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This study describes the development of macro-level (i.e., neighbourhood or traffic zone level) collision prediction models using data from 577 neighbourhoods across the Greater Vancouver Regional District. The objective is to provide a safety planning decision-support tool that facilitates a proactive approach to community planning which addresses road safety before problems emerge. The models are developed using the generalized linear regression modelling (GLM) technique assuming a negative binomial error structure. The resulting models relate traffic collisions to neighbourhood characteristics such as traffic volume, demographics, network shape, and transportation demand management. Several models are presented for total or severe collisions in rural or urban zones using measured and (or) modelled data. It is hoped that quantifying a predictive traffic safety – neighbourhood planning relationship will facilitate improved decisions by community planners and engineers and, ultimately, facilitate improved neighbourhood traffic safety for residents and other road users.Key words: neighbourhood safety, macro-level collision prediction models, road safety, safety planning, transportation demand management, sociodemographic, generalized linear regression modelling.

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The reactive use is described of 35 recently developed macrolevel collision prediction models (CPMs) to conduct a black spot study with data from 577 urban and rural neighborhoods across Greater Vancouver in British Columbia, Canada. The research objective was to investigate macrolevel CPM use in a traditional reactive safety application (macroreactive use): identification, diagnosis, and remedy of hazardous locations. The results suggested that macroreactive use has the potential to complement traditional road safety improvement programs. Several collision-prone zones were identified and ranked for diagnosis. Two zones were analyzed in detail and revealed several potential enhancements to conventional methods. If adopted for normal use by practitioners, macrolevel CPMs could facilitate improved decisions by community planners and engineers and ultimately could facilitate improved neighborhood road safety for residents and other road users.

Pedelecs, popular among elderly cyclists, are associated with a higher injury risk than conventional bicycles. About 17% of these injuries are due to falls while (dis)mounting. Using instrumented bicycles, this study aimed to identify factors contributing to the stability of self-chosen mounting methods in four user groups: 30-45 versus 65+ years of age and males versus females. Mounting stability on pedelecs was compared with that on conventional bicycles, in controlled experimental setting (task in a fenced off parking lot) but also in real traffic conditions (traffic light turns green). Two mounting phases were differentiated: phase 1 as the transition from 'earth bound' to 'balance' and phase 2 as the acceleration to achieve harmonized cycling. Stability was operationalised in terms of the duration of these phases: the shorter their duration, the higher the stability. Pedelecs were shown to be less stable in phase 1 than conventional bicycles, irrespective of user group. For all user groups, only in phase 2 the advantages of electrical support kicked in. Results obtained in traffic conditions confirmed the patterns obtained in the controlled setting, with as only difference a lower speed in traffic conditions, which held for both mounting phases and bicycle types. Also measures of physical limitations due to low muscle strength were shown only to be compensated for by pedal support in phase 2 and not in phase 1. Further, mounting characteristics affected pedelec stability in phase 1 and not in phase 2. Higher stability was associated with a) starting while seated and b) using the pedal to push off. Although, these mounting characteristics were confounded with age, gender, and muscle strength, the pattern of results still suggest certain mounting techniques to be more beneficial for pedelecs. The results further illustrate the importance of a deeper understanding of the interactions of bicycle types and user groups on critical manoeuvres and their potential contribution to the optimisation of pedelec design and the training of safe mounting techniques.