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This paper presents a methodology to investigate the link between bicycle activity and built environment, road and transit network characteristics, and bicycle facilities while also accounting for spatial autocorrelation between intersections. The methodology includes the normalization of manual cyclist counts to average seasonal daily volumes (ASDV), taking into account temporal variations and using hourly, daily, and monthly expansion factors obtained from automatic bicycle count data. To correct for weather conditions, two approaches were used. In the first approach, a relative weather ridership model was generated using the automatic bicycle count and weather data. In the second approach, weather variables were introduced directly into the model. For each approach, the effects of built environment, road and transit characteristics, and bicycle facilities on cyclist volumes were determined. It was found that employment, schools, metro stations, bus stops, parks, land mix, mean income, bicycle facility type (bicycle lanes and cycle tracks), length of bicycle facilities, average street length, and presence of parking entrances were associated with bicycle activity. From these, it was found that the main factors associated with bicycle activity were land-use mix, cycle track presence, and employment density. For instance, intersections with cycle tracks have on average 61 percent more cyclists than intersections without. An increase of 10 percent in land-use mix or employment density would cause an increase of 8 percent or 5.3 percent, respectively, in bicycle flows. The methods and results proposed in this research are helpful for planning bicycle facilities and analyzing cyclist safety. Limitations and future work are discussed at the end of this paper.

Pedestrian safety in proximity to schools is a major concern of transportation authorities, local governments, and residents. In fact, several countermeasures (e.g., school-zone speed limits) are usually in place around schools to provide a safer environment, especially for school-age children. Two questions arise here: (i) are transportation facilities in proximity to schools truly safer than other facilities given a variety of implemented road safety interventions around schools? and (ii) how can we answer the previous question properly using a reliable approach that accounts for possible confounding? While previous literature has mixed results and does not provide clear methodological/empirical guidelines in this regard, we propose an approach that answers the above questions. We illustrate our method on a sample of intersections in Montreal, Canada. Specifically, to underpin a causal interpretation, for the first time in the extent of transportation literature, we develop a heterogeneous endogenous econometric model that estimates the causal effect of proximity to school on pedestrian safety, addressing a complex endogenous relationship between the two. Various built environment, traffic exposure, and road geometric/operational characteristics are considered. The results indicate that if endogeneity is not accounted for, the effect of proximity to school is underestimated, while not being significant at a 5% level of significance. However, after accounting for confounding factors, the proposed endogenous model indicates that proximity to school deteriorates pedestrian safety. Therefore, traffic safety countermeasures and policies in place (if any) during the study period have not been sufficient and/or effective in improving pedestrian safety at intersections near schools. Our heterogeneity in mean and variance formulation provided more insights. For example, we found that, interestingly, as pedestrian volume increases at intersections around schools, the adverse effect of proximity to school on pedestrian ...