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Civil engineering grad student earns top marks in paper competition

Khezerzadeh poses in front of Jesse Hall on the MU campus.

The Strategic Highway Research Program [SHRP] 2 Safety Data Program and the Transportation Research Board [TRB] Oversight Committee for Use and Oversight of SHRP 2 Safety Data, Phase 1 recently selected Amirhossein Khezerzadeh, a graduate student in the MU Civil Engineering Department, as one of the winners of their student paper competition.

The Strategic Highway Research Program [SHRP] 2 Safety Data Program and the Transportation Research Board [TRB] Oversight Committee for Use and Oversight of SHRP 2 Safety Data, Phase 1 recently selected Amirhossein Khezerzadeh, a graduate student in the MU Civil Engineering Department, as one of the winners of their student paper competition.

Khezerzadeh will present his preliminary research at an expenses paid trip to the annual TRB meeting in January in Washington, D.C. In addition, he will have the opportunity to publish his final findings — along with co-author and MU civil engineering doctoral student Boris Claros — in the July edition of TRB’s journal, Transportation Research Circular.

“On Oct. 6, they told us we won the competition,” Khezerzadeh said. “They chose, I believe, six [graduate] students.”

The goal of the competition was to use information from either one or both of the SHRP 2 Naturalistic Driving Study database and Roadway Information Database to attack a particular transportation-based research question. Khezerzadeh’s paper proposed a method through which a series of set variables would be combined to predict crash frequency per driver over a period of time. The method is similar to the way the Highway Safety Manual makes these predictions, but it will use driver, vehicle, and trip information to improve accuracy, based off the NDS database.

“There are about 5.5 million trips recorded over three years [in the databases],” Khezerzadeh said. “They recorded all the crashes by severity – crash, near crash, and crash relevant. It’s a pretty nice dataset.

“We proposed to develop a model that uses this data with different variables — like age, gender, education, marital status, physical and mental state, vehicle and trip variables, and so on. We can predict the number of crashes for each driver within a period of time.”

Khezerzadeh thanked both Claros and his faculty adviser, civil engineering professor Carlos Sun, for their help with his paper and research, and said he’s excited to get the opportunity to present in the nation’s capital and earn a publication credit in a peer-reviewed journal. He added that the publication process should help him come graduation time.

“When you publish a part of your thesis, it’s going to be like already getting credit for it,” Khezerzadeh said. “It’ll be easier to defend it.”