Coordinated Autonomous Vehicle Parking for Vehicle-to-Grid Services: Formulation and Distributed Algorithm

Autonomous vehicles (AVs) will revolutionarize ground transport and take a substantial role in the future transportation system. Most AVs are likely to be electric vehicles (EVs) and they can participate in the vehicle-to-grid (V2G) system to support various V2G services. Although it is generally infeasible for EVs to dictate their routes, we can design AV travel plans to fulfill certain system-wide objectives. In this paper, we focus on the AVs looking for parking and study how they can be led to appropriate parking facilities to support V2G services. We formulate the Coordinated Parking Problem (CPP), which can be solved by a standard integer linear program solver but requires long computational time. To make it more practical, we develop a distributed algorithm to address CPP based on dual decomposition. We carry out a series of simulations to evaluate the proposed solution methods. Our results show that the distributed algorithm can produce nearly optimal solutions with substantially less computational time. A coarser time scale can improve computational time but degrade the solution quality resulting in possible infeasible solution. Even with communication loss, the distributed algorithm can still perform well and converge with only little degradation in speed.postprin

Business models and cost analysis of automated valet parking and shared autonomous vehicles assisted by internet of things

With the rapid development of autonomous vehicles, it is necessary to explore new business opportunities, especially under the assistance of internet of things, which accelerate the penetration in vehicle markets. Automated valet parking and shared autonomous vehicles will be the most active cases promoted by autonomous driving. In this paper, the business models of automated valet parking and shared autonomous vehicles were proposed, further, the cost structures of autonomous vehicles under two cases were investigated from points of car users and owners. In the business models, autonomous driving packages, internet of things devices, and service provider companies are considered as new stakeholders. The cost structure of automated valet parking users changes greatly, with the development of autonomous driving packages whose cost share decreases from ~60% to ~5%. The total cost of automated valet parking users is much higher than conventional parking before 2024. Additionally, the use of shared vehicles relieves financial burden, without trouble of periodical maintenance. For station-based and free-floating car sharing, the price drop of autonomous driving package brings about huge benefits for companies. Peer-to-peer car sharing business effectively decreases financial burden of car owners such that the decrease is less than 20% starting from 2017

Automation-driven transformation of road infrastructure: a multi-perspective case study

Automated driving is widely assumed to play a major role in future mobility. In this paper, we focus on “high driving automation” (SAE level 4) and analyze potentials in terms of more efficient traffic flows, travel times, and user benefits as well as potential impacts on urban neighborhoods and potentials for sustainable urban development. Along selected use cases of automated vehicles in the region of Karlsruhe, Germany, we show that at least moderate user benefits can be expected from travel time savings, with the extent depending on the defined operational design domain of the vehicles and the routes taken. With regard to residential development of urban neighborhoods, there are opportunities for repurposing public space. However, these are limited and require parallel regulatory measures to become effective