This paper explores the attitudes and travel mode preferences of Mansoura University students towards eco-friendly transportation options, specifically shared electric scooters (SESs) and shared bikes (SBs). An online stated preference survey was administered to 790 students via Google Forms, yielding approximately 9,590 choice scenarios for analysis. The dataset was split into training (70%) and testing (30%) sets, with 6,717 cases in the training set and 2,880 cases in the testing set. A multinomial logit model and ten machine learning classifiers were used to predict mode choice behavior. The variables considered in the models include total travel time, travel cost, gender, health issues, bike ownership, ability to ride a bike and scooter, residency, prior knowledge of shared modes, smartphone ownership, frequency of public transport use, trip cost, trip time, and monthly personal income. Model performance was evaluated at two levels: individual and aggregate. At the individual level, accuracy reflects the overall percentage of correct predictions. At the aggregate level, accuracy is assessed based on the predicted market shares for each mode. The Extreme Gradient Boosting (XGB) model was the most accurate, achieving an accuracy slightly above 60%, followed by the Gradient Boosting (GB) and Random Forest (RF) models, both with accuracies slightly above 50%. Ensemble models like RF, GB, and XGB provided relatively accurate aggregate predictions with minimal deviations from actual mode shares. These models slightly overestimated the bus mode share but offered accurate predictions for other modes, making them robust choices for this classification task.

In seeking sustainable, safe, and efficient school commuting tours as non-recurring sources of congestion, it is essential to investigate the dynamic interaction between school students’ pick-up and drop-off (P&D) movements and the traffic operational performance of the surrounding area. This study investigates the traffic operational performance in the vicinity of schools at various P&D time intervals. The Travel and Planning Time indices (TTI, PTI), along with the Level of Service (LOS) are utilized as traffic operational performance indices in this article. A Python script was developed to employ the Google API for estimating the travel times from a real traffic dataset comprising 40 schools distributed across six cities in the Kingdom of Saudi Arabia (KSA). The results indicate that LOS varies from C to D for all cities except Riyadh, which exhibits the poorest traffic performance during P&D time intervals. This paper serves as a guideline for city planners and policymakers seeking to provide valuable insights to enhance traffic operational performance in Saudi Arabia.

This study re-evaluates Egypt’s Differential Speed Limit (DSL) policy by proposing Lane-Based Speed Limits (LBSL), an innovative strategy where speed limits vary across highway lanes. To address a critical research gap, we developed a microsimulation framework using Simulation of Urban Mobility (SUMO) with parameters specifically justified for Egyptian driver behavior. While constrained by data availability, our model moves beyond generic defaults by integrating a key stand-still gap parameter (CC0 = 1.5 m) calibrated from previous research on Egyptian conditions, ensuring a more accurate representation of local driving patterns. We simulated three-lane highway scenarios under varying traffic volumes (500–1750 veh/h/lane), heavy vehicle percentages (2.5–20%), and speed limits (100, 110, 120 km/h). This compared LBSL configurations (speed reductions of 10, 15, and 20 km/h between lanes) against Uniform Speed Limit (USL) and current DSL strategies. Performance was assessed through average delay, travel speed, lane-changing frequency, and conflict ratios using Time-to-Collision thresholds (≤ 2.50, ≤ 1.50, and ≤ 0.50 s). The results indicate that Egypt’s existing DSL strategy offers no statistically significant safety advantages over USL, questioning its effectiveness. Conversely, LBSL significantly improved safety, reducing conflicts by up to 60%, though it introduced a trade-off with operational efficiency by increasing delays by 71–870%. The primary contribution is a contextually grounded analysis demonstrating LBSL as a safer strategic alternative to Egypt’s incumbent DSL policy. This provides Egyptian policymakers with evidence-based insights for potential traffic safety reforms and offers a methodological framework for adapting microsimulation to other regions with similar data constraints.

Two-plus-one (2+1) highways are a special configuration of two-lane two-way (TLTW) highways with a continuous center lane that is used to alternate passing lanes. The main objective of this paper is, therefore, to evaluate the suitability of the 2+1 design for Middle East conditions as a replacement for traditional TLTW roads with higher traffic volumes or as an interim solution before transforming TLTW roads into four-lane highways. In our analysis, we considered both safety and mobility performances by comparing the 2+1 and TLTW designs. The new suggested 2+1 designs were evaluated, with the first design prohibiting overtaking in the opposite direction, while the second design permitted it. Additionally, two-speed-limit strategies, uniform speed limit (USL), and differential speed limit (DSL) were also evaluated. The results showed that the 2+1 design, which prohibited overtaking in the opposite direction, was superior to TLTW in terms of mobility and safety, while the other design compromised safety compared to TLTW. The results provide valuable information to policymakers, urban planners, and transport authorities to guide evidence-based decisions on the integration of the 2+1 design as a viable solution for sustainable and efficient transportation.

Intersections have primary importance in urban networks because most of travel time is wasted at the intersection specially signalized category. Popular solutions of intersection control need to use artificial objects such as speed hump or signals. If both solutions were used together, it causes a manifestation of the delay problem. The study aims at analyzing the impact of speed hump on signalized intersection act in case of traffic mix nature. Quality features such as delay, level of service, and saturation flow rates had been measured and compared for the two consecutive signalized intersections that have approximately the same geometric and operation features in Port Said city. The first intersection has a speed hump and the other is without a speed hump. The study investigates that the existence of speed hump causes the increasing of the average delay by 4.3 %. Also, about half of green time is spent to pass the speed hump. Moreover, the saturation flow rate decreases by about 7 %. The speed hump adjustment factor is 0.93 that declares the harmful impact of speed hump on the saturation flow rate thus it effects on the whole performance of the intersection.

Examining pedestrian crossing violations at high-risk road midblock crossings has become essential, particularly in high-speed corridors, as a result of accidents at crossings resulting in fatalities. Hence, this article investigates such behavior in Alexandria, Egypt, as a credible case study in a developing country. According to our research methodology, a comprehensive dataset of over 2400 field-observed video recordings was used for real-life data collection. Machine learning (ML) models, such as CatBoost and gradient boosting (GB), were employed to predict crossing decisions. The models showed that risky behavior is strongly influenced by waiting time, crossing time, and the number of crossing attempts. The highest predictive performance was achieved by CatBoost and gradient boosting, indicating strong interpersonal influence within small groups engaging in unsafe road-crossing behavior. In the same context, the Shapley additive explanation (SHAP) values for these variables were 3, 2, and 0.60, respectively. Subsequently, based on SHAP sensitivity analysis, the results show that the total time (s) and age group (40–60 Y) had a significant negative influence on model prediction converging to class 0 (e.g., crossing illegally). The results also showed that shorter exposure times increase the likelihood of crossing illegally. This research work is among the few studies that employ a behavior-based approach to understanding pedestrian behavior at midblock crossings. This study offers actionable insights and valuable information for urban designers and transportation planners when considering the design of midblock crossings.