For driving the roads of cities into enjoyable and relaxing places with parks, trees, and seating, a paradigm change in everyone’s commuter behavior is needed. Still, individual transport via cars increases, and thus, the space required for parking and driving these cars shapes our cities — not the people. Next to the space needed, vehicles pollute the environment with CO2, diesel particulate, and even electric cars with tire abrasion. Alternative modes of locomotion, like public transportation and shared mobility, are still not attractive to many people. Intelligent intermodal mobility networks can help address these challenges, allowing for efficient use between various transportation modalities. These mobility networks require good databases and simulation combined into digital twins. This paper presents how such a digital twin can be created in the Simulation of Urban Mobility (SUMO) software using data from available and future city sensors. The digital twin aims to simulate, analyze, and evaluate the different behaviors and interactions between traffic participants when changing commuting incentives. Using the city of Osnabrück and its different available sensor types, the data availability is compared with other towns to discuss how the data density can be improved. Creating a static network from open street data and intersection side maps provided by the city of Osnabrück shows how these data can be integrated into SUMO for generating traffic flows and routes in SUMO based on a database of historical and live data. Within the conclusion, the paper discusses how developing a digital twin in SUMO from static and dynamic data can be improved in the future and what common misconceptions need to be overcome.
{"title":"Simulating Traffic Networks","authors":"Axel Schaffland, Jonas Nelson, Julius Schöning","doi":"10.52825/scp.v5i.1105","DOIUrl":"https://doi.org/10.52825/scp.v5i.1105","url":null,"abstract":"For driving the roads of cities into enjoyable and relaxing places with parks, trees, and seating, a paradigm change in everyone’s commuter behavior is needed. Still, individual transport via cars increases, and thus, the space required for parking and driving these cars shapes our cities — not the people. Next to the space needed, vehicles pollute the environment with CO2, diesel particulate, and even electric cars with tire abrasion. Alternative modes of locomotion, like public transportation and shared mobility, are still not attractive to many people. Intelligent intermodal mobility networks can help address these challenges, allowing for efficient use between various transportation modalities. These mobility networks require good databases and simulation combined into digital twins. This paper presents how such a digital twin can be created in the Simulation of Urban Mobility (SUMO) software using data from available and future city sensors. The digital twin aims to simulate, analyze, and evaluate the different behaviors and interactions between traffic participants when changing commuting incentives. Using the city of Osnabrück and its different available sensor types, the data availability is compared with other towns to discuss how the data density can be improved. Creating a static network from open street data and intersection side maps provided by the city of Osnabrück shows how these data can be integrated into SUMO for generating traffic flows and routes in SUMO based on a database of historical and live data. Within the conclusion, the paper discusses how developing a digital twin in SUMO from static and dynamic data can be improved in the future and what common misconceptions need to be overcome.","PeriodicalId":439794,"journal":{"name":"SUMO Conference Proceedings","volume":" 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141828229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mesoscopic, agent-based simulations efficiently model and assess entire regions’ daily activities and travel patterns, exemplified by smaller countries like Switzerland. The queue-based simulation represents a compromise between computational speed on the one hand and the necessity of detailed modeling infrastructure on the other hand. Thus, mesoscopic simulations enable an efficient and reasonably detailed analysis of the complex interplay between supply and demand in mobility research. Conversely, microsimulations excel at reproducing individual speed profiles and behavior by modeling the interactions between traffic participants, including pedestrians, bicycles, and scooters. Although allowing for more detailed system analysis, the downside is the high computational burden, which often prevents large-scale microscopic simulations from running in optimization or calibration loops. hybridPY, an extension of SUMOPy, aims to close the gap and benefit from both environments. The simulation suite allows the running of mesoscopic as well as microscopic traffic simulations based on the core idea: running a microscopic simulation in a smaller dedicated area, using the routes or mobility plans generated from a larger mesoscopic model. The main features of this software are: (i) import, editing and visualization of MATSim and BEAM CORE networks; (ii) conversion of MATSim plans to SUMO routes or plans within the SUMO area; (iii) configuring and running of MATSim simulations. The capability of hybridPY is demonstrated by two applications: the simulation of Schwabing, Germany, based on the MITO MATSim model, and the San Francisco municipality, USA, based on the mesoscopic BEAM CORE model of the entire San Francisco Bay area. Both scenarios demonstrate that the hybrid approach results in significant computational gains with respect to a pure microscopic approach.
{"title":"hybridPy: The Simulation Suite for Mesoscopic and Microscopic Traffic Simulations","authors":"J¨org Schweizer, Fabian Schuhmann, Cristian Poliziani","doi":"10.52825/scp.v5i.1030","DOIUrl":"https://doi.org/10.52825/scp.v5i.1030","url":null,"abstract":"Mesoscopic, agent-based simulations efficiently model and assess entire regions’ daily activities and travel patterns, exemplified by smaller countries like Switzerland. The queue-based simulation represents a compromise between computational speed on the one hand and the necessity of detailed modeling infrastructure on the other hand. Thus, mesoscopic simulations enable an efficient and reasonably detailed analysis of the complex interplay between supply and demand in mobility research. Conversely, microsimulations excel at reproducing individual speed profiles and behavior by modeling the interactions between traffic participants, including pedestrians, bicycles, and scooters. Although allowing for more detailed system analysis, the downside is the high computational burden, which often prevents large-scale microscopic simulations from running in optimization or calibration loops. hybridPY, an extension of SUMOPy, aims to close the gap and benefit from both environments. The simulation suite allows the running of mesoscopic as well as microscopic traffic simulations based on the core idea: running a microscopic simulation in a smaller dedicated area, using the routes or mobility plans generated from a larger mesoscopic model. The main features of this software are: (i) import, editing and visualization of MATSim and BEAM CORE networks; (ii) conversion of MATSim plans to SUMO routes or plans within the SUMO area; (iii) configuring and running of MATSim simulations. The capability of hybridPY is demonstrated by two applications: the simulation of Schwabing, Germany, based on the MITO MATSim model, and the San Francisco municipality, USA, based on the mesoscopic BEAM CORE model of the entire San Francisco Bay area. Both scenarios demonstrate that the hybrid approach results in significant computational gains with respect to a pure microscopic approach.","PeriodicalId":439794,"journal":{"name":"SUMO Conference Proceedings","volume":" 35","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141831228","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The Train Dispatcher in the Cloud (ZLiC) is a cloud-based approach to digitalize the German Zugleitbetrieb (comparable to American track warrant control). The ZLiC aims to replace the train dispatcher with speech to text, natural-language understanding, a digital occupancy sheet, a prototype interlocking logic, and text to speech. For train conductors, who operate on the trains, the voice-based communication with the train dispatcher remains unchanged. Because the external interfaces of the ZLiC are either voice-based or graphic, understanding and testing the internal components from an integration level is a challenge. To address these challenges, we first injected the Simulation of Urban Mobility (SUMO) as a simulation environment. Since the ZLiC has been developed model-based, the integration requires minimal modifications. Afterward, we fetch the operation commands (e.g., registering trains, locating trains, drive requests for trains) between the components and send them to a SUMO instance for analyzing and visualizing the train operations in the railway network. Lastly, we insert additional planned trains to add simulated traffic. The reproducible operations enable test automation of the ZLiC while reusing the sophisticated models in SUMO. This prototype shows that SUMO can support the development of digitalized railway operating procedures.
{"title":"Using SUMO for Test Automation and Demonstration of Digitalized Railway Concepts","authors":"Arne Boockmeyer, Dirk Friedenberger, Lukas Pirl","doi":"10.52825/scp.v5i.1126","DOIUrl":"https://doi.org/10.52825/scp.v5i.1126","url":null,"abstract":"The Train Dispatcher in the Cloud (ZLiC) is a cloud-based approach to digitalize the German Zugleitbetrieb (comparable to American track warrant control). The ZLiC aims to replace the train dispatcher with speech to text, natural-language understanding, a digital occupancy sheet, a prototype interlocking logic, and text to speech. For train conductors, who operate on the trains, the voice-based communication with the train dispatcher remains unchanged. Because the external interfaces of the ZLiC are either voice-based or graphic, understanding and testing the internal components from an integration level is a challenge. To address these challenges, we first injected the Simulation of Urban Mobility (SUMO) as a simulation environment. Since the ZLiC has been developed model-based, the integration requires minimal modifications. Afterward, we fetch the operation commands (e.g., registering trains, locating trains, drive requests for trains) between the components and send them to a SUMO instance for analyzing and visualizing the train operations in the railway network. Lastly, we insert additional planned trains to add simulated traffic. The reproducible operations enable test automation of the ZLiC while reusing the sophisticated models in SUMO. This prototype shows that SUMO can support the development of digitalized railway operating procedures.","PeriodicalId":439794,"journal":{"name":"SUMO Conference Proceedings","volume":" 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141830686","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Andreas Freymann, Emanuel Reichsoellner, Damir Ravlija, Ingo Trautwein, Mirko Sonntag
Nowadays, shared micromobility has become a trend in cities as an alternative to conventional automotive vehicles, especially for short-distance travel. It also plays an important role in the reduction of the number of automotive vehicles which results in a decrease of air pollution and traffic congestion. Shared micromobility is, however, influenced by the terrain characteristics. Varying elevation within a fleet operational area can cause imbalances in the use of micromobility stations if a steep terrain lies between stations. It also impacts the energy consumption of electric micromobility vehicles such as e-bicycles and e-scooters. Therefore, to simulate the state of charge (SOC) of traction batteries for micromobility close to reality, it is essential to include elevation data into the simulation model. This paper proposes a workflow for Simulation of Urban MObility (SUMO) comprising several steps with concrete implementation and validation in order to prepare and define the simulation model with micromobility stations and the integration of elevation data using a REST API. The integration of elevation and bike station data is validated with a defined vehicle type following a route in the hilly part of Stuttgart, Germany. A comparison of micromobility trips, with and without elevation data, was performed through a simulation by recording changes in energy consumption and driven altitude differences. The proposed workflow provides a basis for more complex use cases such as analysing micromobility business areas, improving vehicle.
如今，作为传统汽车的替代品，共享微型交通已成为城市的一种趋势，尤其是在短途旅行中。它在减少汽车数量方面也发挥了重要作用，从而减少了空气污染和交通拥堵。然而，共享微型流动性受到地形特征的影响。如果站点之间的地形陡峭，车队运营区域内的海拔高度变化会导致微型交通站点的使用不平衡。这也会影响电动微型交通车辆（如电动自行车和电动滑板车）的能耗。因此，要模拟微型交通牵引电池的充电状态（SOC），就必须在模拟模型中加入海拔数据。本文提出了城市移动性仿真（SUMO）的工作流程，包括具体实施和验证的几个步骤，以准备和定义带有微型移动站的仿真模型，并使用 REST API 集成高程数据。在德国斯图加特丘陵地带的一条路线上，对海拔高度和自行车站点数据的整合进行了验证。通过记录能源消耗的变化和驱动的高度差，对有海拔数据和无海拔数据的微移动出行进行了模拟比较。建议的工作流程为更复杂的使用案例提供了基础，例如分析微型交通的业务领域、改进车辆的性能、提高车辆的安全性和可靠性。
{"title":"Integrating Topographical Map Information in SUMO to Simulate Realistic Micromobility Trips in Hilly and Steep Terrains","authors":"Andreas Freymann, Emanuel Reichsoellner, Damir Ravlija, Ingo Trautwein, Mirko Sonntag","doi":"10.52825/scp.v5i.1131","DOIUrl":"https://doi.org/10.52825/scp.v5i.1131","url":null,"abstract":"Nowadays, shared micromobility has become a trend in cities as an alternative to conventional automotive vehicles, especially for short-distance travel. It also plays an important role in the reduction of the number of automotive vehicles which results in a decrease of air pollution and traffic congestion. Shared micromobility is, however, influenced by the terrain characteristics. Varying elevation within a fleet operational area can cause imbalances in the use of micromobility stations if a steep terrain lies between stations. It also impacts the energy consumption of electric micromobility vehicles such as e-bicycles and e-scooters. Therefore, to simulate the state of charge (SOC) of traction batteries for micromobility close to reality, it is essential to include elevation data into the simulation model. This paper proposes a workflow for Simulation of Urban MObility (SUMO) comprising several steps with concrete implementation and validation in order to prepare and define the simulation model with micromobility stations and the integration of elevation data using a REST API. The integration of elevation and bike station data is validated with a defined vehicle type following a route in the hilly part of Stuttgart, Germany. A comparison of micromobility trips, with and without elevation data, was performed through a simulation by recording changes in energy consumption and driven altitude differences. The proposed workflow provides a basis for more complex use cases such as analysing micromobility business areas, improving vehicle.","PeriodicalId":439794,"journal":{"name":"SUMO Conference Proceedings","volume":" 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141830725","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Accurate traffic models are of decisive importance for well-founded traffic engineering and represent the basic framework for comprehensive simulation studies as modelling of traffic demand. Using traffic count and speed measurements of road segments is a common approach for the calibration of a realistic traffic simulation although the data acquisition process can be at very extensive costs. From an academical point of view, there have been many studies addressing the problem of calibration. In this respect, the microscopic simulation software SUMO offers the usage of the tools flowrouter and routesampler for generating network simulations on the base of traffic count measurements. In this paper, we propose a robust method for the calibration of microscopic traffic simulations by using vehicle count and speed measurements from collected GPS-data. The developed approach is a two-step optimization process: The application of integer linear programming (ILP) as a priori optimization is followed by adopting an evolutionary algorithm for minimizing the a posteriori deviation between real and simulated traffic data. As a proof of concept, the proposed method is tested in a subnet-work model of the inner city of Friedrichshafen and compared with the ready-to-use tools from SUMO. The suggested method indicates a promising correlation between simulated and real traffic data showing better calibration results in comparison to the aforementioned functions SUMO provides. Since the approach is network-independent, it also offers the possibility of large-scale traffic calibration.
{"title":"Calibration of Microscopic Traffic Simulation in an Urban Environment Using GPS-Data","authors":"Christopher Stang, Klaus Bogenberger","doi":"10.52825/scp.v5i.1099","DOIUrl":"https://doi.org/10.52825/scp.v5i.1099","url":null,"abstract":"Accurate traffic models are of decisive importance for well-founded traffic engineering and represent the basic framework for comprehensive simulation studies as modelling of traffic demand. Using traffic count and speed measurements of road segments is a common approach for the calibration of a realistic traffic simulation although the data acquisition process can be at very extensive costs. From an academical point of view, there have been many studies addressing the problem of calibration. In this respect, the microscopic simulation software SUMO offers the usage of the tools flowrouter and routesampler for generating network simulations on the base of traffic count measurements. In this paper, we propose a robust method for the calibration of microscopic traffic simulations by using vehicle count and speed measurements from collected GPS-data. The developed approach is a two-step optimization process: The application of integer linear programming (ILP) as a priori optimization is followed by adopting an evolutionary algorithm for minimizing the a posteriori deviation between real and simulated traffic data. As a proof of concept, the proposed method is tested in a subnet-work model of the inner city of Friedrichshafen and compared with the ready-to-use tools from SUMO. The suggested method indicates a promising correlation between simulated and real traffic data showing better calibration results in comparison to the aforementioned functions SUMO provides. Since the approach is network-independent, it also offers the possibility of large-scale traffic calibration.","PeriodicalId":439794,"journal":{"name":"SUMO Conference Proceedings","volume":" 20","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141827790","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study investigates the feasibility and challenges of transferring traffic signal control schemes from the macroscopic signal timing optimization tool Synchro to the microscopic traffic simulator SUMO, focusing on Downtown Seattle as a case study. The research assesses the process of sharing and importing traffic signal timing plans, a crucial aspect of transportation simulations, between these two platforms. We conduct a detailed analysis of the traffic signal characteristics and data formats unique to each simulator and identify elements suitable for conversion. Subsequently, a four-stage framework is developed for semi-automatic integration of traffic signal control between the two. Our results indicate a successful conversion rate of approximately 85% of signalized intersections from Synchro to SUMO. This research not only illustrates the challenges and solutions in converting signal control across different platforms but also paves the way for future studies aimed at improving the interoperability of various traffic simulation tools.
{"title":"Integration Traffic Signal Control From Synchro to SUMO","authors":"Yiran Zhang","doi":"10.52825/scp.v5i.1112","DOIUrl":"https://doi.org/10.52825/scp.v5i.1112","url":null,"abstract":"This study investigates the feasibility and challenges of transferring traffic signal control schemes from the macroscopic signal timing optimization tool Synchro to the microscopic traffic simulator SUMO, focusing on Downtown Seattle as a case study. The research assesses the process of sharing and importing traffic signal timing plans, a crucial aspect of transportation simulations, between these two platforms. We conduct a detailed analysis of the traffic signal characteristics and data formats unique to each simulator and identify elements suitable for conversion. Subsequently, a four-stage framework is developed for semi-automatic integration of traffic signal control between the two. Our results indicate a successful conversion rate of approximately 85% of signalized intersections from Synchro to SUMO. This research not only illustrates the challenges and solutions in converting signal control across different platforms but also paves the way for future studies aimed at improving the interoperability of various traffic simulation tools.","PeriodicalId":439794,"journal":{"name":"SUMO Conference Proceedings","volume":" 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141830880","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper presents "Sumonity," an interface that bridges SUMO (Simulation of Urban MObility) and Unity, combining SUMO's robust traffic modeling capabilities with Unity's advanced graphical and physical engine, enhancing realism in traffic simulations. The study explores Sumonity's development and implementation, showcasing its capabilities. The interface offers a significant improvement in simulation fidelity by adopting a pure pursuit control approach within Unity for simulating each traffic agent. This methodological shift allows for more granular control over individual vehicle behaviors, aligning with autonomous and common vehicle dynamics. The paper also discusses the broader implications of Sumonity for future research in this field.
{"title":"Sumonity: Bridging SUMO and Unity for Enhanced Traffic Simulation Experiences","authors":"Mathias Pechinger, Johannes Lindner","doi":"10.52825/scp.v5i.1115","DOIUrl":"https://doi.org/10.52825/scp.v5i.1115","url":null,"abstract":"This paper presents \"Sumonity,\" an interface that bridges SUMO (Simulation of Urban MObility) and Unity, combining SUMO's robust traffic modeling capabilities with Unity's advanced graphical and physical engine, enhancing realism in traffic simulations. The study explores Sumonity's development and implementation, showcasing its capabilities. The interface offers a significant improvement in simulation fidelity by adopting a pure pursuit control approach within Unity for simulating each traffic agent. This methodological shift allows for more granular control over individual vehicle behaviors, aligning with autonomous and common vehicle dynamics. The paper also discusses the broader implications of Sumonity for future research in this field.","PeriodicalId":439794,"journal":{"name":"SUMO Conference Proceedings","volume":" 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141831176","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper illuminates the utilization of SUMO as a powerful tool for addressing real-world traffic management issues. There is a gap in testing and validating solutions to in-field conditions due to the high cost and complexity of urban and suburban road networks. The validation step is often skipped, which can lead to a higher risk in implementing sophisticated solutions that exist in our multimodal transportation environment. This challenge is addressed by introducing simulations as a crucial preliminary step before real-world application. Accurate simulations require detailed data on intersection geometries, vehicle distribution, and driver behavior to accurately mirror real-world conditions. To meet these criteria, detailed sensor data on trajectories, types of road users, and their locations are extensively employed. This data forms the foundation for calibrated traffic simulations by NoTraffic™ . In conclusion, an in-depth demonstration of the method used to address a real-world traffic problem with SUMO is provided, emphasizing SUMO’s effectiveness in building confidence for deploying solutions in the field.
{"title":"Leveraging SUMO for Real-World Traffic Optimization: A Comprehensive Approach","authors":"Olga Dobrilko, Alon Bublil","doi":"10.52825/scp.v5i.1120","DOIUrl":"https://doi.org/10.52825/scp.v5i.1120","url":null,"abstract":"This paper illuminates the utilization of SUMO as a powerful tool for addressing real-world traffic management issues. There is a gap in testing and validating solutions to in-field conditions due to the high cost and complexity of urban and suburban road networks. The validation step is often skipped, which can lead to a higher risk in implementing sophisticated solutions that exist in our multimodal transportation environment. This challenge is addressed by introducing simulations as a crucial preliminary step before real-world application. Accurate simulations require detailed data on intersection geometries, vehicle distribution, and driver behavior to accurately mirror real-world conditions. To meet these criteria, detailed sensor data on trajectories, types of road users, and their locations are extensively employed. This data forms the foundation for calibrated traffic simulations by NoTraffic™ . In conclusion, an in-depth demonstration of the method used to address a real-world traffic problem with SUMO is provided, emphasizing SUMO’s effectiveness in building confidence for deploying solutions in the field.","PeriodicalId":439794,"journal":{"name":"SUMO Conference Proceedings","volume":" 48","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141829363","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Fabian Schuhmann, Maximilian Sievers, Stefan Schrott, Ivan Kapovich, Lijie Feng, Markus Lienkamp
Mobility in metropolitan regions is changing. The distribution of space in cities, the design of transport modes, and the organization of mobility are being re-thought. However, no matter the changes and innovations on the way to a more sustainable future, essential constants must be upheld: In the event of minor, regionally limited emergencies, medical assistance must reach those in need quickly. When dealing with large-scale emergencies, the ability to evacuate the area promptly must be ensured. The impact analysis of mobility innovations on emergency services within urban areas so far has been based purely on empirical observations using existing data. Currently, it is only possible to analyze what-if considerations in a limited way. Nevertheless, due to the increasingly rapid changes in mobility, a comprehensive and interlinked analysis will be necessary. This is the key contribution of rescuePY: rescuePY is a simulation suite based on the mesoscopic and microscopic simulation environment hybridPY. It allows holistic and microscopic transport modeling of rescue infrastructure to quantify the impact of the mobility transition towards higher sustainability on the performance of rescue services. The main features of this software are: Rescue system assessment for strategic, long-term planning Mobility-influence studies for operative, mid-term planning Activity-based urban evacuation modeling The capabilities of rescuePY are demonstrated by two applications: a simulation- based, mesoscopic system analysis of emergency services in Munich compared to real-world data and microscopic modeling of emergency vehicles (EMVs) in different road architectures. Ongoing developments aim to improve the evaluation methodology for the aggregated impact analysis of mobility innovations on rescue response services.
{"title":"rescuePY: Simulation-Based Rescue Response Impact Assessment","authors":"Fabian Schuhmann, Maximilian Sievers, Stefan Schrott, Ivan Kapovich, Lijie Feng, Markus Lienkamp","doi":"10.52825/scp.v5i.1029","DOIUrl":"https://doi.org/10.52825/scp.v5i.1029","url":null,"abstract":"Mobility in metropolitan regions is changing. The distribution of space in cities, the design of transport modes, and the organization of mobility are being re-thought. However, no matter the changes and innovations on the way to a more sustainable future, essential constants must be upheld: In the event of minor, regionally limited emergencies, medical assistance must reach those in need quickly. When dealing with large-scale emergencies, the ability to evacuate the area promptly must be ensured. The impact analysis of mobility innovations on emergency services within urban areas so far has been based purely on empirical observations using existing data. Currently, it is only possible to analyze what-if considerations in a limited way. Nevertheless, due to the increasingly rapid changes in mobility, a comprehensive and interlinked analysis will be necessary. This is the key contribution of rescuePY: rescuePY is a simulation suite based on the mesoscopic and microscopic simulation environment hybridPY. It allows holistic and microscopic transport modeling of rescue infrastructure to quantify the impact of the mobility transition towards higher sustainability on the performance of rescue services.\u0000The main features of this software are:\u0000\u0000Rescue system assessment for strategic, long-term planning\u0000Mobility-influence studies for operative, mid-term planning\u0000Activity-based urban evacuation modeling\u0000\u0000The capabilities of rescuePY are demonstrated by two applications: a simulation- based, mesoscopic system analysis of emergency services in Munich compared to real-world data and microscopic modeling of emergency vehicles (EMVs) in different road architectures. Ongoing developments aim to improve the evaluation methodology for the aggregated impact analysis of mobility innovations on rescue response services.","PeriodicalId":439794,"journal":{"name":"SUMO Conference Proceedings","volume":" 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141829202","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper examined the performances of the current four battery models in SUMO. The possibility of expanding the model parameterization was also investigated and the corresponding extension was carried out for PHEMlight. Accordingly, the models can be compared more fairly. Three scenarios were used, namely the Worldwide harmonized Light vehicles Test Cycle, a constant high-speed highway scenario and an area scenario with a relatively complex traffic situation. The results show that all models can address recuperation and propulsion, and deliver the similar result at very low acceleration. The models based on average vehicle data generally tend to deliver higher battery consumption than the models with individual vehicle type-specific parameterization, especially PHEMlight5, while HBEFA4 only has one electric vehicle class and is therefore not sensitive to various vehicle characteristics. Moreover, the model by Kurczveil and López (EVM) seems to tend to have the lowest consumption of all models.
{"title":"Comparing and Parameterizing the Electrical Energy Consumption Models in SUMO","authors":"M. Behrisch, Y. Flötteröd, Peter Wagner","doi":"10.52825/scp.v5i.1012","DOIUrl":"https://doi.org/10.52825/scp.v5i.1012","url":null,"abstract":"This paper examined the performances of the current four battery models in SUMO. The possibility of expanding the model parameterization was also investigated and the corresponding extension was carried out for PHEMlight. Accordingly, the models can be compared more fairly. Three scenarios were used, namely the Worldwide harmonized Light vehicles Test Cycle, a constant high-speed highway scenario and an area scenario with a relatively complex traffic situation. The results show that all models can address recuperation and propulsion, and deliver the similar result at very low acceleration. The models based on average vehicle data generally tend to deliver higher battery consumption than the models with individual vehicle type-specific parameterization, especially PHEMlight5, while HBEFA4 only has one electric vehicle class and is therefore not sensitive to various vehicle characteristics. Moreover, the model by Kurczveil and López (EVM) seems to tend to have the lowest consumption of all models.","PeriodicalId":439794,"journal":{"name":"SUMO Conference Proceedings","volume":" 14","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141829948","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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