The continuing growth of traffic congestion on U.S. roadways has become an increasing concern for both travelers and transportation agencies. According to the Texas Transportation Institute’s estimate, the total financial cost of congestion in the U.S. in 2014 was $160 million, or $960 per commuter. In North Carolina, demand for highway travel continues to grow as population increases, particularly in metropolitan areas. Construction of new highway capacity to accommodate this growth in travel has not kept pace. As a matter of fact, it is now well accepted that we cannot build our way out of congestion. Congestion is largely thought of as a big city problem, but delays are becoming increasingly common in small cities and some rural areas as well. As such, developing a system approach to improving bottleneck analysis in North Carolina is essential for reducing traffic congestion, and improving the overall traveling experience for all North Carolinians. The purpose of this dissertation is to develop a holistic bottleneck analysis approach to assist NCDOT in identifying, examining, modeling and mitigating freeway bottlenecks at a system level compared to focusing on local bottlenecks only. This will enable NCDOT to identify, manage and reduce traffic congestion statewide in a systematic, efficient and effective manner. Traditional bottleneck identification methods are developed based on performance measures collected from stationary loop detectors (or Bluetooth sensors). However, the applications of such local sensor based methods are usually restricted by the geographical coverage and the density of embedded detectors on the road. In recent years, the coverage and fidelity of vehicle probe data (VPD) have been greatly improved. The possibility of obtaining extensive, continuous, and dynamic VPD from private sectors such as HERE and INRIX offers a great opportunity to identify and assess freeway bottlenecks at the network level. A number of measures of effectiveness (MOEs) can be derived from VPD and be used for bottleneck identification and evaluation, such as the planning time index (PTI), frequency of congestion (FOC), and travel time index (TTI). In this dissertation, various MOEs were analyzed in terms of their feasibility for freeway bottleneck identification and ranking. The results indicate that using travel time reliability (TTR) measures (such as FOC or PTI) can reveal only a specific facet of the travel time distribution, but are not be able to quantify the intensity dimension of the traffic congestion caused by the bottlenecks. As a consequence, a comprehensive bottleneck identification method which integrates both PTI and TTI is developed. Since both PTI and TTI are dimensionless travel time-based performance measures and are developed using the same benchmark for each roadway segment (i.e., free-flow travel time), it is reasonable to integrate both measures into the bottleneck identification and ranking framework. By doing so, both dimensions of traffic congestion on each roadway segment can be accounted for. A case study is performed to illustrate the proposed methodology, using a total of approximately 34 million speed records collected in INRIX for four major interstate corridors in Mecklenburg County, NC, in 2015. Freeway bottlenecks are identified and prioritized for a.m., p.m., both a.m. and p.m. peak periods, respectively. The potential causes of each bottleneck group are carefully examined by synthesizing the following information: (1) bottleneck identification and ranking results, (2) geometric characteristics around the bottleneck, (3) operational analysis results obtained from the Highway Capacity Software (HCS), and (4) field trip observations. Based on them, a total of 59 scenarios aiming at alleviating bottleneck congestion are designed and evaluated in this study, which include 26 lane-addition scenarios, 15 road pricing scenarios, and 18 combined scenarios (i.e., lane addition and road pricing). Since improved traffic conditions and new infrastructure can directly affect traveler’s route-choice behavior and will lead to a new regional traffic flow pattern, which may either mitigate or exacerbate existing system bottlenecks, a mesoscopic DTA modeling tool is employed in this dissertation to assess the impact of various candidate bottleneck mitigation strategies at the network level. The findings suggest that under certain conditions, simply adding one more lane at the bottleneck may deteriorate traffic performances. Such counterintuitive results have been widely reported in the literature, and such phenomenon is known as the Braess’s paradox. In addition to that, this study also observe the existence of hidden bottlenecks while evaluating candidate bottleneck mitigation projects. Because the causes of bottlenecks can be highly complex and if one is ameliorated, one or more unexpected bottlenecks can quickly emerge downstream. As such, the decision makers must be very careful to ensure that informed decisions are made as to where to apply the bottleneck mitigation countermeasures.A performance-based framework is developed to assist in assessing and prioritizing candidate bottleneck mitigation alternatives. The general project ranking framework includes five components: (1) developing candidate bottleneck mitigation projects, (2) evaluating each project, (3) screening of projects, (4) benefit-cost analysis (BCA), and (5) sensitivity analysis. It is envisioned that the proposed framework can provide insightful and objective information for traffic engineers and decision-makers in choosing effective mobility improvement strategies.
