• International Journal of Highway Engineering
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• v.18 no.6
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• pp.69-76
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• 2016

OBJECTIVES : The objective of this study is to propose a capacity analysis methodology for riverside bike-exclusive roads. METHODS : Three steps were performed to develop a methodology to estimate bikeway capacity. First, we reviewed previous studies on the vehicle-road capacity analysis and proposed their applicability to bikeways. Second, two assumptions were made based on the traffic flow characteristics of bikeways: (1) the capacitated state in bikeways occur within a bicycle platoon, and (2) a bicycle platoon consists of more than three bicycles running in close proximity. In addition, it is assumed that the mean time headway of a bicycle platoon represents the characteristics of the platoon. The normality of the mean-time headway of a bicycle platoon calculated using the central limit theorem leads to the development of a method that estimates the riverside bikeway capacity using data collected from two different riverside bike-exclusive roads (Han-river and Anyangcheon). We used a location-fixed video camera to record videos of running bicycles and wrote a special-purpose software program to code the time-headway data from the videos. RESULTS : Time headways from 189 bicycle platoons were analyzed. The estimated mean-time headway of the capacitated bicycle flow is 1.01 s, from which the capacity of the bikeway is found to be 3578 vehicles/h. CONCLUSIONS : The proposed method that estimates bikeway capacity could be applicable to the analysis of short-range congested area rather than planning the number of lanes. In other words, it determines the sections that are temporarily highly congested and proposes appropriate strategies to mitigate the congestion.

• The Journal of Bigdata
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• v.8 no.2
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• pp.45-54
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• 2023

Seoul's public bicycle system, 'Ttareungyi,' introduced in 2015, has achieved an annual ridership of 40 million in 2022. Similarly, electric scooters, a type of personal mobility device, surpassed one million riders in 2020 due to various sharing platforms. However, the major roadways for these new transportation, bicycle lanes, are notably insufficient compared to other forms of transport. Hence, this study proposes an optimal location selection method for bicycle lanes in Seoul to prevent accidents and enhance bicycle ride safety. The location selection process prioritizes road safety concerning bicycle accident risk. Using regression models, high-risk areas for bicycle accidents are identified. Cluster analysis categorizes these areas into six clusters, each suggesting suitable types of bicycle lanes based on cluster-specific characteristics. We hope that this study will contribute to the improvement of Seoul's transportation environment, including the expansion of dedicated bicycle lanes and lanes for personal mobility devices.

• Journal of Korean Society of Transportation
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• v.23 no.8 s.86
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• pp.203-213
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• 2005

Recently, with the increase of the interest to global environmental problems, bicycle has been recognized as the most environmentally friendly transportation mode. To promote cycling, it is necessary to ensure road space that bicycle can keep running safely and smoothly. This paper aims to evaluate the district with rearranged road space and network, given priority to bicycle, comparing the traditional district which are given priority to car from viewpoints of environment, safety and accessibility. As evaluation indicators, the carbon dioxide emission on the environment. the number of collision between car and bicycle on safety and an accumulated frequency measure on accessibility were used. As the result, it was clarified that bicycle road measures to create bicycle road by reallocation of road space and form bicycle exclusive network were effective.

• Journal of Korea Planning Association
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• v.53 no.7
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• pp.49-66
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• 2018

The purpose of this study is to analyze neighborhood environmental factors affecting bicycle accidents and accidental severity in Seoul, Korea. The use of bicycles has increased rapidly as daily transportation means in recent years. As a result, bicycle accidents are also steadily increasing. Using Traffic Accident Analysis System (TAAS) data from 2015 to 2017, this study uses negative binomial regression analysis to identify neighborhood environmental factors affecting bicycle accidents and accidential severity. The main results are as follows. First, bicycle accidents are more likely to occur in commercial and mixed land use areas where pedestrians, bicycle and vehicles are moving together. Second, bicycle accidents are positively associated with road structures such as four-way intersection. In contrast, three-way intersection is negatively associated with serious bicycle accidents. The density of speed hump or street tree is negatively associated with bicycle accidents and accidential severity. This finding indicates the effect of speed limit or street trees on bicycle safety. Fourth, bicycle infrastructures are also important factors affecting bicycle accidents and accidential severity. Bicycle-exclusive roads or bicycle-pedestrian mixed roads are positively associated with bicycle accidents and accidential severity. Finally, this study suggests policy implications to improve bicycle safety.

• Journal of Environmental Health Sciences
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• v.35 no.6
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• pp.447-453
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• 2009

Cycling has been lately recommended as an alternative commuting mode because it is believed to be good for health and the environment. However, the exposure to environmental pollutants, such as fine particulates, could be a potential problem for cycling in urban environments. In this study, we compared commuters' $PM_{10}$ exposure using the different transportation modes of bicycle and bus. When a bicycle was used as a commuting mode, the additional $PM_{10}$ exposure due to transportation was about 3.5 times higher than that when using a bus. The difference of additional $PM_{10}$ exposures by cycling and bus was statistically significant (p<0.01). The $PM_{10}$ exposure during cycling was significantly correlated with atmospheric $PM_{10}$ concentration (r=0.98, p<0.01) and its correlation coefficient was higher than that of bus (r=0.55, p<0.05). The results of this study demonstrated that the main reasons of higher $PM_{10}$ exposure when using the bicycle as the mode of transport were its vicinity to road traffic and routes that were unavoidably close to road traffic. Bicycle commuting along the road side may not be good for health. Exclusive bicycle lanes away from road traffic are recommended.

• International Journal of Highway Engineering
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• v.9 no.3
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• pp.83-89
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• 2007

When allocating traffic signal at the signalized intersection, minimum green time and clearance time for bicyclists should be significantly considered in order to enhance safety aspects to bicyclists when crossing intersections, especially where intersections with exclusive bicycle paths that are physically separated from pedestrians. In this study, field measurements related to bicycle crossing time, including minimum peen time and clearance time, were collected and analyzed according to bicycles crossing types at the signalized intersections where high rate of bicyclists exists. Three types of bicycle crossing are defined as follows 1) stopping: completely stop before crossing (at least one foot on found) 2) riding: crossing with riding bicycle 3) pulling: crossing without riding bicycles. Minimum green time based on pedestrian speeds should be used as crossing time in this case. For bicyclists, speed of bicycle that is applicable to estimate the minimum green time is in the 1.36m/sec($15^{th}$ percentile) to 1.60m/sec($25^{th}$ percentile) range in case of its stopping. Also it is in the 0.75($15^{th}$ percentile) to 0.87($25^{th}$ percentile) range for pulling at crosswalk. In addition, speed of bicycle to consider for calculating the clearance time is in the 2.51m/sec($15^{th}$ percentile) to 2.79m/sec($25^{th}$ percentile). These values also resulted from $15^{th}$ percentile or $25^{th}$ percentile speeds of riding. The results of this study are expected to be supported in traffic signal allocation process, reflecting bicyclists' characteristics.