An official website of the United States government
California has set a goal for all drayage trucks operating in the state to be zero-emitting by 2035. In order to achieve this goal, drayage operators would need to transition 100% of their Heets to zero-emission vehicles such as battery electric trucks (BETs). This article presents an intelligently controlled charging model for BETs that minimizes charging costs while optimizing subsequent tour completion. To develop this model, real-world activity data from a drayage truck Heet operating in Southern California was combined with a two-stage clustering technique to identify trip and tour patterns. The energy consumption for each trip and tour was then simulated for BETs with a battery capacity of 565 kWh using a 150 kW charging power level. Home base charging load profiles were generated using the proposed charging model, subject to constraints of the energy needed to complete the next subsequent tour and Time-of-Use energy cost rates. A sensitivity analysis evaluated three scenarios: a passive scenario with a 5% state-of-charge (SOC) constraint after completing the subsequent tour, an average scenario with a 50% SOC constraint, and an aggressive scenario with an 80% SOC constraint. Results indicated that the 80% SOC constraint scenario achieved the lowest charging cost. However, it also yielded the lowest tour completion rate (51%). In contrast, the 5% SOC constraint scenario registered the highest tour completion rate. These results revealed that 96% of the tours could be successfully completed using the intelligently controlled charging model. The remaining tours were infeasible, indicating that the available time at the home base was inadequate for charging the necessary energy for the next tour. In terms of total costs, the scenario with a 5% SOC constraint resulted in an annual cost of approximately $40,000, whereas the 80% SOC scenario nearly doubled that amount.
more »
« less
A privacy design problem for sharing transport service tour data
Despite the increasing relevance of private transport operators as Mobility-as-a-Service in the success of smart cities, desire for privacy in data sharing limits collaborations with public agencies. We propose an original model that circumvents this limitation, by designing a diffusion of the data - in this case, service tour data - such that passenger travel times remain reliable to the recipient agency. The Tour Sharing Privacy Design Problem is formulated as a nonlinear programming problem that maximizes entropy. We investigate properties of the model and iterative tour generation algorithms, and conduct a series of numerical experiments on an instance that has 90 feasible tours. The experimental results show that a k-best shortest tour approach of generating tours iteratively initially increases the gap to a lower bound before decreasing toward a final constraint gap. The model is shown to recognize the trade-offs between more reliability in data and more anonymity. Comparisons between the true and diffused travel times and OD matrices are made.
more »
« less
- Award ID(s):
- 1652735
- PAR ID:
- 10082681
- Date Published:
- Journal Name:
- 2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC)
- Page Range / eLocation ID:
- 1 to 6
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
null (Ed.)In 2018, the Center for Renewable Energy Advanced Technological Education (CREATE) received funding from the National Science Foundation to administer an Energy Storage Project with the overarching goal of advancing the renewable energy sector by facilitating integration of energy storage technology into existing two-year college programs. The goals for this project included gathering expertise, conducting job task and curriculum gap analyses, producing instructional materials, implementing pilot energy storage courses, and providing professional development for college instructors. The project's initial task was to work with educators to gather knowledge and expertise around energy storage technologies and energy education. Widespread adoption of energy storage is only beginning in the U.S. and, subsequently, energy storage-related educational programs are few; conversely, energy storage education efforts have already been pioneered and established in Europe, most notably in Germany. As a result, CREATE leveraged its history of improving energy education through international cooperation and organized a study tour to Germany for nine renewable energy educators to examine innovations in renewable energy and energy storage and to research how these technologies are incorporated into German workforce preparation. In the planning and conducting international professional development opportunities for educators, two distinct challenges arise: that of ensuring academic rigor and of anchoring and capturing learning, especially given the additional cognitive load presented by being abroad. CREATE employs an evidence-based, international collaboration model - developed and improved over the course of two previous study tours - to meet these challenges. The learning plan consists of pre-travel online activities, knowledge capture and collaborative sharing during travel, and post travel reflection. These activities combine to support educators in gathering and preserving knowledge gains and to facilitate collaborative knowledge-building that leverages the expertise and skills of the participant cohort. While this paper presents the results of the CREATE professional development model, however the findings are not limited to energy storage or to the energy sector. Indeed, this analysis and the resulting set of recommended practices should be of interest to anyone interested in creating a meaningful educator professional development opportunity, especially if international travel is incorporated.more » « less
-
360-degree video based virtual tours are becoming more and more popular due to travel costs and restrictions. Existing solutions leverage teleport, 3D modeling or image morphing, but none of them offers satisfactory immersion and scalability. In this paper, we propose a morphing based ultra-sparse 360-degree camera virtual tourism solution. It uses a novel bus tour mode to improve immersion; besides, it uses a series of strategies to improve feature matching such that morphing works well for ultra-sparse (15 m apart) cameras and the system can be deployed on a large scale. The experimental results show that our work results in remarkably better feature matching and synthesized views.more » « less
-
In today’s world, people visit many attractive places. On such an occasion, It is of utmost importance to be accompanied by a tour guide, who is known to explain about the cultural and historical importance of places. Therefore, a human guide is necessary to provide tours for a group of visitors. However, Human tour guides might face tiredness, distraction, and the effects of repetitive tasks while providing tour service to visitors. Robots eliminate these problems and can provide tour consistently until it drains its battery. This experiment introduces a tour-guide robot that can navigate autonomously in a known map of a given place and at the same time interact with people. The environment is equipped with artificial landmarks. Each landmark provides information about that specific region. An Animated avatar is simulated on the screen. IBM Watson provides voice recognition and text-to-speech services for human-robot interaction. The experimental results show that the robot takes average time of 10000 seconds to provide a tour. TEB and DWA local planner are compared by allowing the robot to autonomously maneuver the environment for 9 trials which is tabulated in section V.more » « less
-
Immersive virtual tours based on 360-degree cameras, showing famous outdoor scenery, are becoming more and more desirable due to travel costs, pandemics and other constraints. To feel immersive, a user must receive the view accurately corresponding to her position and orientation in the virtual space when she moves inside, and this requires cameras’ orientations to be known. Outdoor tour contexts have numerous, ultra-sparse cameras deployed across a wide area, making camera pose estimation challenging. As a result, pose estimation techniques like SLAM, which require mobile or dense cameras, are not applicable. In this paper we present a novel strategy called 360ViewPET, which automatically estimates the relative poses of two stationary, ultra-sparse (15 meters apart) 360-degree cameras using one equirectangular image taken by each camera. Our experiments show that it achieves accurate pose estimation, with a mean error as low as 0.9 degreemore » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/ITSC.2017.8317692
