Civil Engineering Commons^™

Driving Volatility In Instantaneous Driving Behaviors: Studies Using Large-Scale Trajectory Data, Jun Liu

Doctoral Dissertations

Increasing amounts of data, generated by electronic sensors from various sources that include travelers, vehicles, infrastructure and the environment, referred to as “Big Data”, represent an opportunity for innovation in transportation systems and toward achieving safety, mobility and sustainability goals. The dissertation takes advantage of large-scale trajectory data coupled with travel behavioral information and containing 78 million second-by-second driving records from 100 thousand trips made by nearly four thousand drivers. The data covers 70 counties across the State of California and Georgia, representing various land use types, roadway network conditions and population. The trajectories cover various driving practices made by …

Spatio-Temporal Dynamics Of Short-Term Traffic, Jianjiang Yang

Doctoral Dissertations

Short-term traffic forecasting and missing data imputation can benefit from the use of neighboring traffic information, in addition to temporal data alone. However, little attention has been given to quantifying the effect of upstream and downstream traffic on the traffic at current location. The knowledge about temporal and spatial propagation of traffic is still limited in the current literature. To fill this gap, this dissertation research focus on revealing the spatio-temporal correlations between neighboring traffic to develop reliable algorithms for short-term traffic forecasting and data imputation based on spatio-temporal dynamics of traffic.

In the first part of this dissertation, spatio-temporal …

Self-Learning License Plate Matching Algorithm: Some Enhancements And Its Role In Travel Time Ground Truth Measurements, Stephanie Raven Ann Hargrove

Doctoral Dissertations

Probe vehicle and floating traveler data can provide more detailed information about highway use across a roadway network than traditional transportation data sources. However, there are numerous concerns about accuracy, e.g., road user coverage, locational accuracy, and aggregation methods. To address these concerns, evaluations must be completed using a highly accurate data collection method to capture ideal ground truth. For the purpose of this dissertation, license plate recognition (LPR) technology is considered to be the suitable collection method for, and in lieu of, the all ground truth. The data can be obtained using a pair of mobile LPR units to …