Open Transportation Journal最新文献

{"title":"The Extent of Capacity Loss Caused by Rainfall at Signalised Intersections","authors":"J. Oyaro, J. Ben-Edigbe","doi":"10.2174/1874447802014010214","DOIUrl":"https://doi.org/10.2174/1874447802014010214","url":null,"abstract":"\u0000 \u0000 Even though their physical characteristics exert a constant influence on capacity and saturation flows, signalized intersections are fixed facilities not affected by rainfall. Whilst traffic conditions with varying effects can be regulated, rainfall conditions cannot be regulated but compensated for by warning drivers to reduce speed. Speed reduction has an impact on signalised intersection capacity, whilst signalised intersection capacity is a function of saturation flow, effective green, and cycle time. In this paper, a capacity loss is the differential percentage between ‘with and without’ rainfall scenario.\u0000 \u0000 \u0000 \u0000 The paper investigated the extent of capacity loss caused by rainfall at signalised intersections.\u0000 \u0000 \u0000 \u0000 In Durban, South Africa, rainfall data were collected, collated, and correlated with traffic data in a 'with and without' rainfall intensity study. Rainfall intensity was classified according to the rate of precipitation as follows; rainfall intensity(i): light rain (i <2.5mm/h); Moderate rain (2.5mm/h ≤ i < 10mm/h), and heavy rain (10 ≤ i ≤ 50mm/h) as prescribed by the World Meteorological Society.\u0000 \u0000 \u0000 \u0000 Empirical results show that rainfall intensity has an effect on road capacity at a signalised intersection. Generally, for the vehicles going straight, light rain caused a 4.25% capacity loss; moderate rain 9.18% while heavy rain caused an 11.53% capacity reduction. With right-turning vehicles, light rain caused 7.38% capacity loss; moderate rain caused 14.3%, while heavy rain accounted for 19.15% capacity reduction.\u0000 \u0000 \u0000 \u0000 The paper concluded that rainfall at signalised intersections would cause an anomalous capacity reduction. Since the database for the study is small, the paper advocates for further studies based on a broader database to include yellow interval time.\u0000","PeriodicalId":38631,"journal":{"name":"Open Transportation Journal","volume":"34 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41269266","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":"Wheel Slip-based Road Surface Slipperiness Detection","authors":"Jinhwan Jang","doi":"10.2174/1874447802014010186","DOIUrl":"https://doi.org/10.2174/1874447802014010186","url":null,"abstract":"In this study, wheel slip, defined as the difference between both speeds of vehicular transition and wheel rotation, was used to detect road slipperiness. Three types of experiment cars were repeatedly driven on snowy and dry surfaces to obtain wheel slip data. Three approaches, including regression analysis, support vector machine (SVM), and deep learning, were explored to categorize into two states-slippery or nonslippery.","PeriodicalId":38631,"journal":{"name":"Open Transportation Journal","volume":"14 1","pages":"186-193"},"PeriodicalIF":0.0,"publicationDate":"2020-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46818528","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":"Application of Geographical Information System Techniques to Determine High Crash-Prone Areas in the Fort Peck Indian Reservation","authors":"Sahima Nazneen, Mahdi Rezapour, K. Ksaibati","doi":"10.2174/1874447802014010174","DOIUrl":"https://doi.org/10.2174/1874447802014010174","url":null,"abstract":"\u0000 \u0000 Historically, Indian reservations have been struggling with higher crash rates than the rest of the United States. In an effort to improve roadway safety in these areas, different agencies are working to address this disparity. For any safety improvement program, identifying high risk crash locations is the first step to determine contributing factors of crashes and select corresponding countermeasures.\u0000 \u0000 \u0000 \u0000 This study proposes an approach to determine crash-prone areas using Geographic Information System (GIS) techniques through creating crash severity maps and Network Kernel Density Estimation (NetKDE). These two maps were assessed to determine the high-risk road segments having a high crash rate, and high injury severity. However, since the statistical significance of the hotspots cannot be evaluated in NetKDE, this study employed Getis-Ord Gi* (d) statistics to ascertain statistically significant crash hotspots. Finally, maps generated through these two methods were assessed to determine statistically significant high-risk road segments. Moreover, temporal analysis of the crash pattern was performed using spider graphs to explore the variance throughout the day.\u0000 \u0000 \u0000 \u0000 Within the Fort Peck Indian Reservation, some parts of the US highway 13, BIA Route 1, and US highway 2 are among the many segments being identified as high-risk road segments in this analysis. Also, although some residential roads have PDO crashes, they have been detected as high priority areas due to high crash occurrence. The temporal analysis revealed that crash patterns were almost similar on the weekdays reaching the peak at traffic peak hours, but during the weekend, crashes mostly occurred at midnight.\u0000 \u0000 \u0000 \u0000 The study would provide tribes with the tool to identify locations demanding immediate safety concerns. This study can be used as a template for other tribes to perform spatial and temporal analysis of the crash patterns to identify high risk crash locations on their roadways.\u0000","PeriodicalId":38631,"journal":{"name":"Open Transportation Journal","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46904838","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":"Conjoint Vehicle License Plate Identification System","authors":"Y. Wiseman","doi":"10.2174/1874447802014010164","DOIUrl":"https://doi.org/10.2174/1874447802014010164","url":null,"abstract":"An autonomous vehicle will go unaccompanied to park itself in a remote parking lot without a driver or a passenger inside. Unlike traditional vehicles, an autonomous vehicle can drop passengers off near any location. Afterward, instead of cruising for a nearby free parking, the vehicle can be automatically parked in a remote parking lot which can be in a rural fringe of the city where inexpensive land is more readily available.","PeriodicalId":38631,"journal":{"name":"Open Transportation Journal","volume":"14 1","pages":"164-173"},"PeriodicalIF":0.0,"publicationDate":"2020-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43420709","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":"Comparisons Between Braking Experiments and Longitudinal Train Dynamics Using Friction Coefficient and Braking Pressure Modeling in a Freight Train","authors":"D. Choi, R. Jeong, Yongkook Kim, Jangbom Chai","doi":"10.2174/1874447802014010154","DOIUrl":"https://doi.org/10.2174/1874447802014010154","url":null,"abstract":"The simulation of longitudinal train dynamics of a freight train uses the time integration method of EN 14531. For reasonable simulation results, the characteristics of the train and brake equipment must be considered. For the train characteristics, specifications provided by the vehicle manufacturer are used. The braking characteristics are analyzed by friction coefficient tests and a braking pressure model. The friction coefficients of a locomotive and wagons are tested with a dynamo test bench and statistically expanded to account for variability. Freight trains should take into account the braking delay time. To reflect this in the simulation, the brake cylinder pressure pattern model uses pressures and exponential empirical equations measured at selective positions in a train of 50 vehicles. The simulation results are validated in comparison with those of the braking tests of a freight train consisting of 1 locomotive and 20 wagons.","PeriodicalId":38631,"journal":{"name":"Open Transportation Journal","volume":"14 1","pages":"154-163"},"PeriodicalIF":0.0,"publicationDate":"2020-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44156335","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":"Underground Roundabouts: Analysis of Several Layouts for A Case Study in Urban Area","authors":"M. Guerrieri, M. Sartori","doi":"10.2174/1874447802014010143","DOIUrl":"https://doi.org/10.2174/1874447802014010143","url":null,"abstract":"* Address correspondence to the author at the Department of Civil, Environmental and Mechanical Engineering, University of Trento, Italy; Tel: 3339993614; E-mail: marco.guerrieri@unitn.it Persaud [5] observed that the decrease in all accidents was 40% and the reduction in injury accidents was 80%; Troutbeck [6] observed a 74% reduction in injury accidents following the transformation of 73 roundabouts in Victoria, Australia.","PeriodicalId":38631,"journal":{"name":"Open Transportation Journal","volume":"14 1","pages":"143-153"},"PeriodicalIF":0.0,"publicationDate":"2020-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41565901","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":"The Strategic Positioning of Moroccan Seaports: An Application of the Boston Consulting Group Growth-share Matrix","authors":"Mahdi Birafane, Wei Liu, S. Khalikov","doi":"10.2174/1874447802014010133","DOIUrl":"https://doi.org/10.2174/1874447802014010133","url":null,"abstract":"In this context, the purpose of this study is to analyze the competitive position of the eight (largest, most important, busiest) seaports of Morocco in the four-years period from 2014 to 2017 using a dynamic portfolio analysis known as the Boston Consulting Group (BCG) matrix. This study aims to overcome the regional challenges that have a substantial impact on seaport activities by highlighting competitive strategic positioning, which will enable seaport operators to visualize the position of selected ports, monitor their progress, and predict the future trends of the studied ports.","PeriodicalId":38631,"journal":{"name":"Open Transportation Journal","volume":"14 1","pages":"133-142"},"PeriodicalIF":0.0,"publicationDate":"2020-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47729884","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":"A Comparison of Traffic Flow Performance of Roundabouts and Signalized Intersections: A Case Study in Nigde","authors":"H. G. Demir, Y. K. Demir","doi":"10.2174/1874447802014010120","DOIUrl":"https://doi.org/10.2174/1874447802014010120","url":null,"abstract":"\u0000 \u0000 Intersections affect the safety and capacity of urban traffic. Therefore, the design and selection of the type of intersection need to be made very carefully. According to the demand level, a different intersection can be designed. Signalized intersections are one of the intersection types in which the sequence and duration of the flow at the intersection are provided by the lights. Generally, this type of intersection is used on roads with high traffic volume. Modern roundabouts are one of the types of circular intersections that provide advantages over other types of intersection in terms of smooth operation and safety. Modern roundabouts exist in several types today worldwide. In practice, the distinction about the kinds of roundabouts would not be fully clarified; as a result, queuing and delay can be seen as negative effects.\u0000 \u0000 \u0000 \u0000 In this study, to make a distinction and clarify the kinds of roundabouts, first, the roundabouts types are introduced according to geometric and operational aspects. A signalized intersection, where a circular island is placed and also signalized, was investigated in terms of capacity, delay, and emissions located in Niğde. The traffic flow performance of the current state (nested signalized roundabout) was calculated with HCM Method (for signalized intersection) using SIDRA and compared with roundabout solutions of the intersection with HCM6 (for roundabout) method using SIDRA Intersection analysis software.\u0000 \u0000 \u0000 \u0000 From the results of the intersection capacity analysis study based on HCM6, it was seen that the application of a roundabout scenario (intersection considered as a modern roundabout) showed higher performance at the intersections than the intersection having a secondary signal. Capacity increased to 67.8%, the average delay decreased to 72.8% and 95th percentile queue dropped to 82.2%.\u0000 \u0000 \u0000 \u0000 Roundabout controlling instead of a nested signal system can be an example of the increase in the performance of traffic flow. This highlights the importance of choosing the appropriate roundabout design.\u0000","PeriodicalId":38631,"journal":{"name":"Open Transportation Journal","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47593999","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":"Crowdsourcing as a Social Interaction Tool to Stimulate Sustainable Transportation Mode Use","authors":"Shailesh Chandra, Vinay Kumar","doi":"10.2174/1874447802014010109","DOIUrl":"https://doi.org/10.2174/1874447802014010109","url":null,"abstract":"The empirical data were used to validate mode shift behaviors for 77 participants from California State University Long Beach. Data collection spanned over two phases, Phase I followed by Phase II. Each study phase lasted a month. Participants used one of the four modes – personal car, walking, bicycling and public transit to arrive at the university campus. During Phase I, a control group was created, and individual mode choice of participants were obtained. Individual participants in Phase II were assigned short-encrypted distinct names and were asked to post a daily comment on the quality of experience using the mode that was used to arrive at the campus. The participants were asked to post the comments over a “Twitter” page that was used as the crowdsourcing platform for this study. The encrypted name masked the individual identity of the user. Analysis at the end of Phase II showed that there was an overall mode-shift of almost 19% of personal car users to other sustainable modes of walking, bicycling and transit.","PeriodicalId":38631,"journal":{"name":"Open Transportation Journal","volume":"14 1","pages":"109-119"},"PeriodicalIF":0.0,"publicationDate":"2020-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49603465","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":"Data Processing Techniques for Real-Time Traveler Information: Use of Dedicated Short-Range Communications Probes on Suburban Arterial","authors":"Jinhwan Jang","doi":"10.2174/1874447802014010099","DOIUrl":"https://doi.org/10.2174/1874447802014010099","url":null,"abstract":"In this study, data processing methods for addressing the two issues are proposed. After investigating the characteristic of the travel times on the test section, the modified z-score was suggested for censoring outliers contained in probe travel times. To mitigate the time-lag phenomenon, a recurrent neural network, a class of deep learning where temporal sequence data are normally treated, was applied to predict travel times.","PeriodicalId":38631,"journal":{"name":"Open Transportation Journal","volume":"14 1","pages":"99-108"},"PeriodicalIF":0.0,"publicationDate":"2020-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46329953","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}