Behavioral adaptation of drivers when driving among automated vehicles
DOI: 10.1108/jicv-07-2022-0031
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Summary
This study investigates the structural response of thin flexible pavements subjected to Long Heavy Vehicles (LHVs) under varying seasonal conditions. The research was motivated by Sweden’s increase in allowable gross vehicle weight to 74 tons on certain road networks, a change expected to alter pavement degradation rates. While LHVs offer transportation efficiency benefits, their impact on pavement construction and maintenance costs, particularly on low-volume roads with thin asphalt layers, requires better understanding. The study aims to validate numerical models for a new Mechanistic-Empirical (M-E) pavement design tool by comparing in-situ measurements with theoretical calculations. The researchers instrumented two thin flexible pavement sections in northern Sweden (Lv373 and Lv515) with built-in sensors, including asphalt strain gauges, soil pressure cells, and strain measuring units. Climate sensors monitored temperature and moisture throughout a 12-month period. Four measurement campaigns were conducted during different seasons to capture variations such as spring thaw and winter freezing. Falling Weight Deflectometer (FWD) tests were performed to backcalculate layer stiffness values, which were adjusted for temperature and moisture using established models. The structural response was then measured as three different LHV configurations passed over the sensors at normal speeds. These measured responses were compared against numerical calculations based on Multilayer Elastic Theory (MLET). The results demonstrated a generally good agreement between the measured in-situ stresses and strains and the MLET-calculated values, evidenced by high coefficients of determination ($R^2$). The study successfully accounted for seasonal variations by adjusting asphalt stiffness based on temperature and granular layer stiffness based on moisture content. During frozen periods, the stiffness of frozen layers was set to 2800 MPa. The backcalculation procedure, which minimized the root mean square error between measured and calculated deflection bowls and sensor responses, yielded consistent stiffness values across the different campaigns. The comparison highlighted that MLET can accurately predict pavement response when layer properties are properly adjusted for ambient climate conditions. The significance of this work lies in its validation of MLET for predicting the structural response of thin pavements under heavy loading and varying environmental conditions. By confirming that numerical models can replicate in-situ behavior when seasonal factors are integrated, the study supports the development of more accurate M-E pavement design tools. This improved predictive capability is essential for assessing the long-term performance and maintenance costs of road networks accommodating LHVs, ensuring that infrastructure investments are based on reliable mechanistic data rather than empirical assumptions alone.
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | Crossref | — | — | 1 | 2026-06-20 |
| archive | success | openalex | — | — | 5 | 2026-06-26 |
| extract | success | cached | — | — | 2 | 2026-06-26 |
| clean | success | clean | — | — | 1 | 2026-06-20 |
| chunk | success | chunk | — | — | 1 | 2026-06-20 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-06-20 |
| promote | success | — | — | — | 1 | 2026-06-20 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 1 | 2026-06-26 |
| tag | success | vector_similarity | — | — | 6 | 2026-06-20 |
| verify | partial | — | — | — | 1 | 2026-06-26 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-26; verification: verified_with_issues.
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- Empirical Findings: behavioral performance data, observational prevalence
- Theoretical Contribution: theory or model