Drivers’ Braking Behaviors in Different Motion Patterns of Vehicle-Bicycle Conflicts
Bibliographic record
Abstract
Bicycling is one of the popular modes of transportation, but bicyclists are easily involved in injuries or fatalities in vehicle-bicycle (V-B) accidents. The AEB (Autonomous Emergency Braking) systems have been developed to avoid collisions, but their adaptiveness needs to be further improved under different motion patterns of V-B conflicts. This paper analyzes drivers’ braking behaviors in different motion patterns of V-B conflicts to improve the performance of Bicyclist-AEB systems. For safety and data reliability, a driving simulator was used to reconstruct two typical conflict types, i.e., SCR (a bicycle crossing the road from right in front of a straight going car) and SSR (a bicycle cut-in from right in front of a straight going car). Either conflict contained various parameterized motion patterns, which were characterized by a combination of parameters: <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M1"><mml:mrow><mml:msub><mml:mrow><mml:mi mathvariant="normal">V</mml:mi></mml:mrow><mml:mrow><mml:mi>c</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math> (car velocity), TTC (time-to-collision), <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M2"><mml:mrow><mml:msub><mml:mrow><mml:mi mathvariant="normal">V</mml:mi></mml:mrow><mml:mrow><mml:mi>b</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math> (bicycle velocity), and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M3"><mml:mrow><mml:msub><mml:mrow><mml:mi mathvariant="normal">D</mml:mi></mml:mrow><mml:mrow><mml:mi>l</mml:mi><mml:mi>a</mml:mi><mml:mi>t</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math> (lateral distance between the car and the bicycle) or <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M4"><mml:mrow><mml:msub><mml:mrow><mml:mi mathvariant="normal">V</mml:mi></mml:mrow><mml:mrow><mml:mi>l</mml:mi><mml:mi>a</mml:mi><mml:mi>t</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math> (maximum lateral velocity of the bicycle). Some 26 licensed drivers participated in an orthogonal experiment for braking behavior analysis. Results revealed that drivers brake immediately when V-B conflicts occur; hence the BRT (brake reaction time) is independent of any motion pattern parameters. This was further verified by another orthogonal experiment with 10 participants using the eye tracking device. BRT in SSR is longer than that in SCR due to the less perceptible risk and drivers’ lower expectation of a collision. The braking intensity and brake Pedal Speed are higher in short-TTC patterns in both conflict types. Therefore, TTC is not a proper activation threshold but a reasonable indicator of braking intensity and Pedal Speed for driver-adaptive AEB systems. By applying the findings in the Bicyclist-AEB, the adaptiveness and acceptability of Bicyclist-AEB systems can be improved.
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.
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".