Award Date


Degree Type


Degree Name

Doctor of Philosophy (PhD)


Civil and Environmental Engineering and Construction

First Committee Member

Jee Woong Park

Second Committee Member

Brendan Morris

Third Committee Member

Mohamed Kaseko

Fourth Committee Member

David James

Fifth Committee Member

Mohamed Trabia

Number of Pages



The traditional TRS has been extensively used as a traffic calming device to provide cognitive alerts in the form of sound and vibration to drivers. However, TRS always remains fixed on the road and thus exerts cognitive alerts, irrespective of any potential downstream hazards. Moreover, the continuous exposure to rumble strips has been identified as a source of discomfort and annoyance for drivers, which limits its application to potentially useful scenarios. This study explores a rumble strip design with dynamic behavior named as Demand-Responsive Transverse Rumble Strip (DRTRS) in order to address the limitations of static TRS. The study incorporates DRTRS’ appropriate design dimensions and operation scheme, sound and vibration effect, speed-reducing effect, and pedestrian demand-based activation. In methodological procedures, the study explored four main aspects of DRTRS for designing and evaluating its effectiveness, which includes identification of optimum design dimensions, quantitative experimentation of in-vehicle sound and vibration, quantitative analysis of DRTRS effectiveness on drivers’ speed reductions, and prediction of the pedestrian demand for the activation mechanism of the DRTRS system. The study identified and selected the optimum width and depth of the rumble units of the DRTRS system prototype. The system was found to be effective in engaging the auditory and haptic senses of drivers, by generating discernible in-vehicle sound and vibration. Thereafter, the engagement of drivers’ cognitive senses yielded by the system had a significant effect on reducing vehicle speeds. In addition, the system can be set for flexible activation length based on the need from the crosswalks identified by pedestrian presence and prediction algorithms.


Countermeasure; Pedestrian; Sound and vibration; Statistical modeling; Traffic safety; Vehicle speed


Civil Engineering | Transportation

File Format


File Size

6500 KB

Degree Grantor

University of Nevada, Las Vegas




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