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This study seeks to improve the methodology of determining the relationship between cycling dynamic performance and characteristics of roadway environment considering different bicyclists’ skill le...

Bicycles are an environment-friendly mode of transport and are leading to more sustainable transportation systems. To increase the use of bicycles as a significant transport mode, a bicycle-friendly roadway environment should be provided. From this perspective, assessment of the roadway environment from the bicyclist viewpoint in terms of safety and comfort is of keen interest. This study explores the cycling stability associated with the roadway environment. An Inertial Measurement Unit (IMU), including an accelerometer and a gyro sensor, were used to determine the factors that influence cycling stability. The acceleration and angular velocity for each axis were obtained from the IMU, which were used to quantify the change in average acceleration of the bicycle and determine the changes in roll, pitch, and yaw of the bicycle. These movements were largely associated with cycling stability. An ordered probit model was adopted to model the relationship between the bicyclist perception and the sensor data representing stability. The estimation results demonstrated that the average angular velocity was statistically significant and affected cycling stability.

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...

As interest grows in eco-friendly green transportation systems, transportation management agencies have focused on effectively mitigating vehicle emissions. Extensive research has been conducted to enhance the performance of transportation systems in terms of environmental compatibility. A novel feature of this study includes considering crash occurrences when analyzing near-freeway air quality. This study quantifies the impact of traffic crashes on vehicle emissions and the associated near-freeway air quality. Both crash data and vehicle detection systems (VDS) data, which were obtained in 2012 from a Korean freeway located in a densely populated urban area, were used to determine the impact of traffic crashes on near-freeway air quality. MOVES and CALPUFF were adopted to estimate freeway emissions and air dispersion for crash-involved and crash-free traffic conditions. The contributing factors that affect the severity of emission dispersion were identified by regression analyses. Results show a community near freeways within a 1-km radius of crash locations was affected by traffic-related air pollution exposure. The regression analyses also showed crash characteristics, and weather characteristics affect traffic-related air pollution exposure areas. Finally, this study proposed traffic-related public health strategies to mitigate air pollutants generated from crash occurrences on freeways.

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.

Introduction The concept of a smart city is fast becoming a key instrument in transforming living environments in a better way to enhance the operational efficiency of a transportation system. This paper presents a framework to assess transportation performance measures and smart-growth of cities around the U.S. by including physical activity as one of the main criteria. Methods This study employs Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) as a multi-criteria decision analysis (MCDA) method. The proposed assessment framework is comprised of the evaluation of an individual criterion and the assessment of comprehensive results. The criteria are categorized into four groups including network performance, traffic safety, environmental impact, and physical activity. As a case example, the proposed performance measures were examined for forty-six cities in the U.S., and the required data was gathered from multiple sources. Results The output of the framework contains sustainability and smart-growth rankings of the selected cities as well as uncertainty and sensitivity analysis. The sensitivity analysis was utilized to determine the quantity that each performance measure or weighting factor requires to alter the smart-growth score. It has been illustrated that the dominancy between reversible pairs in the ranking is critically sensitive for almost 15% of cases. Conclusion The results of the proposed framework can be an effective decision supporting tool in analyzing traffic management strategies. Results from the score sensitivity calculation indicate that the proposed framework can be adopted in multifaceted transportation system performance in sustainability and smart-growth of cities.

The number of crashes that involve bicycles and result in severe injuries has increased every year in the Republic of Korea, though bicycling is a promising alternative transportation mode that can help address transportation emission problems. Correspondingly, this study intends to quantitatively examine the impacts of contributing factors on the cyclist injury severity levels and to provide meaningful insight into prioritizing and specifying strategies for improving cyclist safety. To this end, a decision tree and ordered probit regression were integrated in this study. The findings showed that heavy vehicle use and cyclist age should be preferentially considered when implementing cyclist safety improvement strategies: targeting young heavy-vehicle drivers or cyclists, driver education regarding proper curve maneuvering and a law enforcement prohibition of speeding are suggested, and ITS-based traffic management system and road facilities would help enhance light vehicle driver visibility and senior cyclist alertness, particularly in horizontally curving road sections. These data-driven results could quantitatively support the policy makers or practitioners making decisions about prioritizing cyclist safety improvement strategy implementations and further specifying such strategies.

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.

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.

Background Transportation decisions impact human health at least in three ways, such as traffic crashes, environmental impact, and physical fitness. While there have been ample efforts in reducing traffic crashes and environmental impacts, less attention has been paid to their impacts on physical fitness. Recent efforts on the relationship between transportation and physical fitness were mostly from the context of active transportation. Potential benefits of active transportation include saving in mobility costs, benefits from related businesses, community savings in costs associated with health and environmental benefits. Although it is difficult to predict how a particular transportation planning decision affects physical fitness, total impacts are likely to be large. Diseases associated with inadequate physical fitness cause an order of magnitude of more deaths, and more than road crashes. Even modest reductions in these illnesses could provide significant health benefits. Therefore, there is a strong need for investigating how transportation options affect the physical activities and public health. Methods The research team developed a mobile application that collects individuals’ daily travel activities physical fitness activities. While the travel activity data are collected from the GPS information from individuals’ mobile phone, the fitness activity data are collected from Fitbit. Data collected from 200 subjects chosen in Michigan and Texas are transmitted to a server for further analysis. The data allows comparison of physical activity associated with transportation choices in different geographical areas and its seasonal variations. Results The data logged each minute were processed to determine daily activity (type, location, and duration), travel activity (transportation mode, travel time), and physical activity (heart rates and duration). The heart rates collected from Fitbit were useful in determining activity types and the transportation mode. The integrated approach allowed classification of various activity types and transportation modes. The amount of physical activity by activity type and travel mode was quantified by using the heart rate and the activity duration. The initial survey showed that those who were active in physical activity tend to choose active transportation options. Conclusion This study developed a mobile system that is able to collect daily activity, transportation choices, and the amount of physical activity. The data collected were analyzed to quantify the amount of physical activity by different transportation choice. This research is expected to help incorporate public health in evaluating transportation policies and alternatives by providing a method quantifying the amount of physical activities and associated health benefits.

The paper evaluates the effectiveness of various traffic calming measures from the perspectives of traffic performance and safety, and environmental and public health impacts. The proposed framework was applied to four calming measures – two types of speed humps, speed tables, and chicanes – to demonstrate its usefulness and applicability. A field experiment using probe vehicles equipped with global positioning system devices was conducted to obtain vehicle trajectory data for use in more realistic simulations. In addition, a recently developed vehicle emissions model was used for more accurate evaluation of environmental and public health impacts. The results show that chicane is better than the other types of traffic calming measures considered, except in terms of vehicle emissions.

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.

Bicycle is an environment-friendly transport mode contributing to a more sustainable transportation systems. To innovatively increase the use of bicycle as a significant transport mode, bicycle-friendly roadway environment should be provided. This study proposes a method to evaluate cycling environment based on the analysis of data collected from an specially equipped probe bicycle. The inertial measurement unit(IMU) consisting of a gyro sensor, accelerometer, and a global positioning systems(GPS) receiver was installed on the probe bicycle. Cycling stability index(CSI) and bicycle speed data were used as inputs of the proposed evaluation framework adopting the Fault Tree Analysis, which is a well-known technique for the risk analysis. The outcomes of this study will serve as an intelligent assesment tool for cycling environment.자전거는 비동력·무탄소 교통수단으로써 지속가능한 녹색교통수단으로 각광받고 있으며 자전거이용활성화를 위해서는 빠르고 쾌적하며, 안전한 자전거 주행환경을 제공하여 자전거가 가지고 있는 제약을 극복하여 보다 중요한 교통수단으로서의 기능을 할 수 있도록 해야한다 . 따라서 본 연구에서는 자전거 모니터링의 일환으로 주행환경 평가시나리오 및 관성센서 및 자전거 속도계가 장착된 프로브자전거를 활용한 자전거 주행환경 평가기법을 제시하였다 . 또한 제시된 평가기법은 신뢰성 분석기법인 FTA(Fault Tree Analysis)이론을 적용하여 자전거 주행안전성(CSI)과 주행이동성(속도)을 동시에 평가할 수 있는 통합평가지표를 제시함으로써 실효성이 높을 것으로 판단된다 . 본 연구의 결과는 GPS와 관성센서가 통합된 자전거 전용단말기를 개발하여 공공자전거 시스템의 구성요소로 발전시킨다면 보다 지능적인 자전거 교통 모니터링이 가능할 것으로 기대된다 .

A lane departure warning system (LDWS) is an effective technology-based countermeasure for preventing traffic crashes as it provides warning information to drivers. Understanding the characteristics of perception and satisfaction levels on LDWS is fundamental for deriving better performance and functionality enhancements of the system. The purpose of this study is to evaluate the user satisfaction of LDWS. A survey to collect user perception and user preference data was conducted. Both cross-tabulation analysis and binary logistic regression technique were adopted to identify the factors affecting user satisfaction for LDWS. The results revealed that the accuracy and timeliness of warning information was significant for evaluating the effectiveness of LDWS. In particular, the warning accuracy at a curve segment on the road was the most dominant factor affecting user satisfaction. The outcome of this study would be valuable in evaluating and designing LDWS functionalities.본 연구에서는 첨단안전장치의 운전지원장치중 하나인 차선이탈경고장치 (Lane Departure Warning System; LDWS)의 이용자 만족도 분석에 초점을 맞추어 연구를 수행하였다 . 본 연구에서는 국내 실제 화물자동차 이용자를 대상으로 차선이탈경고장치를 보급하여 사용후 차선이탈경고장치의 사용만족도 및 교통사고예방효과등을 설문조사를 수행하였다. 설문분석을 통해 차선이탈경고장치의 효과를 이용자 중심 측면에서 분석하였다 . 대부분 장거리 운전자가 응답대상이 되었으며, 사고발생의 경우 장시간 운전으로 인해 졸음운전등에 위험이 있는 것으로 나타났다 . 교차분석 결과, 사용만족도는 평균주행거리, 경고제공시기, 차로이탈검지정확성, 날씨에 따른 검지정확성, 곡선도로주행시 검지정확성, 경고제공방식만족도와 관련성이 높은 것으로 도출되었다 . 또한, 교통사고 예방효과는 경고제공시기 , 차로이탈 검지정확성, 날씨에 따른 검지정확성, 속도에 따른 검지정확성, 곡선도로주행시 검지정확성이 관련성이 높은 것으로 나타났다. 이항 로지스틱 회귀분석결과 사용만족도는 곡선도로에서의 경고정보시스템 정확성이 이용만족도에 가장 큰 영향을 미치는 것으로 분석되었다 . 본 연구결과는 추후 LDWS와 같은 첨단장비를 장착한 차량들의 확대 보급시 교통안전 효과분석을 위한 기초자료로 활용 가능할 것이다 . 또한 차로이탈경고장치의 연구 및 보완시 도출된 변수에 초점을 맞춘다면 장치의 효과를 극대화 할 수 있을 것으로 판단된다 . 아울러 LDWS기능 및 성능 개선을 위한 평가방법 개발에도 연구결과가 효과적으로 적용될 수 있을 것으로 기대된다 .

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.

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.

Background Cycling has been an important mode of transportation that enhances transportation sustainability by reducing air and noise pollution as well as traffic congestion. This study seeks to improve the methodology for determining the relationship between cycling dynamic performance and roadway environment characteristics across different bicyclists’ skill levels. We examined two facets of performances: mobility and comfortability. Methods To achieve the goal of this study, an Instrumented Probe Bicycle (IPB) equipped with various sensors was built. Using sensors allowed us to monitor bicyclist interactions to roadway environment and dynamic movements. A naturalistic field experiment, including intersections, roundabout, alignment changes, and different road surface conditions, was conducted. The Pavement Surface and Evaluation Rating System (PASER) was used to determine the quality of road surfaces. In addition, two self-reported questionnaires were used in order to obtain each participant's skill level as well as their perception on the level of cycling comfortability. Results Fault Tree Analysis was employed to develop the performance measures for recognizing the probability of fault event occurrence. Bicycle speed is being used to measure the mobility performance of the bicycle environment system. The probability that a particular segment fails to support a rider is defined as mobility performance failure. Moreover, the bicycle dynamic movements as well as the PASER rating estimate the comfortability level of the bicyclists. The probabilistic outcome of the proposed Ordered Probit Model was considered to develop the Cycling Comfortability Index (CCI). CCI is a continuous value between 0 and 1, which is adopted to find the probability of comfort level for each observation. At the end, by having two failure probabilities (mobility and comfort), the probability of a fault event occurrence is calculated. Conclusions We found that the probability of a fault event occurrence, was strongly related to the bicyclist's level of experience. The fact that inexperienced bicyclists had higher failure ratio implies that their levels of mobility and comfortability are lower. In addition, the quality of road surface had a significant impact on the speed as well as the comfortability index. The Ordered Probit Model showed that cycling comfortability was significantly affected by the average Y-axis acceleration and the mean absolute deviation of Z-axis velocity. Steering movements and Z-axis angular movements (yawing) also affected cycling comfortability. The IPB developed in this study turned out to be very useful in collecting cycling maneuver data and in analyzing bicycle safety associated with bicycle infrastructure.

Background While mobility, safety, and environmental friendliness have been major interests in transportation systems, recently people have started to pay more attention to public health related to transportation. Emphasis has been shifted from mobility and convenience to environmental friendliness and public health. However, traditional performance measures are insufficient in addressing such changes. Therefore, there is a need to provide a multifaceted approach to integrate such performance measures. Method This study proposed an assessment framework that integrates four aspects: mobility or network performance, traffic safety, environmental impact, and physical activity. In order to demonstrate its applicability, the proposed framework was employed and tested in Michigan as a case study. Data in individual categories were collected and analyzed. Delay costs, metabolic equivalent (MET), the number of crashes, and concentration of O3 were used as performance measures representing network performance, physical activity, safety, and environmental impact, respectively. Result Using the multifaceted assessment framework, this study compared performance measures by region (Bay Region, Grand Region, Metro Region, North Region, Southwest Region, and University Region) in Michigan. The result with data in 2015 showed that the Metro region, the most populated area in Michigan, was weaker than other reasons with respect to network performance, traffic safety and physical activity. By producing a multidimensional spider diagram, the strengths and weaknesses of each region's transportation performance results were analyzed and visualized. The results demonstrated its capacity to present multifaceted performance measures and their relative performances among regions. Conclusion This study proposed an integrated approach and presented a case example using the observed data in Michigan. The method was useful researchers understanding transportation performances in a comprehensive manner integrating multifaceted measures. The approach is expected to help decision-makers in developing traffic management strategies by allowing analyses of traffic-related public health strategies based on traffic exposure measures. In order to examine the effects of alternative strategies, performance measures could be derived from activity-based travel demand models or simulations. Simulation-based assessments can serve as a decision supporting tool for evaluating and/or selecting various treatment options for public health strategies prior to actual implementation. The application of activity-based travel demand models makes it possible to quantify various measures in the proposed approach by providing the effects of alternative strategies.