To address road accident losses, there is a need to prioritize safety factors, especially in high-risk locations on the road network, toward assuring a sustainable transport system. This paper proposes an approach for quantitative risk assessments of safety factors in hazardous road locations and involves the integration of the Fuzzy logic model, the Analytic Hierarchy Process (FAHP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). This new innovative method offers a way to prioritize and select safety factors associated with hazardous locations using a hierarchical structure. To demonstrate the applicability of this method, a case study was conducted in Egypt. The assessment process involved active participation by professionals through multiple expert meetings. This collaborative approach ensures that the assessment incorporates valuable real-world knowledge and experiences. It analyzed road safety hazardous conditions across various sections, including intersections, non-intersection sections, narrow bridge sections, and curve sections. The application of FAHP-TOPSIS enables the determination of weights for safety factors within each section, facilitating the evaluation of safety indices between them and ranking the safety hazard sections. The achieved analysis revealed that the hazard safety factor index is comparatively higher in curved sections compared to other types of sections. Light utility poles and road barriers significantly affected the hazard index. By utilizing this approach, governments may make informed decisions regarding the allocation of resources and the implementation of safety measures at hazardous road locations.

For sustainable transportation systems, modeling road traffic accidents is essential in order to formulate measures to reduce their harmful impacts on society. This study investigated the outcomes of using different datasets in traffic accident models with a low number of variables that can be easily manipulated by practitioners. Long-horizon aggregated and disaggregated road traffic accident datasets on Egyptian roads (for five years) were used to compare the model’s fit for different data groups. This study analyzed the results of k-means data clustering and classified the data into groups to compare the fit of the base model (Smeed’s model and different types of regression models). The results emphasized that the aggregated data used had less efficiency compared with the disaggregated data. It was found that the classification of the disaggregated dataset into reasonable groups improved the model’s fit. These findings may help in the better utilization of the available road traffic accident data for determining the best-fitting model that can assist decision-makers to choose suitable road traffic accident prevention measures.

Graph theory is crucial for efficient route planning; networks facilitate movement, transportation, communication, and control over matter and energy. This research introduces an overview of graph theory and its basics. The paper illustrates the different types of graphs and their important metrics (such as centrality degree, betweenness degree, and the accessibility degree). These metrics provide insights into connectivity flow and network efficiency, enabling the identification of critical nodes and routes. The provided methodology consists of two parts: the first part is about converting the topographic network to a graph (nodes and links), and the other part is about metrics calculations. Aswan city issued as a case study and all relevant data are displayed. The paper starts with the Aswan scenario graph, and then measures the metrics for all points showing weakness and the strength nodes of the graph. The finding showed an integrated picture of the Aswan road network, explaining the characteristics of each node. The results are considered a benchmark for understanding the nature of Aswan and a useful tool for decision-makers.

Feeder buses play an important role in supporting the accessibility of high-speed railway stations which leads to the improved efficiency of the transportation system. This paper proposes a new optimization technique for the design of feeder bus routes to the stations. It uses dynamic programming with a pulse algorithm seeking to maximize the number of serviced people considering the distance between the urban areas and high-speed railway station. The proposed algorithm was tested in a hypothetical network to find the optimum solutions and the running time needed. Moreover, the algorithm was applied to a real network as a case study in Aswan city, Egypt. Our results demonstrated significant improvements in the route design accuracy and efficiency. By applying the proposed algorithm, the potential demand values increased from 19.8% to 37.9% with a reasonable decrease in the running time compared to the literature. This research contributes to the advancement of transportation planning strategies by providing valuable insights into the optimization of feeder bus systems. The proposed model contributes to the scientific re-search and practical implementation by promoting a coordinated development of high-speed railway stations and urban areas. This may enhance the Egyptian high-speed railway technology, yielding substantial economic and social benefits.

Public transportation plays a crucial role in promoting economic growth, decreasing environmental damage, and providing fair access to key services. This study offers a comparative analysis of fixed and flexible transit systems, considering costs for both operators and users. The research employs a genetic algorithm to analyze transportation scenarios in New Aswan city, Egypt. The outcomes represented in optimal bus size, fleet size, number of zones, and headways for each system. The findings indicate that, in Aswan scenario, a bus size of seven seats give lower costs for the flexible transit system, whereas larger buses give higher cost in the fixed transit system. When comparing the two systems under varying demand conditions, the fixed system proves superior for high demand (exceeding one trip per minute). This research is the first of its kind for Aswan city and could improve transportation planning with enhance the integration of high-speed train stations accessibility.

This research simulates Aswan City’s urban transportation dynamics utilizing the Multi-Agent Transport Simulation (MATSim) framework. As a fast-expanding urban center, Aswan has many transportation difficulties that require extensive modeling toward sustainable mobility solutions. MATSim, recognized for its agent-based methodology, offers a detailed portrayal and analysis of individual travel behaviors and their interactions within the metropolitan transportation system. This study compiled and combined many databases, including demographic data, road infrastructure, public transit plans, and travel demand trends. These data are altered to produce a realistic digital clone of Aswan’s transportation system. Simulated scenarios analyze the consequences of several actions, such as increased public transit scheduling, traffic flow management, and the adoption of alternative transport modes, on minimizing congestion and boosting accessibility. Pilot findings show that MATSim effectively captures the distinct features of Aswan’s transportation network and offers practical insights for decision-makers. The results identified some opportunities to improve mobility and promote sustainable urban growth in developing cities. This study emphasized the importance of agent-based simulations in designing future transportation systems and urban infrastructure.