Causal inference and impact assessment in traffic safety; application of accident investigation and reconstruction methods to address traffic engineering questions; using Bayesian statistical methods in traffic and transportation engineering; application of optimization methods to problems in traffic engineering and transportation planning.
Davis, G. A. 2019. Explaining crash modification factors: Why it's needed and how it might be done. Accident Analysis and Prevention. 131: 225-233.
Davis, G., and Cheong, C., 2019. Pedestrian Injury Severity vs Vehicle Impact Speed: uncertainty quantification and calibration to local conditions, Transportation Research Record, 2673(11): 583-592.
Davis, G. 2019. Explaining Crash Modification Factors: Why It’s Needed and How It Might Be Done, Accident Analysis and Prevention, 131: 225-231.
Davis, G., 2017. Mapping the Middle Ground: Exploratory Surveying as Distributed Cognition, Terrae Incognitae, 49: 21-36.
Gao, J. and Davis, G. 2017. Using Naturalistic Driving Study Data to Investigate the Impact of Driver Distraction on Driver’s Brake Reaction Time in Freeway Rear-End Events in Car-Following Situation, Journal of Safety Research, 63: 195-204.
Davis, G., Moshtagh, V., and Hourdos, J. 2016. Safety-Related Guidelines for Time-of Day Changes in Left Turn Phasing, Transportation Research Record, 2557, 2016, 100-107.
Chatterjee, I., and Davis, G. 2016. Analysis of Rear-Ending Events on Congested Freeways Using Video-Recorded Shockwaves, Transportation Research Record, 2583: 110-118.
Chatterjee, I., and Davis, G. 2014. Using Naturalistic Driving Data to Characterize Driver Behavior in Freeway Shockwaves, Transportation Research Record, 2434: 9-17.
Feng, Y., Hourdos, J., and Davis, G. 2014. Probe Vehicle Based Real Time Traffic Monitoring on Urban Roadways, Transportation Research C, 40: 160-178.
Davis, G. 2014. Crash Reconstruction and Crash Modification Factors, Accident Analysis and Prevention, 62: 294-302.
Feng, Y.; Hourdos, J.; Davis, G. 2014. Probe vehicle based real-time traffic monitoring on urban roadways. Transportation Research Part C: Emerging Technologies. 40: 160-178.
Davis, G. 2014. Sample-based estimation of vehicle speeds from yaw marks: Bayesian implementation using Markov Chain Monte Carlo simulation. SAE Technical Papers.
Chatterjee, I., and Davis, G. 2013. An Evolutionary Game Theoretic Approach to Rear-Ending Events on Congested Freeways, Transportation Research Record, 2386: 121-127.