Behavioral Models and Characteristics of Bicycle-Automobile Mixed-Traffic: Planning and Engineering Implications

Taylor, Dean Brantley; Mahmassani, Hani S. · 1998 · ROSA P / University of Texas at Austin. Center for Transportation Research

archive: archived pipeline: cataloged verified

Get this paper ↗ (full text — opens at the source; we link to it, we don't host it)

Summary

This 1998 technical report by Dean Brantley Taylor and Hani S. Mahmassani addresses the lack of fundamental understanding regarding bicycle-automobile mixed-traffic, a gap identified as a barrier to improving cyclist safety and infrastructure design. Motivated by the need to mitigate traffic hazards and support the goals of the Intermodal Surface Transportation Efficiency Act (ISTEA), the study focuses on three core areas: gap acceptance behavior at intersections, bicyclist behavior at the onset of yellow traffic signals, and the coordination of traffic signals for simultaneous bicycle and automobile progression. The research aims to provide engineers with behavioral models and insights to improve facility design and operations. The methodology combines roadside observational data with theoretical modeling. For gap acceptance, the authors collected data at three sites in Austin, Texas, to develop discrete choice (probit) models for both motorists and cyclists. These models analyzed decisions based on vehicle type, lane position, and maneuver type. For signal timing, the study employed a deterministic model based on kinematic relations to compute adequate clearance intervals, using measured data on bicycle speed, acceleration, and deceleration. Additionally, a probabilistic "probability of stopping" model was calibrated from observations of actual bicyclist behavior at the onset of yellow signals. Finally, the authors developed a conceptual framework for multimodal progression, utilizing multiobjective formulation techniques to balance competing design goals for bicycles and automobiles along signalized streets. Key findings reveal that both cyclists and motorists require longer gaps when the closing vehicle is large (e.g., a bus) and accept shorter gaps when the closing vehicle is a bicycle, compared to passenger cars. Cyclists making right-turns from minor streets were found to accept relatively short gaps. Regarding signal timing, the deterministic and probabilistic models demonstrated that bicycles often require longer clearance intervals than automobiles, particularly at wide intersections, due to differences in deceleration capabilities and perception-reaction times. The study showed that standard automobile clearance intervals may be insufficient for cyclists, increasing crash risk. In the progression analysis, the authors identified that traditional automobile-focused progression often creates hazards for cyclists, such as forcing them to arrive at intersections near the onset of yellow. They proposed techniques, such as varying progression speeds and allocating excess green time, to create safer multimodal progression designs. The significance of this work lies in its provision of a rigorous, evidence-based foundation for bicycle-automobile mixed-traffic engineering. By quantifying behavioral differences and kinematic requirements, the report offers specific tools for designing safer intersections and signal timings. The proposed multiobjective framework allows planners to formally address the competing objectives of bicycle and automobile efficiency, moving beyond automobile-centric designs. These contributions support the development of infrastructure that reduces bicycle-automobile crashes and encourages higher modal shares for bicycling by addressing safety concerns.

Key finding

Both cyclists and motorists require a longer gap when the gap is closed by a large vehicle and accept a shorter gap when closed by a bicycle relative to a passenger car, while bicyclists may require longer clearance intervals than automobiles at sufficiently wide intersections.

Methodology

field_study

Provenance

The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed. Discovered via bulk_ingest_rosap on 2026-05-23 (6 acquisition events logged).

Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.

Topics

Ranked by relevance to this paper. Hover a topic for its definition.

• cyclist safety
• gap acceptance