Principal Investigator(s):
Michael Levin, Assistant Professor, Civil, Environmental and Geo-Engineering
Project summary:
Connected vehicle technology creates new opportunities for obtaining knowledge about the surrounding traffic and using that knowledge to optimize individual vehicle behaviors. This project created an interdisciplinary group to study vehicle connectivity, and this report discusses three activities of this group. First, researchers studied the problem of traffic state (flows and densities) using position reports from connected vehicles. Even if the market penetration of connected vehicles is limited, speed information can be inverted through the flow-density relationship to estimate space-and-time-specific flows and densities. Propagation, according to the kinematic wave theory, is combined with measurements through Kalman filtering. Second, the team studied the problem of cyber-attack communications. Malicious actors could hack the communications to incorrectly report position, speed, or accelerations to induce a collision. By comparing the communications with radar data, the project team developed an analytical method for vehicles using cooperative adaptive cruise control to detect erroneous or malicious data and respond accordingly (by not relying on connectivity for safe following distances). Third, the team considered new spacing policies for cooperative adaptive cruise control and how they would affect city traffic. Due to the computational complexity of microsimulation, the team elected to convert the new spacing policy into a flow-density relationship. A link transmission model was constructed by creating a piecewise linear approximation. Results from dynamic traffic assignment on a city network showed that improvements in capacity reduces delays on freeways, but (surprisingly) route choice increased congestion for the overall city.