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Добірка наукової літератури з теми "ROAD INTERSECTIONS"

Автор: Grafiati

Опубліковано: 16 січня 2024

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Статті в журналах з теми "ROAD INTERSECTIONS"

M. Sa'dillah, Pamela Dinar Rahma, and Claudius Sebi Tawong. "ANALYSIS OF THE UNSIGNALIZED INTERSECTION OF MUHARTO ROAD, KI AGENG GRIBIG ROAD, AND MAYJEND SUNGKONO ROAD." Journal Innovation of Civil Engineering (JICE) 4, no. 1 (June 1, 2023): 13–20. http://dx.doi.org/10.33474/jice.v4i1.19272.

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Delays that occur at intersections greatly affect the performance of the road network. The more intersections there are, the greater the delay value will be. One of the intersections in Malang City is the three unsignalized intersections of Muharto Road, Ki ageng Gribig Road, and Mayjend Sungkono Road or also called the Kedungkandang intersection which is the research location. The research aims to determine the performance and project problems at the Kedungkandang Intersection. The data used in the study include road geometric data, traffic volume, acceptance gap, population, and vehicle growth. Based on the 1997 MKJI guide, the results of the study show that the Kedungkandang intersection is included in the level of service criteria C (DS 1.52) with an intersection delay value of 23.29 sec /mp. Based on the processing of gap data with the Raff method, the gap value is 15.1 seconds for the morning, 16.3 seconds for the afternoon, and 17.2 seconds for the afternoon, thus indicating that driver behavior must wait for a gap when entering the main road. The projection results with the placement of right-turn prohibition signs and geometric widening of Muharto Road and Ki Ageng Gribig Road obtained a level of service value of B (DS 0.69) with an Intersection Delay Value of 12.40 sec/smp. Keywords: Gap Acceptance; MKJI 1997; Unsignalized Intersection; Delay.

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Li, P., Y. Li, J. Feng, Z. Ma, and X. Li. "AUTOMATIC DETECTION AND RECOGNITION OF ROAD INTERSECTIONS FOR ROAD EXTRACTION FROM IMAGERY." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2020 (August 21, 2020): 113–17. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2020-113-2020.

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Abstract. Automatic road extraction from remote sensing imagery is very useful for many applications involved with geographic information. For road extraction of urban areas, road intersections offer stable and reliable information for extraction of road network, with higher completeness and accuracy. In this paper, a segmentation-shape analysis based method is proposed to detect road intersections and their branch directions from an image. In the region of interest, it uses the contour shape of the segmented-intersection area to form a feature vector representing its geometric information. The extracted feature vector is then matched with some template vectors in order to find the best matched intersection pattern, obtain the type of intersection and the direction of connected roads. The experimental analysis are carried out with ISPRS Vaihingen and Toronto images. The experimental results show that the proposed method can extract most of the road intersections correctly. For the Vaihingen image, the the completeness and correctness are 81% and 87%, respectfully, while for the Toronto image, the the completeness and correctness are 78% and 85%, respectfully. It can help to build more correct and complete road network.

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Sui, Haigang, Ning Zhou, Mingting Zhou, and Liang Ge. "Vector Road Map Updating from High-Resolution Remote-Sensing Images with the Guidance of Road Intersection Change Detection and Directed Road Tracing." Remote Sensing 15, no. 7 (March 30, 2023): 1840. http://dx.doi.org/10.3390/rs15071840.

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Updating vector road maps from current remote-sensing images provides fundamental data for applications, such as smart transportation and autonomous driving. Updating historical road vector maps involves verifying unchanged roads, extracting newly built roads, and removing disappeared roads. Prior work extracted roads from a current remote-sensing image to build a new road vector map, yielding inaccurate results and redundant processing procedures. In this paper, we argue that changes in roads are closely related to changes in road intersections. Hence, a novel changed road-intersection-guided vector road map updating framework (VecRoadUpd) is proposed to update road vector maps with high efficiency and accuracy. Road-intersection changes include the detection of newly built or disappeared road junctions and the discovery of road branch changes at each road junction. A CNN-based intersection-detection network (CINet) is adopted to extract road intersections from a current image and an old road vector map to discover newly built or disappeared road junctions. A road branch detection network (RoadBranchNet) is used to detect the direction of road branches for each road junction to find road branch changes. Based on the discovery of direction-changed road branches, the VecRoadUpd framework extracts newly built roads and removes disappeared roads through directed road tracing, thus, updating the whole road vector map. Extensive experiments conducted on the public MUNO21 dataset demonstrate that the proposed VecRoadUpd framework exceeds the comparative methods by 11.01% in pixel-level Qual-improvement and 13.85% in graph-level F1-score.

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Dwi Ratnaningsih, Rudy Ariyanto, Supiyono,. "PENGARUH KEMACETAN DI SIMPANG SABILILLAH TERHADAP IMPLEMENTASI CITRA LALU LINTAS DI SIMPANG PROGRESIF." PROKONS Jurusan Teknik Sipil 9, no. 2 (August 31, 2015): 114. http://dx.doi.org/10.33795/prokons.v9i2.97.

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Progress of a country in line with the progress of traffic (transport). Fluency in traffic is determined by the smoothness of traffic on the road. Problems often arise on the highway is congestion at the intersection. Neither was signalized intersections and signalized intersections. Problems at the intersection is less accuracy green flame at the intersection with the number of vehicles in a segment. A road with high traffic volume vehicle green flame low while other road traffic volume small green flame length. So in a long queue roads, while other roads are deserted while still green flame. This study aims to minimize the occurrence of conflic at the intersection of green flame. Research will make iterations in the intersection, where a road section which will be nominated densely green flame, the flame of the green according to the volume of traffic on these roads. Each road will be a green flame in accordance with the volume of traffic, without having to change any program there is a change in traffic volume.The degree of saturation of the calculation obtained by ....Keywords: roads, hight traffic, progressive intersection, degree saturation

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Liu, Yizhi, Rutian Qing, Yijiang Zhao, and Zhuhua Liao. "Road Intersection Recognition via Combining Classification Model and Clustering Algorithm Based on GPS Data." ISPRS International Journal of Geo-Information 11, no. 9 (September 14, 2022): 487. http://dx.doi.org/10.3390/ijgi11090487.

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Road intersections are essential to road networks. How to precisely recognize road intersections based on GPS data is still challenging in intelligent transportation systems. Road intersection recognition involves detecting intersections and recognizing its scope. There are few works on intersections’ scope recognition. The existing methods always focus on road intersection detection. It includes two parts: one is selecting turning points from GPS data and extracting their geometric features, another is clustering them into center coordinates of road intersections. However, the accuracy of road intersection detection still has improvement room due to two drawbacks: (1) Besides geometric features, spatial features explored from GPS data and the interactions among all features are also important to represent intersections’ semantics more accurately, and (2) How to capture the points around intersections for clustering has great impact on the accuracy of intersection detection. To solve the preceding problems, we propose a novel approach for road intersection recognition via combining a classification model and clustering algorithm based on GPS data, which involves detecting the center coordinate and computing the radius of the intersection. Firstly, we distil geometric features and spatial features from historical GPS points. These features are inputted into the Extreme Deep Factorization Machine (xDeepFM) model which is applied for capturing the GPS points nearby road intersections. Secondly, the preceding points are clustered into center coordinates of road intersections by the Density-Based Spatial Clustering of Applications with Noise algorithm (DBSCAN). Thirdly, we present a new method of radius computing by integrating Delaunay triangulation with circle shape structure. Experiments are carried out on the GPS data of Chengdu, China. Compared with some state-of-the-art methods, our approach achieves higher accuracy on road intersection recognition based on GPS data. The precision, recall, and f-measure of our proposed center coordinates detection method are respectively 99.0%, 92.7%, and 95.8% when the matching area’s radius is 30 m. Moreover, the error of the proposed radius calculation method is less than 26.5%.

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Zhang, Zhonggui, Yi Ming, and Gangbing Song. "A New Approach to Identifying Crash Hotspot Intersections (CHIs) Using Spatial Weights Matrices." Applied Sciences 10, no. 5 (February 29, 2020): 1625. http://dx.doi.org/10.3390/app10051625.

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In this paper we develop a new approach to directly detect crash hotspot intersections (CHIs) using two customized spatial weights matrices, which are the inverse network distance-band spatial weights matrix of intersections (INDSWMI) and the k-nearest distance-band spatial weights matrix between crash and intersection (KDSWMCI). This new approach has three major steps. The first step is to build the INDSWMI by forming the road network, extracting the intersections from road junctions, and constructing the INDSWMI with road network constraints. The second step is to build the KDSWMCI by obtaining the adjacency crashes for each intersection. The third step is to perform intersection hotspot analysis (IHA) by using the Getis–Ord Gi* statistic with the INDSWMI and KDSWMCI to identify CHIs and test the Intersection Prediction Accuracy Index (IPAI). This approach is validated by comparison of the IPAI obtained using open street map (OSM) roads and intersection-related crashes (2008–2017) from Spencer city, Iowa, USA. The findings of the comparison show that higher prediction accuracy is achieved by using the proposed approach in identifying CHIs.

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Lu, Ting, Dan Zhao, and Yanhong Yin. "An Intersection Importance Estimation Method Based on the Road Network Topology." Open Civil Engineering Journal 12, no. 1 (July 6, 2018): 239–49. http://dx.doi.org/10.2174/1874149501812010239.

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Introduction: The expansion of road network and continuous increase of vehicle ownership challenge the performance of routine traffic control. It is necessary to make a balanced adjustment and control from the perspective of the road network to disperse the traffic flow on the entire road network. Methods: This paper develops a method to quantify the intersections’ importance at a global level based on the road network topology, which is the location of the intersection in the road network and the structural characteristics of the intersection decided by the traffic movement. The priority order in traffic signal coordination is the sorting results of intersection’s importance. The proposed method consists of two consecutive algorithms. Firstly, the graph connectivity of network is defined based on the shortest path distance and spatial connectivity between adjacent intersections. Secondly, The Importance Estimation Model (IEM) is built, which is the function of the importance indexes of current intersection and its neighboring intersections. A simulated case of a six by eight grid network was employed to evaluate the effectiveness of the proposed method in TRANSYT. Results and Conclusion: The results show that the Importance Estimation Model (IEM) minimized the measure of effectiveness compared with the schemes obtained by the volume sorting method, the saturation degree sorting method, and the method SMOO. It also created a higher frequency of small queues than the other methods.

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Zhang, Caili, Longgang Xiang, Siyu Li, and Dehao Wang. "An Intersection-First Approach for Road Network Generation from Crowd-Sourced Vehicle Trajectories." ISPRS International Journal of Geo-Information 8, no. 11 (October 24, 2019): 473. http://dx.doi.org/10.3390/ijgi8110473.

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Extracting highly detailed and accurate road network information from crowd-sourced vehicle trajectory data, which has the advantages of being low cost and able to update fast, is a hot topic. With the rapid development of wireless transmission technology, spatial positioning technology, and the improvement of software and hardware computing ability, more and more researchers are focusing on the analysis of Global Positioning System (GPS) trajectories and the extraction of road information. Road intersections are an important component of roads, as they play a significant role in navigation and urban planning. Even though there have been many studies on this subject, it remains challenging to determine road intersections, especially for crowd-sourced vehicle trajectory data with lower accuracy, lower sampling frequency, and uneven distribution. Therefore, we provided a new intersection-first approach for road network generation based on low-frequency taxi trajectories. Firstly, road intersections from vector space and raster space were extracted respectively via using different methods; then, we presented an integrated identification strategy to fuse the intersection extraction results from different schemes to overcome the sparseness of vehicle trajectory sampling and its uneven distribution; finally, we adjusted road information, repaired fractured segments, and extracted the single/double direction information and the turning relationships of the road network based on the intersection results, to guarantee precise geometry and correct topology for the road networks. Compared with other methods, this method shows better results, both in terms of their visual inspections and quantitative comparisons. This approach can solve the problems mentioned above and ensure the integrity and accuracy of road intersections and road networks. Therefore, the proposed method provides a promising solution for enriching and updating navigable road networks and can be applied in intelligent transportation systems.

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Wang, Gang, Yi Zhang, and Geng Sheng Huang. "A Study of Signal Timing Control Based on the Collaborative Strategy of Road Green Wave Effect and Path Selection Entropy." Advanced Materials Research 753-755 (August 2013): 1970–75. http://dx.doi.org/10.4028/www.scientific.net/amr.753-755.1970.

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With the growth of urban road traffic volume and the increase of road network density, correlation between adjacent road intersections is becoming more and more obvious. An intersection traffic signal adjustment tends to affect the smooth traffic flow of a number of adjacent intersections. Its congestion may gradually spread to a few blocks and regions all around the intersection. Therefore, increasingly high demands for urban traffic signal control make a variety of advanced control technology integrated, so as to adjust the intersection control parameter and accordingly achieve a dynamic coordination control over the city traffic. Hopefully, it can satisfy traffic demands and achieve a new dynamic balance between road traffic and transport demand. This paper focuses on the signal timing control over green time extension at adjacent intersections of trunk road by using the collaborative strategy of road green wave effect and path selection entropy, in order to solve the problem of coupling between adjacent intersections, so as to realize the signal coordination control on trunk road. This algorithm makes Signal Timing more flexible.

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Ahn, Joonwoo, Yangwoo Lee, Minsoo Kim, and Jaeheung Park. "Vision-Based Branch Road Detection for Intersection Navigation in Unstructured Environment Using Multi-Task Network." Journal of Advanced Transportation 2022 (August 5, 2022): 1–13. http://dx.doi.org/10.1155/2022/9328398.

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Autonomous vehicles need a driving method to be less dependent on localization data to navigate intersections in unstructured environments because these data may not be accurate in such environments. Methods of distinguishing branch roads existing at intersections using vision and applying them to intersection navigation have been studied. Model-based detection methods recognize patterns of the branch roads, but are sensitive to sensor noise and difficult to apply to various complex situations. Therefore, this study proposes a method for detecting the branch roads at the intersection using deep learning. The proposed multi-task deep neural network distinguishes the branch road into a shape of rotated bounding boxes and also recognizes the drivable area to consider obstacles inside the box. Through the output of the network, an occupancy grid map consisting of one branch road at an intersection is obtained, which can be used as an input to the existing motion-planning algorithms that do not consider intersections. Experiments in real environments show that the proposed method detected the branch roads more accurately than the model-based detection method, and the vehicle drove safely at the intersection.

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Дисертації з теми "ROAD INTERSECTIONS"

Zhang, Zheshuo. "Dynamics of road vehicles crossing rail-road intersections." Thesis, Queensland University of Technology, 2019. https://eprints.qut.edu.au/132688/2/Zheshuo%20Zhang%20Thesis.pdf.

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This project was a step forward in redesigning level crossing for improved safety of level crossing infrastructure. A vehicle-tire-obstacle model capable of predicting the vehicle dynamic behaviour as well as the tire-obstacle contact forces was developed from basic equations of motion. The thesis investigated the profile of redesigned level crossing from the perspective of road vehicle dynamics including the safety risk to the occupant and the dislodgement risk of the freights in the road vehicles. It was shown that the redesigned level crossings can save lives and avoid damages to trains, road vehicles and the related infrastructure.

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Ismail, Emad Abbas. "Highway intersections with alternative priority rules." Thesis, University of Bradford, 1989. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.277143.

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Arndt, Owen Kingsley. "Relationship between unsignalised intersection geometry and accident rates." Thesis, Queensland University of Technology, 2004. https://eprints.qut.edu.au/15815/1/Owen_Arndt_Thesis.pdf.

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The aim of this research is to determine the effect of unsignalised intersection geometry on the rates of the various types of accidents occurring at unsignalised intersections. A literature review has identified that there is little consistency between the results of previous studies. Some studies found that particular parameters had an opposite effect to what was expected. With this in mind, the research identified reasons for these results and developed two basic approaches to mitigate some of the problems with multi-factor type studies. These approaches are 'maximise the efficiency of data collection' and 'develop techniques for analysing less than perfect data'. A database consisting of 206 unsignalised intersection sites from throughout Queensland was used for analysis. The outcome of this research confirms the validity of several of the current design standards for unsignalised intersections, in addition to identifying new engineering procedures.

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Arndt, Owen Kingsley. "Relationship Between Unsignalised Intersection Geometry and Accident Rates." Queensland University of Technology, 2004. http://eprints.qut.edu.au/15815/.

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Hounsell, Nicholas Brian. "The design and performance of signal controlled intersections." Thesis, University of Southampton, 1989. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.328350.

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Adedokun, Adeyemi. "Application of Road Infrastructure Safety Assessment Methods at Intersections." Thesis, Linköpings universitet, Kommunikations- och transportsystem, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-127334.

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Traffic safety at intersections is a particularly difficult phenomenon to study, given the fact that accidents occur randomly in time and space thereby making short-term measurement, assessment and comparison difficult. The EU directive 2008/96/EC introduced road infrastructure safety management, which offers a five layer structure for developing safer road infrastructure has been used to develop tools for accident prediction and black spot management analysis which has been applied in this work to assess the safety level of intersections in Norrköping city in Sweden. Accident data history from STRADA (Swedish Traffic Accident Data Acquisition) and the network demand model for Norrköping city were used to model black spots and predict the expected number of accidents at intersections using PTV Visum Safety tool, after STRADA accident classification was restructured and the Swedish accident prediction model (APM) was configured and tested to work within the tool using the model from the Swedish road administration (SRA). The performance of the default (Swiss) and the Swedish APM was compared and identified locations with the high accident records, predicted accident counts and traffic volumes were audited using qualitative assessment checklist from Street-Audit tool. The results from these methods were analysed, validated and compared. This work provides recommendations on the used quantitative and qualitative methods to prevent accident occurrence at the identified locations.

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Lef��vre, St��phanie. "Risk Estimation at Road Intersections for Connected Vehicle Safety Applications." Phd thesis, Universit�� de Grenoble, 2012. http://tel.archives-ouvertes.fr/tel-00765930.

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Les intersections sont les zones les plus dangereuses du r��seau routier. Les ��tudes d'accidentologie montrent que la plupart des accidents aux intersections sont caus��s par des erreurs des conducteurs, et qu'une majorit�� d'accidents pourraient ��tre ��vit��s gr��ce �� l'utilisation de syst��mes d'aide �� la conduite. Dans ce cadre, les communications inter-v��hiculaire sont une technologie particuli��rement prometteuse. Le partage d'informations entre les v��hicules via des liens sans fil permet �� chaque v��hicule de percevoir son environnement au-del�� des limites de champ de vision de ses capteurs embarqu��s. Il en r��sulte une repr��sentation de l'environnement plus ��tendue dans l'espace et dans le temps, ce qui am��liore la compr��hension de situation et permet d'anticiper le danger. Cette th��se aborde le probl��me de l'estimation du risque sous un angle nouveau : elle propose une structure de raisonnement pour analyser les sc��nes routi��res et le risque de collision �� un niveau s��mantique, contrairement aux approches classiques qui raisonnent au niveau des trajectoires. Le risque est calcul�� en estimant les intentions des conducteurs et en d��tectant les conflits, sans avoir �� pr��dire les trajectoires futures des v��hicules. Plus pr��cis��ment, la d��tection des situations dangereuses est bas��e sur la comparaison entre ce que les conducteurs ont l'intention de faire et ce que les conducteurs devraient faire d'apr��s les r��gles de la circulation. Ce raisonnement est r��alis�� de mani��re probabiliste afin de prendre en compte les incertitudes sur les mesures capteur et les ambig��it��s sur l'interpr��tation de la sc��ne. En th��orie ce raisonnement peut ��tre appliqu�� tout type de sc��ne routi��re ; dans cette th��se nous pr��sentons son application aux intersections. Le mod��le propos�� prend en compte l'influence que la man��uvre d'un v��hicule exerce sur la man��uvre des autres v��hicules. Il incorpore aussi des informations sur l'influence de la g��om��trie et topologie de l'intersection sur le comportement d'un v��hicule. L'approche propos��e a ��t�� valid��e par des tests en environnement r��el avec des v��hicules communicants, ainsi qu'en simulation. Les r��sultats montrent que l'algorithme est capable de d��tecter les situations dangereuses et qu'il est compatible avec des applications s��curitaires temps-r��el.

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Ahn, Heejin. "Safety verification and control for collision avoidance at road intersections." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/119339.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2018.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 145-149).
Car crashes cause a large number of fatalities and injuries, with about 33,000 people killed and 2.3 million injured in the United States every year. To prevent car crashes, the government and automotive companies have taken initiatives to develop and deploy communications among vehicles and between vehicles and infrastructure. By using such communications, we design centralized coordinators at road intersections, called supervisors, that monitor the dynamical state of vehicles and the current input of drivers and override them if necessary to prevent a collision. The primary technical problem in the design of such systems is to determine if the current drivers' input will cause an unavoidable future collision, in which case the supervisor must override the drivers at the current time to prevent the collision. This problem is called safety verification problem which is known to be computationally intractable for general dynamical systems. Our approach to solving the safety verification problem is to translate it to a computationally more tractable scheduling problem. When modeling an intersection as a single conflict area inside which the paths of vehicles intersect, we exactly solve the scheduling problem with algorithms that can handle a small number of vehicles in real-time. For a larger number of vehicles or with more complex intersection models, we approximately solve it within quantified approximation bounds by using mixed integer linear programming (MILP) formulations that, despite the combinatorial complexity, can be solved in real-time by available software such as CPLEX. Based on the solutions to the safety verification problem, we design a supervisor and prove that it ensures safety and is nonblocking, another major challenge of verification-based algorithms. We validate the supervisor using computer simulations and experiments.
by Heejin Ahn.
Ph. D.

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Hoque, Md Shamsul. "The modelling of signalised intersections in developing countries." Thesis, University of Southampton, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.261570.

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LeDew, Christopher. "SAFETY EFFECTS OF TRAFFIC SIGNAL INSTALLATIONS ON STATE ROAD INTERSECTIONS IN NORTHEAST FLORIDA." Master's thesis, University of Central Florida, 2006. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/3446.

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The purpose of this thesis is to explore how the installations of traffic signals affect crash experience at intersections, to identify those factors which help predict crashes after a signal is installed, and to develop a crash prediction model. It is the intent of this thesis to supplement the Manual on Uniform Traffic Control Devices Signal Warrant procedure and aid the traffic engineer in the signal installation decision making process. Crash data, as well as operational and geometric factors were examined for 32 state road intersections in the northeast Florida area before and after signal installation. Signal warrant studies were used as sources for traffic volumes, geometric information and crash history, before signal installation. The Florida Department of Transportation's Crash Analysis Reporting System (CARS) was used to gather crash data for the time period after signal installation. On average, the 32 intersections experienced a 12% increase in the total number of crashes and a 26% reduction in crash rate after signals were installed. The change in the number of crashes was not significant, but the rate change was significant with 90% confidence. Angle crash frequency dropped by 60% and the angle crash rate dropped by 66%, both are significant. Left-turn crashes dropped by 8% and their rate by 16%, although neither was significant. Rear-end crashes increased by 86% and the rear-end crash rate decreased by 5%. Neither of these changes was statistically significant. When crash severity was examined, it was found that the number of injury crashes increased by 64.8% and the rate by only 0.02%. Neither change was significant. Both the number of fatal crashes and the rate decreased by 100% and were significant. Property Damage Only (PDO) crashes increased by 96%, after signalization, but this change was not significant. The PDO rate, however, decreased by 46.5% and is significant. Operational factors such as AADT, turning movement counts, and speed limits; and geometric factors such as medians, turn lanes and numbers of lanes were considered to determine their effect on crashes at signalized intersections. Smaller roads, with low AADT, fewer lanes, and a rural character were found to benefit from signalization more than busier urbanized roads, in terms of crash rate reduction. The AADT, roadway cross section, number of lanes, medians, speed limit and left turn volume were all found to be important factors influencing crash rates. This thesis recommends: 1) the use of crash prediction models to supplement the MUTCD Crash Warrant, 2) the addition of a left-turn warrant to the MUTCD signal warranting procedure, and 3) development of an intersection database containing crash data as well as operational and geometric information to aid in future research.
M.S.C.E.
Department of Civil and Environmental Engineering
Engineering and Computer Science
Civil Engineering

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Книги з теми "ROAD INTERSECTIONS"

Rao, D. Panduranga. Urban road safety. New Delhi: Inter-India Publications, 1997.

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Montana. Dept. of Highways. Department of Highways, IR 90-8(114)443, Shiloh Road Interchange. Helena, Mont: Dept. of Highways, 1989.

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Costello, Michele. The land use potential of national road interchanges. Dublin: University College Dublin, 1994.

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Glembiewski, G. A. Intersection safety: A manual for local rural road owners. Washington, DC: U.S. Dept. of Transportation, Federal Highway Administration, 2011.

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Embedded LEDs in signs. Washington, D.C.]: U.S. Dept. of Transportation, Federal Highway Administration, 2009.

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LED raised pavement markers. Washington, D.C.]: U.S. Dept. of Transportation, Federal Highway Administration, 2009.

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Maryland. State Highway Administration. U.S. 301 transportation study Northern Corridor from the US 301/MD 5 interchange at T.B. to US 50 : public hearing, June 9, 1988, Bowie High School, 1500 Annapolis Road, Bowie, MD 20715. [Baltimore, MD]: State Highway Administration, 1998.

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Montana. Dept. of Transportation. Shiloh Road Interchange Project, IR 90-8(114)443, Yellowstone County, Montana: Draft environmental impact statement. Helena, Mont.]: The Dept.?, 1992.

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United States. Federal Highway Administration. and Maryland State Highway Administration, eds. Environmental assessment for contract no. P874-101-372: I-95 (Capital Beltway) at Ritchie Marlboro Road, Prince George County, Maryland. [Washington, D.C.]: U.S. Dept. of Transporation, Federal Highway Administartion, 1990.

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Administration, Maryland State Highway. Combined location/design public hearing: MD 28/MD 97 (Norbeck Road/Georgia Avenue) : Dec. 9, 2002, Redland Middle School, Rockville, Maryland. Baltimore, Md: Maryland State Highway Administration, 2002.

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Частини книг з теми "ROAD INTERSECTIONS"

Richter, Thomas. "Intersections." In Road Planning - Freeways and Country Roads, 91–187. Wiesbaden: Springer Fachmedien Wiesbaden, 2022. http://dx.doi.org/10.1007/978-3-658-35189-2_10.

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Orgeron, Devin. "Epilogue New Directions and Intersections." In Road Movies, 183–99. New York: Palgrave Macmillan US, 2008. http://dx.doi.org/10.1057/9780230610217_8.

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Lenné, Michael G., and J. Ashleigh Filtness. "EAST at Road Intersections." In Systems Thinking in Practice, 135–55. First edition. | Boca Raton, FL : CRC Press/Taylor & Francis: CRC Press, 2018. http://dx.doi.org/10.1201/9781315104683-7.

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Efthymiopoulos, Marios P. "Strategic Complexity and Comprehension: “The Road to a New Security Architecture”." In Strategic Intersections, 21–41. Belgrade ; Bucharest: University of Defence, Strategic Research Institute ; Institute for Political Studies of Defense ; Military History, 2023. http://dx.doi.org/10.18485/isimod_strint.2023.ch1.

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Richter, Thomas. "Integrated Consideration of Road Sections and Intersections." In Road Planning - Freeways and Country Roads, 189. Wiesbaden: Springer Fachmedien Wiesbaden, 2022. http://dx.doi.org/10.1007/978-3-658-35189-2_11.

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Alphand, F., U. Noelle, and B. Guichet. "Roundabouts and Road Safety." In Intersections without Traffic Signals II, 107–25. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-84537-6_9.

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Tuohy, Sue. "Musical Intersections: Local Festivals As Cosmopolitan Centers of Exchange." In Silk Road Studies, 121–25. Turnhout: Brepols Publishers, 2002. http://dx.doi.org/10.1484/m.srs-eb.4.00257.

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Dafrallah, Safaa, Aouatif Amine, Stéphane Mousset, and Abdelaziz Bensrhair. "Driver Behavior Assistance in Road Intersections." In Embedded Systems and Artificial Intelligence, 53–60. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-0947-6_6.

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Fathi, Alireza, and John Krumm. "Detecting Road Intersections from GPS Traces." In Geographic Information Science, 56–69. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15300-6_5.

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Min, Fanlei, Guan Wang, Liantao Wang, and Jing Liu. "Automatic Lane Recognition for Surveillance at Road Intersections." In Emerging Trends in Intelligent and Interactive Systems and Applications, 751–59. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-63784-2_93.

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Тези доповідей конференцій з теми "ROAD INTERSECTIONS"

Martiakhin, Dmitri, Tatiana Komarova, Dmitri Nemchinov, and Alexandr Mikhailov. "U-turn capacity at signalized intersections." In 6th International Conference on Road and Rail Infrastructure. University of Zagreb Faculty of Civil Engineering, 2021. http://dx.doi.org/10.5592/co/cetra.2020.1012.

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The article presents the results of a study of the intersections capacity, at which the U-turn lane is organized, depending on the traffic flow volume and its organization. Signalized intersection capacity depends on traffic flow, geometry, traffic organization type, driver’s behaviour and headways between drivers in each traffic lane. To analyse signalized intersection capacity it is necessary to determine traffic lanes saturation flow. The study presents field observation analyses of headways between drivers and saturation flow on U-turn lanes at signalised intersections in Moscow. To conduct research and identify patterns, intersections in Moscow were chosen with different conditions and different organization of the U-turns.

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Cvitanić, Dražen, and Biljana Maljković. "The impact of different saturation headway values on intersection capacity." In 6th International Conference on Road and Rail Infrastructure. University of Zagreb Faculty of Civil Engineering, 2021. http://dx.doi.org/10.5592/co/cetra.2020.996.

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Elements of the city road network that determine its capacity are signalized intersections. Their capacity depends of many factors: traffic volume and distribution, traffic flow structure, signal timing, and number of bicyclists and pedestrians. However, the starting parameter for calculation of intersection capacity is saturation headway. This research explores the influence of weather conditions and purpose of trip on saturation headway. Saturation headways were determined on few intersections in the morning peak hour of working and weekend day, in good and bad weather conditions. The impact of different trip purposes and different weather conditions on intersection capacity is analysed, as well as the influence of using mean and median values of saturation headway when calculating the intersection capacity.

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Martínez, Víctor M. G., Moisés R. N. Ribeiro, and Divanilson R. Campelo. "Intelligent Road Intersections: A Case for Digital Twins." In Workshop Brasileiro de Cidades Inteligentes. Sociedade Brasileira de Computação - SBC, 2022. http://dx.doi.org/10.5753/wbci.2022.223311.

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Smart cities are based on complex systems that use legacy infrastructure and modern and intelligent solutions to achieve a highly efficient functioning of society in several verticals. In the context of road intersections, the main objective is to offer safe, efficient, and reliable mobility services for all agents involved in the physical space (infrastructure, vehicles, and pedestrians). The digital twin paradigm has recently been considered by both academia and industry as a means for reaching intelligent transportation solutions. The article makes a case for digital twins in intelligent intersection modeling as it is expected to consolidate real-time monitoring, control, and management of intelligent intersections. The design of a framework and the development of a testbed are presented in this paper. New functionalities for the safe operation of the road intersection are the expected results of this proposal.

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Šarić, Ammar, Sanjin Albinović, Mirza Pozder, Suada Džebo, Žanesa Ljevo, and Emira Muftić. "Improved applicability diagram of two-lane roundabouts." In 6th International Conference on Road and Rail Infrastructure. University of Zagreb Faculty of Civil Engineering, 2021. http://dx.doi.org/10.5592/co/cetra.2020.1026.

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When reconstructing existing or constructing completely new intersections, the main problem is determining the type of future intersection. Capacity is one of the key indicators that influence the choice of traffic control type. In this paper, using different scenarios of theoretical traffic flow distributions and traffic volume scenarios, the authors have determined the applicability area of two-lane roundabouts. The results obtained were used to improve the existing applicability diagrams of the various intersection types presented in several issues of US Highway Capacity Manuals (US HCM). Capacity in each scenario is determined using HCM 2010 and Hagring methods with practically obtained values of the time gap acceptance parameters.

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Chouiekh, Chaymae, Ali Yahyaouy, My Abdelouahed Sabri, Abdellah Aarab, and Badraddine Aghoutane. "Road Traffic Management: Control of Intersections." In INTERNATIONAL CONFERENCE ON BIG DATA, MODELLING AND MACHINE LEARNING (BML'21). SCITEPRESS - Science and Technology Publications, 2021. http://dx.doi.org/10.5220/0010731800003101.

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Matragos, Vassilios, Konstantinos Apostoleris, Basil Psarianos, and Stergios Mavromatis. "Risk ranking on existing two-lane rural roads with respect to alignment and at grade intersections." In 6th International Conference on Road and Rail Infrastructure. University of Zagreb Faculty of Civil Engineering, 2021. http://dx.doi.org/10.5592/co/cetra.2020.1309.

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The objective of this paper is the elaboration of a suitable methodology capable of deploying elements that characterize the existing infrastructure on two-lane rural roads, regarding road geometric elements (horizontal and vertical alignment, superelevation, sight distance), as well as location and geometric elements of intersections with the scope to evaluate the built-in road safety. The overall target is the utilization of these elements to lead to evaluation coefficients that point out the risk level of the examined road sections, as well as the critical areas, in terms of safety levels, curved sections and intersections. In this context, a hierarchy of critical parameters affecting the risk rating of a road network with respect to geometric design and at-grade intersections was primarily carried out. Appropriate mathematical equations were created for each parameter, based on current road design guidelines and the corresponding Crash Reduction Factors (CRF) presented in the literature. Initially, case studies were conducted, out of which special diagrams were produced to assess the risk level of each parameter. Subsequently, a basic statistical analysis of the results was carried out , using regression factors aiming at developing an appropriate mathematical model for the estimation of the risk level. The same analysis was performed for each parameter separately and appropriate weight coefficients were sought in order to obtain a combined rating that characterizes each road section, while at the same time identifies those critical intersections that present high probability of accident occurrence. Finally, data were collected from a significant sample of the existing two-lane road network of Greece, about 1000km of road network with more than 4000 intersections (unpaved road intersections were also included), in order to assess the results of the proposed methodology.

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Ninos, Georgios, and José Diogo Forte de Oliveira Luna. "Model predictive control for connected and autonomous vehicles at road intersections." In Congresso Brasileiro de Automática - 2020. sbabra, 2020. http://dx.doi.org/10.48011/asba.v2i1.1420.

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This work presents a model predictive control (MPC) to coordinate connected and autonomous vehicles (CAVs) with a Vehicle-to-Vehicle (V2V) communication when they enter intersections. With the purpose of minimizing energy as well as passing the intersection smoothly, it uses an individual linear quadratic optimal controller for each CAV, with a predefined path, that will respect mixed-integer linear constraints to guarantee collision avoidance in relation to the nearby vehicles. This method solves different scenarios with a different number of CAVs crossing the intersection, coming from more than one road, including a platoon formation. The results show that MPC is an efficient technique to integrate multiple CAVs to collaborate with the mutual objective of join merging zones without accidents.

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Iwase, Tatsuya, Sebastian Stein, Enrico H. Gerding, and Archie Chapman. "A Polynomial-time Decentralised Algorithm for Coordinated Management of Multiple Intersections." In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/534.

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Autonomous intersection management has the potential to reduce road traffic congestion and energy consumption. To realize this potential, efficient algorithms are needed. However, most existing studies locally optimize one intersection at a time, and this can cause negative externalities on the traffic network as a whole. Here, we focus on coordinating multiple intersections, and formulate the problem as a distributed constraint optimisation problem (DCOP). We consider three utility design approaches that trade off efficiency and fairness. Our polynomial-time algorithm for coordinating multiple intersections reduces the traffic delay by about 41 percentage points compared to independent single intersection management approaches.

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Nedevska, Ivona, Riste Ristov, Zlatko Zafirovski, Slobodan Ognjenovic, and Vasko Gacevski. "Analysis of the capacity and level of service for urban intersection." In 7th International Conference on Road and Rail Infrastructure. University of Zagreb Faculty of Civil Engineering, 2022. http://dx.doi.org/10.5592/co/cetra.2022.1435.

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The augmentation of motorization level leads us to the need for mobility and demands better infrastructure, in urban and suburban areas. The complexity of this problem is especially notable in urban areas where the space delimitations, functional characteristics and different transportation must be considered. The intersection between Partizanska street and Boris Krajger street, in Shtip, has been analysed with the methodology for capacity and level of service, according to international software and manuals. Both streets are with one lane per direction, and lately it is very frequent intersections in Shtip. Number of vehicles is determined by measuring the traffic, and those inputs are used to analyse three solutions: the current solution (unsignalized intersection), four legged intersection and roundabout both with boulevard profile for the main corridor and two way street for the secondary corridor. Calculations are based on custom measurements within a week.

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Mo, Yangan, Mengqi Wang, Tingting Zhang, and Qinyu Zhang. "Autonomous Cooperative Vehicle Coordination at Road Intersections." In 2018 IEEE International Conference on Communication Systems (ICCS). IEEE, 2018. http://dx.doi.org/10.1109/iccs.2018.8689201.

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Звіти організацій з теми "ROAD INTERSECTIONS"

Savolainen, Peter, and Andrzej Tarko. Safety of Intersections on High-Speed Road Segments with Superelevation. West Lafayette, IN: Purdue University, 2004. http://dx.doi.org/10.5703/1288284313307.

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Pulugurtha, Srinivas S., Abimbola Ogungbire, and Chirag Akbari. Modeling and Evaluating Alternatives to Enhance Access to an Airport and Meet Future Expansion Needs. Mineta Transportation Institute, April 2023. http://dx.doi.org/10.31979/mti.2023.2120.

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The continued growth of air travel calls for the incessant construction effort at many airports and their surroundings. Thus, there is a need to determine how airports can better manage existing infrastructure to accommodate this growth. This study, therefore, focuses on (1) investigating how changes in transportation infrastructure have affected travel time reliability (TTR) of the surrounding road network within the airport vicinity over time, and, (2) exploring selected unconventional intersection designs and proposing new inbound/outbound access routes from the nearby major roads to the airport. The efficiency of road networks that surrounds large airports is discussed using Charlotte Douglas International Airport (CLT) as the case study. Firstly, an assessment of how transportation projects impact link-level travel time reliability (TTR) was performed using historical data. Secondly, an assessment of how future transportation projects would affect the traffic in the airport vicinity was performed. A simulation network was developed using the Vissim software, where the peak-hour turning movement counts were used with the existing signal design to replicate and calibrate the base scenario. Unconventional intersection designs such as continuous flow intersections (CFI), mini-roundabouts, and restricted crossing U-turn (RCUT) intersections were considered along with selected bridge design options to determine the impact on TTR. The results were compared with the conventional signalized intersection design. The connectivity projects led to an increase in TTR measures at most of the links within its vicinity after the project’s completion of the project. Similarly, parking areas exhibited the same characteristics, including those used by ridesharing companies. The simulation model showed that unconventional designs like RCUT and direct entry-exit ramps effectively reduced delay as well as the number of stops, increasing our understanding of how expansion projects affect TTR and potentially improving infrastructure optimization.

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Tarko, Andrzej, and Mayank Kanodia. Hazard Elimination Program - Manual on Improving Safety of Indiana Road Intersections and Sections; Volume 1: Research Report and Volume 2: Guidelines for Highway SafetyVolume 2: Guidelines for Improving Safety of Indiana Road Intersections and Sections. West Lafayette, IN: Purdue University, 2004. http://dx.doi.org/10.5703/1288284313235.

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Ahmad, Noshin S., Raul Pineda-Mendez, Fahad Alqahtani, Mario Romero, Jose Thomaz, and Andrew P. Tarko. Effective Design and Operation of Pedestrian Crossings. Purdue University, 2022. http://dx.doi.org/10.5703/1288284317438.

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Pedestrians are vulnerable road users since they are prone to more severe injuries in any vehicular collision. While innovative solutions promise improved pedestrian safety, a careful analysis of local conditions is required before selecting proper corrective measures. This research study had two focuses: (1) methodology to identify roads and areas in Indiana where the frequency and severity of pedestrian collisions are heightened above the acceptable level, and (2) selecting effective countermeasures to mitigate or eliminate safety-critical conditions. Two general methods of identifying specific pedestrian safety concerns were proposed: (1) area-wide analysis, and (2) road-focused analysis. A suitable tool, Safety Needs Analysis Program (SNAP), is currently under development by the research team and is likely the future method to implement an area-wide type of analysis. The following models have been developed to facilitate the road-focused analysis: (1) pedestrian crossing activity level to fill the gap in pedestrian traffic data, and (2) crash probability and severity models to estimate the risk of pedestrian crashes around urban intersections in Indiana. The pedestrian safety model was effectively utilized in screening and identifying high-risk urban intersection segments for safety audits and improvements. In addition, detailed guidance was provided for many potential pedestrian safety countermeasures with specific behavioral and road conditions that justify these countermeasures. Furthermore, a procedure was presented to predict the economic feasibility of the countermeasures based on crash reduction factors. The findings of this study should help expand the existing RoadHAT tool used by the Indiana Department of Transportation (INDOT) to emphasize and strengthen pedestrian safety considerations in the current tool.

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Tarko, Andrew P., Mario A. Romero, Vamsi Krishna Bandaru, and Cristhian Lizarazo. TScan–Stationary LiDAR for Traffic and Safety Applications: Vehicle Interpretation and Tracking. Purdue University, 2022. http://dx.doi.org/10.5703/1288284317402.

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To improve traffic performance and safety, the ability to measure traffic accurately and effectively, including motorists and other vulnerable road users, at road intersections is needed. A past study conducted by the Center for Road Safety has demonstrated that it is feasible to detect and track various types of road users using a LiDAR-based system called TScan. This project aimed to progress towards a real-world implementation of TScan by building two trailer-based prototypes with full end-user documentation. The previously developed detection and tracking algorithms have been modified and converted from the research code to its implementational version written in the C++ programming language. Two trailer-based TScan units have been built. The design of the prototype was iterated multiple times to account for component placement, ease of maintenance, etc. The expansion of the TScan system from a one single-sensor unit to multiple units with multiple LiDAR sensors necessitated transforming all the measurements into a common spatial and temporal reference frame. Engineering applications for performing traffic counts, analyzing speeds at intersections, and visualizing pedestrian presence data were developed. The limitations of the existing SSAM for traffic conflicts analysis with computer simulation prompted the research team to develop and implement their own traffic conflicts detection and analysis technique that is applicable to real-world data. Efficient use of the development system requires proper training of its end users. An INDOT-CRS collaborative process was developed and its execution planned to gradually transfer the two TScan prototypes to INDOT’s full control. This period will be also an opportunity for collecting feedback from the end user and making limited modifications to the system and documentation as needed.

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Tarko, Andrew P., Qiming Guo, and Raul Pineda-Mendez. Using Emerging and Extraordinary Data Sources to Improve Traffic Safety. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317283.

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The current safety management program in Indiana uses a method based on aggregate crash data for conditions averaged over several-year periods with consideration of only major roadway features. This approach does not analyze the risk of crashes potentially affected by time-dependent conditions such as traffic control, operations, weather and their interaction with road geometry. With the rapid development of data collection techniques, time-dependent data have emerged, some of which have become available for safety management. This project investigated the feasibility of using emerging and existing data sources to supplement the current safety management practices in Indiana and performed a comprehensive evaluation of the quality of the new data sources and their relevance to traffic safety analysis. In two case studies, time-dependent data were acquired and integrated to estimate their effects on the hourly probability of crash and its severity on two selected types of roads: (1) rural freeways and (2) signalized intersections. The results indicate a considerable connection between hourly traffic volume, average speeds, and weather conditions on the hourly probability of crash and its severity. Although some roadway geometric features were found to affect safety, the lack of turning volume data at intersections led to some counterintuitive results. Improvements have been identified to be implemented in the next phase of the project to eliminate these undesirable results.

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Li, Howell, Jijo K. Mathew, Woosung Kim, and Darcy M. Bullock. Using Crowdsourced Vehicle Braking Data to Identify Roadway Hazards. Purdue University, 2020. http://dx.doi.org/10.5703/1288284317272.

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Modern vehicles know more about the road conditions than transportation agencies. Enhanced vehicle data that provides information on “close calls” such as hard braking events or road conditions during winter such as wheel slips and traction control will be critical for improving safety and traffic operations. This research applied conflict analyses techniques to process approximately 1.5 million hard braking events that occurred in the state of Indiana over a period of one week in August 2019. The study looked at work zones, signalized intersections, interchanges and entry/exit ramps. Qualitative spatial frequency analysis of hard-braking events on the interstate demonstrated the ability to quickly identify temporary and long-term construction zones that warrant further investigation to improve geometry and advance warning signs. The study concludes by recommending the frequency of hard-braking events across different interstate routes to identify roadway locations that have abnormally high numbers of “close calls” for further engineering assessment.

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Gajera, Hardik, Srinivas S. Pulugurtha, and Sonu Mathew. Influence of Level 1 and Level 2 Automated Vehicles on Fatal Crashes and Fatal Crash Occurrence. Mineta Transportation Institute, June 2022. http://dx.doi.org/10.31979/mti.2022.2034.

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Connected and automated vehicles (CAVs) are expected to improve safety by gradually reducing human decisions while driving. However, there are still questions on their effectiveness as we transition from almost 0% CAVs to 100% CAVs with different levels of vehicle autonomy. This research focuses on synthesizing literature and identifying risk factors influencing fatal crashes involving level 1 and level 2 CAVs in the United States. Fatal crashes involving level 0 vehicles—ones that are not connected and automated—were compared to minimize unobserved heterogeneity and randomness associated with the influencing risk factors. The research team used the fatal crash data for the years 2016 to 2019 for the analysis. A partial proportionality odds model is developed using crash, road, and vehicle characteristics as the independent variables and the fatal crash involving a vehicle with a specific level of automation as the dependent variable. The results of this research indicate that level 1 and level 2 CAVs are less likely to be involved in a fatal crash at four-way intersections, on two-way routes with wide medians, at nighttime, and in poor lighting conditions when compared to level 0 vehicles. However, they are more likely than level 0 vehicles to be involved in a fatal crash with pedestrians and bicyclists. Comparative analysis between vehicles with smart features and other vehicles indicated that pedestrian automatic emergency braking (PAEB) and lane-keeping assistance (LKA) improve the safety by reducing possible collision with a pedestrian and roadside departure, respectively. Contrarily, vehicles with other smart features are still highly likely to be involved in fatal crashes. This research adds to the growing body of literature that will identify potential areas for improvement in the safety of vehicular technologies and road geometry.

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Tarko, Andrew P., Mario A. Romero, Vamsi Krishna Bandaru, and Xueqian Shi. Guidelines for Evaluating Safety Using Traffic Encounters: Proactive Crash Estimation on Roadways with Conventional and Autonomous Vehicle Scenarios. Purdue University, 2023. http://dx.doi.org/10.5703/1288284317587.

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With the expected arrival of autonomous vehicles, and the ever-increasing levels of automation in today’s human driven vehicles, road safety is changing at a rapid pace. This project aimed to address the need for an efficient and rapid method of safety evaluation and countermeasure identification via traffic encounters, specifically traffic conflicts that are considered useful surrogates of crashes. Recent research-delivered methods for estimating crash frequencies based on these events were observed in the field. In this project we developed a method for observing traffic encounters with two LiDAR-based traffic monitoring units, called TScan, which were recently developed in JTRP-funded projects SPR-3831 and SPR-4102. The TScan units were deployed in the field for several hours to collect data at selected intersections. These large data sets were used to improve object detection and tracking algorithms in order to better assist in detecting traffic encounters and conflicts. Consequently, the software of the TScan trailer-based units was improved and the results generated with the upgraded system include a list of potential encounters for further analysis. We developed an engineering application for analyzing the trajectories of vehicles involved in the pre-selected encounters to identify final traffic encounters and conflicts. Another module of the engineering application visualized the traffic encounters and conflicts to inspect the spatial patterns of these events and to estimate the number of crashes for the observation period. Furthermore, a significant modeling effort resulted in a method of producing factors that expand the conflict-based crash estimates in short observation periods to an entire year. This report provides guidelines for traffic encounters and conflicts, the user manuals for setting up and operating the TScan research unit. and manuals for the engineering applications mentioned above.

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Siebke, Christian, Maximilian Bäumler, Madlen Ringhand, Marcus Mai, Felix Elrod, and Günther Prokop. Report on design of modules for the stochastic traffic simulation. Technische Universität Dresden, 2021. http://dx.doi.org/10.26128/2021.245.

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As part of the AutoDrive project, OpenPASS is used to develop a cognitive-stochastic traffic flow simulation for urban intersection scenarios described in deliverable D1.14. The deliverable D4.20 is about the design of the modules for the stochastic traffic simulation. This initially includes an examination of the existing traffic simulations described in chapter 2. Subsequently, the underlying tasks of the driver when crossing an intersection are explained. The main part contains the design of the cognitive structure of the road user (chapter 4.2) and the development of the cognitive behaviour modules (chapter 4.3).

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