Multimodal Signal Retiming Projects: A Survey-Based Exploration of Traffic Signal Professionals’ Practices and Challenges

Abstract

In the realm of traffic signal operations, the Signal Timing Manual second edition (STM2) serves as a foundational guide for professionals engaged in multimodal signal retiming projects. However, it is acknowledged that the STM2 has its limitations, and real-world conditions often necessitate adaptations in the established procedures. Considering this context, this research endeavors to bridge this gap by conducting a comprehensive survey aimed at traffic signal professionals. This study presents the findings of a comprehensive survey conducted among traffic signal professionals to explore the methodologies, challenges, and practices involved in multimodal signal retiming projects. The survey aimed to obtain detailed insights into the current state of signal retiming, the types of data and tools utilized, and the adaptations necessary to address the complexities of multimodal urban transportation networks. The survey highlights and summarizes responses from 36 professionals across North America, providing insight into both the common strategies and unique challenges faced by those responsible for optimizing signal timings in diverse and dynamic urban environments. The survey results reveal a reliance on diverse tools and data types for signal optimization, highlighting the complexities of accommodating different transportation needs. The findings underscore the importance of tailored approaches and advanced technologies in enhancing signal retiming processes. The insights gained from this study will inform future strategies and enhance the effectiveness of signal retiming procedures in urban areas, thereby contributing to improved traffic management and multimodal transportation efficiency.

1. Introduction

Traffic congestion is a growing concern worldwide and in the United States, with drivers spending an average of more than one hundred hours in traffic annually [1]. As traffic congestion increases in urban areas, the efficient operation of road systems becomes even more important. Traffic signal control systems play a crucial role in enhancing the efficiency of urban networks by managing traffic flow and improving safety for all road users [2]. By controlling the flow of traffic at intersections and crosswalks, traffic signals help reduce the number and severity of accidents, minimize travel time, and improve air quality by reducing fuel consumption and emissions from stop-and-go vehicles [3,4,5,6].

The primary goal of traffic signals is to operate an appropriate set of signal timing strategies. In the United States, there are approximately 300,000 traffic signals, and more than 75% of them could benefit from equipment enhancements or timing adjustments [7]. Traffic signals need to be periodically retimed (typically every 3 to 5 years) to adjust to changing demand patterns [8]. Several studies have looked at how to time traffic signals properly. They examined various aspects like procedures, tools, data used, results, and benefits. It is widely observed that the effectiveness of signal retiming is significantly influenced by the accuracy of the data inputs and the signal timing procedures [9,10,11].

The Traffic Signal Timing Manual (STM1), published in 2008 by the Federal Highway Administration, provides comprehensive guidance on traffic signal timing procedures [10]. Although the manual provides comprehensive coverage of traffic signal timing fundamentals and describes the procedures for generating signal timing plans for North American applications, it is mostly focused on urban areas, whereas the signal timing in suburban, rural, or small communities may not be fully covered. Additionally, the manual primarily focuses on vehicle traffic flows, lacking discussions on pedestrians, cyclists, and public transit, which are essential considerations in urban environments. The typical signal timing adjustment involves the use of optimization software tools such as Synchro or TRANSYT-7F, which primarily focus on minimizing vehicular delay and the number of stops [12,13,14]. It is crucial to acknowledge that signal timing is not a universal method and cannot be applied to all situations (e.g., minimizing vehicular delay may not be suitable in every situation). Practitioners are encouraged to adopt an outcome-based approach to signal timing, considering the unique characteristics of the operating environment, user priorities, and local operational objectives.

In 2015, the Transportation Research Board published the STM2, advocating for an outcome-based approach to signal timing development [11]. The outcome-based approach for developing signal timing focuses on the desired performance outcomes rather than rigid standards or methods. It emphasizes defining performance measures like delay, stops, emissions, etc., and setting targets or thresholds to guide timing decisions. Despite these improvements, the procedure has inherent limitations. It often neglects multimodal operations and overlooks certain relevant aspects when determining user priorities. Moreover, it is constrained to conventional performance measures, which may not always align with the objectives. The subsequent section delves into specific examples illustrating these limitations:

• The STM2 correctly emphasizes the significance of location-based variations in objectives (rural, suburban, or urban), but this approach may still prove inadequate. For instance, it is recommended to prioritize pedestrians within an urban grid network. However, even in central business district (CBD) areas, multiple signalized intersections exhibit specific requirements and characteristics, and prioritizing one mode, in general, might not lead to the most appropriate solution.
• The STM2 acknowledges the importance of identifying user priorities, but it lacks a method for prioritizing one user group over another, especially in situations with conflicting requests.

The National Cooperative Highway Research Program (NCHRP) Research Report 969 underscores the significance of maintaining a balance between the needs of motorized and non-motorized users through considerate signal timing practices [15]. This report offers strategies and considerations aimed at enhancing accommodation for pedestrians and bicyclists, drawing upon the fundamental concepts outlined in the signal timing manual.

The Transit Cooperative Research Program (TCRP) conducted a study specifically focused on Transit Signal Priority (TSP) [16]. While the report offers a comprehensive overview of TSP systems and implementations, it provides minimal specific guidance for agencies seeking to optimize traffic signal timing or phasing in conjunction with TSP [17].

Signal retiming, a process that fundamentally involves judgmental elements, represents a genuine form of engineering design. No straightforward signal design and timing procedure can completely include and fully address all the potential complexities that may exist in any given situation and avoid subsequent fine-tuning [18]. This inherent complexity in signal retiming is a primary reason every organization adopts different approaches. Recognizing this diversity, this survey aims to understand the challenges and methods that signal professionals consider, providing valuable insights into the world of signal timing.

The field of traffic signal management is continuously evolving, especially with the increasing complexities of multimodal networks. This study conducted a comprehensive survey among traffic signal professionals in the United States, investigating their approach to addressing multimodal signal retiming projects. While various studies and surveys have explored different aspects of traffic signal control, including data inputs, optimization techniques, and recent advances in evaluation and maintenance, these efforts often lack a comprehensive focus on signal retiming and multimodal considerations. For example, a recent survey primarily concentrated on the state of practice in traffic signal operation, optimization, and management (TSOOMM) in the Southeast United States, highlighting the operational, environmental, economic, and safety benefits of well-designed traffic signal systems and emphasizing the need for transportation authorities to adopt new technologies to realize these benefits fully [19]. However, there remains a limited understanding of how signal timing strategies are adapted to simultaneously accommodate pedestrians, cyclists, and public transit users. This survey uniquely contributes to the field by specifically targeting the incorporation of multimodal elements in signal retiming practices, highlighting the diverse methodologies, challenges, and tools employed by professionals across North America.

The findings reported in this study provide valuable insights into (a) current signal retiming practices of agencies, (b) common challenges faced, and (c) modifications and adaptations to improve the current state of the art through innovative solutions. The primary purpose of the survey was to explore how multimodality is incorporated into signal retiming practices. By collecting data from traffic signal professionals, this research extracts valuable lessons learned and sheds light on the practical nuances of signal retiming projects. The survey explores the specific steps professionals take, the modifications made in response to contextual factors, and the areas where the STM2 guidelines may fall short. This approach emphasizes understanding practitioners’ perspectives and aligns with the study’s objectives to provide a descriptive overview of the diverse methodologies employed in the field.

The paper continues with a methodology section, followed by a detailed interpretation and discussion of the survey results, and concludes with a summary of the findings and recommendations for future actions.

2. Methods

To obtain information from traffic signal professionals, a comprehensive survey questionnaire was developed, incorporating specific inquiries about traffic signal professionals’ strategies in multimodal signal retiming projects. The survey comprised twenty questions that were categorized into several key areas, each addressing specific aspects of signal retiming procedures:

• Characteristics of the respondents (e.g., role and expertise of the respondent, and the number and types of traffic signals managed by them);
• Signal retiming process (e.g., current practices and common challenges, tools and methods, data utilization);
• Modifications to standard procedures to accommodate multimodality (e.g., suggestions and recommendations, adaptations to emerging transportation needs);
• Future directions and improvements (e.g., suggestions for improving current practices, expectations for technology advancements).

Figure 1 illustrates the graphical outline that visually represents the different sections and topics covered in the questionnaire.

Google Forms, a survey administration software included as part of the free, web-based Google Docs editors’ suite, was used to prepare the questionnaire as it provided a user-friendly and accessible platform [20]. Various features of Google Forms were utilized, including multiple choice, checkbox, open-ended, close-ended, and rating scale questions. After the survey was developed, it was evaluated and fine-tuned to ensure that the survey respondents could easily comprehend the questions and submit their responses before being distributed.

The survey was distributed to signal professionals across North America through multiple channels, including email, social media platforms such as LinkedIn and Facebook, and newsletters from professional organizations. Specifically, it was shared via the bi-weekly newsletter of the Mid-Atlantic Section of the Institute of Transportation Engineers (MASITE), and the monthly newsletter of Transportation & Development Institute (T&DI) of American Society of Civil Engineers (ASCE). The target audience comprised signal professionals from transportation agencies, consulting firms, academic institutions, and technology vendors.

The survey remained accessible for 40 days during April and May 2024. During this period, thirty-six participants completed the survey. Responses were collected anonymously, with the option for participants to provide their email addresses voluntarily if they wished to receive follow-up information about the survey outcomes. To uphold ethical standards, the survey included a clear statement outlining the purpose of the research, emphasizing that participation was voluntary and responses would remain confidential.

While the survey aimed to capture a broad range of insights, it has some potential limitations, including the relatively small sample size and the self-selecting nature of the respondents, which may introduce some bias. Additionally, the survey distribution was not segmented by sector, leading to a diverse but non-targeted respondent pool. Consequently, the participants and their responses may not fully reflect the specific characteristics or practices of each sector. Thus, while the findings offer valuable insights into general practices and challenges in signal retiming, the results should be interpreted with caution regarding their representativeness across all sectors within the field.

After a thorough screening process, duplicate or unrelated answers were eliminated. The following sections contain information regarding the received answers as well as the study’s findings and conclusions.

3. Results and Discussion

This section is divided into seven subsections providing a precise description of the survey results and their interpretation.

3.1. Role and Expertise

This section delves into the detailed interpretation of the responses to the survey questions. Thirty-six detailed responses were received from traffic signal professionals working in transportation agencies, consulting firms, academic institutions, or vendors of technology products.

The figure below shows the distribution of respondents’ organization types. Most respondents (55.6%) worked for consulting firms, while 25% worked for national/state/municipality transportation agencies, 16.7% worked for academic or research institutions, and 2.8% worked for vendors of technology products. Figure 2 depicts the distribution of respondents by organization type.

Most of the participants (33.3%) reported that they were conducting up to five signal retiming projects per year. Another 22.2% reported conducting 5–10 projects annually. A smaller proportion, 19.4%, reported conducting 10–20 projects per year, while 25% reported conducting more than 20 projects annually. Figure 3 illustrates the results of the question asking about the average number of signal retiming projects per year conducted by participants’ organizations. This distribution indicates that while most organizations conducted a modest number of signal retiming projects yearly, there was a notable minority handling a significant workload.

3.2. System Network Characteristics

The survey revealed that 78% of participants were responsible for managing traffic signals, with the majority overseeing coordinated systems. Conversely, 22% of respondents indicated that they did not have any signals under their management. Based on the survey responses, the percentage of coordinated signals and isolated signals that were managed by responding participants is shown in Figure 4. On average, approximately 70% of signals managed by respondents were coordinated, while the remaining 30% were isolated.

Figure 4 further illustrates this pattern using the boxplot presentation, with the range for the percentage of coordinated signals between 50% and 80%, while isolated intersections fell within the range of 20–50%. Only a small fraction of participants, likely two or three individuals, reported managing more isolated signals than coordinated ones. These findings highlight the dominance of coordinated signal systems among the surveyed professionals, underscoring the importance of understanding both isolated and coordinated systems in traffic signal management.

The survey results on the types of traffic signals under management varied widely among participants. Consistent with earlier findings, 22% of respondents indicated they did not manage any traffic signals. The remaining participants reported various proportions of pretimed, semi-actuated, fully actuated, and adaptive systems, as depicted in Figure 5.

Adaptive signals were the least common, ranging from 0% to 20% of the signals under the management of most participants, with one exception reporting exclusive management of adaptive systems which is shown with the outlier data point on top of the green bar in Figure 5. Fully actuated signals had the highest representation, with percentages reaching up to 60%. Semi-actuated and pretimed signals were reported in similar ranges, each constituting up to 50% of the managed signals.

Even though some responses were dismissed due to inconsistent reporting, valuable insights were provided through additional comments. One participant mentioned that their fully actuated and adaptive systems operated as semi-actuated systems during nighttime hours. Another participant reported that most of their isolated intersections were semi-actuated, while coordinated intersections were adaptive. Additionally, one respondent noted that the type of signals they managed depended on the time of day and varied throughout the week. It is worth nothing that in the following summary, the results of these questions were used regardless of the types of traffic signal operations the respondents were responsible for.

3.3. Signal Retiming Process

The survey results reveal the diverse range of guidelines that organizations employ for typical signal retiming procedures. The most widely used guideline was the MUTCD (Manual on Uniform Traffic Control Devices), with 58% of respondents indicating its use. This guideline is a foundational resource for traffic control and is extensively adopted across various agencies.

Local or agency-specific guidelines were the second most used, followed by 53% of the participants. These guidelines are tailored to the specific requirements and conditions of local agencies, municipalities, or states, reflecting the unique traffic conditions, inquiries, and priorities of each region.

The Signal Timing Manual (NCHRP Report 812, 2015) was also frequently referenced, with 33% of respondents incorporating it into their signal retiming procedures. This manual provides comprehensive guidance on developing and implementing signal timing plans and is a valuable resource for traffic signal professionals, which came out as the second edition of the Signal Timing Manual (FHWA-HOP-08-024, 2008).

In addition to these primary guidelines, a notable portion of respondents reported using ITE recommendations and both editions of the Signal Timing Manual (2008 and 2015). These resources collectively form a robust framework for signal retiming. However, some guidelines were less commonly utilized. The Transit Signal Priority: Current State of the Practice (TCRP Synthesis 149), Traffic Signal Control Strategies for Pedestrians and Bicyclists (NCHRP Research Report 969), and Traffic Signal Retiming Practices in the United States (NCHRP Report 409) were among the least referenced by survey participants.

Figure 6 illustrates these results providing an overview of the guidelines currently in use for signal retiming procedures. It is important to note that this represents a snapshot of current practices, and the preferred guidelines may evolve over time.

Furthermore, the survey aimed to assess the effectiveness of existing guidelines in meeting the needs for signal retiming projects in multimodal networks. The results, as illustrated in Figure 7, showed a mixed perception among respondents, with a significant portion expressing moderate satisfaction with the current guidelines.

A substantial portion of participants, about 45%, rated the coverage of existing guidelines at a notable level of 4 out 5, suggesting a reasonably comprehensive alignment with their needs. Additionally, 14 respondents (40%) rated the coverage at 3, indicating a neutral stance regarding the adequacy of the guidelines. A smaller yet noteworthy group of four participants gave a score of 5, signifying complete satisfaction with the existing guidelines’ capability to meet their requirements. Conversely, a minimal number of respondents, only two individuals, expressed dissatisfaction by rating the coverage at 2. Notably, no participants rated the coverage at the lowest level, indicating that while there may be room for improvement, the existing guidelines generally fulfilled a baseline level of expectations.

These results highlight the differing perspectives of signal professionals on how comprehensive the current guidelines are in handling the complex nature of multimodal networks. While a significant percentage acknowledged their effectiveness to a certain extent, there is still room for improvement and enrichment to better meet diverse needs and emerging trends in signal retiming practices.

To gain deeper insights into the signal retiming procedure, it is essential to examine the types of supplemental data utilized by traffic signal professionals. Figure 8 illustrates the types of data used for signal retiming purposes, as reported by respondents. The data reveal a diverse array of sources employed in signal retiming projects, reflecting the comprehensive approach taken by professionals in this field.

As can be seen, vehicular traffic volumes emerged as the most utilized type of data, with 83.3% of respondents incorporating this information into their retiming processes. Following closely behind, pedestrian volumes were utilized by 80.6% of respondents, highlighting the significance of pedestrian traffic in signal timing procedure. This high response rate highlights the need to better incorporate this critical data into methodologies used to determine timing plans, emphasizing the importance of multi-modal optimization methods.

Data on queue lengths and historical traffic patterns (e.g., ADT, AADT, peak hour traffic, seasonal variations, special event impact, etc.) were also commonly used; 69.4% of respondents said they depended on these sources in their signal retiming procedure. These data points offer valuable insight into past traffic behavior and current congestion levels, helping the process of signal retiming.

Data on cyclist volumes, speed, and travel times were used by 55.6% of professionals, highlighting their critical role in signal timing development in multimodal networks. Heavy vehicle volume data also played a significant role, with 52.8% of experts using it to account for the specific needs of larger transport modes.

The integration of public transportation data, such as boarding and alighting, dwell times, occupancy level, bus schedules, bus routes, bus stop locations, etc., with signal timing, was a practice adopted by about 40% of the participants.

While not as widely used, emergency vehicle data were being utilized by 25% of respondents. These data types are essential for signal retiming strategies, especially when immediate or direct situational assessment is required.

Furthermore, some of the participants added additional information about conducting in-person field visits during morning and evening peak traffic hours to gather comprehensive data or using observation cameras. Others mentioned that depending on the resolution of the study, they might consider using all the data types mentioned in the survey.

The survey demanded information regarding the use of signal optimization software and methods. Figure 9 illustrates a summary of the participants’ responses.

The most widely used software was SYNCHRO, with 42% of respondents employing it for their projects [21]. This indicates a strong preference for this software in signal retiming projects.

Highway Capacity Software (HCS) is the second most popular method, utilized by 16% of the respondents [22]. This was followed by manual fine-tuning of controllers in the field, a method employed by 11% of the respondents, demonstrating a significant reliance on hands-on adjustment techniques.

Around 11% of the respondents reported using various methods to leverage Automated Traffic Signal Performance Measures (ATSPM) data, such as performance monitoring, optimizing signal timing plans, adaptive signal control, and traffic responsive control. This highlights a growing trend towards data-driven approaches in signal retiming.

Both VISTRO [23] and manual time-space diagrams were used by 6% of respondents each, indicating a moderate level of adoption for these methods. Tru-Traffic was utilized by a minimal proportion of the respondents (around 5%). One respondent also noted using WaySync, demonstrating the variety of techniques accessible for multimodal network signal optimization and tuning.

Moreover, the survey evaluated the effectiveness of existing signal optimization software from the participants’ perspective. The results, as illustrated in Figure 10, showed moderate satisfaction with the existing tools. A substantial portion of participants, more than 75%, rated the coverage of existing tools at a notable level of 3, 4, or 5 out 5, suggesting reasonably broad satisfaction with the existing software. Conversely, a minimal number of respondents, only five individuals, expressed dissatisfaction by rating the coverage at levels 1 and 2.

Afterwards, survey participants were asked to report on their use of simulation or modeling tools to support multimodal signal retiming projects. Figure 11 clearly illustrates the results.

The most used simulation software among the respondents was VISSIM, with 47% of organizations utilizing it [24]. Following VISSIM, SimTraffic was employed by approximately 41% of respondents, indicating the significant role of this software in signal retiming projects [25].

AIMSUN and Transmodeler were less commonly used by the traffic signal professionals, with adoption rates of 6% and 4%, respectively [26]. Additionally, only one participant reported the use of TSIS/CORSIM. It is noteworthy that two participants reported not using any simulation or modeling tools within their multimodal signal retiming projects.

3.4. Challenges Faced

An important challenge in signal retiming projects involves managing the complexities posed by non-platoon arrivals of right/left-turning vehicles sharing the turn lane with through movement. Figure 12 illustrates the responses of 36 participants on how they would address this situation.

The most common strategy, endorsed by 21 participants (58%), was implementing dedicated turn lanes to separate turning vehicles from through traffic. While this approach appears to be optimal, it has some drawbacks. The geometry of many intersections may not support the addition of dedicated turn lanes, requiring extensive and costly construction. Thus, it is crucial to consider alternative solutions that can be more feasible and cost effective.

Utilizing simulation modeling software to evaluate the impact of turning vehicles, and subsequently defining a tailored strategy, is another widespread method, adopted by 18 participants (50%). This technique allows for precise planning based on simulated scenarios before taking any actions in the field. Leveraging modern technologies, such as adaptive signal control, to respond to fluctuating traffic demands in real time was mentioned by 16 participants (44%). Deploying advanced detection systems to better detect and manage turning vehicles was a strategy checked by 12 participants (33%). Adjusting signal timings to prioritize turning movements during peak hours was a method chosen by 14 participants (39%). This approach gives turning vehicles more time during busy periods, helping to reduce delays and ease congestion.

Another challenging aspect to consider in signal retiming is accounting for fluctuations in pedestrian activity. Survey participants were asked about the treatments they used to manage these fluctuations in their signal retiming strategies. The responses are depicted in Figure 13.

The most common treatment, used by 47% of respondents, was adjusting pedestrian crossing times based on observed or historical demand patterns. This approach helps to ensure that pedestrian crossing times are aligned with pedestrian traffic. Integrating pedestrian detection systems to dynamically optimize signal timing was chosen by 33% of respondents. These systems allow real-time adjustments based on current pedestrian activity, enhancing responsiveness and efficiency.

Implementing special pedestrian treatments, such as exclusive pedestrian phases, to enhance pedestrian safety and accessibility, was utilized by 28% of respondents. This strategy reduces conflicts between pedestrians and vehicles. Implementing pedestrian priority phases during peak pedestrian hours was used by 25% of respondents. This method gives pedestrians more time to cross during busy periods.

Notably, 20% of respondents indicated that they did not consider fluctuations in pedestrian activity in their signal retiming strategies. This highlights a segment of the population that may benefit from exploring more pedestrian-responsive approaches.

Some other suggestions were derived from the survey, with participants noting additional methods they used to address fluctuations in pedestrian activity. These included implementing pedestrian recalls, leading pedestrian intervals (LPI), and designing pedestrian timings for 24 h accommodating pedestrian activity throughout the day. These approaches further demonstrate the comprehensive efforts undertaken by professionals to optimize pedestrian safety and accessibility within signal retiming strategies.

The optimization of signal timings to accommodate multi-modal transportation in urban areas presents a unique set of challenges. Survey participants were asked to identify specific challenges (between the provided options) they faced in this regard, and their responses are depicted in Figure 14.

The most common challenges, identified by 23 participants (64%), were balancing the conflicting needs and requests between different modes of transportation, such as pedestrians, cyclists, public transit, and vehicular traffic, and addressing potential conflicts between turning vehicles and vulnerable road users like pedestrians and cyclists.

Coordinating signal timings for special events or peak demand periods, such as concerts or festivals, represented an important challenge for 17 participants (47%). Such events can have a significant impact on traffic patterns and require adjustments to signal timings to mitigate congestion.

Adjusting signal timing parameters to accommodate the special needs of non-motorized vehicles and pedestrians was a challenge faced by 13 participants (36%). This includes factors such as pedestrian crossing times and cyclist signal phases, which must be optimized to enhance safety and accessibility. Moreover, incorporating data from public transit to adjust signal timing decisions was noted as a challenge by nine participants (25%). Integrating transit data into signal timing strategies can improve transit efficiency and reliability. Eight participants (22%) identified addressing the impact of signal retiming on adjacent neighborhoods and communities as a challenge.

Additionally, one participant highlighted the challenges of incorporating LPI, emphasizing the complexities involved in accommodating pedestrian movements.

Signal retiming projects in urban areas often require adaptation of standard procedures due to their complexities. The necessity for adapting standard procedures frequently arises in the context of signal retiming projects in urban areas to address the complexities inherent in multimodal transportation effectively. Survey participants were asked to identify areas where adaptation based on standards, such as the Signal Timing Manual (STM), was needed in the signal retiming procedure. The responses are depicted in Figure 15.

The most common areas requiring adaptation, identified by 21 participants (58%) each, were:

• Emergency vehicle preemption: Implementing measures to facilitate the passage of emergency vehicles, particularly near healthcare centers.
• Pedestrian/bicycle timing adjustments: This involves modifying signal timings to accommodate pedestrian and bicyclists’ needs.
• Closely following these, with 20 participants (56%), was the need for:
• Transit signal priority implementation: Integrating strategies to prioritize transit vehicle movements, such as exclusive bus lanes, helps enhance public transit efficiency and reliability.

Other areas requiring adaptation included:

• Pedestrian/bicycle phasing: Incorporating signal phases specific to pedestrian/bicycle traffic, particularly near bike tracks or exclusive bike lanes, was identified by 19 participants (53%).
• Coordinating signal timings with bike lanes or shared roadways: To reduce conflicts and provide smooth mobility, 10 participants (28%) highlighted the need for adaptation of signal timing procedure while coordinating signal timings with bike lanes or shared roadways.
• Special considerations for heavy vehicles: Adapting timings to accommodate the unique characteristics of heavy vehicles, especially near intermodal facilities, was noted by six participants (16%).
• Consideration of micro-mobility patterns: Adapting signal timings for emerging micro-mobility modes, such as scooters, was identified by three participants (8%).

These responses underscore the necessity for flexibility and customization in signal retiming procedures to effectively address the diverse requirements of multimodal transportation in urban environments.

3.5. Prioritizing Signal Retiming Objectives in a Multi-Modal Urban Network

The process of signal retiming in urban areas requires careful consideration of various objectives to accommodate the multi-modal nature of the transportation network. Survey participants were asked to rank the seven key objectives in order of priority, with Rank 1 being the most important and Rank 7 being the least important. The responses from 36 participants are presented in Figure 16.

The objective most frequently ranked as the highest priority (Rank 1) was “Prioritize vehicular traffic flow”, chosen by 42% of participants (highlighted in red in the figure). This indicates a strong emphasis on ensuring the smooth movement of vehicles. “Enhance pedestrian safety and convenience” followed closely, being ranked as the second highest priority by 33% of participants (highlighted in yellow). This objective also held the first place as Rank 2, with 40% of participants prioritizing pedestrian safety next after vehicular flow.

Regarding Rank 3, there was a tie between “Enhance pedestrian safety and convenience” and “Enhance emergency vehicle response time”, with each being selected by 19% of participants (shown in yellow and blue, respectively). This underscores the significance of both pedestrian safety and emergency vehicle efficiency in the context of urban signal retiming.

“Improve public transit efficiency” was predominantly ranked 4th, with 28% of participants (shown in orange) assigning this priority. Furthermore, Rank 5 was significantly associated with “Optimize cyclist mobility”, chosen by 33% of participants.

“Minimize environmental impacts” (highlighted in green) was ranked 6th and 7th by most participants, 31% and 40%, respectively. This indicates that while environmental concerns were considered, they often fell lower in the priority list compared to other objectives.

Additionally, the objective “Balance all modes equally” (shown in gray) appeared consistently across all the rankings, with around 10–20% of participants choosing it. It was most frequently ranked 7th, selected by 25% of participants, suggesting that while the equal balance of all modes was standard, it was not the top priority for most respondents or possibly not the most feasible one.

Following the ranking of signal retiming objectives, participants were asked how they determined which objectives to prioritize in multimodal urban networks. The results, depicted in Figure 17, indicate various approaches chosen by traffic signal professionals in this decision-making process.

The most common method, endorsed by 27 participants (75%), was conducting thorough field observations and data collection. This approach allows for a detailed understanding of the current traffic conditions and informs objective prioritization based on real-world data.

Engaging stakeholders, including transportation agencies and local communities, in the decision-making process was utilized by 21 participants (59%). This collaborative approach ensures that the perspectives and needs of various stakeholders are considered, leading to more concise and appropriate decisions. Utilizing advanced simulation and modeling techniques was a method adopted by 18 participants (50%). These techniques enable professionals to predict the outcomes of different retiming strategies and make data-driven decisions to optimize the considered objectives.

Incorporating feedback from previous signal retiming projects was cited by 13 participants (36%). Learning from past experiences helps to refine and improve current practices, ensuring that effective strategies are replicated, and drawbacks are avoided from the lessons learned. Conducting pilot studies to evaluate proposed solutions, including before-and-after studies, was employed by 11 participants (30%). This approach allows for the testing of new strategies on a smaller scale and feedback from communities before permanent implementation, helping to assess their effectiveness and make necessary adjustments.

Additionally, some participants mentioned using crash data to determine where to deploy lower progression speeds, LPIs, and other safety measures. Another participant highlighted the importance of active management and daily observation through traffic cameras to continuously assess and adjust signal timings.

These varied approaches underscore the importance of a comprehensive and adaptive methodology in determining signal retiming priorities. By combining field data, stakeholder input, advanced techniques, past feedback, and pilot studies, traffic signal professionals can make informed decisions that enhance the efficiency and safety of urban transportation networks and all road users.

3.6. Modifications to Standard Procedures

As part of the survey’s closing section, participants were asked to share the typical modifications (fine-tuning) they made based on field observations for bicycles, pedestrians, and transit after the implementation of their retiming plans. The responses indicate that professionals employed a range of adjustments to fine-tune and enhance traffic signal performance in multimodal environments.

A common modification involved increasing the minimum or maximum green times for bicycles and pedestrians, as well as implementing transit signal priority (TSP)-specific measures. Adjustments to pedestrian crossing times were frequently mentioned in the literature, with some respondents emphasizing recalls, rest-in-walk phases, LPIs, and enhanced crossing times to improve pedestrian safety and convenience. Long wait times for pedestrians and cyclists, crossing out of phase, high crash densities, and worsening headways were issues that prompted further adjustments, including extending LPIs, adding LPIs, and ensuring adequate clearance times.

Other strategies employed included adjustments to phase duration and the limitation of fixed cycle lengths, with the objective of reducing pedestrian delays when crossing main streets. Some respondents aimed to provide better progression for various modes of transportation by changing cycle lengths and offsets to improve bandwidth.

Several participants suggested specific approaches such as checking conflict points to optimize the system, ensuring proper detection systems, and reviewing vulnerable road user (VRU) usage and approaches to traversing intersections or corridors. Adjusting crosswalk locations, adding pedestrian detection systems, and modifying signal timing parameters were additional strategies highlighted by respondents.

One participant detailed a comprehensive approach that included adjusting green times for pedestrian crossings, providing dedicated signal phases for bicycles and transit vehicles, and implementing LPIs to enhance safety and efficiency for pedestrians. Another noted that in areas with consistently high pedestrian volumes, cycle lengths are limited to reduce delays, and pedestrian recalls with LPIs are implemented to give pedestrians a head start in crosswalks.

In terms of administrative procedures, some participants indicated that their local agencies submitted requests, which were then processed according to predefined models. Others indicated that contractors and agency field teams typically handled post-implementation adjustments based on field observations. It should be noted that 10 participants stated that they were not involved in post-implementation activities.

3.7. Recommendations for Improving Signal Retiming Processes

As the final question, participants were asked to share their recommendations for improving current signal retiming processes. Their responses highlight several key areas for enhancement, emphasizing the importance of data, technology, stakeholder engagement, and practical considerations.

3.7.1. Data Collection and Analysis

A recurring theme among the recommendations was the need for improved data collection and analysis. Respondents emphasized the importance of collecting accurate and up-to-date data on traffic volume, speed, and traffic patterns. This data-driven approach can significantly enhance signal retiming processes. Field visits and data collection were considered crucial, with suggestions to review queue lengths and travel time runs in before-and-after settings. Utilizing advanced technologies for data collection, such as adaptive traffic signal performance measures (ATSPM) that include multimodal considerations, was also highlighted.

3.7.2. Technology and Software Improvements

Several participants recommended the utilization of novel technologies and the enhancement of existing software. For instance, enhancing Synchro software and incorporating adaptive signal control systems were suggested.

It is recommended that software optimization be undertaken to accommodate multiple transportation modes and objectives. This should include the development of more usable pedestrian level of service (LOS) metrics in Synchro or Vistro.

3.7.3. Stakeholder Engagement

Engaging stakeholders, including residents, businesses, transportation agencies, and local community groups, was pointed out as an effective step in signal retiming. It is recommended that stakeholder priorities be balanced, and that corridor consistency be ensured to meet user expectations. The participants also emphasized the importance of a practice guide that differentiates strategies based on urban vs. suburban contexts and priorities for different modes such as pedestrians, bicycles, and cars.

3.7.4. Practical Adjustments and Best Practices

Practical adjustments, such as improving signage and road markings, were suggested to enhance the effectiveness of signal retiming. The importance of having a standard priority list and considering cost-effective approaches in implementing changes was noted as well.

There were some suggestions for developing best practice guides that break down different retiming strategies, including recommendations for weighting systems to balance user needs. Participants highlighted the need for a multimodal mindset among transportation engineers, considering pedestrian safety and the unique characteristics of various vehicle classes and modes. Additionally, there was a call for developing a new performance measure similar to the Highway Capacity Manual (HCM) multimodal LOS framework. Despite the HCM framework’s limited popularity and primary use for planning purposes, it provides a foundation upon which a similar measure could be developed specifically for retiming methods, incorporating the multimodality aspect of these projects.

3.7.5. Emerging Trends

Considering emerging trends, one participant mentioned the increasing number of scooter riders and the need for their consideration in signal retiming processes.

Overall, improving signal retiming processes requires a combination of advanced data collection and analysis techniques, stakeholder engagement, and the use of innovative technology. Balancing the needs of various transportation modes and maintaining a cost-effective approach are essential for efficient signal retiming in urban areas.

4. Conclusions

To gather comprehensive insights from traffic signal professionals on multimodal signal retiming practices, a detailed survey was developed and distributed. The questionnaire comprised 20 questions, covering various aspects such as the characteristics of respondents, current practices, common challenges, and recommendations for improving signal retiming processes. The survey was distributed through multiple channels, including email, social media, and professional newsletters, targeting professionals from transportation agencies, consulting firms, academic institutions, and technology vendors. The survey remained open for 40 days during April and May 2024, resulting in 36 responses from participants across North America.

The survey results provide a comprehensive overview of the practices and challenges faced by traffic signal professionals in multimodal signal retiming projects. The findings underscore the necessity for continuous improvement and adaptation of standard procedures to meet the diverse needs of urban transportation networks. Although there was a moderate level of satisfaction with the existing guidelines, the use of a variety of supplementary data and optimization methods highlights the complexity of these projects.

Participants identified significant challenges such as balancing the conflicting needs of different transportation modes and addressing conflicts between turning vehicles and vulnerable road users. Adaptations to standard procedures, like modifying signal timings for pedestrians and bicycles, and implementing emergency vehicle preemption, reflect the necessity for flexibility.

To enhance the effectiveness of signal retiming, traffic signal professionals frequently make field modifications post-implementation, with a particular focus on vehicular traffic flow, pedestrian safety, and public transit mobility. The recommendations for improvement focused on the collection of better data, the engagement of stakeholders, and the use of advanced technologies.

A notable area for future development is the potential creation of a measure of effectiveness that incorporates multimodal features of the projects. This measure would enable practitioners to better evaluate the effectiveness of their signal retiming efforts in accommodating the needs of various transportation modes, ensuring a more balanced and comprehensive approach to urban traffic management.

Overall, this survey has shed light on the complexities and diverse strategies involved in multimodal signal retiming projects. The findings underscore the importance of a data-driven, flexible approach that can adapt to the unique challenges of urban transportation networks. Future research could focus on integrating advanced technologies, developing novel methodologies for signal optimization, incorporating stakeholder feedback, and conducting continuous field observations. These approaches can help traffic signal professionals better manage the complexities of multimodal signal retiming, ultimately improving the efficiency and safety of urban traffic systems.