Accommodating More Users in Highway Electric Vehicle Charging through Coordinated Booking: A Market-Based Approach
Bibliographic record
Abstract
This paper presents a coordinated booking mechanism for highway electric vehicle charging management. The mechanism improves charging facility utilization and user satisfaction through coordinating users' charging schedules based on their travel time flexibility and required charging time for their trip. Given that users compete for limited charging resources to obtain their preferred schedules, we model them as self-interested agents who consider their flexibility as their private information and may be reluctant to reveal it to the scheduler. In order to compute high-quality schedules, we propose a market-based scheduling mechanism which motivates users to reveal their flexibility. This mechanism is implemented using an iterative bidding procedure which allows users to progressively reveal their feasible travel time windows as needed. The goal is to maximize the number of served users given limited charging capacity and users' travel time window constraints. Our computational study shows that the proposed booking mechanism achieves on average 90% efficiency compared with optimal solutions. We also observe that high efficiency solutions usually require more flexibility information to be revealed by the users.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".