Mobility on Demand in the United States

The growth of shared mobility services and enabling technologies, such as smartphone apps, is contributing to the commodification and aggregation of transportation services. This chapter reviews terms and definitions related to Mobility on Demand (MOD) and Mobility as a Service (MaaS), the mobility marketplace, stakeholders, and enablers. This chapter also reviews the U.S. Department of Transportation’s MOD Sandbox Program, including common opportunities and challenges, partnerships, and case studies for employing on-demand mobility pilots and programs. The chapter concludes with a discussion of vehicle automation and on-demand mobility including pilot projects and the potential transformative impacts of shared automated vehicles on parking, land use, and the built environment

Agent-Based Team Aiding in a Time Critical Task

In this paper we evaluate the effectiveness of agent-based aiding in support of a time-critical team-planning task for teams of both humans and heterogeneous software agents. The team task consists of human subjects playing the role of military commanders and cooperatively planning to move their respective units to a common rendezvous point, given time and resource constraints. The objective of the experiment was to compare the effectiveness of agent-based aiding for individual and team tasks as opposed to the baseline condition of manual route planning. There were two experimental conditions: the Aided condition, where a Route Planning Agent (RPA) finds a least cost plan between the start and rendezvous points for a given composition of force units; and the Baseline condition, where the commanders determine initial routes manually, and receive basic feedback about the route. We demonstrate that the Aided condition provides significantly better assistance for individual route planning and team-based re-planning

Current state of the art and use case description on geofencing for traffic management

This report is a result of a literature review and document gathering focused on geofence use cases specific for road traffic management. It presents geofence use cases that are trialled or to be trialled, implemented use cases, as well as conceptual and potential future use cases, showing for which type of transport they are used and how geofence zones are applied or to be applied. The report was conducted in the project GeoSence – Geofencing strategies for implementation in urban traffic management and planning. It is a Joint programme initiative (JPI) Urban Europe project funded by European Union´s Horizon 2020, under ERA-NET Cofund Urban Accessibility and Connectivity and gather project partners from Germany, Norway, Sweden and UK. The goal is to present the current state of art, and describe use cases, based on the working definition of geofencing in the project, where geofence is defined as a virtual geographically located boundary, statically or dynamically defined. The study shows that for implemented and real-traffic trial use case, geofencing has been applied within private car transport, shared micro-mobility, freight and logistics, public bus transportation and ridesourcing. For the future use cases, geofencing has been tested or conceptually developed also for automated vehicles and shared automated mobility, among others. The report summarises main use cases and find them to answering to especially four challenges in traffic management: safety, environment, efficiency, and tracking and data collection. Some of the use cases however answer to several of these challenges, such as differentiated road charging, and the use cases in micro-mobility. Further, the system and functionality of the trialled and/or implemented use cases, show different types of regulation geofence use cases can be used for, from informing, assisting, full enforcement, incentivising and penalisation. Guidelines and recommendations so far form national authorities show that the existence of joint regulation or guidelines for the use of geofencing for different use cases is low – with some exceptions. Digital representation of traffic regulation will be crucial for enabling geofencing