Quantifying and Mitigating the Impact of Vehicular Routing on the Urban Environment
Bibliographic record
Abstract
Urbanization pressures cities to efficiently accommodate the increasing demand for mobility, making traffic optimization challenging due to the complex interplay between road networks and traffic dynamics, as drivers' routing choices significantly influence one another. City-related services, such as navigation services (e.g., TomTom) and mobility policies (e.g., road closures), impact traffic patterns and emissions. Navigation services can unintentionally increase emissions when many vehicles converge on the same routes, while mobility policies may have counterintuitive effects on traffic. We propose a simulation framework to assess the impact of road closure policies and navigation services on the urban environment. We use this framework and find that targeted road closures in Milan can reduce emissions by up to 10%, while others can increase emissions by nearly 50%. Then, we examine navigation services' impact on vehicular traffic and CO2 emissions, finding that they reduce emissions at low traffic loads. However, at high traffic loads and penetration rates, they cause conformist behavior, leading to inefficiencies and potentially higher emissions. To mitigate the conformist behavior induced by navigation services and reduce CO2 emissions, we propose three solutions: (i) an individualistic approach using existing Alternative Routing (AR) algorithms, (ii) Metis, a coordinated solution that coordinates drivers and dynamically estimates traffic to diversify routes, and (iii) Polaris, an individual AR algorithm which considers road popularity to optimize traffic distribution. Motivated by the varying effectiveness of AR solutions across cities, we study cities' route diversification, defining shortest path instability and introducing diverCity, a metric to assess a city's propensity towards route diversity. Analysis shows that diverCity benefits from extensive road networks, leading to less congestion. We also address the impact of mobility attractors on diverCity and propose mitigation strategies. This thesis comprehensively studies vehicular traffic dynamics, offering a simulation framework to evaluate the environmental impact of mobility policies and navigation services. In addition, it presents solutions to mitigate negative impacts and proposes metrics to quantify a city's potential to offer route diversity.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".