<?xml version="1.0" encoding="utf-8"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>TRB Publications Index</title><link>http://pubsindex.trb.org/</link><atom:link href="http://pubsindex.trb.org/common/TRIS Suite/feeds/rss.aspx?tc=NN%3ADcmthcskjy" rel="self" type="application/rss+xml" /><description></description><language>en-us</language><copyright>Copyright © 2015. National Academy of Sciences. All rights reserved.</copyright><docs>http://blogs.law.harvard.edu/tech/rss</docs><managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor><webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster><image><title>TRB Publications Index</title><url>http://pubsindex.trb.org/Images/PageHeader-wTitle.png</url><link>http://pubsindex.trb.org/</link></image><item><title>Understanding Drivers' Compliance Behavior: Data-Driven Assessment of Longer Yellow Intervals</title><link>http://pubsindex.trb.org/view/2414239</link><description><![CDATA[Red-light running (RLR) behavior poses significant risks at signalized intersections and has emerged as a leading cause of intersection-related crashes. The Phoenix metropolitan area had 113 RLR-related fatalities and 9,320 injuries from 2014 to 2020. To effectively mitigate RLR violations and uphold the safety of all road users, it is crucial to investigate RLR behavior at local intersections, evaluate the impact of different signal timing parameters—such as the yellow interval—on the frequency of RLR violations, and, finally, identify effective countermeasures. This study investigated the effect of updating the yellow interval on the frequency of red-light violations. Twelve intersections within the City of Phoenix were carefully selected as study sites. Then, smart sensors were installed to collect various data types, such as signal timing parameters, the vehicle count, and RLR violation data. Based on the ITE 2020 guidelines, yellow intervals were adjusted at each intersection. The effects of increased yellow intervals on RLR violations were examined by utilizing a comprehensive experimental before-and-after design. The before-and-after study results indicated that increasing the yellow intervals significantly reduced the average frequency of RLR violations for both through and left-turn movements by 83% and 72%, respectively. The results of this research are instrumental in informing transportation agencies, enabling them to adopt evidence-based approaches to signal timing strategies that enhance intersection safety and effectively reduce RLR violations.]]></description><pubDate>Mon, 12 Aug 2024 08:51:40 GMT</pubDate><guid>http://pubsindex.trb.org/view/2414239</guid></item><item><title>Evaluation of Dynamic Flashing Yellow Arrow Decision Support System in the Field Using Before and After Real-Time Data</title><link>http://pubsindex.trb.org/view/2144056</link><description><![CDATA[A permissive left turn is one of the most dangerous movements a driver can make because the driver travels across opposing traffic lanes. In recent years, flashing yellow arrow (FYA) signals have been proven to help drivers make safer left turns. The four-section signal display with FYA permissive left-turn indication creates an opportunity to enhance the left-turn phase with a variable mode that can change on demand. A challenge to using this system is knowing the best times of day to apply the FYA indication. The authors developed an exclusive hardware platform: first, to provide a generic device compatible with the different controller types used by different jurisdictions and, second, to automate selection of the FYA left-turn modes based on available gaps in the opposing traffic at intersections acquired in real time from existing sensors in the field. Phase IV provided conclusive field testing and evaluation of the decision support system (DSS), by switching between red and FYA modes in a rational manner consistent with driver expectations and left-turning gap acceptance thresholds. It was also concluded that coordinated signals with long cycle lengths, 3?min and longer, help provide adequate gaps even in heavy traffic patterns since most of the vehicle arrivals are in platoons and at the beginning of the cycle. The analysis showed that the utilization factor for the DSS recommendations for all the intersections ranged between 65% and 75% during peak conditions on weekdays and between 90% and 95% during off-peak conditions and weekends. The total delay in the before study for all the intersections amounted to 737 vehicle-hours and in the after-study was 440 vehicle-hours of delay. An overall reduction of about 40% in delay which confirms the operational benefit of the dynamic FYA DSS. The developed platform is applicable at any four-section head configuration to maximize safety and efficiency of the intersections.]]></description><pubDate>Mon, 03 Apr 2023 09:00:17 GMT</pubDate><guid>http://pubsindex.trb.org/view/2144056</guid></item><item><title>Safety Evaluation for Conversion From Protected-Only Left-Turn Phasing to Time-of-Day Protected-Permissive Left-Turn Phasing Using Flashing Yellow Arrows</title><link>http://pubsindex.trb.org/view/2117675</link><description><![CDATA[This study investigated the safety effects of the conversion from a protected-only left turn to protected-permissive left turn with flashing yellow arrow (FYA-PPLT) with time-of-day operation. The observational before–after study with the comparison group method was used to develop crash modification factors (CMFs) for the total crashes and two types of target crashes that involve left-turning vehicles on treated approaches (left-turn-same roadway and rear-end crashes). For all potential crashes, crash reports, crash diagrams, and narratives were manually inspected to identify the actual target crashes. The CMFs were separately developed for a full 24-h day and specific time-of-day based on FYA-PPLT operation, and for two severity categories (all severities and fatal &amp; injury). The results showed that the total crashes for 24?h had a slight increase, whereas the target crashes had substantially larger changes (increase in left-turn-same roadway crashes and decrease in rear-end crashes). When looking at the specific time-of-day use of FYA-PPLT, the increase in left-turn-same roadway crashes was significantly higher than the full 24-h period. This implies that engineers could extend protected-only use more on the fringes of the peak periods to mitigate the increase in left-turn-related crashes. The analysis results also showed a trade-off between left-turn–same roadway and rear-end crashes after the signal conversion. The findings reveal how important it is for engineers to properly understand the safety effects on the different categories of target crashes and time periods when considering the signal conversion from a protected-only left turn to FYA-PPLT.]]></description><pubDate>Tue, 14 Feb 2023 12:00:49 GMT</pubDate><guid>http://pubsindex.trb.org/view/2117675</guid></item><item><title>Determining Yellow Change and Clearance Intervals for Left-Turning Phases: Evaluation of the Current Guidelines with Connected Vehicle Data</title><link>http://pubsindex.trb.org/view/1956342</link><description><![CDATA[In March 2020, the Institute of Transportation Engineers (ITE) published new guidelines for determining traffic signal change and clearance intervals that included using an extended kinematic equation for left turns. Whereas previous guidelines assumed constant speed for all vehicles approaching an intersection, this new equation accounted for left-turning vehicles needing more yellow time because they decelerate (assuming a maximum safe and comfortable rate) before making turning maneuvers. This paper evaluates these guidelines using real-world vehicle trajectories from the Ann Arbor Connected Vehicle Test Environment (AACVTE). These trajectories confirm that free-flowing left-turning vehicles decelerate, but deceleration usually starts at a moderate rate before reaching the critical distance and continues to the middle of the intersection. Vehicles then accelerate to a departure speed at the clearance point. Since the goal of the yellow change interval is to eliminate the dilemma zone such that a free-flowing vehicle can safely traverse the critical distance, these observations imply that the extended kinematic equation will overestimate the required duration for the following two reasons: (1) the critical distance is shortened by the speed reduction before the braking point; (2) the average traversing speed is higher as vehicles usually decelerate at a moderate rate instead of the maximum rate. The equation will underestimate the clearance interval as the average traversing speed through the intersection is slower than the intersection entry speed. We propose a new left-turn kinematic equation for determining yellow change and clearance intervals, and the results are validated from the observed vehicle trajectories.]]></description><pubDate>Tue, 24 May 2022 15:47:17 GMT</pubDate><guid>http://pubsindex.trb.org/view/1956342</guid></item><item><title>Speeds of Right-Turning Vehicles at Signalized Intersections during Green or Yellow Phase</title><link>http://pubsindex.trb.org/view/1851798</link><description><![CDATA[The operation and design of signalized intersections involves tradeoffs between operational efficiency and safety for a variety of users, including motorists, pedestrians, and bicyclists. Additionally, the mix of vehicle types in the fleet sometimes requires special considerations. These concerns especially apply to the selection of curb radius at the corners, where right-turning vehicles operate close to pedestrians. Larger curb radii accommodate the swept paths of trucks and allow right turns to occur at higher speeds but may compromise safety and security for pedestrians by increasing the crossing distance and increasing the frequency of higher-speed turns. The authors collected right-turn vehicle speeds at 31 urban signalized intersection approaches in Texas with radii ranging from 15 to 70?ft. The authors calibrated a model to predict right-turn speeds as a function of site characteristics including curb radius, leading headway, vehicle type (car versus truck), maneuver of the preceding vehicle (through versus right turn), and signal indication (yellow or green). The analysis results indicate that right-turn speeds increase slightly with increasing radius, if the preceding vehicle proceeds through (rather than turning right) at the intersection, or if the signal indication is yellow rather than green. The calculated 85th percentile turning speed is generally higher than the assumed speed calculated using the radius of curvature equation. These trends should be considered if the intersection is expected to have notable volumes of pedestrians or trucks, as lower speeds are desirable for pedestrian safety, but larger radii may be necessary to accommodate turning trucks.]]></description><pubDate>Fri, 14 May 2021 10:45:17 GMT</pubDate><guid>http://pubsindex.trb.org/view/1851798</guid></item><item><title>Assessing Drivers’ Compliance with Restrictive Yellow Traffic Lights in a Developing Country</title><link>http://pubsindex.trb.org/view/1758929</link><description><![CDATA[Driving rules adopt permissive or restrictive policies concerning yellow light running (YLR). In a restrictive policy, vehicles behind the stop line are not allowed to enter the intersection on yellow no matter how close they are to the stop line. YLR policy affects driving risks, safety, and operation. There is limited knowledge about the restrictive policy and drivers’ compliance with this rule. Previous studies on YLR are limited in scope since they tended to use binary stop/go decision models without considering red light running decisions. This potentially results in the loss of information about drivers’ conformity to red signals. This paper examines whether drivers are only non-compliant with yellow lights or whether non-conformity to any prohibitive yellow/red signal emerges as a wider behavioral issue. This study develops regression choice models to predict drivers’ illegal yellow-light passing decisions in a developing country with a poor safety record and explores reasons for drivers’ non-compliance. The results obtained show that the restrictive policy is ineffective in relation to driver compliance, especially in cases where drivers’ non-conformity to any restrictive rule emerges as a behavioral issue of concern. Drivers make their stop/go decisions according to the time needed to cross the intersection, and they consider the yellow light as an opportunity for crossing. Yellow (red) light running rates were 101 (31) per 1,000 vehicles per hour (vph) for the restrictive policy, whereas these rates for the U.S.A., with a permissive policy, were at most 29 (6) per 1,000 vph.]]></description><pubDate>Mon, 28 Dec 2020 16:49:49 GMT</pubDate><guid>http://pubsindex.trb.org/view/1758929</guid></item><item><title>Modifying Highway Capacity Manual Methodology for Inclusion of Flashing-Yellow-Arrow Delay and Suppression</title><link>http://pubsindex.trb.org/view/1742826</link><description><![CDATA[Dallas phasing is an effective strategy for increasing the efficiency of protected-permissive left turns (PPLTs) at signalized intersections, without creating left-turn traps. The flashing yellow arrow (FYA) is the most widely used PPLT signal indication when Dallas phasing is utilized. The Highway Capacity Manual (HCM) signalized intersection methodology currently contains guidance on how to handle PPLTs with Dallas phasing. At intersections with the FYA indication, some agencies have been using a feature known as FYA delay, which delays the FYA indication, usually by 1 to 4 s. More recently, some agencies have also began using another feature, which suppresses the FYA when a conflicting pedestrian phase is active. The HCM does not contain guidance on how to handle FYA delay or suppression. This research proposed modifications to the HCM signalized intersection methodology to address these two FYA strategies. A sensitivity analysis was conducted to check the reasonableness of the proposed modifications. The sensitivity analysis showed that the proposed modifications are reasonable and produced the expected results.]]></description><pubDate>Tue, 13 Oct 2020 22:21:10 GMT</pubDate><guid>http://pubsindex.trb.org/view/1742826</guid></item><item><title>Monte Carlo Simulation Approach to the Duration of Yellow Lights at Signalized Intersections Considering the Stochastic Characteristics of Drivers</title><link>http://pubsindex.trb.org/view/1689767</link><description><![CDATA[In China, around 90% of traffic crashes at signalized intersections take place within the signal change intervals, especially during signal change from green to red. Hence, yellow time, which is a part of inter-green time, is of great significance to the safety of signalized intersections. The conventional calculation method for duration of yellow light (DYL) ignores the stochastic characteristics of drivers, which the authors believe is an important factor in this calculation. Therefore, the purpose of this research is to investigate a new approach to calculate DYL based on safety reliability theory in which the randomness of human factors is taken into consideration. Firstly, a comprehensive literature review concerning the conventional calculation methods of DYL is conducted. Secondly, a theoretical calculation method of DYL based on safety reliability theory is put forward which, different from the conventional methods, accounts for the stochastic characteristics of drivers. Additionally, a driving simulation experiment is designed to obtain two driving behavior parameters of Chinese drivers: perception–reaction time (PRT) and safe acceptable acceleration (SAA). Thirdly, a Monte Carlo simulation is employed to simulate the interactive process of PRT and SAA, and solve the proposed model. Finally, according to the Monte Carlo simulation results, a look-up table describing the relationship between DYL, safety reliability (50–90%) and approaching speed (15–40 km/h) is made. Results show that this method successfully incorporates the probabilistic nature of driving behavior. Taking the safety reliability into consideration can provide a more reasonable method to calculate the DYL of signalized intersections.]]></description><pubDate>Thu, 05 Mar 2020 16:54:48 GMT</pubDate><guid>http://pubsindex.trb.org/view/1689767</guid></item><item><title>Determining Length of Red Intervals for Effective Protected-Permissive Left Turn Phase Operation with Flashing Yellow Arrow Signal</title><link>http://pubsindex.trb.org/view/1573331</link><description><![CDATA[Protected-permissive left turn (PPLT) phasing has been popular and widely used in many urban intersections in North America because of its operational benefits. A significant number of intersections have recently been upgraded with four-section signal heads with flashing yellow arrow (FYA) indication for an effective protected-permissive left turn operation. The present study seeks to find appropriate length of two red times whose roles are important, but different during the FYA-PPLT phasing. One is red time for delayed-start of permissive left turn movements; the other is additional red time for delayed-start of opposing through movements. Micro-traffic simulation and conflict analysis are explored to assess the effects of the red time length on intersection efficiency and safety. A useful reference, which describes the balanced length of the two red times under varying traffic levels, is developed as a result.]]></description><pubDate>Fri, 01 Mar 2019 15:51:32 GMT</pubDate><guid>http://pubsindex.trb.org/view/1573331</guid></item><item><title>Safety Effects of Flashing Yellow Arrows Used in Protected Permitted Phasing: Comparison of Full Bayes and Empirical Bayes Results</title><link>http://pubsindex.trb.org/view/1494912</link><description><![CDATA[Using the flashing yellow arrow (FYA) signal indication for the permissive portion of protected-permissive left-turn (PPLT) phasing has become an increasingly popular treatment for left-turn signals as drivers are believed to understand the FYA better than the traditional circular green indication. A before-and-after safety evaluation of deploying FYA at PPLT signals at 28 intersections in Virginia was conducted. Each of the study intersections had FYA for the permitted portion of the phase on at least one left-turn approach. The focus was on left-turns that operated in the protected-permissive mode (with circular green indication for the permissive portion) before being converted to PPLT operations with the FYA indication for the permissive portion (PPLT-FYA). Crash records from before and after the activation of FYA were compared using both the full Bayes and empirical Bayes approaches. The results indicate that using the FYA signal indication instead of the circular green indication had a statistically significant effect in reducing overall frequency and severity of crashes. For the intersections studied in this research, total crashes reduced by 12% following conversion from PPLT to PPLT–FYA. The results also indicated that the full Bayes approach to safety effectiveness evaluation can, at a minimum, provide similar results to the well-established empirical Bayes approach. The 95% credible intervals for the expected crash reduction rates estimated with the full Bayes method were generally narrow, suggesting a good degree of confidence in the estimates.]]></description><pubDate>Thu, 22 Mar 2018 11:57:28 GMT</pubDate><guid>http://pubsindex.trb.org/view/1494912</guid></item><item><title>Field Evaluation of the Dilemma Zone Protection System at Suburban Intersections</title><link>http://pubsindex.trb.org/view/1495584</link><description><![CDATA[Despite the fact that both traffic researchers and highway agencies have devoted considerable efforts over the past few decades to improving intersection safety, development of effective strategies to contend with this vital issue remains a challenging task. This research presents the field evaluation results of a Dilemma Zone Protection System (DZPS) implemented at two hazardous intersections in Maryland, U.S.A. The deployed DZPS can offer both proactive and reactive protections to drivers approaching a signalized intersection during a yellow phase. Field evaluations conducted at two intersections with DZPS deployed confirmed a 100% detection rate for red-light-running vehicles, timely activation of the all-red extension to prevent right-angle crashes, and effectively discouraging drivers from taking aggressive “pass” decisions during the yellow or all-red phases. The potential extension of the DZPS for speed harmonization on arterial traffic flows is also discussed.]]></description><pubDate>Mon, 05 Feb 2018 11:26:08 GMT</pubDate><guid>http://pubsindex.trb.org/view/1495584</guid></item><item><title>Estimating Rear-End Accident Probabilities with Different Driving Tendencies at Signalized Intersections in China</title><link>http://pubsindex.trb.org/view/1495513</link><description><![CDATA[Rear-end accidents are the most common accident type at signalized intersections because of the different driving tendencies in the dilemma zone (DZ), where drivers are faced with indecisiveness of making stop or go decisions at yellow onset. In various research, the number of vehicles in the DZ has been used as a safety indicator—the more vehicles in the DZ, the higher the probability of rear-end accidents. However, the DZ-associated rear-end accident potential varies depending on drivers’ driving tendency and the situation (position and speed) at the yellow onset. This study’s primary objective was to explore how the driving tendency impacts the DZ distribution and the probability of rear-end accidents. To achieve this, the types of driving tendency were classified by using K-means clustering analysis based on driving variables. Further, the boundary of the DZ is determined by logistic regression models of drivers’ stop/go decision. Then, the authors proposed the conditional probability model of rear-end accidents and developed a Monte Carlo simulation framework to calculate the model. The results indicate that the rear-end accident probability is dependent on the driving tendency even at the same position with the same speed in the DZ. The aggressive type is the highest followed by conservative and then the normal. The quantitative results of the study can provide the basis for rear-end accident assessments.]]></description><pubDate>Mon, 05 Feb 2018 11:26:07 GMT</pubDate><guid>http://pubsindex.trb.org/view/1495513</guid></item><item><title>Modeling Driver Behavior at Signalized Intersection Dilemma Zone Under Mixed Traffic Conditions</title><link>http://pubsindex.trb.org/view/1495452</link><description><![CDATA[Signalized Intersections are important node points in the road network, ensuring safe and efficient way of maneuvering the traffic. Even though traffic signals are considered to be the most effective way of controlling the traffic, they stand second in the fatal accidents next to the un-signalized intersections. One of the main contributing factor in traffic signal related crashes is the presence of dilemma zone, where a driver becomes indecisive whether to pass or stop at the intersection on the yellow onset. Significant amount of research has been done on the dilemma driver behavior under homogeneous traffic conditions, however little or no research has been found on mixed traffic conditions, where vehicles vary in physical and dynamic characteristics. The main motive of this study is to investigate the factors influencing the driver behavior in dilemma zone at signalized approaches in India under mixed traffic conditions. Field data was collected at five signalized approaches using video capturing technique to investigate the driver behavior. Frame by frame manual extraction resulted in 998 driver responses at the yellow onset and binary logistic regression model is developed to represent the observed behavior. Distance from stop line, vehicle’s approach speed and duration of yellow signal were found as most important parameters in drivers stop/go decisions. Vehicle type, which is a characteristic of mixed traffic conditions is found to have a significant impact on the driver’s decision. The insights from this study can be used to improve the safety and performance at signalized intersections in developing countries.]]></description><pubDate>Mon, 05 Feb 2018 11:26:06 GMT</pubDate><guid>http://pubsindex.trb.org/view/1495452</guid></item><item><title>Field Testing of the Interactive Decision Support System to Predict Flashing Yellow Arrow Left-Turn Mode by Time of Day</title><link>http://pubsindex.trb.org/view/1439684</link><description><![CDATA[The flashing yellow arrow (FYA) signal display creates an opportunity to enhance the left-turn phase with a variable mode that can be changed on demand. This paper presents phase II of the research. Phase I developed a decision support system (DSS) to select the FYA left-turn mode, and changing by time of day at intersections. There was a need to continue to refine the interactive framework to improve its service. However, the ultimate objective of the continued research of phase II was to demonstrate the ability to execute the automation of the process. Phase II of the FYA project provided additional intersection data that refined the model. Virtual testing of the DSS was first conducted using VISSIM application programming interface (API) before the field testing environment. A Custom communications software was developed to retrieve instantaneous channel input data, synchronize opposing thru green phase, analyze traffic information, provide the algorithm decision, and generate a real-time log recording the events to determine whether it would be optimal to switch the red arrow to a flashing yellow arrow. The algorithm determines the time interval between the successive arrivals of vehicles and computes the corresponding headway for each lane by cycle on a second-by-second basis. The DSS was ultimately tested at two different intersections in Seminole County. The FYA 4-section configuration provides the opportunity for a fully adjustable system and provides the traffic management centers (TMCs) with more tools to operate the intersections as efficiently as possible at peak and off-peak times]]></description><pubDate>Wed, 15 Mar 2017 17:15:08 GMT</pubDate><guid>http://pubsindex.trb.org/view/1439684</guid></item><item><title>The Impact of Starting Amber Traffic Signal on Traffic Flow and Safety: a Driving Simulator Study</title><link>http://pubsindex.trb.org/view/1437982</link><description><![CDATA[Due to the growing demand for efficient transportation and limited capacity, the performance of the existing infrastructure and traffic control systems need to be optimized in order to control the growing saturation of roads and intersections. This study gives a first indication of the traffic safety and traffic flow implications of the starting amber phase on Belgian traffic signals. Non-Belgian studies reported an increased capacity of intersections after the implementation of the starting amber, but warned for an increase of early departures and violations. During the experiments of this study, forty four participants completed four experimental drives by which a comparison between the conventional traffic light scheme and the starting amber phase was made. This study concludes that a starting amber of 2 seconds has a positive impact on the traffic flow as the driver gains a time advantage of 1.1 seconds compared to the traditional traffic light scheme. Drivers could prepare themselves for the oncoming green phase and started accelerating earlier. Traffic Safety effects were tested by including conflict situations with pedestrians and crossing vehicles, but due to the usage of a driving simulator, no valid results were found. This immediately forms the foundation of further investigation.]]></description><pubDate>Thu, 02 Mar 2017 17:04:04 GMT</pubDate><guid>http://pubsindex.trb.org/view/1437982</guid></item></channel></rss>