Book Description

Crash-based safety evaluation is often hampered by randomness, lack of timeliness, and rarity of crash occurrences. Surrogate safety data are commonly used as an alternative to crash data; however, its current practice is still resource intensive and prone to human errors. The advent of connected vehicle technology allows vehicles to communicate with each other as well as infrastructure wirelessly. Through this platform, vehicle movements and signal status at the facilities can be automatically and continually monitored in real time. This study explores the viability of long-term safety performance evaluation at signalized intersection using connected vehicle technology. The development focuses on vehicle-to-infrastructure (V2I) communications which require one road-side equipment (RSE) and some level of on-board equipment to be successful. To accomplish the objective, the researchers defined useful safety measures and developed specific algorithms to derive them in real time from the V2I communication data sets. The safety measures were categorized into single-OBE measures and dual-OBE measure based on the number of the equipped vehicle needed to be monitored. We used vehicles trapped in dilemma zone as the single-OBE measure. The dual-OBE measures included rear-end and crossing conflicts. Different simulation scenarios were designed in VISSIM to test the effectiveness of the proposed framework, effect of market penetration rate as well as required observation period for effective implementation. The evaluation results indicated that the application can effectively detect changes in safety performance at full market penetration. It can detect a shift of crash pattern from rear-end crashes to right-angle crashes due to the shorted inter green interval at low traffic volume as well as the mitigation of this pattern during the medium-to-high traffic volume. The selected measures can also identify the increasing risk of rear-end and right-angle crashes after removing advance detectors at the major approaches. Sensitivity analysis from the 60 simulation hours' data showed that more than 40% and 60% penetration rate is likely to be required for a reliable detection in the low volume level and medium-to-high volume level, respectively. Increase of traffic volume activated the corresponding phases more frequently and may result in fewer safety measures being collected. Although losing the power of detection, single-OBE measure was demonstrated to be more reliable at lower penetration rate. Under low OBE market penetrations, observation period can be extended to compensate for small sample size. However, the required observation periods vary with the types of safety indicators being collected and the levels of OBE saturation. The electronic version of this dissertation is accessible from http://hdl.handle.net/1969.1/152565