<p dir="ltr">This research evaluates shared mobility services in the United States, focusing on e-scooter sharing, bike-sharing, and ride-hailing in various urban settings. It aims to understand public and user perceptions, usage patterns, and the impact of urban design on these services. Key research questions include the differences in usage around campuses, public perceptions of shared mobility, future usage intentions post-COVID-19, and the influence of bike lane construction on shared mobility. The study uses survey data and various analytical methods to provide insights for policymakers and operators, introducing the CYCLES framework to enhance shared mobility systems and promote sustainable transportation solutions.</p>

The 4th Symposium on Management of Future Motorway and Urban Traffic Systems (MFTS) was held in Dresden, Germany, from November 30th to December 2nd, 2022. Organized by the Chair of Traffic Process Automation (VPA) at the “Friedrich List” Faculty of Transport and Traffic Sciences of the TU Dresden, the proceedings of this conference are published as volume 9 in the Chair’s publication series “Verkehrstelematik” and contain a large part of the presented conference extended abstracts. The focus of the MFTS conference 2022 was cooperative management of multimodal transport and reflected the vision of the professorship to be an internationally recognized group in ITS research and education with the goal of optimizing the operation of multimodal transport systems. In 14 MFTS sessions, current topics in demand and traffic management, traffic control in conventional, connected and automated transport, connected and autonomous vehicles, traffic flow modeling and simulation, new and shared mobility systems, digitization, and user behavior and safety were discussed. In addition, special sessions were organized, for example on “Human aspects in traffic modeling and simulation” and “Lesson learned from Covid19 pandemic”, whose descriptions and analyses are also included in these proceedings.:1 Connected and Automated Vehicles 1.1 Traffic-based Control of Truck Platoons on Freeways 1.2 A Lateral Positioning Strategy for Connected and Automated Vehicles in Lane-free Traffic 1.3 Simulation Methods for Mixed Legacy-Autonomous Mainline Train Operations 1.4 Can Dedicated Lanes for Automated Vehicles on Urban Roads Improve Traffic Efficiency? 1.5 GLOSA System with Uncertain Green and Red Signal Phases 2 New Mobility Systems 2.1 A New Model for Electric Vehicle Mobility and Energy Consumption in Urban Traffic Networks 2.2 Shared Autonomous Vehicles Implementation for a Disrupted Public Transport Network 3 Traffic Flow and Simulation 3.1 Multi-vehicle Stochastic Fundamental Diagram Consistent with Transportations Systems Theory 3.2 A RoundD-like Roundabout Scenario in CARLA Simulator 3.3 Multimodal Performance Evaluation of Urban Traffic Control: A Microscopic Simulation Study 3.4 A MILP Framework to Solve the Sustainable System Optimum with Link MFD Functions 3.5 On How Traffic Signals Impact the Fundamental Diagrams of Urban Roads 4 Traffic Control in Conventional Traffic 4.1 Data-driven Methods for Identifying Travel Conditions Based on Traffic and Weather Characteristics 4.2 AI-based Multi-class Traffic Model Oriented to Freeway Traffic Control 4.3 Exploiting Deep Learning and Traffic Models for Freeway Traffic Estimation 4.4 Automatic Design of Optimal Actuated Traffic Signal Control with Transit Signal Priority 4.5 A Deep Reinforcement Learning Approach for Dynamic Traffic Light Control with Transit Signal Priority 4.6 Towards Efficient Incident Detection in Real-time Traffic Management 4.7 Dynamic Cycle Time in Traffic Signal of Cyclic Max-Pressure Control 5 Traffic Control with Autonomous Vehicles 5.1 Distributed Ordering and Optimization for Intersection Management with Connected and Automated Vehicles 5.2 Prioritization of an Automated Shuttle for V2X Public Transport at a Signalized Intersection – a Real-life Demonstration 6 User Behaviour and Safety 6.1 Local Traffic Safety Analyzer (LTSA) - Improved Road Safety and Optimized Signal Control for Future Urban Intersections 7 Demand and Traffic Management 7.1 A Stochastic Programming Method for OD Estimation Using LBSN Check-in Data 7.2 Delineation of Traffic Analysis Zone for Public Transportation OD Matrix Estimation Based on Socio-spatial Practices 8 Workshops 8.1 How to Integrate Human Aspects Into Engineering Science of Transport and Traffic? - a Workshop Report about Discussions on Social Contextualization of Mobility 8.2 Learning from Covid: How Can we Predict Mobility Behaviour in the Face of Disruptive Events? – How to Investigate the Mobility of the Future / Das 4. Symposium zum Management zukünftiger Autobahn- und Stadtverkehrssysteme (MFTS) fand vom 30. November bis 2. Dezember 2022 in Dresden statt und wurde vom Lehrstuhl für Verkehrsprozessautomatisierung (VPA) an der Fakultät Verkehrswissenschaften„Friedrich List“ der TU Dresden organisiert. Der Tagungsband erscheint als Band 9 in der Schriftenreihe „Verkehrstelematik“ des Lehrstuhls und enthält einen Großteil der vorgestellten Extended-Abstracts des Symposiums. Der Schwerpunkt des MFTS-Symposiums 2022 lag auf dem kooperativen Management multimodalen Verkehrs und spiegelte die Vision der Professur wider, eine international anerkannte Gruppe in der ITS-Forschung und -Ausbildung mit dem Ziel der Optimierung des Betriebs multimodaler Transportsysteme zu sein. In 14 MFTS-Sitzungen wurden aktuelle Themen aus den Bereichen Nachfrage- und Verkehrsmanagement, Verkehrssteuerung im konventionellen, vernetzten und automatisierten Verkehr, vernetzte und autonome Fahrzeuge, Verkehrsflussmodellierung und -simulation, neue und geteilte Mobilitätssysteme, Digitalisierung sowie Nutzerverhalten und Sicherheit diskutiert. Darüber hinaus wurden Sondersitzungen organisiert, beispielsweise zu „Menschlichen Aspekten bei der Verkehrsmodellierung und -simulation“ und „Lektionen aus der Covid-19-Pandemie“, deren Beschreibungen und Analysen ebenfalls in diesen Tagungsband einfließen.:1 Connected and Automated Vehicles 1.1 Traffic-based Control of Truck Platoons on Freeways 1.2 A Lateral Positioning Strategy for Connected and Automated Vehicles in Lane-free Traffic 1.3 Simulation Methods for Mixed Legacy-Autonomous Mainline Train Operations 1.4 Can Dedicated Lanes for Automated Vehicles on Urban Roads Improve Traffic Efficiency? 1.5 GLOSA System with Uncertain Green and Red Signal Phases 2 New Mobility Systems 2.1 A New Model for Electric Vehicle Mobility and Energy Consumption in Urban Traffic Networks 2.2 Shared Autonomous Vehicles Implementation for a Disrupted Public Transport Network 3 Traffic Flow and Simulation 3.1 Multi-vehicle Stochastic Fundamental Diagram Consistent with Transportations Systems Theory 3.2 A RoundD-like Roundabout Scenario in CARLA Simulator 3.3 Multimodal Performance Evaluation of Urban Traffic Control: A Microscopic Simulation Study 3.4 A MILP Framework to Solve the Sustainable System Optimum with Link MFD Functions 3.5 On How Traffic Signals Impact the Fundamental Diagrams of Urban Roads 4 Traffic Control in Conventional Traffic 4.1 Data-driven Methods for Identifying Travel Conditions Based on Traffic and Weather Characteristics 4.2 AI-based Multi-class Traffic Model Oriented to Freeway Traffic Control 4.3 Exploiting Deep Learning and Traffic Models for Freeway Traffic Estimation 4.4 Automatic Design of Optimal Actuated Traffic Signal Control with Transit Signal Priority 4.5 A Deep Reinforcement Learning Approach for Dynamic Traffic Light Control with Transit Signal Priority 4.6 Towards Efficient Incident Detection in Real-time Traffic Management 4.7 Dynamic Cycle Time in Traffic Signal of Cyclic Max-Pressure Control 5 Traffic Control with Autonomous Vehicles 5.1 Distributed Ordering and Optimization for Intersection Management with Connected and Automated Vehicles 5.2 Prioritization of an Automated Shuttle for V2X Public Transport at a Signalized Intersection – a Real-life Demonstration 6 User Behaviour and Safety 6.1 Local Traffic Safety Analyzer (LTSA) - Improved Road Safety and Optimized Signal Control for Future Urban Intersections 7 Demand and Traffic Management 7.1 A Stochastic Programming Method for OD Estimation Using LBSN Check-in Data 7.2 Delineation of Traffic Analysis Zone for Public Transportation OD Matrix Estimation Based on Socio-spatial Practices 8 Workshops 8.1 How to Integrate Human Aspects Into Engineering Science of Transport and Traffic? - a Workshop Report about Discussions on Social Contextualization of Mobility 8.2 Learning from Covid: How Can we Predict Mobility Behaviour in the Face of Disruptive Events? – How to Investigate the Mobility of the Future

lt has been shown that engagement in secondary tasks may contribute to cyclists crash risk [1 ], meditated by cycling errors or risky behaviors. For influences on secondary task: engagement, it is generally found that phone use is negatively correlated with age. In most studies, males are more found engaged in phone tasks than females. lt was also found that users of a bicycle-sharing program more often to wear headphones and engage in more unsafe behavior. The use of safety gear (e.g., wearing a helmet, using reflectors) is often negatively correlated with distracted cycling. Also, cyclists engaged in a secondary task exhibit other risky behaviors more often [2]. The present study's first aim was to get (an updated) estimate of the observable frequency of different secondary tasks, use of additional safety equipment, and rule violations while riding bicycles and e-scooters in Germany. The second aim was to examine possible differences in secondary task: engagement, use of additional safety equipment, and rule violations between different types of users of the cycling infrastructure, i.e., riders of conventional bikes, e-bikes, scooters, and e-scooters. A third aim was to explore whether riders' secondary task engagement is related to active safety precautions (e.g., wearing a helmet), traffic rule violations, and at-fault conflicts and if there are rider profiles regarding safety-related behaviors. As the study is explorative, no hypotheses were formulated. [From: Introduction]

Kollaborativ konsumtion och bildelningstjänster är två fenomen som under de senaste åren blivit allt mer populära som ett sätt att bemöta hållbarhetskrisen. Bildelningstjänster är en form av kollaborativ konsumtion och är ofta drivna av kommersiella krafter. Syftet med tjänsterna är att erbjuda kunder moderna och hållbarhetsdrivna lösningar som ett alternativ till det privata bilägandet. I användandet av bildelningstjänster uppstår interaktioner mellan olika aktörer, mänskliga såväl som icke-mänskliga, både direkt- och indirekt. I användningen av bildelningstjänster och i dessa interaktioner, skapas en upplevelse för användarna. Genom en enkät och nio semistrukturerade intervjuer med användare av bildelningstjänster, studerar vi i denna studie, dessa upplevelser. Användarupplevelsemål och delade användarupplevelser, samt aktör-nätverksteori används som teoretiska ramverk för att analysera och diskutera den insamlade datan. I denna studie drar vi slutsatsen att användandet av bildelningstjänster inte enbart handlar om användarens individuella upplevelse av att använda bilen och mobilapplikationen. Användandet av bildelningstjänster består av flera samverkande faktorer som påverkarvarandra och som tillsammans påverkar användarupplevelsen. Slutligen ger studien ytterligare insikter i hur aktörer påverkar förarens användarupplevelse av bildelningstjänster. Med kunskapen om hur förarens upplevelse, i användandet av bildelningstjänster, påverkas av både mänskliga och icke-mänskliga aktörer. Dessa aktörer utgörs för omfånget av denna studie den mobila applikationen, bilen, kundtjänsten, den tidigare föraren och passagerarna. / Collaborative consumption, shared mobility, and car sharing services are three modern phenomena that in recent years have become a popular way to respond to the sustainability crisis. Carsharing services are a subcategory of collaborative consumption and are often driven by commercial forces. The aim of the services is to offer modern and sustainably-driven solutions to users as an alternative to private car ownership. In the use of carsharing services, an interaction occurs between different actors, human as well as non-human actors, both direct- and indirect. These interactions generate a user experience which this thesis aims to study through a survey and nine semistructured interviews with users of carsharing services. User experience goals, shared user experience, as well as Actor-network theory, is used as theoretical frameworks to analyze and discuss the collected data. Through this study, we conclude that the act of using car sharing services isn’t solely an individual experience between the users and the artifacts such as the car or the mobile application. Instead, the use of carsharing services often consists of several collaborating actors who influence each other and together affect the user experience. Lastly, the study contributes further insights into how actors affect the driver's user experience of carsharing services. With the knowledge of how the driver's experiences in the use of carsharing services are affected by both human and non-human actors. These actors consist of the mobile application, the car, previous users, customer service, and passengers.