announcement
Dr. Mohammed Almannaa will give the talk “AI in Traffic Engineering: Applications and…
introduction/brief CV
Transportation Engineering and Road Safety
Dr. Mohammed Hamad Almannaa is an Associate Professor in the Department of Civil Engineering at King Saud University and Supervisor of the Traffic Simulation Laboratory. His research and consulting focus on road safety, congestion management, intelligent transportation systems, and data-informed decisions using AI.
He is a part-time consultant to the National Center for Transport Safety since August 2026 and chairs the Scientific Advisory Council of Aman Association for Traffic Accident Prevention. He holds a PhD in Transportation Engineering from Virginia Tech (2019), is classified as a Professional Engineer by the Saudi Council of Engineers, and holds Saudi Patent SA368033.
Traffic Simulation Laboratory
He supervises the Traffic Simulation Laboratory in the Department of Civil Engineering, which is dedicated to traffic simulation, congestion analysis, and network performance evaluation. The laboratory supports traffic engineering courses, graduate programs in transportation engineering, and graduation projects.
Laboratory page on the College of Engineering website (Arabic)
Consulting, Training and Collaboration
He provides consulting, training and research collaboration for government agencies, companies, engineering firms and universities in Riyadh and across Saudi Arabia:
- Traffic impact studies: preparation and review for residential and commercial developments, traffic counts, trip generation, level of service, and parking.
- Crash investigation and road safety: technical reports, crash-severity analysis, risk factors, and expert input on traffic cases.
- Congestion and data analytics: speed and network analysis, traffic simulation, machine learning, and AI applications.
- Training: road safety, human factors and RSP1, traffic impact assessment, crash investigation, and AI agents.
- Research collaboration: joint projects and publications, and co-supervision of master’s and doctoral theses.
Delivered the course “Traffic Engineering and Transport Planning” for Riyadh Municipality engineers (28–29 October 2026).
Contact: malmannaa@ksu.edu.sa — Office phone and WhatsApp +966 11 806 3197 — WhatsApp chat
Riyadh Economic Forum Traffic Congestion Study
Dr. Mohammed Almannaa speaking at the third discussion workshop of the study “The Impact of Traffic Congestion in Major Saudi Cities: Causes and Solutions” (May 2026, in Arabic).
Selected Recent Research
What Pushes Cyclists To Grab Their Phones? The Relative Influence Of Risk Perception And Technology Affinity
2026 — an international study of mobile phone use among cyclists, risk perception, and technology affinity.
Effect of Gender, Cognitive Distraction, and Environmental Conditions on Young Drivers’ Behavior: A Study Using Physiological Sensors and a Driving Simulator
IEEE Access (2026) — driving-simulator and physiological-sensor data are used to examine young drivers, cognitive distraction, and road conditions.
Ramadan as a Natural Experiment in Urban Mobility: Evidence of Network-Level Peak Redistribution from Probe Traffic Data
IEEE RTSI 2026, Espoo, Finland — probe traffic data are used to examine how Ramadan redistributes peak traffic across Riyadh’s road network.
Multi-criteria facility location for emergency medical services using AHP and GIS: Public sector supply chain case in Riyadh
Journal of Engineering Research (2025) — AHP and GIS support multi-criteria planning of emergency medical service facilities in Riyadh.
All publications — classified and ordered by year
Site Pages
- Full CV — education, projects, leadership, committees and memberships
- Publications — journals, conferences, reports and theses
- Teaching, supervision and office hours
- Scientific visits and field applications
- News, coverage and articles
- Event photos and videos
Research Profiles and Contact
Google Scholar | ORCID | Scopus | Web of Science | LinkedIn | X
Office 2A70, Department of Civil Engineering, College of Engineering, King Saud University, Riyadh, Saudi Arabia — malmannaa@ksu.edu.sa — WhatsApp
areas of expertise
- Traffic safety and crash analysis: crash severity modeling, risk factor identification, technical crash investigation, and policy-support studies.
- AI in transportation: machine learning and deep learning, traffic state and demand prediction, spatial and temporal data analysis, and AI agents.
- Intelligent transportation systems and simulation: traffic simulation, connected and automated vehicles, and vehicle-to-infrastructure communication.
- Congestion and network operations: congestion diagnosis at intersection, corridor, and network level, and analysis of speed and traffic data.
- Traffic impact studies and planning: traffic impact assessment of developments, and optimization of EMS station locations and response times.
- Active mobility and micromobility: bike-sharing and e-scooter systems, usage analysis, and operations optimization.
publications
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A multinational online survey of 15,312 adult cyclists in 44 countries is analyzed with structural equation modeling to test whether phone use while riding relates to self…
The study compares crash involvement among drivers with and without arthritis. Naturalistic driving data provide vehicle movements and behavioral observations.
A conference presentation on Optimal Intersection Control of Automated and Cooperative Vehicles.
courses
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Course Description A three-credit elective introducing machine learning and AI fundamentals and their applications to transportation, including road safety, micromobility, and…
Scientific Visits and Field Applications The course includes scientific visits connecting transport planning, road safety and incident response with practice in specialist organizations.…
Course Description A two-credit course introducing the analysis and design of transportation systems, including highways, traffic systems, public transport, and air transportation. Topics…
office hours
| Saturday | Sunday | Monday | Tuesday | Wednesday | Thursday | Friday | |
|---|---|---|---|---|---|---|---|
| from | _ | 11:00 AM | _ | 11:00 AM | _ | 10:00 AM | _ |
| to | _ | 12:00 PM | _ | 12:00 PM | _ | 12:00 PM | _ |
| location | _ | مكتب 2A70 / Office 2A70 مكتب 2A70 / Office 2A70 | _ | مكتب 2A70 / Office 2A70 مكتب 2A70 / Office 2A70 | _ | مكتب 2A70 / Office 2A70 مكتب 2A70 / Office 2A70 | _ |