Quantifying the role of disturbances and speeds on separated bicycle facilities

Abstract

Abstract:As cities aim to spur cycling, a key issue revolves around the location and quality of separated bicycle facilities. However, sometimes owing to impedances, these facilities fail to have the desired overall utility for cyclists. This study focuses on the role of non-stationary disturbances, i.e., the presence of users of other modes. The aim is to quantify the effects and frequencies of disturbances on offstreet bicycle facilities (from other cyclists and pedestrians) and compare them to disturbances (from motorized vehicles) while cycling in mixed traffic. Using three segments in Bologna, Italy, we measured the frequency, type, and speed reduction attributed to different types of disturbances. We analyzed speed and likelihood of events to calculate a weighted average of the cyclists' speed for separated bicycling facilities and on the roadway. For two of the segments, weighted speed reductions were minimal. However, in a third segment-one with considerably more disturbances-speed reductions were considerable: 20 percent for the separated facility and 40 percent for the mixed traffic. When married with cycling use patterns along the facilities, the notable speed reductions point to a possible trade-off cyclists make in choosing between different routes. The results help quantify relationships between cyclists and non-stationary disturbances; they also caution transport officials about possible unintended outcomes for separated bicycle facilities. OverviewAs cities worldwide aim to spur more bicycling in cities, a key issue revolves around the nature and design of specific, bicycling-oriented facilities. What design treatments might be necessary to best separate cyclists and pedestrians from traffic? What are associated land use constraints? Available guidelines

Data-driven Bicycle Network Analysis Based on Traditional Counting Methods and GPS Traces from Smartphone

“…As expected, cyclists accept deviations in order to travel on roads with: (1) a high share of reserved bikeways, (2) a high share of low priority roads (roads with one lane per direction and speed limits of 30 km/h), (3) a low intersection density, and (4) a low share of mixed access, such as lanes with bike/bus access or lanes where bikes and pedestrians are allowed. This last result confirms the findings of the research carried out by Bernardi et al [39], in which the authors quantified the effects and frequencies of disturbances on bicycle facilities, particularly from pedestrians and buses. The statistics of the road link attributes of the overlapping sections of each trip (i.e., all links where the chosen and shortest routes coincide) are presented in the last column of Table 1.…”

Visual Eye Gaze While Cycling: Analyzing Eye Tracking at Signalized Intersections in Urban Conditions

“…The bulk of what is known about bicycling derives from studies examining use (e.g., speed, rates of use, types of cyclists) as influenced by the nature of bicycling facilities, land use features, or types of intersection treatments [5][6][7][8][9]. Other lines of research focus on elements that impact safety, drawing attention to general contexts (e.g., types of corridors) or salient design treatments [10][11][12][13].…”

Map‐matching algorithm applied to bicycle global positioning system traces in Bologna

“…This length-proportional element is expected to achieve two effects: (i) the routing algorithm will choose the minimum distance in the absence of GPS points and (ii) routes containing reserved ways for bicycles will be preferred by the routing algorithm. It has been observed, especially for those urban contexts where the bicycle network is fragmented, poorly designed or mixed with pedestrian, that a cyclist preference for bikeway links cannot be taken for granted: the percentage of cyclists choosing to ride on the roadway, mixing with motorised traffic, rather than on a bicycle facility, can be relevant [17,18]. Nevertheless, for the aim of the map-matching algorithm, we believe this assumption is reasonable and the use of the bike factor an advantage, as it can be eventually adjusted to observe attitudes in a specific context.…”