Shinhye Joo

Methodology for Evaluating Cycling Environment using GPS-based Probe Bicycle Speed Data

The bicycle is an environment-friendly transport mode leading to a more sustainable transportation system. To innovatively increase the use of bicycle as a significant transport mode, bicycling-friendly roadway environment should be provided. From this perspective, the scientific and effective assessment of roadway environment in term of the bicyclist perception for safety and comfortability is of keen interest. This study develops a methodology for evaluation cycling environment using probe bicycles. A global positioning system(GPS) based speedometer was used to collect bicycle speed data. Cycling comfortability index(CCI) was derived for the purpose of evaluating cycling environment. The proposed CCI can be effectively used as an assessment tool in the field of bicycle transportation.

Evaluating the effects of supplemental rest areas on freeway crashes caused by drowsy driving

To prevent crashes caused by drowsy driving, supplemental rest areas have been installed in the South Korean freeway system to allow road users to rest. These supplemental rest areas are very small-sized resting facilities located between the larger regular rest areas, which is a unique design. This study aimed to evaluate the effects of the supplemental rest areas on reducing crashes caused by drowsy driving. Between 2011 and 2012, supplemental rest areas were first installed in the Gyeongbu Freeway, which was selected as the study area for this study. The first 160km and 178km stretches of the southbound and northbound lanes, respectively, of the Gyeongbu Freeway were considered the reference areas. For both the southbound and northbound lanes, the downstream stretch of the Gyeongbu Freeway was considered the treatment area where the supplemental rest areas were installed. Based on a negative binomial regression of the crashes estimated in the reference and treatment areas, an empirical Bayes approach was employed to quantitatively validate the effects of the supplemental rest areas on reducing crashes caused by drowsy driving. The results showed that the supplemental rest areas reduced freeway crashes caused by drowsy driving by 14%. The supplemental rest areas were most effective in reducing drowsy driving related crashes particularly in freeway sections with 2 or 3 travel lanes or with ramps. As the first data-driven study evaluating the effects of these supplemental rest areas, the results imply that supplemental rest areas provide more opportunities to avoid drowsy driving, and, therefore they should be encouraged for freeways as cost-effective safety improvement facilities.

Algorithm for Identifying Highway Horizontal Alignment using GPS/INS Sensor Data

Geometric information is a key element for evaluating traffic safety and road maintenance. This study developed an algorithm to identify horizontal alignment using global positioning system(GPS) and inertial navigation system(INS) data. Roll and heading information extracted from GPS/INS were utilized to classify horizontal alignment into tangent, circular curve, and transition curve. The proposed algorithm consists of two components including smoothing for eliminating outlier and a heuristic classification algorithm. A genetic algorithm(GA) was adopted to calibrate parameters associated with the algorithm. Both freeway and rural highway data were used to evaluate the performance of the proposed algorithm. Promising results, which 90.48% and 88.24% of classification accuracy were obtainable for freeway and rural highway respectively, demonstrated the technical feasibility of the algorithm for the implementation.

A multi-criteria analysis framework including environmental and health impacts for evaluating traffic calming measures at the road network level

ABSTRACT Recent interests in both vehicle emissions and public health have facilitated the development of more eco-friendly transportation systems. This study developed a multi-criteria evaluation framework to evaluate the effectiveness of traffic calming measures (TCMs) from the various perspectives at the road network level; operational efficiency, traffic safety, environmental and health impacts. The proposed methodology employs four-step sequential simulation experiments, including driving, traffic flow, emissions, and air dispersion simulations. The results obtained from these four simulations are used to evaluate the effectiveness in terms of safety and operational efficiency in addition to environmental and health impacts. A multi-criteria value function based on the weights estimated from the analysis of an analytical hierarchy process (AHP) is applied in the evaluation framework. As an application, chicanes and speed humps widely implemented in Korean school zones were evaluated at the road network level. The proposed simulation-based approach is expected to be effectively used for the decision-making process in selecting better alternatives for TCM.

Methodology for Designing Bicycle Speed Hump Using Multi-critiria Decision Making Process

PURPOSES : Effective speed management is necessary for preventing traffic crashes on the road. Speed hump is known as an effective tool for managing speed. Unlike existing studies which are mainly focused on humps for vehicles, this study proposed a novel method to determine design parameters for bicycle speed humps based on a multi-criteria decision making process. METHODS : Three objectives including the effectiveness of speed reduction, bicycle safety, and user`s comfortability were incorporated into the proposed evaluation framework for determining design parameters. A multi-criteria value function was also derived and utilized as a part of the proposed method. RESULTS : Extensive simulations and statistical tests show that an integrated bike-box way is identified as the best in terms of operational efficiency and safety. CONCLUSIONS : It is expected that the outcomes of this study can be a valuable precursor for developing design guidelines for bicycle road and facility.

Analysis of Factors Affecting Traffic Accident Severity on Freeway Climbing Lanes

PURPOSES : The objective of this study is to analyze factors affecting traffic accident severity for determining countermeasures on freeway climbing lanes. METHODS : In this study, an ordered probit model, which is a widely used discrete choice model for categorizing crash severity, was employed. RESULTS : Results suggest that factors affecting traffic accident severity on climbing lanes include speed, drowsy driving, grade of uphill 3%, gender (male offender and male victim), and cloud weather. CONCLUSIONS : Several countermeasures are proposed for improving traffic safety on freeway climbing lanes based on the analysis of crash severity. More extensive analysis with a larger data set and various modeling techniques are required for generalizing the results.

Evaluation of Left-Turn Passages for Bicycle Traffic in Mixed Traffic Stream at Signalized Intersections

PURPOSES: This study proposes a novel method based on microscopic simulation models to evaluate bicycle passing ways in mixed traffic flow conditions at signalized intersections. METHODS: Both operational efficiency and safety are taken into consideration in the evaluation. A widely used performance measure, delay, is used for evaluating the operational efficiency. Regarding the safety evaluation, surrogate safety measures (SSM) to represent traffic conflicts and the level of crash severity, DeltaS and Max.DeltaV, are applied in the proposed method. RESULTS: Extensive simulations and statistical tests show that an integrated bike-box way is identified as the best in terms of operational efficiency and safety. CONCLUSIONS: The proposed method and outcomes of this study will be valuable for bicycle traffic operations and facility design.