Real time queue length estimation for signalized intersections using travel times from mobile sensors

We study how to estimate real time queue lengths at signalized intersections using intersection travel times collected from mobile traffic sensors. The estimation is based on the observation that critical pattern changes of intersection travel times or delays, such as the discontinuities (i.e., sudden and dramatic increases in travel times) and non-smoothness (i.e., changes of slopes of travel times), indicate signal timing or queue length changes. By detecting these critical points in intersection travel times or delays, the real time queue length can be re-constructed. We first introduce the concept of Queue Rear No-delay Arrival Time which is related to the non-smoothness of queuing delay patterns and queue length changes. We then show how measured intersection travel times from mobile sensors can be processed to generate sample vehicle queuing delays. Under the uniform arrival assumption, the queuing delays reduce linearly within a cycle. The delay pattern can be estimated by a linear fitting method using sample queuing delays. Queue Rear No-delay Arrival Time can then be obtained from the delay pattern, and be used to estimate the maximum and minimum queue lengths of a cycle, based on which the real-time queue length curve can also be constructed. The model and algorithm are tested in a field experiment and in simulation.     

The optimization of lane assignment and signal timing at the tandem intersection with pre‐signal

This paper presents an integrated model for optimizing lane assignment and signal timing at tandem intersection, which is introduced recently. The pre‐signal is utilized in the tandem intersection to reorganize the traffic flow; hence, the vehicles, regardless of whether left‐turns or through vehicles, can be discharged in all the lanes. However, the previous work does not consider the extra traffic disruption and the associated delay caused by the additional pre‐signal. In the paper, the extra delay aroused by the coordination is incorporated in a lane assignment and signal timing optimization model, and the problem is converted into a mixed‐integer non‐linear programming. A feasible directions method is hence introduced to solve the mixed‐integer non‐linear programming. The result of the optimization shows that the performance of the tandem intersection is improved and the average delay is minimized. The comparison between the tandem and the conventional configuration is presented, and the results verify that the former shows better performance than the latter. In addition, the optimal sequence corresponding to the turning proportion and the optimal lane assignment at the upstream approach of the pre‐signal are presented. Furthermore, if the number of lanes is equal in all arms, the paper proves that the average delay will be reduced if lane assignment is proportional to the turning proportion and the vehicles with low proportion are discharged in advance. Copyright © 2013 John Wiley & Sons, Ltd.     

Development of a delay model for unsignalized intersections applicable to traffic assignment

Abstract

This paper develops a model for estimating unsignalized intersection delays which can be applied to traffic assignment (TA) models. Current unsignalized intersection delay models have been developed mostly for operational purposes, and demand detailed geometric data and complicated procedures to estimate delay. These difficulties result in unsignalized intersection delays being ignored or assumed as a constant in TA models.

Video and vehicle license plate number recognition methods are used to collect traffic volume data and to measure delays during peak and off-peak traffic periods at four unsignalized intersections in the city of Tehran, Iran. Data on geometric design elements are measured through field surveys. An empirical approach is used to develop a delay model as a function of influencing factors based on 5- and 15-min time intervals. The proposed model estimates delays on each approach based on total traffic volumes, rights-of-way of the subject approach and the intersection friction factor. The effect of conflicting traffic flows is considered implicitly by using the intersection friction factor. As a result, the developed delay model guarantees the convergence of TA solution methods.

A comparison between delay models performed using different time intervals shows that the coefficients of determination, R ², increases from 43.2% to 63.1% as the time interval increases from 5- to 15-min. The US Highway Capacity Manual (HCM) delay model (which is widely used in Iran) is validated using the field data and it is found that it overestimates delay, especially in the high delay ranges.     

New approach for developing warrants of protected left-turn phase at signalized intersections

The research embodied in this paper presents a new approach for the development of guidelines for the installation of a protected left-turn phase at signalized intersections when permissive-only left-turn operation is present. This approach is based on maintaining intersection traffic operation at optimum efficiency. Three analyses were presented and discussed and they involved the use of the new approach on some hypothetical basic scenarios at a four-legged intersection with single lane in each approach. The first scenario involved exclusive left-turn lane operation while the other two scenarios involved shared-lane operation. Exhaustive signal optimization analyses were conducted using a signal optimization software package called “Signal Expert”. Regression models were developed from optimization results that allow the analyst to make the decision on protected left-turn phase installation using the basic input data of signal timing design without the need to perform field measurements. The regression results showed that the transition from permissive to protected/permissive left-turn operation, based on system optimization, is mainly a function of traffic conditions and that this transition (interface) is predictable. The results also suggested that these warrants are of reasonable accuracy when compared with those in the current practice.     

Multi-stage stochastic program to optimize signal timings under coordinated adaptive control

In the wake of traffic congestion at intersections, it is imperative to shorten delays in corridors with stochastic arrivals. Coordinated adaptive control can adjust green time flexibly to deal with a stochastic demand, while maintaining a minimum through-band for coordinated intersections. In this paper, a multi-stage stochastic program based on phase clearance reliability (PCR) is proposed to optimize base timing plans and green split adjustments of coordinated intersections under adaptive control. The objective is to minimize the expected intersection delay and overflow of the coordinated approach. The overflow or oversaturated effect is explicitly addressed in the delay calculation, which greatly increases the modeling complexity due to the interaction of overflow delays across cycles. The notion of PCR separates the otherwise related green time settings of consecutive cycles into a number of stages, in which the base timing plan and actual timing plan in different cycles are handled sequentially. We then develop a PCR based solution algorithm to solve the problem, and apply the model and the solution algorithm to actual intersections in Shanghai to investigate its performance as compared with Allsop’s method and Webster’s method. Preliminary results show the PCR-based method can significantly shorten delays and almost eliminates overflow for the coordinated approaches, with acceptable delay increases of the non-coordinated approaches. A comparison between the proposed coordinated adaptive logic and a coordinated actuated logic is also conducted in the case study to show the advantages and disadvantages.     

Operational performance comparison of four unconventional intersection designs using micro‐simulation

Several unconventional intersection designs have been proposed as an innovative approach to mitigate congestion at heavily congested at‐grade signalized intersections. Many of these unconventional designs were shown to outperform conventional intersections in terms of the average control delay and the overall intersection capacity. Little research has been conducted to compare the performance of these unconventional intersections to each other under different volume conditions. This study evaluated and compared the operational performance of four unconventional intersection schemes: the crossover displaced left‐turn (XDL), the upstream signalized crossover (USC), the double crossover intersection (DXI) (i.e., half USC), and the median U‐turn (MUT). The micro‐simulation software vissim (PTV Planung Transport Verkehr AG, Karlsruhe, Germany) was used to model and analyze the four unconventional intersections as well as a counterpart conventional one. The results showed that the XDL intersection constantly exhibited the lowest delays at nearly all tested balanced and unbalanced volume levels. The operational performance of both the USC and the DXI was similar in most volume conditions. The MUT design, on the other hand, was unable to accommodate high approach volumes and heavy left‐turn traffic. The capacity of the XDL intersection was found to be 99% higher than that of the conventional intersection, whereas the capacity of the USC and the DXI intersections was about 50% higher than that of the conventional intersection. The results of this study can provide guidance on choosing among alternative unconventional designs according to the prevailing traffic conditions at an intersection. Copyright © 2012 John Wiley & Sons, Ltd.     

A real-time adaptive signal control in a connected vehicle environment

The state of the practice traffic signal control strategies mainly rely on infrastructure based vehicle detector data as the input for the control logic. The infrastructure based detectors are generally point detectors which cannot directly provide measurement of vehicle location and speed. With the advances in wireless communication technology, vehicles are able to communicate with each other and with the infrastructure in the emerging connected vehicle system. Data collected from connected vehicles provides a much more complete picture of the traffic states near an intersection and can be utilized for signal control. This paper presents a real-time adaptive signal phase allocation algorithm using connected vehicle data. The proposed algorithm optimizes the phase sequence and duration by solving a two-level optimization problem. Two objective functions are considered: minimization of total vehicle delay and minimization of queue length. Due to the low penetration rate of the connected vehicles, an algorithm that estimates the states of unequipped vehicle based on connected vehicle data is developed to construct a complete arrival table for the phase allocation algorithm. A real-world intersection is modeled in VISSIM to validate the algorithms. Results with a variety of connected vehicle market penetration rates and demand levels are compared to well-tuned fully actuated control. In general, the proposed control algorithm outperforms actuated control by reducing total delay by as much as 16.33% in a high penetration rate case and similar delay in a low penetration rate case. Different objective functions result in different behaviors of signal timing. The minimization of total vehicle delay usually generates lower total vehicle delay, while minimization of queue length serves all phases in a more balanced way.     

Real-time queue length estimation for congested signalized intersections

How to estimate queue length in real-time at signalized intersection is a long-standing problem. The problem gets even more difficult when signal links are congested. The traditional input–output approach for queue length estimation can only handle queues that are shorter than the distance between vehicle detector and intersection stop line, because cumulative vehicle count for arrival traffic is not available once the detector is occupied by the queue. In this paper, instead of counting arrival traffic flow in the current signal cycle, we solve the problem of measuring intersection queue length by exploiting the queue discharge process in the immediate past cycle. Using high-resolution “event-based” traffic signal data, and applying Lighthill–Whitham–Richards (LWR) shockwave theory, we are able to identify traffic state changes that distinguish queue discharge flow from upstream arrival traffic. Therefore, our approach can estimate time-dependent queue length even when the signal links are congested with long queues. Variations of the queue length estimation model are also presented when “event-based” data is not available. Our models are evaluated by comparing the estimated maximum queue length with the ground truth data observed from the field. Evaluation results demonstrate that the proposed models can estimate long queues with satisfactory accuracy. Limitations of the proposed model are also discussed in the paper.     

Optimal operation of displaced left-turn intersections: A lane-based approach

Displaced left-turn (DLT) intersections that resolve the conflict between left-turn and opposing-through movements at the pre-signal are probably the most extensively used innovative intersection designs. The DLT intersection concept can be extended to ten different types according to the location of the left-turn transition area, the number of DLT approaches, and the possible setting of the bypass right-turn lane. This paper presents a generalized lane-based optimization model for the integrated design of DLT intersection types, lane markings, the length of the displaced left-turn lane, and the signal timings. The optimization is formulated as a mixed-integer non-linear program. This program is further transformed to a series of mixed-integer linear programming problems that can be solved by the standard branch-and-bound technique. Results from extensive numerical analyses reveal the effectiveness of the proposed method, as well as the promising property of assisting transportation professionals in the proper selection of DLT intersection types, and the design of geometric layout and signal timings.     

A two-stage fuzzy logic controller for traffic signals

This paper presents the design and evaluation of a fuzzy logic traffic signal controller for an isolated intersection. The controller is designed to be responsive to real-time traffic demands. The fuzzy controller uses vehicle loop detectors, placed upstream of the intersection on each approach, to measure approach flows and estimate queues. These data are used to decide, at regular time intervals, whether to extend or terminate the current signal phase. These decisions are made using a two-stage fuzzy logic procedure. In the first stage, observed approach traffic flows are used to estimate relative traffic intensities in the competing approaches. These traffic intensities are then used in the second stage to determine whether the current signal phase should be extended or terminated. The performance of this controller is compared to that of a traffic-actuated controller for different traffic conditions on a simulated four-approach intersection.     

Effects of countdown timers on queue discharge characteristics of through movement at a signalized intersection

This study investigates how countdown timers installed at a signalized intersection affect the queue discharge characteristics of through movement during the green phase. Since the countdown timers display the time remaining (in seconds) until the onset of the green phase, drivers waiting in the queue at the intersection are aware of the upcoming phase change, and are likely to respond quicker. Thus, the countdown timers could reduce the start-up lost time, decrease the saturation headway, and increase the saturation flow rate. This study observed vehicle flow at an intersection in Bangkok for 24 h when the countdown timers were operating, and for another 24 h when the countdown timers were switched off. The signal plans and timings remained unchanged in both cases. Standard statistical t-tests were used to compare the difference in traffic characteristics between the “with timer” and “without timer” cases. It was found that the countdown timers had a significant impact on the start-up lost time, reducing it by 1.00–1.92 s per cycle, or a 17–32% time saving. However, the effects on saturation headway were found to be trivial, which implies that the countdown timers do not have much impact on the saturation flow rate of signalized intersections, especially during the off-peak day period and the late night period. The savings in the start-up lost time from the countdown timers was estimated to be equivalent to an 8–24 vehicles/h increase for each through movement lane at the intersection being studied.     

A programmable calculation procedure for number of traffic conflict points at highway intersections

Traffic movement conflict points at intersections are the points at which traffic movements intersect (including crossing, merging, and diverging). Numbers and distribution of different types of conflict points are used to evaluate intersection access management designs and safety performance. Traditionally, the determination of the numbers of conflict points for different traffic movements is based on manual methods, which causes the difficulty for computerized procedures to evaluate safety performance of different access management designs. Sometimes, a programmable calculation procedure may provide more effective solutions as compared with manual methods. This paper presents a programmable calculation procedure for the determination of the numbers of conflict points, which could be used as a basis for a computerized procedure. Concepts of virtual movement lanes and intersection quadrants are introduced to specify types of intersections, traffic lane configurations, and traffic movement regulations. Calculation models, based on such concepts, for traffic movement conflict points at signalized and unsignalized intersections can be obtained. In support of the procedure, case studies are presented in the paper. The procedure presented in the paper can be programmed into a computer program for the purpose of a computerized evaluation of intersection safety and design performance of different access management or control approaches. Copyright © 2012 John Wiley & Sons, Ltd.     

Modeling delay at signalized intersections with channelized right‐turn lanes considering the impact of blockage

This paper presents a probabilistic delay model for signalized intersections with right‐turn channelization lanes considering the possibility of blockage. Right‐turn channelization is used to improve the capacity and to reduce delay at busy intersections with a lot of right‐turns. However, under heavy traffic conditions the through vehicles will likely block the channelization entrance that accrues delay to right‐turn vehicles. If the right‐turn channelization gets blocked frequently, its advantage in reducing the intersection delay is neglected and as a result the channelization lane becomes inefficient and redundant. The Highway Capacity Manual (HCM) neglects the blockage effect, which may be a reason for low efficiency during peak hours. More importantly, using HCM or other standard traffic control methods without considering the blockage effects would lead to underestimation of the delay. To overcome this issue, the authors proposed delay models by taking into account both deterministic and random aspects of vehicles arrival patterns at signalized intersections. The proposed delay model was validated through VISSIM, a microscopic simulation model. The results showed that the proposed model is very precise and accurately estimates the delay. In addition, it was found that the length of short‐lane section and proportion of right‐turn and through traffic significantly influence the approach delay. For operational purposes, the authors provided a step‐by‐step delay calculation process and presented approach delay estimates for different sets of traffic volumes, signal settings, and short‐lane section lengths. The delay estimates would be useful in evaluating adequacy of the current lengths, identifying the options of extending the short‐lane section length, or changing signal timing to reduce the likelihood of blockage. Copyright © 2016 John Wiley & Sons, Ltd.     

Performance analysis of the phase swap sorting strategy for an isolated intersection

A separate left-turn phase wastes the capacity of intersection, because all the lanes on the approach are not fully utilized during either the left-turn or through green phase. Under the phase swap sorting strategy (Xuan, 2011), different types of movements can be reorganized by a pre-signal so that all the lanes in the sorting area can be used to discharge vehicles during their green phases. Thus the capacity is improved significantly. In fact, when a pre-signal is installed upstream of the intersection signal (also named main signal), the two signals will have a great impact on not only the capacity, but other traffic performances, such as delays, queue formations, maximum queue length, residual queue, and spillback, etc., which are very important performance factors for the design and application of the phase swap sorting strategy. In order to more fully quantify and characterize the performance of the phase swap sorting strategy, a three-dimensional Markov queueing model is presented. Two levels of performance evaluation indices are formulated using the matrix analytic techniques. All these indices can be used to establish a more comprehensive analytical framework to evaluate the use of the phase swap sorting strategy. Model validation shows that the proposed model can provide a reliable performance analysis for the phase swap sorting strategy under various different conditions. In addition, in order to intuitively illustrate the effects of various factors on the performance of the phase swap sorting strategy, a series of numerical experiments is conducted.     

Improved vehicle classification from dual-loop detectors in congested traffic

Vehicle classification is an important traffic parameter for transportation planning and infrastructure management. Length-based vehicle classification from dual loop detectors is among the lowest cost technologies commonly used for collecting these data. Like many vehicle classification technologies, the dual loop approach works well in free flow traffic. Effective vehicle lengths are measured from the quotient of the detector dwell time and vehicle traversal time between the paired loops. This approach implicitly assumes that vehicle acceleration is negligible, but unfortunately at low speeds this assumption is invalid and length-based classification performance degrades in congestion.To addresses this problem, we seek a solution that relies strictly on the measured effective vehicle length and measured speed. We analytically evaluate the feasible range of true effective vehicle lengths that could underlie a given combination of measured effective vehicle length, measured speed, and unobserved acceleration at a dual loop detector. From this analysis we find that there are small uncertainty zones where the measured length class can differ from the true length class, depending on the unobserved acceleration. In other words, a given combination of measured speed and measured effective vehicle length falling in the uncertainty zones could arise from vehicles with different true length classes. Outside of the uncertainty zones, any error in the measured effective vehicle length due to acceleration will not lead to an error in the measured length class. Thus, by mapping these uncertainty zones, most vehicles can be accurately sorted to a single length class, while the few vehicles that fall within the uncertainty zones are assigned to two or more classes. We find that these uncertainty zones remain small down to about 10 mph and then grow exponentially as speeds drop further.Using empirical data from stop-and-go traffic at a well-tuned loop detector station the best conventional approach does surprisingly well; however, our new approach does even better, reducing the classification error rate due to acceleration by at least a factor of four relative to the best conventional method. Meanwhile, our approach still assigns over 98% of the vehicles to a single class.     

Field implementation feasibility study of cumulative travel‐time responsive (CTR) traffic signal control algorithm

The cumulative travel‐time responsive (CTR) algorithm determines optimal green split for the next time interval by identifying the maximum cumulative travel time (CTT) estimated under the connected vehicle environment. This paper enhanced the CTR algorithm and evaluated its performance to verify a feasibility of field implementation in a near future. Standard Kalman filter (SKF) and adaptive Kalman filter (AKF) were applied to estimate CTT for each phase in the CTR algorithm. In addition, traffic demand, market penetration rate (MPR), and data availability were considered to evaluate the CTR algorithm's performance. An intersection in the Northern Virginia connected vehicle test bed is selected for a case study and evaluated within vissim and hardware in the loop simulations. As expected, the CTR algorithm's performance depends on MPR because the information collected from connected vehicle is a key enabling factor of the CTR algorithm. However, this paper found that the MPR requirement of the CTR algorithm could be addressed (i) when the data are collected from both connected vehicle and the infrastructure sensors and (ii) when the AKF is adopted. The minimum required MPRs to outperform the actuated traffic signal control were empirically found for each prediction technique (i.e., 30% for the SKF and 20% for the AKF) and data availability. Even without the infrastructure sensors, the CTR algorithm could be implemented at an intersection with high traffic demand and 50–60% MPR. The findings of this study are expected to contribute to the field implementation of the CTR algorithm to improve the traffic network performance. Copyright © 2017 John Wiley & Sons, Ltd.     

Dynamic network traffic control

This study developed a dynamic traffic control formulation designated as dynamic intersection signal control optimization (DISCO). Traffic in DISCO is modeled after the cell-transmission model (CTM), which is a convergent numerical approximation to the hydrodynamic model of traffic flow. It considers the entire fundamental diagram and captures traffic phenomena such as shockwaves and queue dynamics. As a dynamic approach, the formulation derives dynamic timing plans for time-variant traffic patterns. We solved DISCO based on a genetic algorithm (GA) approach and applied it to a traffic black spot in Hong Kong that is notorious for severe congestion. For performance comparisons, we also applied TRANSYT to the same scenarios. The Results showed that DISCO outperformed TRANSYT for all the scenarios tested especially in congested traffic. For the congested scenarios, DISCO could reduce delay by as much as 33% when compared with TRANSYT. Even for the uncongested scenarios, DISCO’s delays could be smaller by as much as 23%.     

A gradient boosting logit model to investigate driver’s stop-or-run behavior at signalized intersections using high-resolution traffic data

Driver’s stop-or-run behavior at signalized intersection has become a major concern for the intersection safety. While many studies were undertaken to model and predict drivers’ stop-or-run (SoR) behaviors including Yellow-Light-Running (YLR) and Red-Light-Running (RLR) using traditional statistical regression models, a critical problem for these models is that the relative influences of predictor variables on driver’s SoR behavior could not be evaluated. To address this challenge, this research proposes a new approach which applies a recently developed data mining approach called gradient boosting logit model to handle different types of predictor variables, fit complex nonlinear relationships among variables, and automatically disentangle interaction effects between influential factors using high-resolution traffic and signal event data collected from loop detectors. Particularly, this research will first identify a series of related influential factors including signal timing information, surrounding traffic information, and surrounding drivers’ behaviors using thousands drivers’ decision events including YLR, RLR, and first-to-stop (FSTP) extracted from high-resolution loop detector data from three intersections. Then the research applies the proposed data mining approach to search for the optimal prediction model for each intersection. Furthermore, a comparison was conducted to compare the proposed new method with the traditional statistical regression model. The results show that the gradient boosting logit model has superior performance in terms of prediction accuracy. In contrast to other machine learning methods which usually apply ‘black-box’ procedures, the gradient boosting logit model can identify and rank the relative importance of influential factors on driver’s stop-or-run behavior prediction. This study brings great potential for future practical applications since loops have been widely implemented in many intersections and can collect data in real time. This research is expected to contribute to the improvement of intersection safety significantly.     

Evaluation of actuated control of diamond interchanges with advanced experimental design

Two three‐phase actuated control strategies at diamond interchanges were investigated for different ramp spacings and traffic patterns. An advanced experimental design, hardware‐in‐the‐loop control, was employed for the simulation study. Operational performance was identified in terms of cycle length, average delay and total stops. Experimental results showed that the two phasing strategies gave similar performance in terms of cycle length and average delay, but not stops. The cycle length of three‐phase operation increased slightly as the ramp spacing became wider. The delay of each strategy was dependent on the traffic pattern, but there was a distinct movement preference for each strategy. The total stops decreased as the spacing increased, and it was the most sensitive variable for the studied traffic demand level. It was also shown that the concept of the hardware‐in‐the‐loop control provides an effective way to evaluate the signal phasing and control strategies.     

Identification of oversaturated intersections using high-resolution traffic signal data

Conceptually, an oversaturated traffic intersection is defined as one where traffic demand exceeds the capacity. Such a definition, however, cannot be applied directly to identify oversaturated intersections because measuring traffic demand under congested conditions is not an easy task, particularly with fixed-location sensors. In this paper, we circumvent this issue by quantifying the detrimental effects of oversaturation on signal operations, both temporally and spatially. The detrimental effect is characterized temporally by a residual queue at the end of a cycle, which will require a portion of green time in the next cycle; or spatially by a spill-over from downstream traffic whereby usable green time is reduced because of the downstream blockage. The oversaturation severity index (OSI), in either the temporal dimension (T-OSI) or the spatial dimension (S-OSI) can then be measured using high-resolution traffic signal data by calculating the ratio between the unusable green time due to detrimental effects and the total available green time in a cycle. To quantify the T-OSI, in this paper, we adopt a shockwave-based queue estimation algorithm to estimate the residual queue length. S-OSI can be identified by a phenomenon denoted as “Queue-Over-Detector (QOD)”, which is the condition when high occupancy on a detector is caused by downstream congestion. We believe that the persistence duration and the spatial extent with OSI greater than zero provide an important indicator for measuring traffic network performance so that corresponding congestion mitigation strategies can be prepared. The proposed algorithms for identifying oversaturated intersections and quantifying the oversaturation severity index have been field-tested using traffic signal data from a major arterial in the Twin Cities of Minnesota.