Pedestrian Delay Research Articles

Investigation of Analyzable Solutions for Left-Turn-Centered Congestion Problems in Urban Grid Networks

Traffic congestion caused by left-turning vehicles in a coordinated corridor is a multifaceted problem requiring tailored solutions. This study explores the impact of shared left-turn lanes within one-way couplets, particularly during peak hours, where high left-turn volumes, limited side street storage, and the overlapped green time between pedestrians and left-turners contribute to queue spillbacks, coordination interruption, and network congestion. The focus of this paper is on the solutions that can be easily analyzed by practitioners, here called “analyzable solutions”. This approach stands in contrast to solutions derived from “non-transparent” optimization tools, which do not allow for a clear assessment of the solution’s adequacy or the ability to predict its impact in real-world applications. This paper investigates the effects of employing two analyzable signal timing strategies: Lagging Pedestrian (LagPed) phasing and Left-Turn Progression (LTP) offsets. Using high-fidelity microsimulation, the authors evaluated different scenarios, assessing pedestrian delays, queue lengths, travel time index, area average travel time index, and environmental impacts such as Fuel Consumption (FC) and CO2 emissions. The effectiveness of the proposed strategies was comprehensively evaluated against the base case scenario, demonstrating considerable improvements in various performance measures, including approximately a 5% reduction in FC and CO2 emissions. Implementation of the LTP strategy alone yields substantial reductions in delays, the number of stops, the queue length for left-turning vehicles, travel times for all road users, and ultimately FC and CO2 emissions. This study offers innovative approach to addressing the complex and multifaceted problem of left-turn-centered congestion in urban grid networks using efficient and down-to-earth analyzable solutions.

Multi-objective Optimization Framework for Trade-Off Among Pedestrian Delays and Vehicular Emissions at Signal-Controlled Intersections

Traffic congestion has several adverse effects on urban traffic networks. Increased travel times of vehicles, with the addition of excessive greenhouse emissions, can be listed as harmful effects. To address these issues, transportation engineers aim to reduce private car usage, reduce travel times through different control strategies, and mitigate harmful effects on urban networks. In this study, we introduce an innovative approach to optimizing traffic signal control settings. This methodology takes into account both pedestrian delays and vehicular emissions. Non-dominated sorting genetic algorithm-II and Multi-objective Artificial Bee Colony algorithms are adopted to solve the multi-objective optimization problem. The vehicular emissions are modeled through the MOVES3 emission model and integrated into the utilized microsimulation environment. Initially, the proposed framework is tested on a hypothetical test network, followed by a real-world case study. Results indicate a significant improvement in pedestrian delays and lower emissions.

A Bi-Objective Traffic Signal Optimization Model for Mixed Traffic Concerning Pedestrian Delays

Urban traffic networks suffer in numerous ways from traffic congestion. Some of these adverse effects are increased travel times of cars, buses, bicycle users, pedestrians etc., with the addition of excessive greenhouse gas emissions. Transportation engineers and policy makers try to improve the quality of urban transportation systems by developing projects to enhance the pedestrian experience, reduce private car usage, reduce total time spent in the network through different control strategies, and diminish the detrimental effects. In this context, this study takes Connected and Automated Vehicles (CAVs) and pedestrians into account at signal-controlled intersections. A novel intersection signal control optimization methodology that incorporates pedestrian delays and vehicular emissions from CAVs is presented. Non-dominated sorting genetic algorithm-II is utilized to solve the multiobjective optimization problem. For the emission calculations, the MOVES3 emission model is utilized. The proposed framework is tested on real-world case study. Simulation experiments showed major improvements in pedestrian delays and lower emissions.

A Coordinated Allocation Method for Right-Turn Strategy at Signalized Intersections with Optimal Pedestrian and Vehicle Delays

With strict enforcement of pedestrian right of way at all intersections, the inappropriate right-turn resource allocation from a spatial and temporal perspective will lead to a reduction in the operational efficiency of the intersection. In this paper, three spatiotemporal resource allocation schemes for right-turning vehicles are proposed, considering the vehicle and pedestrian traffic efficiency in all directions of the intersection. To minimize vehicle and pedestrian delay at the intersection individually, an optimization model is established with the effective green time of each phase and three schemes as decision variables. A right-turn vehicle and pedestrian conflict delay model is developed based on the pedestrian-vehicle interaction behavior as the constraints of the optimization model. The NSGA-II algorithm is used to solve the model, and the quantitative criteria for the exclusive right-turn lane and phase are obtained by sensitivity analysis. The results of this paper can be used as a guide for traffic design and for planning and controlling the operation of right-turning vehicles at intersections.

USER PERCEPTIONS BASED LEVEL OF SERVICE FOR UNCONTROLLED MID-BLOCK CROSSINGS USING TRAFFIC SURVEYS AND ITS REGRESSION ANALYSIS

The exponential growth of urban populations has led to a substantial increase in traffic on urban roads, prompting extensive research into optimizing road networks for vehicular traffic. However, there has been a noticeable lack of attention given to the safety and well-being of pedestrians. One particularly perilous scenario for pedestrians occurs at mid-block crossing locations where well-designed crosswalks are absent. In such areas, pedestrians are forced to identify safe crossing points, often with limited safety measures in place. Ensuring the safety, convenience, comfort, and minimal delay for pedestrians in these situations is imperative. To address this gap, a comprehensive evaluation of the quality of service at mid-block crosswalks is necessary. This research study focused on assessing the quality of service at non-signalized mid-block pedestrian crossings from the perspective of consumers. The analysis employed regression techniques and gathered data from four distinct mid-block crossing locations in different areas of Visakhapatnam. Data collection involved video image surveillance to obtain data on pedestrian quantities, volume-based characteristics, walking speeds, capacity, and gap sizes, complemented by questionnaires to capture real-time experiences and opinions of pedestrians. The questionnaire encompassed various variables affecting crossing quality, including demographic information and pedestrian perceptions of safety and comfort. Pedestrians rated these attributes on a scale of one to six, with their scores serving as variables for subsequent analysis. This approach seeks to ensure that pedestrians have the safest, most comfortable, and efficient means to cross the street while minimizing potential delays. Keywords:Pedestrian safety,Mid-block crossing,Quality of service,Urban road traffic,Crosswalk design, Consumer perspective,Data collection, ,Questionnaires,Perception,Safety measures,Comfort, Demographic information,,Efficiency,Delay mitigation,Regression analysis,Vehicular traffic optimization,Urbanization impact.

Improving Pedestrian Progression at Multistage Crossings Using Pedestrian–Left Turn Overlaps

At signalized intersections where pedestrian crossings are divided into two stages by using a median island, pedestrian delay can be very long if the partial-crossing phases have poor progression. One technique for reducing pedestrian delay is pedestrian–left turn overlaps, in which half-crossings that are not in conflict with a left turn are allowed to run during the left turn phase as well as during the parallel vehicle through phase. Such an overlap can enable some pedestrians to cross in a single pass, or to have a far shorter wait at the median. Because this technique requires surrendering some of the flexibility with which left turn phases normally operate—in phases with a pedestrian call, the left turn phase cannot be skipped and may require a longer minimum green—there can also be an impact on vehicle delay. A case study of two intersections in Brookline, MA found that, compared with the current timing plan, using pedestrian–left turn overlaps could reduce pedestrian delay from about 100 to 35 s, with a negligible impact on vehicle delay. A methodological innovation introduced in this study was that average pedestrian delay was calculated for three pedestrian speeds and averaged together, thus accounting for how pedestrian delay at multistage crossings can be far lower for faster pedestrians who may be able to cross in a single pass than for slower pedestrians who have to wait at the crossing island.

Evaluation of a pedestrian call extension and cancelation system at a signalized midblock crossing

ABSTRACT Unnecessary vehicular delay occurs at actuated signalized intersections during ‘ghost’ pedestrian intervals when a pedestrian activates the pushbutton then jaywalks. Safety issues arise when pedestrians remain in the crosswalk at the end of the Flashing Don’t Walk phase, and vehicles receive a circular green. A Pedestrian Call Extension and Cancelation System was evaluated at a signalized midblock crossing in Hillsboro, OR. Thermal sensors and controller logic were implemented to detect pedestrians and passively cancel or extend calls. A Case 1-after study was conducted to evaluate how vehicular delay and pedestrian behavior was impacted by the system. 1,649 observations Case 1 and 3,002 observations after system installation were recorded. Pedestrian delay did not change, but average vehicular stop time delay significantly decreased by 12 sec. 76 extensions occurred with 99.2% accuracy. Findings suggest that transportation agencies could improve driver waiting time and pedestrian safety by using dynamic passive pedestrian detection.

Pedestrian delay models for compliant & non-compliant behaviour at signalized midblock crosswalks under mixed traffic conditions

The present study aimed to propose new pedestrian delay models for Signalized Midblock Crosswalks (SMC) for mixed traffic conditions. A detailed study of the literature revealed that most of the existing pedestrian delay models were developed for signalized intersections. Thus, the need for the study was established and data were collected at eight SMC in Hyderabad, one of the most densely populated metropolitan cities in India, using video-graphic technique. Two delay models were developed based on the compliance behaviour and non-compliance behaviour of pedestrians. Both models have two components i.e., waiting delay and crossing delay where the latter has two subset components i.e., frictional delay and pedestrian-vehicle interaction delay. The bidirectional effect (pedestrian-pedestrian interaction while crossing the road) of pedestrians was addressed as frictional delay while the non-compliance behaviour by pedestrians and vehicles was addressed as pedestrian-vehicle interaction delay in the present models. The waiting delay component was defined by modifying the Webster delay model for non-uniform pedestrian arrivals. The proposed delay models yielded an error of 5% and 7% for compliance behaviour model and non-compliance behaviour model respectively. The proposed models can be used for optimizing the signal timings and defining Level of Service (LOS) of facilities.

Optimization-Based Intersection Control for Connected Automated Vehicles and Pedestrians

Traffic at larger or busier urban intersections is currently coordinated using traffic signals to prevent dangerous traffic situations and to regulate the flow of traffic. In future scenarios with 100% connected automated vehicles, conventional traffic signals could be replaced, and vehicles at intersections could be seamlessly coordinated via vehicle-to-vehicle and vehicle-to-infrastructure communication. In the past two decades, many such control strategies have been presented, commonly referred to as autonomous intersection management (AIM). In recent years, an evolution from simpler first come, first served to more sophisticated optimization-based AIM strategies can be observed. Optimization-based AIM can significantly improve capacity and reduce delays as compared to slot-based strategies and conventional traffic signal control (TSC). In addition, it allows for prioritizing road users. This paper is among the first to consider pedestrians in optimization-based AIM. The proposed approach consists of a signal-free vehicle control in combination with pedestrian signal phases that are fully integrated into the optimization problem. Since the communication range of the controller is limited in real-world applications, a rolling horizon scheme is presented and explained in detail. The presented strategy is implemented and evaluated using a microscopic traffic simulation framework. Results show that vehicle delays can be significantly reduced and vehicle capacity can be increased compared to fully actuated TSC, while pedestrian waiting times are comparable. In addition, focus is put on how vehicle and pedestrian delays can be balanced in the presented setup. Three different control parameters can be adjusted, which need to be tuned based on the considered demand scenario.

Cyber-Physical System for Smart Traffic Light Control.

In recent years, researchers have proposed smart traffic light control systems to improve traffic flow at intersections, but there is less focus on reducing vehicle and pedestrian delays simultaneously. This research proposes a cyber-physical system for smart traffic light control utilizing traffic detection cameras, machine learning algorithms, and a ladder logic program. The proposed method employs a dynamic traffic interval technique that categorizes traffic into low, medium, high, and very high volumes. It adjusts traffic light intervals based on real-time traffic data, including pedestrian and vehicle information. Machine learning algorithms, including convolutional neural network (CNN), artificial neural network (ANN), and support vector machine (SVM), are demonstrated to predict traffic conditions and traffic light timings. To validate the proposed method, the Simulation of Urban Mobility (SUMO) platform was used to simulate the real-world intersection working. The simulation result indicates the dynamic traffic interval technique is more efficient and showcases a 12% to 27% reduction in the waiting time of vehicles and a 9% to 23% reduction in the waiting time of pedestrians at an intersection when compared to the fixed time and semi-dynamic traffic light control methods.

A Signal Optimization Model of Adjacent Closely Spaced Intersections Which Optimizes Pedestrian Crossing

Adjacent closely spaced intersections with characteristics of short link distance and high pedestrian flow are primarily located in high-density urban areas. To address the problems of queue overflow, poor traffic operation, and high pedestrian travel delays, a pedestrian-motor vehicle signal optimization method for adjacent closely spaced intersections was proposed in this paper. First, the traffic flow entering the closely spaced intersections is divided into nonarterial and arterial flow categories to establish a delay model of pedestrian crossing. Then, a pedestrian crossing delay model based on pedestrian demand is constructed according to pedestrian crossing time and a space diagram. An optimization model for pedestrians and vehicles at adjacent closely spaced intersections is established, and an artificial intelligence algorithm is used to optimize this model. Finally, a selected case intersection is optimized. The results show that compared with a traditional single optimization method, vehicle delay decreased about 4%, 13.8%, 17.1%, and 25.9% and total pedestrian delay decreased by 3%, 15%, 25%, and 31%, respectively, for the four proposed scenarios.

Do existing split failure metrics accurately reflect pedestrian operation at signalized intersections?

Automated Traffic Signal Performance Measures (ATSPMs) uses high-resolution data to develop operational performance measures for signalized intersections. Split Failure (SFs) is one of the primary metrics to identify intersections with operational issues. These SFs are determined by measuring vehicle occupancy for a given movement during its green time (i.e., Green Occupancy Ratio or GOR) and immediately after the signal turns red (i.e., Red Occupancy Ratio or ROR5). While the SF metric is a great tool for signal operations and rebalancing green times, it focuses entirely on vehicular measures and ignores the treatment of pedestrians at the intersection. Prioritizing vehicular movements may lead to excess pedestrian delay, which may cause pedestrians to violate traffic signals.To address this issue, this paper examines the relationship between pedestrian delay and GOR or ROR5. The main objective was to identify whether the GOR and ROR5 could be adequately used as a proxy for pedestrian delays. To achieve this goal, high-resolution data was collected from the ATSPMs database at a signalized intersection in Salt Lake City, Utah. To predict GOR or ROR5 as a function of pedestrian delay, a linear regression model was developed. The results reveal that there is very weak to no relationship between these metrics. This implies that using only GOR or ROR5 in quantifying signal performance does not meaningfully capture pedestrian delay and thus might overemphasize vehicle movements. Specific pedestrian delay metrics should be included in a signal operation analysis to identify operational issues.

Comparison of Pedestrian Delay Models at Signalized Midblock Crossings Under Mixed Traffic Conditions

In the field of transportation engineering, one of the most important factors for the traffic engineers and road users (pedestrian and vehicle) is the delay which governs the LOS of a facility. Past studies shows that various delay models like HCM, Webster, and Austroads work well for the homogeneous traffic conditions. However, Limited studies were done on mixed traffic conditions like in India and in other developing countries. Apart from that, all the models were developed based on the conditions of signalized intersection whereas signalized midblock crosswalks were completely overlooked by the researchers. The present study aims to compare pedestrian field delay at signalized midblock sections with the existing models. Six mid-block crossings have been selected from Hyderabad, India and data was collected using video-graphic technique. Field Pedestrian waiting delays were measured by plotting queue length against cycle time and area under the curve was calculated using Simpson's 1/3rd rule. Field crossing delay was calculated as the difference between actual crossing time and ideal crossing time. The performance of all the models were evaluated using t-test and other performance indices like MAPE, RMSE and R2. It was observed from the statistical tests that there is a significant difference between the means of field delay and delay by existing models. Also all the existing models yielded an error of more than 20% with an R2 value of less than 0.3. Calibrated results can be used in the modelling of new pedestrian delay for signalized midblock crosswalks.

Discussions on pedestrian delay models and applications at signalized crosswalks

Discussions on pedestrian delay models and applications at signalized crosswalks

Modeling the Pedestrian Delay at Signalized Intersections with Two-Stage Crossing: Considering Physical Queuing Length

Modeling the Pedestrian Delay at Signalized Intersections with Two-Stage Crossing: Considering Physical Queuing Length

Regional Coordinated Bus Priority Signal Control Considering Pedestrian and Vehicle Delays at Urban Intersections

Bus priority signal control can reduce bus delay at intersections and improve bus operation efficiency. The existing research focus mainly on bus priority control methods at isolated intersections, as well as urban arterial corridors. Rarely existing works consider a network-level bus priority control. Treating regional-wide intersections can be challenging, given that more traffic directions and large multi-modal traffic volume should be considered. The conventional transit signal priority (TSP) research focus on the delay of buses and social vehicles and neglect the delay of pedestrians. To fill these gaps, this paper proposes a regional coordinated bus priority signal control (RCBPSC) method, which is a network-level bus priority control method considering pedestrian and passenger delays. This method is divided into two stages. The first stage is the regional coordinated signal control to obtain the basic signal timing schemes. The second stage is the bus priority signal control. At this stage, the timing schemes at each intersection will be adjusted according to the bus arrival time and the delays. In order to verify the effectiveness of this method, we choose four intersections in Chengdu to study. The results show that the total delay of the proposed method at the first stage (control case 1) can be reduced by 602s (2.3%) and 606s (3.7%) comparing with the conventional timing method in the peak and non-peak period. At the second stage, the proposed method can reduce more pedestrian delay than the conventional TSP method in both <xref ref-type="other" rid="other1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">scenario 1</xref> and <xref ref-type="other" rid="other2" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">scenario 2</xref> .

Investigating the characteristic delay time in the leader-follower behavior in children single-file movement

The single-file movement experiment offered a convenient way to investigate the one-dimensional leader–follower behavior of pedestrians. This study investigated the time delays of children pedestrians in the leader–follower behavior by introducing a time-dependent delayed speed correlation. A total of 118 German students from the fifth grade (aged 11–12 years old) and the 11th grade (aged 17–18 years old) participated the single-file experiment. The characteristic delay time for each pedestrian was identified by optimising the time-dependent delayed speed correlation. The influences of the curvature of the experimental scenario, density, age, and gender on the delay time were statistically examined. The results suggested that to a large extent, the revealed characteristic delay time was a density-dependent variable, and none of the curvatures, the age and gender of the individual, and the age and gender of the leader had a significant influence on it. The findings from this study are variable resources to understand the leader–follower behavior among children pedestrians and to build related simulation models.

Application of Pedestrian Upstream Detection Strategy in a Mixed Flow Traffic Circumstance

Walking is an environment-friendly trip mode and can help ease the congestion caused by automobiles. Proper design of pedestrian facilities that promotes effi-ciency and safety can encourage more people to choose walking. Upstream detection (UD) strategy is proposed by previous studies to reduce pedestrian waiting time at mid-block crosswalk (MBC). This paper applied UD strategy to MBC under mixed traffic circumstance where the crosswalk serves both pedestrians and non-motor us-ers. Traffic data was collected from an MBC in the city of Nanjing, China. Simulation models were developed by using the VISSIM software and its add-on module Vehicle Actuated Programming (VAP). The models were catego-rised by the volume and composition of pedestrians and non-motor users. Models were simulated according to different experimental schemes to explore the effective-ness of the UD strategy under mixed traffic circumstance. T-test and analysis of variance (ANOVA) were used to interpret the simulation results. The main conclusions of this paper are that the UD strategy is still effective at the MBC with a mixed traffic circumstance despite the pro-portion of non-motor users. However, as the proportion of non-motor users becomes higher, the average delay of pedestrians and non-motor users will increase compared to pure pedestrian flow.

A Study on the Conversion Method Based on Standard Pedestrian Equivalent Factors at Signalized Crosswalks in China

In order to more accurately assess the pedestrian level of service (PLOS) of crosswalks and to more rationally design the pedestrian signal timing, a method of calculating the standard pedestrian equivalent (SPE) factors at the signalized crosswalk in China was proposed in this study by considering the differences in static and dynamic characteristics amongst pedestrians. Firstly, the pedestrians were classified into five types using the pedestrian field data collected at the 3 signalized crosswalks in Chongqing, China. Then, by considering the parameters selection of the pedestrian LOS at signalized crosswalks, the SPE method based on pedestrian delays was derived, and the calculation models of pedestrian delays were presented for different pedestrian arrival patterns. A case analysis was conducted using the methods proposed in this paper, and the results show that the SPE values for minors, young and middle-aged females, elderly males and elderly females were 1.213, 1.067, 1.229 and 1.348, respectively. In addition, the results of the in-situ application to the pedestrian signal timing at the signalized crosswalk were achieved. This research can provide reference for practice related to transportation fields such as pedestrian capacity analysis and pedestrian signal timing design.

Modeling vehicular and pedestrian delays at signalized midblock crosswalk under mixed traffic conditions

ABSTRACT The present study aims to develop vehicular and pedestrians delay models for signalized midblock crosswalks under mixed traffic conditions. In this study, the primary data on pedestrian and vehicle flow characteristics were recorded using video-graphic technique. The mixed traffic characteristics and other field conditions were simulated in the Vissim micro-simulation tool. The traffic flow characteristics were calibrated and validated using GEH statistics, which came out to be 2.5. For modeling the pedestrian and vehicle delays, several scenarios were simulated by varying the traffic flow and traffic signal characteristics. For each scenario, the simulated delay values were recorded. Considering the data set simulated, the delay models were developed using multiple linear regression technique with 10-fold cross validation. These models were then validated which yielded an error (MAPE) of 17% and 13% in estimating pedestrian and vehicle delays respectively. These models can be used as a tool designing better pedestrian facilities at signalized midblock crosswalks.