Signalized Intersection Approaches Research Articles

Investigating factors that affect conflicts between bicyclists and right turning vehicles at signalized intersections

Due to the recognition of active transportation as a beneficial alternative to more traditional modes of transportation, there is increasing interest in designing infrastructure systems to promote the safe use of forms such as bicycling. Collision data, which are typically used in road safety studies, may be incomplete and the use of such data is reactive as it requires collisions to have already taken place. Additionally, collisions involving bicyclists and vehicles are less common than those between vehicles. As a result, alternative approaches for evaluating the safety effect of various infrastructure attributes, such as the use of surrogate safety measures, specifically traffic conflicts, could be considered. Most collisions between bicyclists and vehicles occur at intersections and of these, collisions between right turning vehicles and bicyclists form the majority. The main objective of this study was to use cross-sectional regression models to investigate various intersection characteristics, including geometry, signal phasing, and bicycle infrastructure, with a view to determining which attributes are associated with a significant effect on right turning conflicts and how this may vary with different conflict severity levels. Using data for 65 signalized intersection approaches across Canada, various intersection attributes were found to be associated with the frequency of right turning conflicts such as exposure levels, the lateral offset of the bicycle facility and the grade of the approach to the intersection. The significance levels of the associated effects of certain attributes were observed to change with the severity level of the conflicts.

Capacity characteristics of long-term work zones on signalized intersection approaches

This study explored the capacity characteristics of five long-term WZ configurations at a major signalized intersection in Toronto. In total, 1,766 cycles and 22,057 inter-vehicle headway observations were recorded using over 140 h of real-time traffic videos. The saturation flow rate ranged from 1318.7 to 1767.3 pc/hr/ln across the study sites. Interestingly, the Highway Capacity Manual WZ model was found to significantly overestimate the traffic capacity at the study sites. The analysis assessed the hypothesis that the saturation headway is further compressed when long queues are present on site. The average saturation headway during oversaturated conditions was found to be shorter by 5 to 11% across the study sites as compared to undersaturated conditions. Other influential factors such as day versus night and late-merge were assessed. The saturation flow under daytime conditions was higher by 3 to 5% as compared to nighttimes. Vehicles merging late from the closed lanes had a shorter headway as compared to vehicles approaching from the open lane by around 8 to 10%. Probability distribution functions of the saturation headway were developed, the best-fit curve for all cases was found to be the three-parameter lognormal distribution. The study also developed multiple regression equations to estimate WZ capacity reduction induced by heavy vehicles for a wide range of heavy vehicle percentages. On average, oversaturated conditions yielded a 5.4% additional flow reduction as compared to undersaturated conditions for the same HV%. Moreover, the impact of different snow conditions on the saturation flow was estimated. The fully slushy, partly slushy, and bare-and-wet snow categories resulted in headway elongation of 35.1 to 42%, 21.2 to 23.4%, and 6.2 to 12.6%, respectively. The study explains how the findings can assist transportation agencies and practitioners in improving the policies, practices, and guidelines related to WZ activities and planning.

Factors Influencing Stopping Locations of Motorcycle Riders on Signalized Urban Intersection Approaches

In developing countries, motorcycle riders normally attempt to stop at their desired locations during queue formation on signalized intersection approaches. Under mixed-traffic conditions, motorcycle positioning in a queue affects the operational and safety performance of the intersection. This study aimed to identify factors influencing motorcycle riders’ stopping locations at signalized urban intersections. This study applied Unmanned Aerial Vehicles (UAVs) to observe the stopping behavior of 1413 motorcycle riders on 24 approaches from 10 signalized intersections in Thailand (N = 1413). Multinomial logistic regression analysis was used to determine the relationship between the stopping locations of motorcycle riders and rider- and motorcycle-related variables and traffic- and environmental-related variables. The statistical analyses presented a Cox and Snell R2 and Nagelkerke R2 of 0.466 and 0.499, respectively, indicating that the model accounted for almost 50% of the variation among the five stopping locations of motorcycle riders. The results showed that, under mixed-traffic conditions in Thailand with left-hand traffic, motorcycle riders intending to turn right, the morning peak period, the presence of shadows, motorcycle riders not wearing helmets, the presence of a larger vehicle in the queue, and the density of desired stopping locations significantly influenced the motorcyclists’ choice of stopping locations on signalized intersection approaches. Practical policy-related recommendations drawn from the findings are provided to improve motorcyclists’ safety on signalized intersection approaches.

Acceleration and Deceleration Rates of Various Vehicle Categories at Signalized Intersections in Mixed Traffic Conditions

The acceleration and deceleration rates vary from one vehicle type to another. The same vehicle type also exhibits variations in acceleration and deceleration rates due to vast variation in their dynamic and physical characteristics, ratio between weight and power, driver behaviour during acceleration and deceleration manoeuvres. Accurate estimation of acceleration and deceleration rates is very important for proper signal design to ensure minimum control delay for vehicles, which are passing through the intersection. The present study measures acceleration and deceleration rates for four vehicle categories: Two-wheeler, Three-wheeler, Car, and Light Commercial Vehicle (LCV), by using Open Street Map (OSM) tracker mobile application. The acceleration and deceleration rates were measured at 24 signalized intersection approaches in Hyderabad and Warangal cities. The study also developed acceleration and deceleration models for each vehicle type and the developed models were validated based on field data. The results showed that the predicted acceleration and deceleration models showed close relation with those measured in the field. The developed models are useful in predicting average acceleration and deceleration rate for different vehicle types under mixed and poor lane disciplined traffic conditions.

Design of an Efficient Vehicle-Actuated Signal Control Logic for Signalized Intersections

The effectiveness of fixed-time management systems dramatically decreases in case of fluctuated traffic demands at signalized intersection approaches. This leads to the waste of time in traffic and may cause material, psychological and ecological problems. Especially in recent years, to minimize the negative impacts of these problems, many researchers focus on Intelligent Transportation Systems (ITS). As it is known, one of the Intelligent Transportation Systems applications is called vehicle-actuated (traffic-actuated) management systems. Because the success of these types of applications is directly related to the created control logic, the selection of the most proper control parameters for the created control logic is an important issue. This study aims to create an effective control logic and flow chart for the vehicle-actuated management system. At the end of the analyses, it is seen that the created vehicle-actuated management system can adapt to fluctuations in traffic demands at signalized intersection approaches. Average vehicle delays, fuel consumptions and exhaust emissions can be reduced significantly by the created system. Especially, in case of fluctuations in traffic demands at intersection approaches exist, it is concluded that the performance of the intersection can increase enormously with the created vehicle-actuated management system.

Speeds of Right-Turning Vehicles at Signalized Intersections during Green or Yellow Phase

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.

The Influence of Motorcycles on Discharge Headway and Saturation Flows at Signalized Intersections under Mixed Traffic Conditions

The high proportion of motorcycles and lack of lane discipline at signalized intersections under mixed traffic conditions are the motivation to conduct this study. The discharge headway models are constructed at three (3) signalized intersections in the SARBAGITA urban area in Bali. The result shows that motorcycles affect saturation flow due to their shorter headway than light vehicles while increasing discharge headway of other vehicles. The discharge headway between pairs of heavy vehicles is longer than these of motorcycles due to their slower acceleration at signalized intersections. This study also found that the discharge headway plays a significant role in determining the saturation flow and capacity of a signalized intersection. If a heavy vehicle is one of the pairs, then it has the potential to have a headway exceeding the other vehicle pairs. This indicates, however, that the higher proportion of motorcycles at the signalized intersection approach does not necessarily mean shorter discharge headway. There may be other influencing factors, such as the riding behavior of motorcyclists. The dominance of motorcycles can affect the value of the saturated flow, but an increase in the proportion of heavy vehicles may reduce the effect of motorcycles on the saturation flows.

The influence of motorcycle behavior on saturation flow rate at signalized intersections with and without exclusive stopping space for motorcycle (ESSM)

Traffic in most developing nations is considered mixed or heterogeneous. Motorcycle and other vehicle’s behavior at signalized intersections would not probably have a similar influence on intersection capacity and time of the traffic signals. In theory, the saturation flow rate is a basic parameter to estimate the intersection capacity and time of the traffic signals. This study, therefore, aims to analyze the influence of motorcycle behavior on the saturation flow rate at signalized intersections in Denpasar, Bali. Traffic flow data are observed at four signalized intersection approaches that have similar width and traffic characteristics. Two approaches have exclusive stopping space for motorcycles (ESSM) while the other two do not. The study results show that more than 50% of motorcycles tend to be distributed beside flow at signalized intersections with ESSM on either light or dense traffic flows. In contrast, at the signalized intersections without ESSM, motorcycles are found to be distributed inside flow during low traffic conditions, while distributed beside flow during dense traffic flow. Besides, the saturation flow rates of motorcycle inside flow are less than that of beside flow at signalized intersections both with and without ESSM. A new method to estimate saturation flow is proposed.

Vendor-Independent Reliability Testing Model for Vehicle-to-Infrastructure Communications

This paper describes a vendor-independent reliability testing approach for vehicle-to-infrastructure (V2I) communications in connected vehicle traffic signal system applications. It provides an alternative to using the communication data reported by proprietary vendor-supplied interfaces. This approach was based on building a rigorously tested translation model that uses measured received signal strength indicator (RSSI) from any V2I communication equipment to predict the corresponding packet delivery ratio (PDR). This was achieved by correlating the signal strength, measured using a generic power meter, to PDR values reported in the communication interface of the equipment of different vendors. Both stationary and in-motion (10–40 mph) field data collection tests were conducted at three intersections. These tests were performed over distances of up to 500 m between the road-side units (RSUs) and the on-board units (OBUs). In each test, the RSSI values for line-of-sight packet exchange between various RSUs and OBUs was collected in the field, using both a generic power meter and vendor-specific tools. Next, the results were statistically analyzed and logistic and linear regression models that predict PDR values were developed. A case study to test and validate this new PDR prediction model was conducted at two intersections in Boise, Idaho. This prediction model will enable transportation system operators to test and validate the efficiency of connected vehicle RSU/OBU communications at signalized intersection approaches under different traffic conditions, independent of vendor-provided tools.

Before–After Evaluation of Left-Turn Lane Extension Considering Injury Severity and Collision Type

Left-turn lanes are commonly used to provide space to accommodate vehicle deceleration and provide adequate storage of turning vehicles. The objective of this study is to evaluate the safety effectiveness of extending the length of left-turn lanes at signalized intersection approaches. Five years of collision data including injury severity and collision type from three treatment sites and 31 comparison sites in the City of Surrey, Canada were used in the study. The analysis focused on target crashes including left-turn-related rear-end and left-turn-related sideswipe collisions. A full Bayesian (FB) before–after analysis was conducted for all collisions, severity levels, and collision types. Multivariate Poisson–lognormal linear intervention models were used for the analysis. The treatment effectiveness index was calculated to quantitatively measure the effectiveness of the safety treatment. The FB before–after results showed that the treatment-related collisions were reduced by 57.4% following the implementation of extended left-turn lane. The reduction in injuries and fatalities collisions (63.8%) was greater than that in property damage only collisions (55.7%). The decrease in rear-end collisions (62.8%) was greater than that in sideswipe collisions (58.1%). The findings indicate a remarkable improvement in safety after the length extension of the left-turn lane.

Determination and Utilization of Dilemma Zone Length and Location for Safety Assessment of Rural High-Speed Signalized Intersections

The objective of the present study is to see how the dilemma zone length and location are related to intersection safety at rural high-speed signalized intersections. For that, dilemma zones at 30 rural signalized intersection approaches where similar traffic operations and land-use conditions are present were identified, and traffic conflicts associated with the dilemma zones were investigated. Drivers’ stop or go behaviors as well as vehicle dynamics (e.g., vehicle speeds and locations) during the yellow and red clearance intervals were collected and analyzed to determine the dilemma zone length and location of each site. Red-light running violations and vehicles’ abrupt stops were also collected to investigate the relationship between such conflicts and dilemma zone length and location. As a result, two dilemma zone conflict models were developed. The analysis results show that the conflict models are accurate enough to predict the safety level of high-speed signalized intersections using the two dilemma zone variables. Results show that the chance of intersection angle conflicts increases if the dilemma zone is located farther from the intersection stop bar. Results also show that there would be a high chance of rear-end conflicts if the dilemma zone length is longer. The models were validated with additional datasets, and acceptable root means square error and mean absolute percentage error values were obtained as a result.

Real-Time Estimation of Vehicle Counts on Signalized Intersection Approaches Using Probe Vehicle Data

This paper presents a novel method for estimating the number of vehicles traveling along signalized approaches using probe vehicle data only. The proposed method uses the Kalman Filtering technique to produce reliable vehicle count estimates using real-time probe vehicle estimates of the expected travel times. The proposed method introduces a novel variable estimation interval that allows for higher estimation precision, as the updating time interval always contains a fixed number of probe vehicles. The proposed method is evaluated using empirical and simulated data, the former of which were collected along a signalized roadway in downtown Blacksburg, VA. Results indicate that vehicle count estimates produced by the proposed method are accurate. The paper also examines the model's accuracy when installing a single stationary sensor (e.g., loop detector), producing slight improvements especially when the probe vehicle market penetration rate is low. Finally, the paper investigates the sensitivity of the estimation model to traffic demand levels, showing that the model works better at higher demand levels given that more probe vehicles exist for the same market penetration rate.

Hardware-in-the-Loop Testing of Connected and Automated Vehicle Applications: A Use Case for Queue-Aware Signalized Intersection Approach and Departure

Most existing studies on connected and automated vehicle (CAV) applications apply simulation to evaluate system effectiveness. Model accuracy, limited data for calibration, and simulation assumptions limit the validity of evaluation results. One alternative approach is to use emerging hardware-in-the-loop (HIL) testing methods. HIL test environments enable physical test vehicles to interact with virtual vehicles from traffic simulation models, providing an evaluation environment that can replicate deployment conditions at early stages of CAV technology implementation without incurring excessive costs related to large field tests. In this study, a HIL testing system for vehicle-to-infrastructure (V2I) CAV applications is developed. The involved software and hardware includes a physical CAV controlled in real time, a traffic signal controller, communication devices, and a traffic simulator (VISSIM). Such HIL systems increase validity by considering the physical vehicle’s trajectories—which are constrained by real-world factors such as GPS accuracy, communication delay, and vehicle dynamics—in a simulated traffic environment. The developed HIL system is applied to test a representative early deployment CAV application: queue-aware signalized intersection approach and departure (Q-SIAD). The Q-SIAD algorithm generates recommended speed profiles based on the vehicle’s status, signal phase and timing (SPaT), downstream queue length, and system constraints and parameters (e.g., maximum acceleration and deceleration). The algorithm also considers the status of other vehicles in designing the speed profiles. The experiment successfully demonstrated this functionality with one test CAV driving through one intersection controlled by a fixed-timing traffic signal under various simulated traffic conditions.

Quality of Bicycle Traffic Management at Urban Road Links and Signalized Intersections Operating under Mixed Traffic Conditions

This study proposes bicycle level of service (BLOS) models for the urban road links and signalized intersection approaches operating under heterogeneous traffic flow conditions prevailing in developing countries. Extensive data collection was carried out through field investigations, videography techniques, and perception surveys to inspect which parameters primarily affect the quality of bicycling in the mentioned facilities. As many as 74 road links and 70 intersection approaches of nine different Indian cities were included in the study locations. In addition, the perceived satisfaction ratings of 22,320 on-site bicyclists (i.e., 155 bicyclists from each site) were included in the database. These ratings ranged from 1 to 6 (excellent–worst bicycling conditions), and were used as the array of dependent variable in the model development process. Separate BLOS models were developed for road links and bicycle through movement at signalized intersections through the application of a novel evolutionary artificial intelligence technique, namely multi-gene genetic programming. The link model included eight significant variables in total whereas the intersection model included a total of seven. With compacted structures, both models represented excellent reliabilities in the present context and produced high coefficient of determination ( R2) values of above 0.86 with averaged observations. These models will help traffic planners and engineers to evaluate the service levels of urban bicycle facilities of developing countries. Statistical analysis of modeled parameters has reported that the traffic volume and crossing pedestrians have the highest influences on the quality of bicycle traffic management at urban road links and intersection approaches, respectively.

Multivariate Poisson-lognormal model for analysis of crashes on urban signalized intersections approach

ABSTRACTMany studies investigate contributing factors of intersection crashes, but very limited studies focus on cashes on the intersection approach. It is important to address the characteristics of intersection-approach crashes to better understand intersection safety. This article analyzes the crashes on signalized intersection approach on urban arterials with a focus on traffic and geometric elements. The intersection approach is defined as the segment between stop bar and the location 200 ft upstream from the stop bar. The multivariate Poisson log-normal (MVPLN) model is used to model crash counts by severity. Ten-year crash data collected from 643 signalized intersections in Nebraska are used for analysis. One-way road is found to be negatively related to all three severity levels (light crash, moderate crash, and severe crash) of crashes. Compared to the 12 ft lane width, narrower lane widths generally lead to fewer crashes. The intersection approaches on urban arterials are expected to have more crashes than collector roads. The numbers of right-turn, left-turn, and through lanes, as well as the annual average daily traffic on the intersection approach and its crossing approach are statistically significant factors increasing crash frequency. The MVPLN model is compared to univariate and zero-inflated Poisson models. The results reveal that the MVPLN model provides a superior fit over the univariate Poisson model.

Modeling Driver Behavior in Dilemma Zone under Mixed Traffic Conditions

Abstract When signal changes from green to yellow at a signalized intersection, often drivers become skeptical, whether to cross the intersection or stop without entering the intersection. Improper decision might lead to right angle collision or rear end collision. The area in which the drivers are skeptical is termed as dilemma zone or indecision zone. Most of the studies in the literature have investigated the dilemma zone driving behavior in homogeneous traffic conditions, but traffic in developing countries like India is heterogeneous containing various vehicle types, where vehicles vary in their physical dimensions 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. This study investigated the driver behavior by videotaping 398 driver responses at two signalized intersection approaches with different yellow durations. Binary logistic regression model is developed to represent the driver behavior in mixed traffic conditions. Vehicle type, which is a characteristic of mixed traffic conditions is found to have a significant impact on the driver’s decision process along with the vehicle speed, distance from the stop line and duration of yellow signal.

Framework for evaluating risk of limited sight distance for permitted left-turn movements: case study

A reliability analysis framework is used to evaluate the risk of limited sight distance for permitted left-turn movements due to the presence of opposing left-turn vehicles. Two signalized intersection approaches in the city of Surrey were used as case studies for the framework. Geometric and traffic video data was collected and analyzed using a computer vision tool to extract the input variables probability distributions. The data was used in the reliability analysis where first-order and Importance Sampling methods were performed. The analysis showed that the probability of non-compliance was considerable at one approach due to its large left-turn lane offset. The analysis also showed that the probability of non-compliance increased substantially when the obstacle vehicle was a bus rather than a passenger car. Moreover, the time gap had a higher impact on the probability of non-compliance compared to speed. Strategies were suggested to overcome the high probability of non-compliance.

Crash Modification Functions for Installation of Left-Turn Lanes at Signalized Intersection Approaches

This paper presents the results of a study that developed crash modification (CM) functions for installing left-turn lanes at signalized intersection approaches. CM functions were obtained from a longitudinal before–after safety study that accounted for treatment location characteristics (heterogeneity). This approach for developing CM functions has several advantages over the commonly used cross-sectional evaluations, which have several statistical shortcomings. The developed CM functions incorporate a time variable to acknowledge that the safety treatment effects do not occur instantaneously but are spread over future time; this result was achieved with a nonlinear intervention model with the full Bayes method. Twelve treatment sites were selected for the evaluation, along with 67 comparison sites. The treatment included the addition of one or more LT lanes for each intersection. The analysis showed significant safety improvements for fatal-plus-injury and total collisions but statistically nonsignificant reductions for property-damage-only collisions. The significant covariates included in the CM functions were the time trend, total entering volumes, and category of the new left-turn lanes installation.

Investigating the Speed and Rear-End Collision Relationship at Urban Signalized Intersections

Rear-end collisions are often the overrepresented type of collisions at urban signalized intersections. Although these collisions can occur for a variety of reasons, speed can always play a significant role in rear-end collisions, as the stopping distance increases with speed. The study presented in this paper investigated the relationship between speed and rear-end collisions at urban signalized intersections. Collisions, speed characteristics, traffic volume, and geometry data for a group of urban signalized intersection approaches were collected for the analysis. Negative binomial safety performance functions were developed to establish the relationship between collisions and various speed characteristics, while controlling for the traffic volume and road geometry. The goodness of fit of the estimated models was checked with several measures to ensure model adequacy. The results revealed intuitive findings for various parameter estimates of the models. It was found that a 1-km/h increase in the standard deviation of speed was associated with 6.3%, 8.2%, and 5.7% increases in the frequency of total, injury, and property-damage-only (PDO) rear-end collisions, respectively. For both the average and the 85th percentile speed change, the estimated collision reductions were almost the same. An increase in 85th percentile speed by 1 km/h was associated with 1.1%, 1.6%, and 0.9% increases in the frequency of total, injury, and PDO rear-end collisions, respectively. Moreover, as the level of speeding increased, collision frequencies increased exponentially. The results of the study suggest that speed management upstream of the intersection approach could reduce rear-end collisions at urban signalized intersections.

Automated cars: Queue discharge at signalized intersections with ‘Assured-Clear-Distance-Ahead’ driving strategies

This study addresses the impacts of automated cars on traffic flow at signalized intersections. We develop and subsequently employ a deterministic simulation model of the kinematics of automated cars at a signalized intersection approach, when proceeding forward from a stationary queue at the beginning of a signal phase. In the discrete-time simulation, each vehicle pursues an operational strategy that is consistent with the ‘Assured Clear Distance Ahead’ criterion: each vehicle limits its speed and spacing from the vehicle ahead of it by its objective of not striking it, regardless of whether or not the future behavior of the vehicle ahead is cooperative. The simulation incorporates a set of assumptions regarding the values of operational parameters that will govern automated cars’ kinematics in the immediate future, which are sourced from the relevant literature.We report several findings of note. First, under a set of assumed ‘central’ (i.e. most plausible) parameter values, the time requirement to process a standing queue of ten vehicles is decreased by 25% relative to human driven vehicles. Second, it was found that the standard queue discharge model for human–driven cars does not directly transfer to queue discharge of automated vehicles. Third, a wet roadway surface may result in an increase in capacity at signalized intersections. Fourth, a specific form of vehicle-to-vehicle (V2V) communications that allows all automated vehicles in the stationary queue to begin moving simultaneously at the beginning of a signal phase provides relatively minor increases in capacity in this analysis. Fifth, in recognition of uncertainty regarding the value of each operational parameter, we identify (via scenario analysis, calculation of arc elasticities, and Monte-Carlo methods) the relative sensitivity of overall traffic flow efficiency to the value of each operational parameter.This study comprises an incremental step towards the broader objective of adapting standard techniques for analyzing traffic operations to account for the capabilities of automated vehicles.