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Traffic conflict indicators are essential for evaluating traffic safety and analyzing trajectory data, especially in the absence of crash data. Previous studies have used traffic conflict indicators to predict and identify conflicts, including time-to-collision (TTC), proportion of stopping distance (PSD), and deceleration rate to avoid a crash (DRAC). However, limited research is conducted to understand how to set thresholds for these indicators while accounting for traffic flow characteristics at different traffic states. This paper proposes a clustering framework for determining surrogate safety measures (SSM) thresholds and identifying traffic conflicts in different traffic states using high-resolution trajectory data from the Citysim dataset. In this study, unsupervised clustering is employed to identify different traffic states and their transitions under a three-phase theory framework. The resulting clusters can then be utilized in conjunction with surrogate safety measures (SSM) to identify traffic conflicts and assess safety performance in each traffic state. From different perspectives of time, space, and deceleration, we chose three compatible conflict indicators: TTC, DRAC, and PSD, considering functional differences and empirical correlations of different SSMs. A total of three models were chosen by learning these indicators to identify traffic conflict and non-conflict clusters. It is observed that Mclust outperforms the other two. The results show that the distribution of traffic conflicts varies significantly across traffic states. A wide moving jam (J) is found to be the phase with largest amount of conflicts, followed by synchronized flow phase (S) and free flow phase(F). Meanwhile, conflict risk and thresholds exhibit similar levels across transitional states.

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.

Crash events identification and prediction plays a vital role in understanding safety conditions for transportation systems. While existing systems use traffic parameters correlated with crash data to classify and train these models, we propose the use of a novel sensory unit that can also accurately identify crash events: microphone. Audio events can be collected and analyzed to classify events such as crash. In this paper, we have demonstrated the use of a deep Convolutional Neural Network (CNN) for road event classification. Important audio parameters such as Mel Frequency Cepstral Coefficients (MFCC), log Mel-filterbank energy spectrum and Fourier Spectrum were used as feature set. Additionally, the dataset was augmented with more sample data by the use of audio augmentation techniques such as time and pitch shifting. Together with the feature extraction this data augmentation can achieve reasonable accuracy. Four events such as crash, tire skid, horn and siren sounds can be accurately identified giving indication of a road hazard that can be useful for traffic operators or paramedics. The proposed methodology can reach accuracy up to 94%. Such audio systems can be implemented as a part of an Internet of Things (IoT) platform that can complement video-based sensors without complete coverage.

Real-time safety analysis has become a hot research topic as it can reveal the relationship between real-time traffic characteristics and crash occurrence more accurately, and these results could be applied to improve active traffic management systems and enhance safety performance. Most of the previous studies have been applied to freeways and seldom to arterials. Therefore, this study attempts to examine the relationship between crash occurrence and real-time traffic and weather characteristics based on four urban arterials in Central Florida. Considering the substantial difference between the interrupted traffic flow on urban arterials and the free flow on freeways, the adaptive signal phasing was also introduced in this study. Bayesian conditional logistic models were developed by incorporating the Bluetooth, adaptive signal control, and weather data, which were extracted for a period of 20 minutes (four 5-minute interval) before the time of crash occurrence. Model comparison results indicate that the model based on 5-10 minute interval dataset is the most appropriate model. It reveals that the average speed, upstream volume, and rainy weather indicator were found to have significant effects on crash occurrence. Furthermore, both Bayesian logistic and Bayesian random effects logistic models were developed to compare with the Bayesian conditional logistic model, and the Bayesian conditional logistic model was found to be much better than the other two models. These results are important in real-time safety applications in the context of Integrated Active Traffic Management., Comment: Presented at Transportation Research Board 97th Annual Meeting

Participatory landscape approaches are currently being positioned as the essential basis for sustainable landscape development. However, with the current democratic transform and the consequent decentralization of the spatial planning policy in Egypt, no practices have been conducted in this field. Accordingly, there is a vital need for coherent and integrated approaches for the practical application of participatory landscape. This paper represents one of a series of research papers targeting this aim. It focuses on poor urban settings in existing informal areas and in new cities’ districts, represented by the case studies of Monashaet Nasser and the sixth district in the 6th of October city, respectively, which are used to carry out the questionnaires, followed by a statistical analysis and illustrative causal loop diagrams. The questionnaire integrates measuring local residents’ willingness and participation methods together with the practitioners’ recommendations for their degree of involvemen...

This paper introduces a new statistical methodological approach for the real estate appraisal based on the consideration of the changing purchasing power of money, by deducing an equation based mainly on all the affecting urban context variables other than the market, cost, and income approach that are currently used for that purpose. This is achieved through testing the proposed statistical model using these urban variables on one of the most important districts in downtown Cairo, Maspiro (next to Tahrir Square incorporating 1130 land lots), together with comparing its predicted values with a sample evaluated by professional real estate appraisers to ensure its validity. Maspiro district confronts the Nile River, and faces the Egyptian Union of Radio and Television Building, Ministry of Foreign Affairs, Embassy of Brazil, Embassy of Italy, and others. Accordingly, the paper fi nally illustrates that all theoretical approaches dealing with the real estate appraisal are subject to some defects ignoring the changing circumstances of each district and the urban planning variables that constitute its real value. They mainly depend on factors that are subject to change from time to time in accordance with the surrounding political, social, and economic circumstances. Over or underestimations may lead to economic loss and mislead the proposed developmental plans for the regions. The urban variables, on the other side, once measured for each real estate are not subject to these changes. Therefore, the research tests the validity of fistrong correlation between these variables and their real value, in the form of an equation by using statistical methods.

This study began by raising the question of whether international organizations have effectively contributed to the revitalization of the old historic districts, and whether the community participation approaches they implemented succeeded in sustaining the development and in preserving the heritage, or just resulting in attractive, temporary, exterior treatments that are not a part of the local identity. The paper answers these questions through an analytical and statistical assessment for the role of the Aga Khan Project in the rehabilitation of Darb Alahmar in Cairo. It deduces statistical correlations between the role of international organizations in the revitalization of historic districts and the community participation with the physical, social, and economic development aspects of the areas. The study then plots the correlations between the role of these organizations and community participation. The paper concludes with the fact that rehabilitation plans managed by these organizations hav...

Thirty echinoid species (18 regular and 12 irregular) and an undetermined species belonging to 14 genera are studied from the Turonian-Santonian sequence (14 species from Turonian, two species from Turonian-Santonian and 14 species from Coniacian-Santonian) of Abu Roash, Wadi Dakhl and Wadi Abu Qaada, Egypt. Two new species are established: Thylechinus (Thylechinus) sinaiensis n. sp. from the Turonian of Wadi Abu Qaada and Toxaster dakhlensis n. sp. from the Turonian of Wadi Dakhl. Orthopsis ovata (Coquand, 1862), which is known in other parts of the Tethyan region, is reported for the first time from Egypt. The rank of one subspecies is raised to species level: Coenholectypus roachensis (Fourtau, 1914) n. stat. The generic name of three species is changed: Echinobrissus humei Fourtau, 1906 is changed to Petalobrissus humei (Fourtau, 1906) n. comb.; Periaster duncani (Fourtau, 1906) and Periaster roachensis Gauthier, 1900 are transfered to the genus Mecaster Pomel, 1883. The ontogenetic changes o...

This paper describes the experimental analysis techniques and modelling efforts applied to sequential pre-trip route choice behavior data under the influence of an Advanced Traveler Information System (ATIS). This effort is the first step in a process to develop a basic understanding of the factors which influence route choice and how ATIS will affect drivers' route choice behavior over time.