For thousands of years, people have been innovating new technologies to make their travel faster, the latest of which is GPS technology that is used by millions of drivers every day. The routes recommended by a GPS device are computed by path planning algorithms (e.g., fastest path algorithm), which aim to minimize a certain objective function (e.g., travel time) under the current traffic condition. When the objective is to arrive the destination as early as possible, waiting during travel is not an option as it will only increase the total travel time due to the First-In-First-Out property of most road networks. However, some businesses such as logistics companies are more interested in optimizing the actual on-road time of their vehicles (i.e., while the engine is running) since it is directly related to the operational cost. At the same time, the drivers’ trajectories, which can reveal the traffic conditions on the roads, are also collected by various service providers. Compared to the existing speed profile generation methods, which mainly rely on traffic monitor systems, the trajectory-based method can cover a much larger space and is much cheaper and flexible to obtain. This paper proposes a system, which has an online component and an offline component, to solve the minimal on-road time problem using the trajectories. The online query answering component studies how parking facilities along the route can be leveraged to avoid predicted traffic jam and eventually reduce the drivers’ on-road time, while the offline component solves how to generate speed profiles of a road network from historical trajectories. The challenging part of the routing problem of the online component lies in the computational complexity when determining if it is beneficial to wait on specific parking places and the time of waiting to maximize the benefit. To cope with this challenging problem, we propose two efficient algorithms using minimum on-road travel cost function to answer the query. We further introduce several approximation methods to speed up the query answering, with an error bound guaranteed. The offline speed profile generation component makes use of historical trajectories to provide the traveling time for the online component. Extensive experiments show that our method is more efficient and accurate than baseline approaches extended from the existing path planning algorithms, and our speed profile is accurate and space efficient.
The VLDB Journal – Springer Journals
Published: Mar 21, 2018
It’s your single place to instantly
discover and read the research
that matters to you.
Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.
All for just $49/month
Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly
Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.
Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.
Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.
All the latest content is available, no embargo periods.
“Hi guys, I cannot tell you how much I love this resource. Incredible. I really believe you've hit the nail on the head with this site in regards to solving the research-purchase issue.”Daniel C.
“Whoa! It’s like Spotify but for academic articles.”@Phil_Robichaud
“I must say, @deepdyve is a fabulous solution to the independent researcher's problem of #access to #information.”@deepthiw
“My last article couldn't be possible without the platform @deepdyve that makes journal papers cheaper.”@JoseServera