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Acceptable Planning: Influencing Individual Behavior to Reduce Transportation Energy Expenditure of a City
Our research aims at developing intelligent systems to reduce the transportation-related energy expenditure of a large city by influencing individual behavior.
Impact of Narrow Lanes on Arterial Road Vehicle Crashes: A Machine Learning Approach
The RF was used to compute the importance of the lane width predictors in our regression model based on two different measures.
A Comparative Analysis of E-Scooter and E-Bike Usage Patterns: Findings from the City of Austin, TX
Results also show a similar usage pattern for the average speed of e-bikes and e-scooters throughout the days of the week and a different usage pattern for the average speed of e-bikes and e-scooters over the hours of the day.
Toward a Rational and Ethical Sociotechnical System of Autonomous Vehicles: A Novel Application of Multi-Criteria Decision Analysis
There is a pressing need to address relevant social concerns to allow for the development of systems of intelligent agents that are informed and cognizant of ethical standards.
Environmental and Safety Impacts of Vehicle-to-Everything Enabled Applications: A Review of State-of-the-Art Studies
With the rapid development of communication technology, connected vehicles (CV) have the potential, through the sharing of data, to enhance vehicle safety and reduce vehicle energy consumption and emissions.
Optimization of Vehicle Trajectories Considering Uncertainty in Actuated Traffic Signal Timings
The results present the required levels of confidence in these predictions to achieve most of the possible savings in fuel consumption.
