LIVIVO - Search results -

Search results

Result 1 - 10 of total 15

Search options

Article ; Online: The impact of target speed on pedestrian, bike, and speeding crash frequencies.

Mahmoud, Nada / Abdel-Aty, Mohamed / Abdelraouf, Amr

2023 Volume 192, Page(s) 107263

Abstract: This research aims to investigate the influence of adopting the target speed concept on different types of crashes including pedestrian, bike, and speeding-related crashes. The Target speed is the highest speed that vehicles should operate on a roadway ... ...

Abstract	This research aims to investigate the influence of adopting the target speed concept on different types of crashes including pedestrian, bike, and speeding-related crashes. The Target speed is the highest speed that vehicles should operate on a roadway segment in a specific context. Based on the reviewed literature, this is the first study to investigate the relationship between target speed and crash frequency. Hence, big data including probe-vehicle data, traffic characteristics, geometric features, and land use attributes were utilized to develop crash prediction models. The main contributions of this research are to quantify the impacts of target speed on traffic safety considering context categories and to conclude the potential recommendations to lower different types of crashes. The 85th percentile speed was calculated and utilized in the developed models. Three crash prediction models were developed for pedestrian, bike, and speeding-related crashes. They were used in the analysis to quantify the impact of adopting target speed on different crash types. The results showed a significant reduction in the three crash types when using the target speed. Most of the improvements took place in three context categories: C3C: Suburban Commercial Segments, C3R: Suburban Residential Segments, and C4: Urban General Segments. Hence, this research recommends adopting target speed specifically in urban and suburban areas. Further, it suggests considering some measures to lower vulnerable road users' and speeding-related crashes. Following the recommendations of this research would help to reduce different types of crash frequency, hence, improving the mobility and safety for all users in different context classifications.
MeSH term(s)	Humans ; Accidents, Traffic/prevention & control ; Automobile Driving ; Safety ; Bicycling ; Pedestrians
Language	English
Publishing date	2023-08-11
Publishing country	England
Document type	Journal Article
ZDB-ID	210223-7
ISSN	1879-2057 ; 0001-4575
ISSN (online)	1879-2057
ISSN	0001-4575
DOI	10.1016/j.aap.2023.107263
Database	MEDical Literature Analysis and Retrieval System OnLINE

In stock of ZB MED Cologne/Königswinter

Zs.A 2461: Show issues

Location:
Je nach Verfügbarkeit (siehe Angabe bei Bestand)
bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
Jg. 1995 - 2021: Lesesall (2.OG)
ab Jg. 2022: Lesesaal (EG)

Order via subito

This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

Details ▾
- See ZB MED holdings
- Order with fees

Article ; Online: Advances and applications of computer vision techniques in vehicle trajectory generation and surrogate traffic safety indicators.

Abdel-Aty, Mohamed / Wang, Zijin / Zheng, Ou / Abdelraouf, Amr

Accident; analysis and prevention

2023 Volume 191, Page(s) 107191

Abstract: The application of Computer Vision (CV) techniques massively stimulates microscopic traffic safety analysis from the perspective of traffic conflicts and near misses, which is usually measured using Surrogate Safety Measures (SSM). However, as video ... ...

Abstract	The application of Computer Vision (CV) techniques massively stimulates microscopic traffic safety analysis from the perspective of traffic conflicts and near misses, which is usually measured using Surrogate Safety Measures (SSM). However, as video processing and traffic safety modeling are two separate research domains and few research have focused on systematically bridging the gap between them, it is necessary to provide transportation researchers and practitioners with corresponding guidance. With this aim in mind, this paper focuses on reviewing the applications of CV techniques in traffic safety modeling using SSM and suggesting the best way forward. The CV algorithms that are used for vehicle detection and tracking from early approaches to the state-of-the-art models are summarized at a high level. Then, the video pre-processing and post-processing techniques for vehicle trajectory extraction are introduced. A detailed review of SSMs for vehicle trajectory data along with their application on traffic safety analysis is presented. Finally, practical issues in traffic video processing and SSM-based safety analysis are discussed, and the available or potential solutions are provided. This review is expected to assist transportation researchers and engineers with the selection of suitable CV techniques for video processing, and the usage of SSMs for various traffic safety research objectives.
MeSH term(s)	Humans ; Accidents, Traffic/prevention & control ; Safety ; Transportation ; Computers ; Algorithms ; Automobile Driving
Language	English
Publishing date	2023-07-08
Publishing country	England
Document type	Review ; Journal Article
ZDB-ID	210223-7
ISSN	1879-2057 ; 0001-4575
ISSN (online)	1879-2057
ISSN	0001-4575
DOI	10.1016/j.aap.2023.107191
Database	MEDical Literature Analysis and Retrieval System OnLINE

In stock of ZB MED Cologne/Königswinter

Zs.A 2461: Show issues

Location:
Je nach Verfügbarkeit (siehe Angabe bei Bestand)
bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
Jg. 1995 - 2021: Lesesall (2.OG)
ab Jg. 2022: Lesesaal (EG)

Order via subito

Details ▾
- See ZB MED holdings
- Order with fees

Article ; Online: Effect of signal timing on vehicles' near misses at intersections.

Islam, Zubayer / Abdel-Aty, Mohamed / Goswamy, Amrita / Abdelraouf, Amr / Zheng, Ou

Scientific reports

2023 Volume 13, Issue 1, Page(s) 9065

Abstract: Driving characteristics often vary between the different states of the signal. During red and yellow phase, drivers tend to speed up and reduce the following distance which in turn increases the possibility of rear end crashes. Intersection safety, ... ...

Abstract	Driving characteristics often vary between the different states of the signal. During red and yellow phase, drivers tend to speed up and reduce the following distance which in turn increases the possibility of rear end crashes. Intersection safety, therefore, relies on the correct modelling of signal phasing and timing parameters, and how drivers respond to its changes. This paper aims to identify the relationship between surrogate safety measures and signal phasing. Unmanned aerial vehicle (UAV) video data has been used to study a major intersection. Post encroachment time (PET) between vehicles was calculated from the video data as well as speed, heading and relevant signal timing parameters such as all red time, red clearance time, yellow time, etc. Random parameter ordered logit model was used to model the relationship between PET and signal timing parameters. Overall, the results showed that yellow time and red clearance time is positively related to PETs. The model was also able to identify certain signal phases that could be a potential safety hazard and would need to be retimed by considering the PETs. The odds ratios from the models also indicate that increasing the mean yellow and red clearance times by one second can improve the PET levels by 10% and 3%, respectively.
Language	English
Publishing date	2023-06-05
Publishing country	England
Document type	Journal Article
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-023-36106-3
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Book ; Online: Advances and Applications of Computer Vision Techniques in Vehicle Trajectory Generation and Surrogate Traffic Safety Indicators

Abdel-Aty, Mohamed / Wang, Zijin / Zheng, Ou / Abdelraouf, Amr

2023

Abstract	The application of Computer Vision (CV) techniques massively stimulates microscopic traffic safety analysis from the perspective of traffic conflicts and near misses, which is usually measured using Surrogate Safety Measures (SSM). However, as video processing and traffic safety modeling are two separate research domains and few research have focused on systematically bridging the gap between them, it is necessary to provide transportation researchers and practitioners with corresponding guidance. With this aim in mind, this paper focuses on reviewing the applications of CV techniques in traffic safety modeling using SSM and suggesting the best way forward. The CV algorithm that are used for vehicle detection and tracking from early approaches to the state-of-the-art models are summarized at a high level. Then, the video pre-processing and post-processing techniques for vehicle trajectory extraction are introduced. A detailed review of SSMs for vehicle trajectory data along with their application on traffic safety analysis is presented. Finally, practical issues in traffic video processing and SSM-based safety analysis are discussed, and the available or potential solutions are provided. This review is expected to assist transportation researchers and engineers with the selection of suitable CV techniques for video processing, and the usage of SSMs for various traffic safety research objectives.
Keywords	Computer Science - Computer Vision and Pattern Recognition
Subject code	380
Publishing date	2023-03-27
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Book ; Online: M$^2$DAR

Ma, Yunsheng / Yuan, Liangqi / Abdelraouf, Amr / Han, Kyungtae / Gupta, Rohit / Li, Zihao / Wang, Ziran

Multi-View Multi-Scale Driver Action Recognition with Vision Transformer

2023

Abstract: Ensuring traffic safety and preventing accidents is a critical goal in daily driving, where the advancement of computer vision technologies can be leveraged to achieve this goal. In this paper, we present a multi-view, multi-scale framework for ... ...

Abstract	Ensuring traffic safety and preventing accidents is a critical goal in daily driving, where the advancement of computer vision technologies can be leveraged to achieve this goal. In this paper, we present a multi-view, multi-scale framework for naturalistic driving action recognition and localization in untrimmed videos, namely M$^2$DAR, with a particular focus on detecting distracted driving behaviors. Our system features a weight-sharing, multi-scale Transformer-based action recognition network that learns robust hierarchical representations. Furthermore, we propose a new election algorithm consisting of aggregation, filtering, merging, and selection processes to refine the preliminary results from the action recognition module across multiple views. Extensive experiments conducted on the 7th AI City Challenge Track 3 dataset demonstrate the effectiveness of our approach, where we achieved an overlap score of 0.5921 on the A2 test set. Our source code is available at \url{https://github.com/PurdueDigitalTwin/M2DAR}. Comment: Accepted in the 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
Keywords	Computer Science - Computer Vision and Pattern Recognition
Subject code	629 ; 006
Publishing date	2023-05-12
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Book ; Online: CEMFormer

Ma, Yunsheng / Ye, Wenqian / Cao, Xu / Abdelraouf, Amr / Han, Kyungtae / Gupta, Rohit / Wang, Ziran

Learning to Predict Driver Intentions from In-Cabin and External Cameras via Spatial-Temporal Transformers

2023

Abstract: Driver intention prediction seeks to anticipate drivers' actions by analyzing their behaviors with respect to surrounding traffic environments. Existing approaches primarily focus on late-fusion techniques, and neglect the importance of maintaining ... ...

Abstract	Driver intention prediction seeks to anticipate drivers' actions by analyzing their behaviors with respect to surrounding traffic environments. Existing approaches primarily focus on late-fusion techniques, and neglect the importance of maintaining consistency between predictions and prevailing driving contexts. In this paper, we introduce a new framework called Cross-View Episodic Memory Transformer (CEMFormer), which employs spatio-temporal transformers to learn unified memory representations for an improved driver intention prediction. Specifically, we develop a spatial-temporal encoder to integrate information from both in-cabin and external camera views, along with episodic memory representations to continuously fuse historical data. Furthermore, we propose a novel context-consistency loss that incorporates driving context as an auxiliary supervision signal to improve prediction performance. Comprehensive experiments on the Brain4Cars dataset demonstrate that CEMFormer consistently outperforms existing state-of-the-art methods in driver intention prediction.
Keywords	Computer Science - Computer Vision and Pattern Recognition
Subject code	006
Publishing date	2023-05-13
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: Molecular Noninvasive Diagnosis of Hepatocellular Carcinoma Using Microsatellite Instability.

Mamdouh, Samah / Aboushousha, Tarek / Abdelraouf, Amr / Hamdy, Hussam / Seleem, Mohamed / Hassan, Hanem

Asian Pacific journal of cancer prevention : APJCP

2021 Volume 22, Issue 10, Page(s) 3337–3346

Abstract: Objective: Hepatocellular carcinoma (HCC) accounts for more than 80% of primary liver cancers. Moreover, in the next 10 years, more than one million patients are expected to die from liver cancer as estimated by the World Health Organization. The aim of ...

Abstract	Objective: Hepatocellular carcinoma (HCC) accounts for more than 80% of primary liver cancers. Moreover, in the next 10 years, more than one million patients are expected to die from liver cancer as estimated by the World Health Organization. The aim of the present study is to define the microsatellite phenotype in the blood, tumor and nontumor tissue samples from hepatocellular carcinoma cases to develop a simple non-invasive method for diagnosis and detection of the disease. Methods: A total of 100 patients with histologically-proven HCC were enrolled in this study, blood samples and tissue specimens from tumor and nontumor tissue were obtained from each patient. DNA was extracted and microsatellite instability MSI status was determined by polymerase chain reaction (PCR) using 5 mononucleotide and 5 dinucleotide repeats. Results: Among the 100 HCC tumors analyzed, (8%) considered as displaying a typical MSI-H phenotype as defined by instability in at least 3 of the 10 repeats analyzed, (61%) tumors displayed MSI-L and (31%) displayed MSS while in plasma the instability was (40%) for MSI-H, (44%) for MSI-L and (16%) for MSS. Conclusion: our findings could point to the achievement that HCC patients could be diagnosed by MSI analysis using blood sample as non-invasive way and this conclusion achieved our aim as the study shows impressive and promising results.
MeSH term(s)	Carcinoma, Hepatocellular/blood ; Carcinoma, Hepatocellular/diagnosis ; Carcinoma, Hepatocellular/genetics ; Carcinoma, Hepatocellular/pathology ; Female ; Humans ; Liver Neoplasms/blood ; Liver Neoplasms/diagnosis ; Liver Neoplasms/genetics ; Liver Neoplasms/pathology ; Male ; Microsatellite Instability ; Middle Aged ; Phenotype ; Polymerase Chain Reaction ; Sequence Alignment
Language	English
Publishing date	2021-10-01
Publishing country	Thailand
Document type	Journal Article
ZDB-ID	2218955-5
ISSN	2476-762X ; 1513-7368
ISSN (online)	2476-762X
ISSN	1513-7368
DOI	10.31557/APJCP.2021.22.10.3337
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Article: Evaluation of preoperative duloxetine use for postoperative analgesia following laparoscopic cholecystectomy: A randomized controlled trial.

Mansour, Noha O / Boraii, Sherif / Elnaem, Mohamed Hassan / Elrggal, Mahmoud E / Omar, Tamer / Abdelraouf, Amr / Abdelaziz, Doaa H

Frontiers in pharmacology

2022 Volume 13, Page(s) 944392

Abstract: Background: ...

Abstract	Background:
Language	English
Publishing date	2022-09-29
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2587355-6
ISSN	1663-9812
ISSN	1663-9812
DOI	10.3389/fphar.2022.944392
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Book ; Online: CitySim

Zheng, Ou / Abdel-Aty, Mohamed / Yue, Lishengsa / Abdelraouf, Amr / Wang, Zijin / Mahmoud, Nada

A Drone-Based Vehicle Trajectory Dataset for Safety Oriented Research and Digital Twins

2022

Abstract: The development of safety-oriented research ideas and applications requires fine-grained vehicle trajectory data that not only has high accuracy but also captures a substantial number of critical safety events. This paper introduces the CitySim Dataset, ... ...

Abstract	The development of safety-oriented research ideas and applications requires fine-grained vehicle trajectory data that not only has high accuracy but also captures a substantial number of critical safety events. This paper introduces the CitySim Dataset, which was devised with a core objective of facilitating safety-based research and applications. CitySim has vehicle trajectories extracted from 1140-minutes of drone videos recorded at 12 different locations. It covers a variety of road geometries including freeway basic segments, weaving segments, expressway merge/diverge segments, signalized intersections, stop-controlled intersections, and intersections without sign/signal control. CitySim trajectories were generated through a five-step procedure which ensured the trajectory accuracy. Furthermore, the dataset provides vehicle rotated bounding box information which is demonstrated to improve safety evaluation. Compared to other video-based trajectory datasets, the CitySim Dataset has significantly more critical safety events with higher severity including cut-in, merge, and diverge events. In addition, CitySim facilitates research towards digital twin applications by providing relevant assets like the recording locations'3D base maps and signal timings. These features enable more comprehensive conditions for safety research and applications such as autonomous vehicle safety and location-based safety analysis. The dataset is available online at https://github.com/ozheng1993/UCF-SST-CitySim-Dataset.
Keywords	Computer Science - Computer Vision and Pattern Recognition ; Statistics - Machine Learning
Subject code	629
Publishing date	2022-08-23
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Book ; Online: Real-time Learning of Driving Gap Preference for Personalized Adaptive Cruise Control

Zhao, Zhouqiao / Liao, Xishun / Abdelraouf, Amr / Han, Kyungtae / Gupta, Rohit / Barth, Matthew J. / Wu, Guoyuan

2023

Abstract: Advanced Driver Assistance Systems (ADAS) are increasingly important in improving driving safety and comfort, with Adaptive Cruise Control (ACC) being one of the most widely used. However, pre-defined ACC settings may not always align with driver's ... ...

Abstract	Advanced Driver Assistance Systems (ADAS) are increasingly important in improving driving safety and comfort, with Adaptive Cruise Control (ACC) being one of the most widely used. However, pre-defined ACC settings may not always align with driver's preferences and habits, leading to discomfort and potential safety issues. Personalized ACC (P-ACC) has been proposed to address this problem, but most existing research uses historical driving data to imitate behaviors that conform to driver preferences, neglecting real-time driver feedback. To bridge this gap, we propose a cloud-vehicle collaborative P-ACC framework that incorporates driver feedback adaptation in real time. The framework is divided into offline and online parts. The offline component records the driver's naturalistic car-following trajectory and uses inverse reinforcement learning (IRL) to train the model on the cloud. In the online component, driver feedback is used to update the driving gap preference in real time. The model is then retrained on the cloud with driver's takeover trajectories, achieving incremental learning to better match driver's preference. Human-in-the-loop (HuiL) simulation experiments demonstrate that our proposed method significantly reduces driver intervention in automatic control systems by up to 62.8%. By incorporating real-time driver feedback, our approach enhances the comfort and safety of P-ACC, providing a personalized and adaptable driving experience.
Keywords	Electrical Engineering and Systems Science - Systems and Control ; Computer Science - Human-Computer Interaction
Subject code	380 ; 629
Publishing date	2023-09-10
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

To top

More links

Kategorien

In stock of ZB MED Cologne/Königswinter

Order via subito

More links

Kategorien

In stock of ZB MED Cologne/Königswinter

Order via subito

More links

Kategorien

Order via subito

Full text online

More links

Kategorien

Inter-library loan at ZB MED

Full text online

More links

Kategorien

Inter-library loan at ZB MED

Full text online

More links

Kategorien

Inter-library loan at ZB MED

More links

Kategorien

Order via subito

More links

Kategorien

Order via subito

Full text online

More links

Kategorien

Inter-library loan at ZB MED

Full text online

More links

Kategorien

Inter-library loan at ZB MED