Towards a better implementation of accessibility indicators in land use and transport planning practice
Bibliographic record
Abstract
In order to address the shortcomings of mobility-centered transport planning, planning for accessibility is increasingly considered as an essential complementary approach. This approach aims to provide reasonable access to destinations (employment centers, amenities, social and health services, etc.) to the entire population instead of prioritizing the optimization of travel times. Although a large body of literature has explored how to conceptualize and measure accessibility, research on how to incorporate accessibility in transport planning is scarce. Knowing that accessibility is currently marginalized in transport planning, the overarching goal of this dissertation is to contribute to the implementation of accessibility measures in land use and transport planning practice, by answering the following research question: How can accessibility measures be incorporated into current land use and transport planning practice in order to improve our understanding of the performance of land use and transport systems?To answer this question, the following objectives will be pursued: 1. To determine how accessibility is used in land use and transport planning practice; 2. To identify appropriate measures of accessibility to be used in land use and transport planning practice; 3. To generate measures of accessibility in a data-challenging context in collaboration with local transport planners. To reach these objectives, this dissertation follows a manuscript-based approach, with four studies building on one another. Collectively, these manuscripts address both the planning and research realms of transport planning through a multifaceted approach.Through an analysis of 32 metropolitan transport plans around the world, the first study reveals that, while the concept of accessibility is considered in most planning documents, it is rarely translated into goals and indicators that reflect the ease of reaching destinations. The findings of the first study are strengthened by a second study surveying 343 practitioners about accessibility. The results of the study demonstrate that most practitioners, although aware of the concept of accessibility, do not consider the ease of reaching destinations in their work. In addition, the results identify two main barriers to the implementation of accessibility indicators: lack of knowledge and lack of data. In light of the knowledge and data barriers, the third study assesses the usability of various accessibility measures from a planning perspective. Three measures of accessibility to jobs by public transport in the Greater Toronto and Hamilton Region are generated and assessed through a mode share regression model. The study concludes that the simplest measure – the number of jobs that can be reached within 45 minutes of travel at 8 am – is the most adequate to assess the performance of land use and transport systems at the regional level. Using the measure identified in the above study, the last study conducts an equity assessment of public transport services in four large metropolitan areas in Brazil. The study, led in a data-challenging context, proposes a methodology that can be easily applied by any transport agencies and illustrates the relevance of the accessibility indicators to inform planning processes. Conducted in collaboration with local transport planners, the study also contributes to an enhanced collaboration between research and planning. Overall, this dissertation presents a set of complementary studies to bridge the gap between research and practice and better understand how accessibility indicators can be incorporated into current land use and transport planning practice. This dissertation demonstrates the importance of carefully and critically thinking about how to include accessibility indicators in practice, be it with respect to how it is defined or how it is measured, and about how research can better contribute to the current challenges faced by professionals.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.128 | 0.243 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.010 | 0.016 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.021 | 0.022 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".