Traffic Aware Many-Objective Dynamic Route Planning
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We study 4-objective dynamic route planning based on real road network and real traffic data from Aarhus, Denmark. Our 4 objectives include total vehicular emission cost (TEC), travel time, number of turns, and distance. The first two objectives are time-dependent and traffic-dependent. The third objective is a novel objective for simpler routing and better user experience. The fourth objective is standard for all route planning problems. We provide a thorough explanation of how to design NSGA-II to solve the 4-objective dynamic route planning problem. Our experiments produce a diverse set of solutions for this problem and provide user the flexibility of selecting a path based on their preferences of the four objectives. Our work provides a good framework for many-objective dynamic route planning and can be extended to other techniques such as many-objective Particle Swarm Optimzation (PSO) and many-objective Ant Colony Optimization (ACO).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it