Factors influencing bike share membership: An analysis of Melbourne and Brisbane

The number of bike share programs has increased rapidly in recent years and there are currently over 700 programs in operation globally. Australia’s two bike share programs have been in operation since 2010 and have significantly lower usage rates compared to Europe, North America and China. This study sets out to understand and quantify the factors influencing bike share membership in Australia’s two bike share programs located in Melbourne and Brisbane. An online survey was administered to members of both programs as well as a group with no known association with bike share. A logistic regression model revealed several significant predictors of membership including reactions to mandatory helmet legislation, riding activity over the previous month, and the degree to which convenience motivated private bike riding. In addition, respondents aged 18–34 and having docking station within 250 m of their workplace were found to be statistically significant predictors of bike share membership. Finally, those with relatively high incomes increased the odds of membership. These results provide insight as to the relative influence of various factors impacting on bike share membership in Australia. The findings may assist bike share operators to maximize membership potential and help achieve the primary goal of bike share – to increase the sustainability of the transport system.     

Comparative analysis of household car,motorcycle and bicycle ownership between Osaka metropolitan area,Japan and Kuala Lumpur,Malaysia

The interactions among different types of vehicle ownership including car, motorcycle and bicycle are examined by developing simultaneous vehicle ownership models in this study. Large scale person trip survey data for Osaka metropolitan area, Japan and Kuala Lumpur, Malaysia are used for empirical analysis. The results suggest that population density at residential area significantly and negatively affects car ownership for both areas, and that the effects are larger for Osaka metropolitan area than for Kuala Lumpur. Also, bicycle ownership becomes higher at higher population density area for Osaka area, while higher at lower population density area for Kuala Lumpur, which represents the different usage patterns of bicycle between the two areas.

We can all get along: The alignment of driver and bicyclist roadway design preferences in the San Francisco Bay Area

Two trends in the United States—growth in bicycling and enthusiasm for complete streets—suggest a need to understand how various roadway users view roadway designs meant to accommodate multiple modes. While many studies have examined bicyclists’ roadway design preferences, there has been little investigation into the opinions of non-bicyclists who might bicycle in the future. Additionally, little research has explored the preferences of the motorists who share roads with cyclists—despite the fact that motorists compose the vast majority of roadway users in the United States and similarly developed countries.This paper presents results from an internet survey examining perceived comfort while driving and bicycling on various roadways among 265 non-bicycling drivers, bicycling drivers, and non-driving bicyclists in the San Francisco Bay Area. Analysis of variance tests revealed that both drivers and bicyclists are more comfortable on roadways with separated bicycling facilities than those with shared space. In particular, roadways with barrier-separated bicycle lanes were the most popular among all groups, regardless of bicycling frequency. Striped bicycle lanes, a common treatment in the United States, received mixed reviews: a majority of the sample believed that they benefit cyclists and drivers through predictability and legitimacy on the roadway, but the lanes were rated significantly less comfortable than barrier-separated treatments—particularly among potential bicyclists.These findings corroborate research on bicyclists’ preferences for roadway design and contribute a new understanding of motorists’ preferences. They also support the U.S. Federal Highway Administration’s efforts to encourage greater accommodation of bicyclists on urban streets.     

Using the built environment to oversample walk,transit, and bicycle travel

Characteristics of the built environment (BE) have been associated with walk, transit, and bicycle travel. These BE characteristics can be used by transportation researchers to oversample households from areas where walk, transit, or bicycle travel is more likely, resulting in more observations of these uncommon travel behaviors. Little guidance, however, is available on the effectiveness of such built environment oversampling strategies. This article presents measures that can be used to assess the effectiveness of BE oversampling strategies and inform future efforts to oversample households with uncommon travel behaviors. The measures are sensitivity and specificity, positive likelihood ratio (LR+), and positive predictive value (PPV). To illustrate these measures, they were calculated for 10 BE-defined oversampling strata applied post-hoc to a Seattle area household travel survey. Strata with an average block size of <10 acres within a ¼ mile of household residences held the single greatest potential for oversampling households that walk, use transit, and/or bicycle.     

Prioritizing new bicycle facilities to improve low-stress network connectivity

This paper introduces a new method to prioritize bicycle improvement projects based on accessibility to important destinations, such as grocery stores, banks, and restaurants. Central to the method is a new way to classify “bicycling stress” using marginal rates of substitution which are commonly developed through empirical behavioral research on bicyclist route choice. MRS values are input parameters representing bicycling stress associated with the number of lanes and speed limit of a street. The method was programmed as a geographic information system tool and requires commonly available data. The tool is demonstrated on three improvement scenarios that were recently proposed for Seattle, Washington. The full build-out scenario consists of 771 projects that include various new bike lanes, protected bike lanes, and multi-use trails. The tool produces priority rankings based on a project’s ability to improve low-stress connectivity between homes and important destinations. The analysis identifies specific areas and neighborhoods that can be expected to exhibit better bikeability. Transportation planners can use the tool to help communicate anticipated project impacts to decision-makers and the public.     

Model-based predictive control for bicycling in urban intersections

In this paper, a model predictive control approach for improving the efficiency of bicycling as part of intermodal transportation systems is proposed. Considering a dedicated bicycle lanes infrastructure, the focus in this paper is to optimize the dynamic interaction between bicycles and vehicles at the multimodal urban traffic intersections. In the proposed approach, a dynamic model for the flows, queues, and number of both vehicles and bicycles is explicitly incorporated in the controller. For obtaining a good trade-off between the total time spent by the cyclists and by the drivers, a Pareto analysis is proposed to adjust the objective function of the MPC controller. Simulation results for a two-intersections urban traffic network are presented and the controller is analyzed considering different methods of including in the MPC controller the inflow demands of both vehicles and bicycles.     

Prioritizing bicycle paths in Belo Horizonte City,Brazil: Analysis based on user preferences and willingness considering individual heterogeneity

Using bicycles as a commuting mode has proven to be beneficial to both urban traffic conditions and travelers’ health. In order to efficiently design facilities and policies that will stimulate bicycle use, it is necessary to first understand people’s attitudes towards bicycle use, and the factors that may influence their preferences. Such an understanding will enable reliable predictions of bicycle use willingness level, based on which cycling facility construction can be reasonably prioritized.As people often have different perceptions on exercising, green transportation, and traffic conditions, effects of potentially influencing factors on people’s willingness of using bicycles tend to be highly heterogeneous. This paper uses a random parameter ordered probit model to analyze how travelers’ willingness of using bicycles is influenced by various socio-economic factors in Belo Horizonte City, Brazil, with the consideration of individual heterogeneity. The data was collected through the 2010 bicycle use survey in Belo Horizonte City. Results show that, first, the willingness of using bicycle is favored by middle income class household, and negatively related with commuting time. Second, people who rent apartments tend to be more willing to use bicycles. Third, if a person is currently walking a long time to work, he/she would be most willing to commute with a bicycle in the future. Those currently commuting a relatively short distance by motorcycle and bus follow this group in terms of willingness to commute by bicycle in the future. Car users seem to be difficult to convert to bicycle users. Moreover, the estimation shows clear evidence that significant individual heterogeneity indeed exists, especially for education level, necessitating the consideration of such an effect. With the calibrated model, residents’ willingness of using bicycle commuting is then estimated for the entire Belo Horizonte City using the 2010 Census and the 2012 O/D survey data. The results are cross validated using the bicycle path preference information, also obtained from the 2010 bicycle use survey.     

Categorizing bicycling environments using GPS-based public bicycle speed data

A promising alternative transportation mode to address growing transportation and environmental issues is bicycle transportation, which is human-powered and emission-free. To increase the use of bicycles, it is fundamental to provide bicycle-friendly environments. The scientific assessment of a bicyclist’s perception of roadway environment, safety and comfort is of great interest. This study developed a methodology for categorizing bicycling environments defined by the bicyclist’s perceived level of safety and comfort. Second-by-second bicycle speed data were collected using global positioning systems (GPS) on public bicycles. A set of features representing the level of bicycling environments was extracted from the GPS-based bicycle speed and acceleration data. These data were used as inputs for the proposed categorization algorithm. A support vector machine (SVM), which is a well-known heuristic classifier, was adopted in this study. A promising rate of 81.6% for correct classification demonstrated the technical feasibility of the proposed algorithm. In addition, a framework for bicycle traffic monitoring based on data and outcomes derived from this study was discussed, which is a novel feature for traffic surveillance and monitoring.     

Sliding mode observers for vehicle mode detection

This paper explores the use of sliding mode observers to detect the onset of potentially dangerous vehicle modes such as oversteer, understeer or split-μ braking. Provided these modes can be detected quickly enough, existing stability controllers can be engaged to ensure safe performance of the vehicle. It is shown that the equivalent output error injection signals associated with the sliding mode observer have distinctive signatures depending on the particular mode encountered. Appropriate thresholds on these signals can be set so the scheme ignores variations which arise during normal driving, but can detect and isolate different undesirable vehicle modes within 0.3 seconds of their onset.     

Prohibited–permitted right-turn phasing strategy based on capacity analysis of right-turn movements

In traffic-crowded metropolitan areas, such as Shanghai and Beijing in China, right-turn vehicles that operate with a permitted phase at signalized intersections are normally permitted to filter through large numbers of pedestrians and bicycles. To alleviate such conflicts and improve safety, traffic engineers in Shanghai introduced a prohibited–permitted right-turn operation, adding a subphase to the permitted phase in which right-turns are prohibited. Unfortunately, the prohibited subphase would reduce the capacity of right-turn movements when it prohibits right turns even if there are few pedestrians and bicycles crossing the street. This paper aims at quantifying the impact of both non-vehicular flows and the prohibited subphase on the right-turn capacity, and then proposes a strategy to determine appropriate prohibited–permitted right-turn operation that minimizes the capacity reduction caused by the prohibited subphase. To achieve this goal, we improved the pedestrian and bicycle adjustment factor described in the Highway Capacity Manual by taking into account: (1) the variety in space competition between pedestrians and bicycles, and (2) the effect of two conflict zones in each phase on right-turn operation. In addition, we revised the capacity estimation model in the Highway Capacity Manual, and developed a model based on bicycle/pedestrian volume fluctuation to describe the capacity reduction due to both non-vehicular flows and the prohibited subphase. Furthermore, we proposed a timing strategy for the onset and duration of appropriate prohibited subphase. When bicycle and pedestrian volumes are low, the actuated strategy turns to the permitted phase. When these volumes are moderate, the strategy turns to the prohibited–permitted operation. With the volumes increasing, the prohibited subphase onset advances and duration increases. In these two scenarios, the new strategy has higher right-turn capacity than the current pretimed prohibited–permitted operation. Unfortunately, when bicycle and pedestrian volumes are high, the strategy yields similar right-turn capacity. However, the new prohibited subphase has less potential vehicle–bicycle and vehicle–pedestrian conflicts.