Wagner, Olaf Angelo Banse Bueno and Christian Rakow • Video - Paper

Session 5: Emission

Online calibration with SUMO for network-wide traffic and emission monitoring – Case study ITS Huainan - Yun-Pang Flötteröd and Michael Behrisch • Video - Paper
Simulation based method for the analysis of energy-efficient driving algorithms using SUMO - Benedikt Buhk and Rasmus Rettig • Video
Optimising Low-Emissions Zone Geofencing Strategy using SUMO with Vehicle Co-Simulation - James Manuelyan, Joshua Dalby and Peter Fussey • Video

Session 6: Tools

Validating a parking lot assignment method by Eclipse SUMO - Levente Alekszejenkó and Tadeusz P. Dobrowiecki • Video - Paper
High-Fidelity Modeling of Curbside Driving Behavior in SUMO - Qichao Wang, Joseph Severino, Juliette Ugirumurera and Caleb Phillips • Video
A comparison of SUMO’s count based and countless demand generation tools - Pauline Hartwig and Michael Behrisch • Video - Paper

Session 7: Scenarios

The impact of heavy vehicles on traffic - Francois Vaudrin and Mathieu Vaudrin • Video
Automated Calibration of Traffic Demand and Traffic Lights in SUMO Using Real-World Observations - Michael Harth, Marcel Langer and Klaus Bogenberger • Video - Paper
Evaluating time-loss algorithm with SUMO - Menno van der Woude • Video

Session 8: ITS

Augmenting SUMO with Ring-and-Barrier Structured Traffic Signal Controller Module - Qichao Wang, Tianxin Li and Wesley Jones • Video
Using Deep Reinforcement Learning to Coordinate Multi-Modal Journey Planning with Limited Transportation Capacity - Lara Codeca and Vinny Cahill • Video - Paper
Last-Mile Logistics Simulation in SUMO - Fabian Post and El Mehdi Essadki • Video

Session 9: Other traffic modes and models

The Development of Pedestrian Gap Acceptance and Midblock Pedestrian Road Crossing Behavior Utilizing SUMO - Peter Lawrence, Veronica Pellacini, Darren Blackshields and Lazaros Filippidis • Video - Paper
Calibrating spatio-temporal network states in microscopic traffic simulation on a global level - Henriette Triebke, Markus Kromer and Peter Vortisch • Video
Investigating the Effect of Enabled Mesoscopic Settings within a Sensitivity Analysis - Christina Presinger • Video

You can find all videos here:

Keynote

Ride-hailing and ride-pooling: State of the art, future research directions, and the role of traffic simulation

Univ.-Prof. Dr.-Ing. Klaus Bogenberger

Chair of Traffic Engineering and Control
TUM Department of Civil, Geo and Environmental Engineering
Technical University of Munich
Website

Already today, on-demand mobility services such as Uber and Lyft in the USA, and Didi in China have taken over a noticeable share of the modal split. Furthermore, the market value assessment of these companies is now higher than the one of established vehicle producers, as they are considered to have a very high potential despite current losses with regard to autonomous driving. With the elimination of driver costs, it is expected that ride-hailing and ride-pooling can be offered at a substantially lower cost than today, generating a significant increase in demand. To understand the impact of such automated on-demand systems on future transportation systems, simulations are needed to evaluate both fleet efficiency and their interaction with the overall transportation system.

Studies to date have focused mainly on efficient vehicle-customer assignments and fleet strategies such as proactive repositioning in static networks. For example, a study comparing a current car-sharing operation with an autonomous ride-hailing system was able to show that although 10% empty trips were generated in the ride-hailing operation, it significantly increased fleet utilization. Additionally, it can be observed that system efficiency increases as fleet and demand scale. These positive scaling effects are even more prominent in ride-pooling systems. Larger demand and fleet increase pooling opportunities, which increases the occupancy rate and reduces additional fleet miles per trip request. In a simulation study for Munich, the evaluation of the trajectories of all fleet vehicles showed that these bundling potentials mainly occur on main arterial roads, while additional mileage is induced on secondary roads. These scaling effects in combination with low-cost operation can lead to a fundamental change in the established traffic system. To prevent undesirable effects on the overall system, regulations such as fleet limits, tolling, or public transport integration can help, but their tools still need to be understood in detail.

So far, the mutual effects of ride-hailing and ride-pooling as well as traffic flow have only been modeled in a simplified way. The effective coupling to microscopic traffic simulations like SUMO can be of great benefit here. Such simulation models are already valuable tools in studies on traffic control algorithms, up to the analysis of the effects of automated vehicles. In the context of ride-hailing and ride-pooling, these simulation models can additionally help to further understand traffic flow effects arising from the introduction of large-scale on-demand services. Corresponding impacts of such operations onto traffic states can then be modelled dynamically. Vice-versa, dynamic travel time estimations can be beneficial for the modelling of ride-hailing and ride-pooling operation. Furthermore, the impact of required empty trips due to repositioning or bundled passenger flows due to pooling in urban transportation networks is still poorly understood. In addition, microscopic simulations are needed to efficiently organize boarding and loading processes, detect bottlenecks, and identify any needed infrastructure at an early stage.

Wonder.me

During the conference we are going to offer a virtual room to meet and talk. Move your avatar around to meet people, just make sure to have your mic and webcam on!

We are going to have a fun SUMO-related quiz using Menti. Join our Zoom meeting and have a smartphone/tablet ready at hand. Test your knowledge of SUMO and win the glorious and prestigious prize of attaching your name to an easter egg in “sumo-gui”.

SUMO guru of the year 2021: Lara Codeca.

(Check out the hall of fame, by pressing Shift + F11 in sumo-gui 1.8.0 or newer)

Prices

Participation at this year’s conference will be free of charge!

Language

The conference language is English.

Venue

Given the extraordinary situation we are facing, this year’s SUMO User Conference will be again online - via Zoom.

Contact

Please contact the conference team via mail at sumo-conference@dlr.de