Assessment of influential factors on motorcyclist' Safety on rural roads.

Abstract

This doctoral dissertation investigates motorcyclist safety on rural roads by integrating multiple data sources and analytical methods. It comprises six empirical chapters addressing different dimensions of motorcycle risk. The introductory chapter sets up the methodology and presents the problem statement. Chapter 2 analyzes single-vehicle crashes using police crash data, identifying key predictors of severe outcomes, including crash type and characteristics, pavement condition, and rider-related factors. Chapter 3 evaluates the safety performance of various roadside barrier types, highlighting the necessity for motorcyclist-friendly solutions. In Chapter 4, speeding behavior is examined through models that incorporate temporal, infrastructural, and locational factors, revealing a higher likelihood of speeding in specific road environments and at certain times. Chapter 5 develops an updated Motorcycle Rider Behavior Questionnaire (MRBQ) based on the sample of Croatian riders. In Chapter 6, MRBQ-based models confirm the predictive value of behavior patterns and perceived infrastructure flaws for crash involvement, near-crashes, and traffic fines. Chapter 7 utilizes smartphone-based naturalistic riding data, demonstrating that aggressive acceleration and higher over-limit speeds predict increased speeding duration, while motorway riding has a mitigating effect. The findings support all three main hypotheses and emphasize the role of contextual, behavioral, and infrastructural influences. The final part of the dissertation concludes with targeted recommendations for rural safety strategies. It outlines future research directions, including geospatial analysis, cross-national comparisons, and the application of intelligent safety systems for motorcyclists.