Adoption of autonomous and shared autonomous vehicles: a multi-criteria decision-making approach Omar Alharasees, Haitham A. Al Hasanat, Dania Alothman International Journal of Transportation Science and Technology, 2026 • AHP and FAHP were used to evaluate AV/SAV adoption criteria in Amman. • A novel hierarchical model integrates UTAUT and TAM frameworks. • User Perception emerged as the top criterion across all expert groups. • Safety, infrastructure, and policy readiness are key adoption barriers. • Gradual AV/SAV integration was favored by non-drivers for smoother adoption. This research investigates the adoption of autonomous vehicles (AVs) and shared autonomous vehicles (SAVs) in Amman, Jordan, utilizing a multi-method approach. A comprehensive literature review was conducted, synthesizing existing research on AV and SAV adoption factors within Amman’s transportation landscape. Subsequently, a local community feedback survey was conducted to understand their perspectives on AV and SAV adoption. Using multi-criteria decision-making (MCDM) techniques, specifically the analytic hierarchy process (AHP) and fuzzy AHP (FAHP), this study assesses local community acceptance and adoption levels of AVs and SAVs. The novel hierarchical model is derived from the unified theory of acceptance and use of technology (UTAUT) and technology acceptance model (TAM). The findings highlight the critical importance of user perception (UP), particularly performance expectancy (PE), across all expert groups. Safety concerns, infrastructure readiness, and regulatory frameworks emerged as pivotal factors shaping public acceptance and adoption of AVs and SAVs in Amman, emphasizing the vital role of governmental support and well-structured regulatory frameworks that are crucial for facilitating the integration of AVs and SAVs into the existing transportation infrastructure. The study provides insights and recommendations for policymakers and stakeholders, emphasizing the necessity of collaborative efforts, pilot programs, and targeted public outreach to promote AV and SAV adoption. These measures are essential for advancing urban mobility and mitigating traffic congestion in Amman.
Interpretable machine learning for imbalanced pedestrian injury severity prediction in urban Jordan Haitham A. Al Hasanat, Ahmad B. Hassanat, Omar Alharasees, Ahmad S. Tarawneh, Ghada A. Altarawneh, Lujain A. Alhasanat, Muhamed Begović Journal of King Saud University Engineering Sciences, 2025 This study presents a machine learning framework for predicting pedestrian accident severity using Amman, Jordan's first complete 10-year traffic dataset (2014–2023). Addressing the critical class imbalance where minor injuries predominate (85%), causing standard models to poorly detect severe cases (< 25% recall), we implement cost-sensitive algorithms and specialized undersampling techniques, such as XGBoost with Balancing the Loss Function (XGBLF) and Random Data Partitioning with Voting Rule (RDPVR), which enhanced learning from underrepresented Major/Fatal cases while maintaining data authenticity. Through mixed-type correlation analysis and statistical testing, vehicle speed, road illumination, vehicle type, driver age, and road conditions emerged as the most significant predictive factors. RDPVR achieved a 63% true positive rate for Major/Fatal injuries, a 2.78-fold improvement over standard classifiers, and XGBLF achieved 95%, but this achievement was on account of the accuracy of the minor cases. Comprehensive interpretability analysis (SHAP, LIME, and Permutation Importance) revealed that heavy vehicles, poor lighting, and high-speed driving strongly predict Major/Fatal outcomes. Notably, the analysis demonstrates Jordan's improved safety trajectory, with 2020–2023 showing reduced severe accidents compared to 2014–2016, indicating measurable policy impact. This study delivers the first interpretable, context-sensitive AI framework for Amman/Jordan pedestrian safety, translating technical insights into actionable recommendations for targeted interventions, urban planning, and data-driven enforcement strategies to reduce pedestrian injury severity in high-risk zones.
A Comprehensive Human Factors Approach to Pedestrian Accidents Analysis in Urban Environments Omar Alharasees, Haitham A. Al Hasanat, Rana Al-Matarneh 2025 2nd International Conference on Advanced Innovations in Smart Cities Icaisc 2025, 2025 This research aims to investigate the causes of pedestrian accidents in Amman city from 2014 to 2023 using Human Factors models, including the Human Factors Analysis and Classification System (HFACS), Systems-Theoretic Accident Model and Processes (STAMP), and the Haddon Matrix Model, Additionally, a Random Forest computational model was applied to predict pedestrian injury severity, offering data-driven insights into accident outcomes. The study identifies the key human, environmental, and organizational factors contributing to pedestrian fatalities and injuries by analyzing accident data and categorizing it within these frameworks. Findings suggest that there should be a focus on unsafe acts by drivers, and road design conditions play a critical role in pedestrian accidents. Recommendations focus on infrastructure improvements, training and Traffic cultural programs, and stakeholder engagement to mitigate these issues. The integration of such computational approaches can enhance predictive accuracy and support smarter urban safety planning.
Capacity of Single-lane Roundabouts in Hungary Haitham A. Al Hasanat, Dania Alothman, Omar AlHarasees Periodica Polytechnica Transportation Engineering, 2025 Roundabouts are a prevalent type of intersection known for their potential to enhance traffic flow. Ensuring their effective design is crucial for optimizing traffic performance. This study focuses on evaluating the capacity of roundabouts, essential for both planning new installations and assessing existing ones. Field data from thirteen roundabouts in Hungary were analyzed to estimate critical gap and follow-up headway values for each entry. Employing Raff's graphical method, critical gap values were determined, while follow-up headway was calculated by averaging the time taken for two waiting vehicles to accept the same gap over eight instances. The critical gaps and follow-up headway values for all forty-one entries ranged between 2.41–3.46 s and 1.8–2.4 s, respectively. Subsequently, the Highway Capacity Manual (HCM) roundabout capacity equation was calibrated using these gap acceptance parameters. The proposed model yielded higher entry capacity (1,672 PCU/h) compared to the HCM model. Validation against actual field entry capacity values demonstrated a strong correlation (R2 = 0.94), affirming the model's accuracy. Comparisons with international models, such as HCM 2016, Brilon-Wu, and Brilon-Bondzio, revealed the superiority of the proposed model in terms of entry capacity (1,672 PCU/h versus 1,380 PCU/h, 1,241 PCU/h and, 1,218 PCU/h respectively).
EVALUATION OF VEHICLE LATERAL POSITIONING FOR LANE-KEEPING PERFORMANCE ACROSS MULTIPLE SITES Haitham AL HASANAT, Omar ALHARASEES, Lafee ALSHAMAILEH Scientific Journal of Silesian University of Technology Series Transport, 2025 This study investigates lateral lane-keeping behavior among human-driven passenger vehicles on Jordanian multi-lane roads. Using overhead video footage collected at five sites, 500 vehicles traveling alone in the leftmost lane under free-flow, daylight conditions were manually annotated for centerline deviation. The lateral position was analyzed using descriptive statistics, temporal trends, and spectral frequency analysis. Results show that 61% to 83% of vehicles remained within a ±0.5 m “safe zone” from the lane center. No vehicle exceeded the ±1.75 m legal lane boundary, and wheel position plots confirmed consistent lateral margins. Sites 1 and 2 exhibited a slight rightward bias, while Sites 3 through 5 showed a leftward tendency, especially Site 3, which had the highest variability (std dev = 0.43 m). Spectral analysis revealed consistent low-frequency oscillations (~0.01-0.02 Hz), indicating slow, smooth steering adjustments with no erratic corrections. The study confirms that under ideal conditions, drivers maintain stable lateral control within 3.5 m lane widths. These results provide valuable reference data for autonomous vehicle calibration, infrastructure planning, and future research into lane-keeping behavior under variable traffic and environmental conditions.
Public Perception of Autonomous and Shared Autonomous Vehicles: Case Study of Amman Omar Alharasees, Haitham A. Al Hasanat, Dania Alothman Proceedings 2024 2nd International Conference on Technology Innovation and Its Applications Ictiia 2024, 2024 This study evaluates the public perception and adoption potential of autonomous vehicles (AVs) and shared autonomous vehicles (SAVs) in Amman, Jordan. Key factors influencing public perception and adoption include safety concerns, infrastructure readiness, and regulatory frameworks. The research highlights the necessity of governmental support and well-structured regulations. Despite recent advancements in Amman's transportation sector, challenges such as congestion, inadequate public transport, and infrastructure maintenance persist. Significant steps, including enhancing community preparedness and addressing public concerns, are crucial for successful AV and SAV integration. The study offers insights and recommendations to guide policymakers and stakeholders in fostering Amman's sustainable urban mobility ecosystem. Collaborative efforts, pilot programs, and targeted outreach are essential for advancing A V and SA V adoption.
Connected Automated Vehicles Entry Capacity on Roundabouts- Case Study Hungary Haitham A. Al Hasanat, Omar Alharasees, Dania Alothman Proceedings 2024 2nd International Conference on Technology Innovation and Its Applications Ictiia 2024, 2024 This study delves into roundabout entry capacity in Hungary, introducing a new model emphasizing the impact of circulating flow and geometric variables. The relationship between estimated entry capacity and various circulating flows and geometric factors is expressed multiplicatively. Central island diameter and splitter island width are identified as key factors, surpassing others. Comparisons with European models validate the new model's reliability, especially at low circulating traffic levels. Additionally, the study explores Connected and Autonomous Vehicles (CAVs) effects on single-lane roundabout capacity. Using adjustment factors from the 2022 Highway Capacity Manual (HCM), the study estimates entry capacity for varying CAV penetration levels, revealing significant increases as CAV levels rise with R2 of 0.723. Central island diameter and splitter island width notably contribute to these increases.
Development of Empirical Models to Predict Gap Acceptance Parameter Based on the Geometrical and Operational Parameters of Different Roundabouts Haitham A. Al Hasanat, János Juhász Periodica Polytechnica Civil Engineering, 2023 This paper develops a mathematical formula that accounts the influence of roundabout’s design and performance parameters to predict the gap acceptance parameter “Critical gap”. Thirteen roundabouts in Hungary having different geometric and operational parameters were selected. The geometrical and operational data of each roundabout’s leg was collected. Raff's method was used to estimate the critical gap for each roundabout leg. Firstly, the collinearity analysis was carried out to identify independent parameters to avoid any possible negative impact on the developed predictive models. Nine out of ten parameters passed the collinearity test. These nine parameters are the main parameters used in the model development. Three models were developed. The first model (M1) is based on Multivariate Adaptive Regression Spline (MARS) algorithm. The second model (M2) is based on Pearson correlation. The last model (M3) was based on Spearman correlation. Linear regression models were constructed using the retained parameters of the M2 and M3 models. Subsequently a comparison of the three developed models is done based on R2 and RMSE values. Based on the results obtained from the comparison, the MARS model (M1) is the best predictive model of the critical gap. According to the results of the MARS model, the most important parameters for predicting critical gap value are circulating traffic flow and the distance between neighboring legs.
DEVELOPMENT OF ROUNDABOUTS EMPIRICAL CAPACITY MODEL - CASE STUDY OF HUNGARY Haitham AL HASANAT, Juhasz JANOS Scientific Journal of Silesian University of Technology Series Transport, 2023 Roundabouts are commonly used worldwide because they offer several advantages over traditional intersections. The capacity that a roundabout can handle is an important factor in ensuring smooth traffic flow at a particular location. Therefore, various models have been developed to describe traffic conditions and driver behaviour at different sites or countries. However, existing models cannot be directly applied to other countries without proper calibration of the models to ensure an accurate estimation of capacity. In this study, five roundabouts in Hungary were selected to develop a general capacity model and compare it with international models. First, all sets of entry and circulating data were obtained from video recordings of each roundabout entry. These data were used to develop a model for each entry and then for each roundabout separately. Finally, all the data sets from all sixteen entries were used to develop a general capacity model (GM). The general capacity model (GM) was compared with the Highway Capacity Manual (HCM) 2016, the Brilon-Bondzio, and the Brilon-Wu models. The maximum capacity of the general capacity model (GM) was 1390 pcu/h, slightly higher than the maximum capacity of the HCM 2016 model of 1380 pcu/h. The percentage differences between the generated general capacity model (GM), HCM 2016, Brilon-Bondzio, and Brilon-Wu models were +0.71%, +12.4%, and +10.7%, respectively.
Multi-Method Assessment of Soak Pits in Jordan: Environmental, Economic, and Public Health Implications MA AlMubaidin, O Alharasees, HA Al Hasanat Water, Air, & Soil Pollution 237 (10), 598 , 2026 2026
Adoption of autonomous and shared autonomous vehicles: a multi-criteria decision-making approach O Alharasees, HA Al Hasanat, D Alothman International Journal of Transportation Science and Technology , 2026 2026
Interpretable machine learning for imbalanced pedestrian injury severity prediction in urban Jordan HA Al Hasanat, AB Hassanat, O Alharasees, AS Tarawneh, ... Journal of King Saud University–Engineering Sciences 37 (7), 1-42 , 2025 2025 Citations: 1
The influence of geometry and connected automated vehicles on single-lane roundabout capacity HAA Hasanat, O Alharasees Innovative Infrastructure Solutions 10 (9), 412 , 2025 2025 Citations: 4
A comprehensive human factors approach to pedestrian accidents analysis in urban environments O Alharasees, HA Al Hasanat, R Al-Matarneh 2025 2nd international conference on advanced innovations in smart cities … , 2025 2025 Citations: 6
Evaluation of vehicle lateral positioning for lane-keeping performance across multiple sites H Al Hasanat, O Alharasees, L Alshamaileh Scientific Journal of Silesian University of Technology. Series Transport, 5-25 , 2025 2025
Capacity of Single-lane Roundabouts in Hungary HA Al Hasanat, D Alothman, O AlHarasees Periodica Polytechnica Transportation Engineering , 2025 2025 Citations: 7
Public perception of autonomous and shared autonomous vehicles: Case study of Amman O Alharasees, HA Al Hasanat, D Alothman 2024 2nd International Conference on Technology Innovation and Its … , 2024 2024 Citations: 6
Connected automated vehicles entry capacity on roundabouts-case study Hungary HA Al Hasanat, O Alharasees, D Alothman 2024 2nd International Conference on Technology Innovation and Its … , 2024 2024 Citations: 10
DEVELOPMENT OF ROUNDABOUTS EMPIRICAL CAPACITY MODEL–CASE STUDY OF HUNGARY HA AL HASANAT, J JANOS Scientific Journal of Silesian University of Technology. Series Transport 120 , 2023 2023 Citations: 10
Development of empirical models to predict gap acceptance parameter based on the geometrical and operational parameters of different roundabouts J Juhasz Periodica Polytechnica-civil Engineering , 2023 2023 Citations: 13
THE INFLUENCE OF CIRCULATING AND ENTERING FLOWS ON CRITICAL GAPS VALUE IN ROUNDABOUTS. HA Al Hasanat, J Juhasz International Journal for Traffic & Transport Engineering 12 (3), 322-339 , 2022 2022 Citations: 10
Relationship between Critical Gap and Certain Geometrical Parameters in Roundabouts HA Al Hasanat, G Schuchmann Periodica Polytechnica Civil Engineering , 2022 2022 Citations: 15
Critical Gap in Roundabouts–A Short Comparison of Estimation Methods HA Al Hasanat, G Schuchmann Periodica Polytechnica Transportation Engineering 50 (3), 273-278 , 2022 2022 Citations: 12
MOST CITED SCHOLAR PUBLICATIONS
Relationship between Critical Gap and Certain Geometrical Parameters in Roundabouts HA Al Hasanat, G Schuchmann Periodica Polytechnica Civil Engineering , 2022 2022 Citations: 15
Development of empirical models to predict gap acceptance parameter based on the geometrical and operational parameters of different roundabouts J Juhasz Periodica Polytechnica-civil Engineering , 2023 2023 Citations: 13
Critical Gap in Roundabouts–A Short Comparison of Estimation Methods HA Al Hasanat, G Schuchmann Periodica Polytechnica Transportation Engineering 50 (3), 273-278 , 2022 2022 Citations: 12
Connected automated vehicles entry capacity on roundabouts-case study Hungary HA Al Hasanat, O Alharasees, D Alothman 2024 2nd International Conference on Technology Innovation and Its … , 2024 2024 Citations: 10
DEVELOPMENT OF ROUNDABOUTS EMPIRICAL CAPACITY MODEL–CASE STUDY OF HUNGARY HA AL HASANAT, J JANOS Scientific Journal of Silesian University of Technology. Series Transport 120 , 2023 2023 Citations: 10
THE INFLUENCE OF CIRCULATING AND ENTERING FLOWS ON CRITICAL GAPS VALUE IN ROUNDABOUTS. HA Al Hasanat, J Juhasz International Journal for Traffic & Transport Engineering 12 (3), 322-339 , 2022 2022 Citations: 10
Capacity of Single-lane Roundabouts in Hungary HA Al Hasanat, D Alothman, O AlHarasees Periodica Polytechnica Transportation Engineering , 2025 2025 Citations: 7
A comprehensive human factors approach to pedestrian accidents analysis in urban environments O Alharasees, HA Al Hasanat, R Al-Matarneh 2025 2nd international conference on advanced innovations in smart cities … , 2025 2025 Citations: 6
Public perception of autonomous and shared autonomous vehicles: Case study of Amman O Alharasees, HA Al Hasanat, D Alothman 2024 2nd International Conference on Technology Innovation and Its … , 2024 2024 Citations: 6
The influence of geometry and connected automated vehicles on single-lane roundabout capacity HAA Hasanat, O Alharasees Innovative Infrastructure Solutions 10 (9), 412 , 2025 2025 Citations: 4
Interpretable machine learning for imbalanced pedestrian injury severity prediction in urban Jordan HA Al Hasanat, AB Hassanat, O Alharasees, AS Tarawneh, ... Journal of King Saud University–Engineering Sciences 37 (7), 1-42 , 2025 2025 Citations: 1
Multi-Method Assessment of Soak Pits in Jordan: Environmental, Economic, and Public Health Implications MA AlMubaidin, O Alharasees, HA Al Hasanat Water, Air, & Soil Pollution 237 (10), 598 , 2026 2026
Adoption of autonomous and shared autonomous vehicles: a multi-criteria decision-making approach O Alharasees, HA Al Hasanat, D Alothman International Journal of Transportation Science and Technology , 2026 2026
Evaluation of vehicle lateral positioning for lane-keeping performance across multiple sites H Al Hasanat, O Alharasees, L Alshamaileh Scientific Journal of Silesian University of Technology. Series Transport, 5-25 , 2025 2025
