Vinson & Elkins

Abstract In this paper, we prove in a first step for a smooth and elliptic anisotropy existence of an expanding regular network under anisotropic curvature flow with initial value given by three different half-lines starting in the same point. To achieve this, we adapt an analogous result from [O. C. Schnürer and F. Schulze, Self-similarly expanding networks to curve shortening flow, Ann. Sc. Norm. Super. Pisa Cl. Sci. (5) 6 (2007), 4, 511–528] in the isotropic case. In a second step, we extend the existence result with similar methods to the situation where the initial value consists of four different half-lines starting from the same point.

This paper introduces a nonlinear state-space model for a Dynamic Wireless Power Transfer System (DWPT). DWPT enables the continuous delivery of power to an electric vehicle while it moves along the road, allowing long-haul vehicles to operate with a relatively small battery. The system comprises primary side coils, which are supplied by DC/AC converters. These coils transmit power through induction to an electric vehicle. Within the vehicle (secondary side), a power receiver coil is connected to a full bridge diode rectifier, followed by the standard electric vehicle system. In the second step, the paper presents the design of a control system that ensures the seamless transfer of power to the vehicle as it moves along the road. The chosen controller is an Extremum Seeking algorithm, capable of implementation in high-speed systems compatible with real-time control for fast-moving vehicles. The following step involves conducting test-bed experiments using the designed controller to verify the alignment of the proposed mathematical model with the real system. Furthermore, the controller achieves maximum power transfer and maintains power and voltage across the load during transient states. The proposed model effectively captures the relevant dynamics and is well-suited for control design. Additionally, it offers faster simulation times compared to the full electrical model. Due to its good fit with experimental results, the model can be utilized for sizing, design, and tuning of both the system and control algorithms. This is especially valuable before conducting more detailed simulations on the electrical model and, eventually, test-bed experiments and real-life deployment.

With the advent of Autonomous Vehicles (AV) technology, extensive research around the design of on-demand mobility systems powered by such vehicles is performed. An important part of these studies consists in the evaluation of the economic impact of such systems for involved stakeholders. In this work, a cost–benefit analysis (CBA) is applied to the introduction of AV services in Paris-Saclay, an intercommunity, south of Paris, simulated through MATSim, an agent-based model capable of capturing complex travel behaviors and dynamic traffic interactions. AVs would be implemented as a feeder service, first- and last-mile service to public transit, allowing intermodal trips for travelers. The system is designed to target the challenges of public transport accessibility in periurban areas and high private car use, which the AV feeder service is designed to mitigate. To our knowledge, this study is one of the first CBA analyses of an intermodal AV system relying on an agent-based simulation. The introduction of AV in a periurban environment would generate more pressure on the road network (0.8% to 1.7% increase in VKT for all modes, and significant congestion around train stations) but would improve traveler utilities. The utility gains from the new AV users benefiting from a more comfortable mode offsets the longer travel times from private car users. A Stop-Based routing service generates less congestion than a Door-to-Door routing service, but the access/egress time counterbalances this gain. Finally, in a periurban environment where on-demand AV feeder service would be added to reduce the access and egress cost of public transit, the social impact would be nuanced for travelers (over 99% of gains captured by the 10% of most benefiting agents), but externality would increase. This would benefit some travelers but would also involve additional congestion. In that case, a Stop-Based routing on a constrained network (e.g., existing bus network) significantly improves economic viability and reduces infrastructure costs and would be less impacting than a Door-to-Door service.

The EU-funded Horizon 2020 5GMED project aims to promote Cooperative Intelligent Transportation Systems (CITS) in Europe by deploying Cooperative, Connected, and Automated Mobility (CCAM) services across international borders. In this context, this paper presents a 5G-based road traffic safety & management service based on the development of multiple actors and components capable of assessing the traffic status and providing the proper information to Connected Vehicles (CVs) through 5G and Vehicle-to-Everything (V2X) communication technologies. Performance evaluation has been carried out through real-world experiments and trials conducted along the 5GMED cross-border corridor (CBC) between Spain and France, leading to interesting findings and lessons learned presented in the conclusion of this paper.

Vehicle-to-Infrastructure (V2I) cooperation has emerged as a fundamental technology to overcome the limitations of the individual ego-vehicle perception. Onboard perception is limited by the lack of information for understanding the environment, the lack of anticipation, the drop of performance due to occlusions and the physical limitations of embedded sensors. The perception of V2I in a cooperative manner improves the perception range of the ego vehicle by receiving information from the infrastructure that has another point of view, mounted with sensors, such as camera and LiDAR. This technical paper presents a perception pipeline developed for the infrastructure based on images with multiple viewpoints. It is designed to be scalable and has five main components: the image acquisition for the modification of camera settings and to get the pixel data, the object detection for fast and accurate detection of four wheels, two wheels and pedestrians, the data fusion module for robust fusion of the 2D bounding boxes from multiple viewpoints, the object tracking to get the history of movement for each object over time and the generation of perception message for V2I communication. The infrastructure-based solution has been implemented and demonstrated in real-world scenarios, including two different intersections with up to six mounted cameras to cover an extended area. The qualitative results show that the detected objects have high accuracy with similar performances between two different environments, which proves the scalability of the solution. With a not optimized setup for these first deployments, we observe for the whole pipeline an execution time between 226ms and 256ms depending on the number of objects to be fused in the map based on the processing of six cameras.