Topic
Fleet management
About: Fleet management is a research topic. Over the lifetime, 2505 publications have been published within this topic receiving 44745 citations. The topic is also known as: vehicle management.
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TL;DR: A novel methodology for predicting the spatial distribution of taxi-passengers for a short-term time horizon using streaming data and demonstrates that the proposed framework can provide effective insight into the spatiotemporal distribution of Taxi-passenger demand for a 30-min horizon.
Abstract: Informed driving is increasingly becoming a key feature for increasing the sustainability of taxi companies. The sensors that are installed in each vehicle are providing new opportunities for automatically discovering knowledge, which, in return, delivers information for real-time decision making. Intelligent transportation systems for taxi dispatching and for finding time-saving routes are already exploring these sensing data. This paper introduces a novel methodology for predicting the spatial distribution of taxi-passengers for a short-term time horizon using streaming data. First, the information was aggregated into a histogram time series. Then, three time-series forecasting techniques were combined to originate a prediction. Experimental tests were conducted using the online data that are transmitted by 441 vehicles of a fleet running in the city of Porto, Portugal. The results demonstrated that the proposed framework can provide effective insight into the spatiotemporal distribution of taxi-passenger demand for a 30-min horizon.
602 citations
TL;DR: An overview of emerging trends and challenges in the field of intelligent and autonomous, or self-driving, vehicles is provided.
Abstract: In this review, we provide an overview of emerging trends and challenges in the field of intelligent and autonomous, or self-driving, vehicles. Recent advances in the field of perception, planning,...
493 citations
TL;DR: This paper presents two mixed integer linear program formulations of a routing model that generalizes existing routing models in the literature and indicates that one of the formulations is very effective in obtaining high quality solutions to real life instances of the problem.
454 citations
Patent•
22 Feb 2001
TL;DR: In this paper, a commercial vehicle fleet management system which integrates a vehicle on-board computer, precise positioning system, and communication system to provide automated calculating and reporting of jurisdictional fuel taxes, road use taxes, vehicle registration fees, and the like.
Abstract: A commercial vehicle fleet management system which integrates a vehicle on-board computer, a precise positioning system, and communication system to provide automated calculating and reporting of jurisdictional fuel taxes, road use taxes, vehicle registration fees, and the like. In a further aspect, there is provided an online mobile communication system and a system for monitoring carrier vehicle efficiency and vehicle driver performance.
435 citations
TL;DR: In this article, the authors explore the management of a fleet of shared autonomous electric vehicles (SAEVs) in a regional, discrete-time, agent-based model, and examine the operation of SAEVs under various vehicle range and charging infrastructure scenarios in a gridded city modeled roughly after the densities of Austin, Texas.
Abstract: There are natural synergies between shared autonomous vehicle (AV) fleets and electric vehicle (EV) technology, since fleets of AVs resolve the practical limitations of today’s non-autonomous EVs, including traveler range anxiety, access to charging infrastructure, and charging time management. Fleet-managed AVs relieve such concerns, managing range and charging activities based on real-time trip demand and established charging-station locations, as demonstrated in this paper. This work explores the management of a fleet of shared autonomous electric vehicles (SAEVs) in a regional, discrete-time, agent-based model. The simulation examines the operation of SAEVs under various vehicle range and charging infrastructure scenarios in a gridded city modeled roughly after the densities of Austin, Texas. Results based on 2009 NHTS trip distance and time-of-day distributions indicate that fleet size is sensitive to battery recharge time and vehicle range, with each 80-mile range SAEV replacing 3.7 privately owned vehicles and each 200-mile range SAEV replacing 5.5 privately owned vehicles, under Level II (240-volt AC) charging. With Level III 480-volt DC fast-charging infrastructure in place, these ratios rise to 5.4 vehicles for the 80-mile range SAEV and 6.8 vehicles for the 200-mile range SAEV. SAEVs can serve 96–98% of trip requests with average wait times between 7 and 10 minutes per trip. However, due to the need to travel while “empty” for charging and passenger pick-up, SAEV fleets are predicted to generate an additional 7.1–14.0% of travel miles. Financial analysis suggests that the combined cost of charging infrastructure, vehicle capital and maintenance, electricity, insurance, and registration for a fleet of SAEVs ranges from $0.42 to $0.49 per occupied mile traveled, which implies SAEV service can be offered at the equivalent per-mile cost of private vehicle ownership for low-mileage households, and thus be competitive with current manually-driven carsharing services and significantly cheaper than on-demand driver-operated transportation services. When Austin-specific trip patterns (with more concentrated trip origins and destinations) are introduced in a final case study, the simulation predicts a decrease in fleet “empty” vehicle-miles (down to 3–4% of all SAEV travel) and average wait times (ranging from 2 to 4 minutes per trip), with each SAEV replacing 5–9 privately owned vehicles.
416 citations