Traffic Bottlenecks: Identification and Solutions

EXECUTIVE SUMMARY

It is usually accepted that unnecessary traffic delays and vehicle emissions produce adverse impacts on quality of life. The Texas A&M Transportation Institute’s (TTI) TTI’s 2012 Urban Mobility Report further summarizes the ways in which traffic problems are tied to the Nation’s economy.⁽¹⁾ Given these impacts on mobility, the environment, and the economy, decades of research have been performed on congestion and bottleneck mitigation.^(2–4) However, this research is becoming outdated. New technologies and new ideas are expanding the array of possible solutions. Root causes of congestion and bottlenecks, which have been identified by prior research, have been found to be oversimplified.⁽⁵⁾ As a result, the traditional approaches must be updated, and new solutions must be found to solve these bigger problems.

To solve the U.S. traffic congestion problem, mitigation or elimination of bottlenecks is believed to be a top priority. The 2004 report, Traffic Congestion and Reliability: Linking Solutions to Problems, indicates that bottlenecks are a major cause of traffic congestion.⁽⁵⁾ For example, figure 1 implies that bottlenecks are the single largest source of traffic congestion. Another reason for prioritizing mitigation or elimination of bottlenecks is the exponentially increasing delay experienced by drivers affected by bottlenecks.

Figure 1. Graph. Traffic congestion causes from 2004.⁽⁵⁾

Figure 2 illustrates the simplified version of this well-known relationship, which is documented in the 2010 Highway Capacity Manual (HCM).⁽⁶⁾ With traffic congestion, there is typically a tipping point at which smooth vehicle flow breaks down, and it transitions into stop-and-go conditions. Subsequently, these stop-and-go conditions often form a bottleneck, severely degrading mobility throughout the affected area. Any successful efforts to prevent bottlenecks from forming, minimize the duration of unavoidable bottlenecks, or minimize the intensity of unavoidable bottlenecks would bring much greater benefits than congestion reductions in areas where bottlenecks do not occur. Indeed, a 5 percent reduction in congestion on the left side of the congestion curve shown in figure 2 would bring only modest reductions in vehicle delay, whereas a 5 percent reduction in congestion on the right side of the congestion curve (i.e., typical bottleneck conditions) would bring much steeper reductions in vehicle delay.

Figure 2. Graph. Vehicle delay versus degree of traffic congestion.

Given that bottleneck mitigation is a top priority, the question becomes how can bottleneck mitigation be achieved or improved. The bottleneck mitigation process can be divided into three subprocesses: identification, diagnosis, and solutions. In order to be mitigated, the bottleneck must first be identified and diagnosed.

Although traffic engineers and typical drivers often have a good sense of when and where bottlenecks tend to occur in their area, significant room for improvement exists in the ability to precisely quantify and prioritize these bottlenecks. This process is known as “bottleneck identification.” To justify investments towards improved traffic operations, engineers and policymakers need scientific and accurate methods of bottleneck identification. However, status quo methods are limited and/or outdated. Peak-hour analyses are becoming outdated as a sole source of bottleneck identification because they fail to account for changing conditions throughout the year. There has been a movement toward reliability modeling, which attempts to capture these annual effects. But due to significant input data and calibration requirements, the reliability models suffer from practicality issues. Additionally, there have been recent improvements in data-driven intelligent transportation system (ITS) technologies, which identify bottlenecks in real time. However, there is room for improvement in the robustness of performance measures derived from these technologies. Finally, some engineers have compared and ranked bottlenecks on the basis of experience and judgment. Despite their cost effectiveness, judgment-based qualitative assessments lack credibility unless backed by quantitative results. This report discusses project-specific software development, which produced innovative performance measures for bottleneck identification. This report also includes the insights that can be gained through the use of these performance measures. Figure 3 illustrates the Congestion and Bottleneck Identification (CBI) software tool developed as part of this project. It is hoped that the new performance measures will be adopted by States and/or commercial products for a new level of robustness in bottleneck identification.

Figure 3. Screenshot. CBI software tool.

Once the bottleneck locations are precisely identified, the question becomes how to prioritize them for subsequent mitigation. The bottleneck identification process provides an initial indicator of the likely prioritization through performance measures that reveal their operational impacts. However the bottleneck diagnoses and solutions also affect prioritization because they shed light on the true benefit-cost (B/C) ratio. This report does not delve deeply into bottleneck diagnosis issues. Instead, it provides a comprehensive set of solutions, which should be analyzed by engineers to determine whether or not they are compatible with their bottlenecks.

Bottleneck solutions in this report are divided into three categories. First, there is a playbook of 70 bottleneck solutions divided into 7 categories. Second, there is a set of low-cost bottleneck solutions that currently have real-world implementations but are likely underdeployed in the United States. Third, there is a set of low-cost innovative solutions that are not yet deployed in the United States. The report focuses on potentially underrated strategies as opposed to popular strategies, like ramp metering, which have been extensively researched and implemented in recent decades. Moreover, this report focuses on low-cost solutions as opposed to solutions requiring excessive infrastructure investments or advanced vehicle technologies. While it is certainly hoped that connected and automated vehicles will produce significant congestion relief in the upcoming years, the magnitude and/or timeliness of this relief cannot be taken for granted, which motivates the pursuit of alternative solutions. This report focuses on solutions involving dynamic lane use, contraflow or reversible lane use (e.g., dynamic reversible left-turn (DRLT) lanes at signalized diamond interchanges, as illustrated in figure 4 and figure 5), hard shoulder lane use, lane width reduction, and modest extension of auxiliary lanes. These solutions produce significant operational benefits with only minor modifications to existing infrastructure. This report also provides design guidance on signing, signalization, and striping for these strategies, with a follow-on human factors study for two of the strategies. Finally, this report provides microsimulation and a B/C analysis for the strategies.

 

Figure 4. Screenshot. Conventional lanes at a signalized diamond interchange.

 

Figure 5. Screenshot. DRLT lanes at a signalized diamond interchange.

In summary, this report presents the results of a significant research project devoted to bottlenecks. It provides a modernized view of U.S. bottleneck mitigation by (1) introducing new methods of robust bottleneck identification, (2) describing new bottleneck mitigation strategies, and (3) presenting new research on the operational effectiveness and B/C ratios of these methods. The new methods of bottleneck identification are made possible by recent developments in high-resolution data collection technologies. Promising new mitigation strategies were identified and studied by a research team familiar with traffic operations state of the practice. Operational effectiveness of the bottleneck mitigation strategies was primarily assessed through simulation studies, and B/C ratios were estimated for five specific strategies.