Jiangfeng Wang, Qian Zhang, Yinhai Wang, Jinxian Weng, Xuedong Yan
{"title":"Analysis of Sideswipe Collision Precursors Considering the Spatial-Temporal Characteristics of Freeway Traffic","authors":"Jiangfeng Wang, Qian Zhang, Yinhai Wang, Jinxian Weng, Xuedong Yan","doi":"10.1061/(ASCE)TE.1943-5436.0000896","DOIUrl":"https://doi.org/10.1061/(ASCE)TE.1943-5436.0000896","url":null,"abstract":"AbstractTo avoid bias caused by the high percentage of rear-end collisions in the generic models, only the observed sideswipe collisions on Highway I-5 in the central Puget Sound, Washington State, area are used to analyze the matched case-control logistic regression model. Considering the spatial-temporal characteristics of traffic flow and short-term variation of the sideswipe collision occurrence, a comprehensive analysis of sideswipe collision occurrence and its relationship with the freeway flow across lanes and detector locations are studied. The results imply that sideswipe collisions are more likely to occur at straight and level segments of multilane freeways in off-peak hours. High average occupancy and low average flow and speed variance upstream of collision location tend to increase the probability of sideswipe collision in congested scenarios. In contrast, high average speed and coefficient of variation in speed, low speed variance and coefficient of variation in occupancy, and high average ...","PeriodicalId":305908,"journal":{"name":"Journal of Transportation Engineering-asce","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113943858","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Implementation of Variable Speed Limits: Preliminary Test on Whitemud Drive, Edmonton, Canada","authors":"Xu Wang, M. Seraj, Y. Bie, T. Qiu, Lei Niu","doi":"10.1061/(ASCE)TE.1943-5436.0000895","DOIUrl":"https://doi.org/10.1061/(ASCE)TE.1943-5436.0000895","url":null,"abstract":"AbstractCongestion has become highly recognized as a worldwide traffic problem, as traffic demand has grown steadily over the past few decades. Variable speed limits (VSLs) are an intelligent transportation system (ITS) measure that limits mainline flow to mitigate bottleneck congestion. Currently, VSLs have become proactive based on short-term prediction. Proactive VSLs succeed in simulation evaluations, but few have been deployed in the field and their real-world effectiveness has not been proven. Various factors may lead to this limitation, such as the absence of reliable field application software, accuracy of prediction models, and high computation time for proactive control. To address this research gap, this study reports a preliminary VSL test and details its implementation results on Whitemud Drive, Edmonton, Canada. First, based on field traffic measurements before VSL control, recurrent bottleneck locations are identified. Second, the proactive control algorithm is briefly introduced. Then, a s...","PeriodicalId":305908,"journal":{"name":"Journal of Transportation Engineering-asce","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134122046","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jiaqi Ma, M. Fontaine, Fang Zhou, Jia Hu, David K. Hale, Michael O. Clements
{"title":"Estimation of Crash Modification Factors for an Adaptive Traffic-Signal Control System","authors":"Jiaqi Ma, M. Fontaine, Fang Zhou, Jia Hu, David K. Hale, Michael O. Clements","doi":"10.1061/(ASCE)TE.1943-5436.0000890","DOIUrl":"https://doi.org/10.1061/(ASCE)TE.1943-5436.0000890","url":null,"abstract":"AbstractAdaptive traffic-signal control (ATSC) is a traffic management strategy in which traffic-signal timings change, or adapt, based on observed traffic demand. Although ATSC can improve mobility, it also has the potential to reduce crashes because mainline stops should be reduced. This paper aims to evaluate the safety effectiveness of ATSC using the empirical Bayes method. This analysis examines 47 urban or suburban intersections where ATSC was deployed in Virginia using 235 site-years of before data and 66 site-years of after data. Installing ATSC was found to produce a crash modification factor (CMF) for total intersection crashes of 0.83 with a standard error of 0.05. This CMF was statistically significant at a 95 percent confidence level. Fatal and injury crashes did not change by a statistically significant amount, indicating that the primary safety benefit of ATSC was reduction in property damage crashes. Analyses of ATSC safety effects by crash type, by traffic volume level, and by operational...","PeriodicalId":305908,"journal":{"name":"Journal of Transportation Engineering-asce","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131208095","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
O. Elbagalati, M. Elseifi, Kevin Gaspard, Zhongjie Zhang
{"title":"Prediction of In-Service Pavement Structural Capacity Based on Traffic-Speed Deflection Measurements","authors":"O. Elbagalati, M. Elseifi, Kevin Gaspard, Zhongjie Zhang","doi":"10.1061/(ASCE)TE.1943-5436.0000891","DOIUrl":"https://doi.org/10.1061/(ASCE)TE.1943-5436.0000891","url":null,"abstract":"AbstractNonstructural factors, such as surface distresses and ride quality, have been commonly used as the main indicators of in-service pavement conditions. In the last decade, the concept of implementing a structural condition index in pavement management system (PMS) to complement functional condition indices has become an important goal for many highway agencies. The rolling wheel deflectometer (RWD) provides the ability to measure pavement deflection while operating at the posted speed limits causing no user delays. The objective of this study was to develop a model to predict pavement structural capacity at a length interval of 0.16 km (0.1 mi) based on RWD measurements and to assess its effectiveness in identifying structurally deficient pavement sections. Rolling wheel deflectometer data collected from 153 road sections (more than 1,600 km) in District 05 of Louisiana were used in this study. The predicted structural number (SNRWD0.16) showed an acceptable accuracy with a root-mean square error (R...","PeriodicalId":305908,"journal":{"name":"Journal of Transportation Engineering-asce","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125290714","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Clustering Vehicle Class Distribution and Axle Load Spectra for Mechanistic-Empirical Predicting Pavement Performance","authors":"Amanul Hasan, R. Islam, R. Tarefder","doi":"10.1061/(ASCE)TE.1943-5436.0000876","DOIUrl":"https://doi.org/10.1061/(ASCE)TE.1943-5436.0000876","url":null,"abstract":"AbstractPast studies have determined the effects of the pavement mechanistic-empirical (ME) default (Level 3) values of vehicle class distribution (VCD) and axle load spectra (ALS) on pavement performance. However, it is still not clear how the clustered VCD and ALS affect the ME predicted pavement performance. In this study, traffic data from 10 weigh-in-motion (WIM) stations were gathered and analyzed to develop the VCD and ALS values using arithmetic average and clustering methods (Level 2). Next, using Level 2, Level 3, and site-specific (Level 1) inputs of VCD and ALS, the pavement ME predicted performance was determined. The results show that the predicted performance by the cluster (Level 2) data are very close to those of the site-specific data (Level 1). Performance generated by the ME default values (Level 3) are significantly different from those generated by the site-specific or cluster values. When comparing the performance of the ME design default (Level 3) with those of the statewide averag...","PeriodicalId":305908,"journal":{"name":"Journal of Transportation Engineering-asce","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128727972","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Multiobjective Optimization of Roadway Lighting Projects","authors":"K. Hyari, A. Khelifi, H. Katkhuda","doi":"10.1061/(ASCE)TE.1943-5436.0000853","DOIUrl":"https://doi.org/10.1061/(ASCE)TE.1943-5436.0000853","url":null,"abstract":"AbstractRoadway lighting systems play a major role in maintaining nighttime traffic safety as they reduce both the number and severity of nighttime traffic accidents. While the design of roadway lighting systems involves multiple objectives, past studies have focused on optimizing only one of the multiple objectives that should be considered. This paper presents a multiobjective optimization model for roadway lighting projects that simultaneously optimizes four design objectives. The incorporated objectives are (1) maximizing the average lighting level on the road surface; (2) maximizing the lighting uniformity along the roadway; (3) minimizing the glare to road users produced by the lighting system; and (4) minimizing the cost of operating the lighting system. The model is designed and developed as a multiobjective genetic algorithm to help decision-makers in their endeavor to provide efficient roadway lighting systems that strike a balance between the four conflicting objectives. The present model consi...","PeriodicalId":305908,"journal":{"name":"Journal of Transportation Engineering-asce","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131940780","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
S. Ghasemi, M. Jalayer, Mahdi Pour-Rouholamin, A. Nowak, Huaguo Zhou
{"title":"State-of-the-Art Model to Evaluate Space Headway Based on Reliability Analysis","authors":"S. Ghasemi, M. Jalayer, Mahdi Pour-Rouholamin, A. Nowak, Huaguo Zhou","doi":"10.1061/(ASCE)TE.1943-5436.0000851","DOIUrl":"https://doi.org/10.1061/(ASCE)TE.1943-5436.0000851","url":null,"abstract":"AbstractStipulating a space headway is a pivotal concern in traffic engineering. Although consideration of a larger headway leads to safer traffic movement, consideration for a smaller headway can serve more traffic volume, which is significant from an economic standpoint. Implementation of a smaller headway, however, could lead to the tailgating phenomenon (short distances between two vehicles), which is perceived as troublesome and dangerous. Evaluating the space headway provides a reasonable approach to understanding the operational benefit for safety and traffic concerns. Using probabilistic analysis to account for uncertainty can be one of the best applicable methods because the headway data are not deterministic and are treated as random variables. More specifically, by emphasizing the reliability analysis, it is feasible to determine the appropriate space headway. The objective of this paper is to present a state-of-the-art approach for the evaluation of the statistical parameters of the headway by...","PeriodicalId":305908,"journal":{"name":"Journal of Transportation Engineering-asce","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133244126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xueli Hao, A. Sha, Zhaoyun Sun, Wei Li, Zhao Haiwei
{"title":"Evaluation and Comparison of Real-Time Laser and Electric Sand-Patch Pavement Texture-Depth Measurement Methods","authors":"Xueli Hao, A. Sha, Zhaoyun Sun, Wei Li, Zhao Haiwei","doi":"10.1061/(ASCE)TE.1943-5436.0000842","DOIUrl":"https://doi.org/10.1061/(ASCE)TE.1943-5436.0000842","url":null,"abstract":"AbstractIn order to measure the texture depth of asphalt pavement automatically and accurately, a data set generated by a real-time laser pavement texture meter (RLPTM) was realized, and a calculation method was developed. Three groups of experiments were designed and conducted to calibrate the measure results of the electric sand patch method (ESPM) to the ASTM sand patch method and compare the performance of the RLPTM with the ESPM. Experimental results showed that the correlation coefficient of the ESPM and sand patch method have reached up to 0.9830, indicating a good correlation. The RLPTM method had higher resolution (more significant figures) and better repeatability (lower coefficients of variation) than ESPM. The correlation coefficient between RLPTM and ESPM was 0.9207, demonstrating the good repeatability of the overall measurements. The absolute errors of the results obtained by RLPTM and ESPM were within 0.3 mm. Further analysis indicated that results of RLPTM were slightly over predicted (sl...","PeriodicalId":305908,"journal":{"name":"Journal of Transportation Engineering-asce","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127770294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Design of Turbo Roundabouts Based on the Rules of Vehicle Movement Geometry","authors":"Tamara Džambas, Saša Ahac, Vesna Dragčević","doi":"10.1061/(ASCE)TE.1943-5436.0000850","DOIUrl":"https://doi.org/10.1061/(ASCE)TE.1943-5436.0000850","url":null,"abstract":"This paper describes a turbo roundabout design procedure based on the rules of design vehicle movement geometry. Previous studies carried out on various junction types have shown that this design approach ensures the usage of optimal roundabout element dimensions as well as safety and comfort during driving. A five-step design procedure is suggested, including a detailed description of relevant influential parameters. They are choosing a design vehicle, implementing the initial roundabout scheme on which the vehicle swept path is analyzed, choosing a method of assigning input parameters for swept path requirements testing procedure, choosing optimal design elements of a standard turbo roundabout, and fastest path vehicle speed analysis.","PeriodicalId":305908,"journal":{"name":"Journal of Transportation Engineering-asce","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114158545","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Modeling Human Learning and Cognition Structure: Application to Driver Behavior in Dilemma Zone","authors":"S. G. Machiani, M. Abbas","doi":"10.1061/(ASCE)TE.1943-5436.0000885","DOIUrl":"https://doi.org/10.1061/(ASCE)TE.1943-5436.0000885","url":null,"abstract":"AbstractIn transportation studies, modeling human learning and decision-making processes plays a key role in developing realistic safety countermeasures and appropriate crash-mitigation strategies. In this study, a human learning model was created that captures the cognitive structure of human memory. The relationship between long-term and short-term memories was incorporated into a reinforcement learning technique to construct the human learning model. The model was then applied to dilemma zone data collected in a simulator study. Dilemma zone is an area of roadway ahead of the signalized intersection in which drivers have difficulty deciding whether to stop or proceed through at the onset of yellow. Driver choice behavior and learning process in dilemma zones was modeled, taking into account drivers’ experiences at the previous intersections, and was compared to a pure machine learning model. The results of the model revealed lower and faster-merging errors when human learning was considered in training...","PeriodicalId":305908,"journal":{"name":"Journal of Transportation Engineering-asce","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116043846","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}