Special provisions for left turns at signalized intersections to increase capacity and safety

Heavy left-turns at intersections are not only difficult to accommodate but also often cause traffic accidents. Such problem can be reduced by adopting an exclusive left-turn signal phase, but in this case the cycle length needs to be extended and the overall intersection capacity reduced. This problem is particularly important in such countries as Korea where unprotected left turns are rarely used. Innovative intersection designs and operational methods for avoiding these problems are presented and their effects of increasing capacity and reducing vehicle delay are analyzed. They rule out the requirement for exclusive left-turn phase while accommodating a large volume of left-turns quite safely.     

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.     

A study on adjustment factors for U-turns in left-turn lanes at signalized intersections

U-turns are treated as left-turns in the current procedures for estimating saturation flow rates at signalized intersections. While U-turning vehicles are usually mixed with left-turning vehicles in inside or left-turn lanes and conflict with opposing through traffic as left-turning vehicles, the vehicle operating characteristics are different. The objective of this paper is to investigate the effects of U-turns on the traffic flow in left-turn lanes. Field data of 600 headways of left-turning passenger cars and 160 headways of U-turning passenger cars are recorded. The average headways of U-turning passenger cars are found to be significantly larger than those of left-turning passenger cars. The effects of U-turning vehicles depend upon the percent of U-turning vehicles in the left-turn lane, as well as the order of formation in the traffic stream. Adjustment factors for varying percents of U-turning vehicles in left-turn lanes are established.     

Effect of shadows and time of day on performance of video detection systems at signalized intersections

This paper presents the effect of shadows and time of day on the performance of three video detection systems (VDS): Autoscope, Peek and Iteris, at a signalized intersection. Vendors were given two opportunities to improve the performance of their initial VDS setup before the final data collection. The evaluation and the results are based on 40 h of data from 20 days. Four performance measures: false calls, missed calls, dropped calls, and stuck-on calls were used in this study. Automated analysis of the data was performed in conjunction with manual verification of videos to identify the detection errors. The results for stop bar detection zones are presented in this paper. All the VDS reported false calls and depending on the lane, time of day, and sunny or cloudy conditions, the average false calls varied from 0.2% to 36%. The false calls were higher in sunny conditions than in cloudy conditions due to the shadows. Also, false calls for the leftmost lane were higher in sunny morning than in sunny midday due to shadows of turning vehicles from the middle lane. The false calls in the other two lanes were not affected by the time of day. Under the studied conditions, Autoscope, Peek, and Iteris missed detecting 2, 9, and 0 vehicles, respectively, in more than 7000 vehicles that went through the intersection. Autoscope, Peek, and Iteris had 87, 5, and 1 stuck-on calls, respectively, and there were more stuck-on calls in the morning than at midday. None of the three VDS had any dropped calls.     

Increasing the capacity of signalized intersections with separate left turn phases

A separate turn phase is often used on the approach leg to an intersections with heavy left turns. This wastes capacity on the approach because some of its lanes cannot discharge during its green phases. The paper shows that the problem can be eliminated by reorganizing traffic on all the lanes upstream of an intersection using a mid-block pre-signal. If drivers behave deterministically, the capacity that can be achieved is the same as if there were no left turns. However, if the reorganization is too drastic, it may be counterintuitive to drivers. This can be remedied by reorganizing traffic on just some of the available lanes. It is shown that such partial reorganization still increases capacity significantly, even if drivers behave randomly and only one lane is reorganized. The paper shows how to optimize the design of a pre-signal system for a generic intersection. It also identifies both, the potential benefits of the proposed system for a broad class of intersections, and the domain of application where the benefits are most significant.     

An Adaptive Neuro-Fuzzy Inference System for estimating the number of vehicles for queue management at signalized intersections

Queue management is a valuable but underutilized technique which could be used to minimize the negative impacts of queues during oversaturated traffic conditions. One of the main obstacles of applying queue management techniques along signalized arterials is the unavailability of a robust and sufficiently accurate method for measuring the number of vehicles approaching a signalized intersection. The method based on counting vehicles as they enter and exit a specific detection zone with check-in and check-out detectors is unreliable because of the likely systematic under or over counting and the resulting cumulative errors. This paper describes the application of the Adaptive Neuro-Fuzzy Inference System (ANFIS) in the development of a new fuzzy logic-based approach for estimating the Number of Vehicles in a Detection Zone (NVDZ) by using detector time-occupancy data (instead of detector counts). Microscopic simulation results are used to evaluate the accuracy of the NVDZ estimates. Tests were carried out to determine the transferability of a tuned Fuzzy Inference System (FIS) and to check the sensitivity of the calibrated FIS to detection coverage, the location of the detection zone relative to the signalized (bottleneck) intersection, the length of the detection zone, and different signal timings at the bottleneck intersection. Results show that the NVDZ estimation based on fuzzy logic seems to be a feasible approach. Although the primary objective of developing the NVDZ estimation technique has been queue management, other applications such as ramp metering and incident detection could potentially use the same technique.     

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.     

Simulating pedestrian movements at signalized crosswalks in Hong Kong

This paper presents a new pedestrian simulation (PS) model for signalized crosswalks in Hong Kong. This PS model is capable of estimating the variations of walking speed particularly on the effects of bi-directional pedestrian flows so as to determine the minimum required duration of pedestrian crossing time. Video records taken from the observational surveys at the selected crosswalk in urban area were used to extract the required data for model calibration. It was found that the design walking speed for signalized crosswalks should be varied by the effects of the bi-directional pedestrian flows. It was also interesting to note that the negative impact of the bi-directional flow effects (ranging from uni-directional to bi-directional pedestrian flows) on the chance of pedestrian crossing the crosswalk is increasing from free-flow to at-capacity flow conditions. The new PS model is also validated using an independent data set so as to examine the reliability of the simulation results. The validation results show that the new PS model can provide an accurate evaluation on the changes of walking speed and its standard deviation under different scenarios with particular emphasis on the effects of the bi-directional pedestrian flows. The advancement of this PS model can be applied to assess the effects of each improvement measure and to evaluate the benefits of each scenario in practice.     

Signalized intersections with variable flow rates: II A model for delay estimation

This second part of our work develops a model for delay estimation at intersections whose traffic signal controls are continuously being updated. Generally, these traffic signals are centrally controlled. The foundation for the delay estimation model is based on a queuing theory model called “Preemptive resume discipline for M/G/1 with two priority levels.” This queuing model assumes that two customers arrive at acertain point by a Poisson arrival process, and that one customer has service priority over the second customer. The analogy for the case of intersection control is that the preferred customers are the red lights and the secondary customers are the vehicles. In order to adapt the model to the realistic behavior of vehicle traffic at continuously adjusted signals, components are derived to modify the model. The simulation results of the first part of this work are used to calculate adjustment factors that fairly accurately reproduce the simulated delays. This gives rise to the advantage of using in practice a closed mathematical model, in particular when trying to optimize the operation of signalized intersections at the network level.     

Application of social force model to pedestrian behavior analysis at signalized crosswalk

Limited pedestrian behavior models shed light on the case at signalized crosswalk, where pedestrian behavior is characterized by group or individual evasion with surrounding pedestrians, collision avoidance with conflicting vehicles, and response to signal control and crosswalk boundary. This study fills this gap by developing a microscopic simulation model for pedestrian behavior analysis at signalized intersection. The social force theory has been employed and adjusted for this purpose. The parameters, including measurable and non-measurable ones, are either directly estimated based on observed dataset or indirectly derived by maximum likelihood estimation. Last, the model performance was confirmed in light of individual trajectory comparison between estimation and observation, passing position distribution at several cross-sections, collision avoidance behavior with conflicting vehicles, and lane-formation phenomenon. The simulation results also concluded that the model enables to visually represent pedestrian crossing behavior as in the real world.     

A Methodology for estimating traffic safety improvements at intersections

Intersection accidents represent a significant proportion of overall motor vehicle accidents. More accurate estimates of the actual effectiveness of intersection safety improvements are required. This study develops an improved methodology for post-implementation evaluation of safety countermeasures at intersections. Accidents are random, rarely occurring events. For a given time period, this leads to random fluctuations in accident frequencies, which suggests that statistical analysis employing confidence intervals, rather than point estimates, is required. Two technical problems complicate this treatment of accident occurrence as a random variable. The first problem is that identifying of hazardous locations is generally based on above-average accident frequency during the most recent period(s) for which data is available. The second problem arises from changes in external factors such as traffic volume, motor vehicle safety standards, etc., during the period of analysis, which may also affect traffic safety. A “combined” approach which addresses these technical issues is developed. Empirical Bayesian methodology is combined with regression techniques to derive a more accurate measure of the effect of safety treatments. An important consideration is the derivation of the variance of this measure, so that appropriate confidence intervals may be constructed. The approach is then applied to a sample of locations that underwent treatment by the Massachusetts Department of Public Works (MDPW). We compare our results to those which might be obtained using alternative methodologies that correct for neither or only one of the technical problems. We also illustrate how preliminary conclusions may be drawn regarding the effectiveness of broad categories of treatments, and how individual sites requiring further investigation may be identified.     

Improving noise assessment at intersections by modeling traffic dynamics

Three families of road noise prediction models can be distinguished. Static noise models only consider free-flow constant-speed traffic with uniformly distributed vehicles. Analytic noise models assume that all vehicles are isolated from one another but account for their mean kinematic profile over the network. Micro-simulation noise models relax the hypothesis of no interaction between vehicles and fully capture traffic flow dynamic effects such as queue evolution. This study compares the noise levels obtained by these three methodologies at signalized intersections and roundabouts. It reveals that micro-simulation noise models outperform the other approaches. Particularly, they are able to capture the effects of stochastic transient queues in under-saturated conditions as well as stop-and-go behaviors in oversaturated regime. Accounting for traffic dynamics is also shown to improve predictions of noise variations due to different junction layouts. In this paper, a roundabout is found to induce a 2.5 dB(A) noise reduction compared to a signalized intersection in under-saturated conditions while the acoustic contributions of both kinds of junctions balance in oversaturated regime.     

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.     

Explaining crashes at intersections with red light cameras: A note

This note examines if offsetting driver behavior affects rear end crashes at intersections with red light cameras. It models offsetting driver behavior and estimates simultaneous probit equations to analyze this behavior. It finds that in the city considered the effect of red light cameras on the probability of a rear end crash occurring is very strong and positive, thus suggesting that offsetting behavior is present.     

Red-light cameras at intersections: Estimating preferences using a stated choice model

Red-light cameras placed at intersections have the potential to increase safety, but they are often viewed as an invasion of privacy. Preferences for these cameras were explored using a stated choice model that presents key attributes of camera placements. Stated choice models involve careful experimental design, akin to experimental control in laboratory settings. A variety of design approaches were used, settling on a composition of the choice sets people face in the survey. To illustrate the approach, an internet survey was used with a convenience sample containing a high percentage of college students. The results show that while not the case independently, as the number of cameras and fines for violators are simultaneously increased, the preferences for one particular red light cameras program are likely to improve.     

Analysis of the environmental benefits of a motorcycle idling stop policy at urban intersections

In an attempt to reduce CO₂ emissions from motorized transport, the Taiwanese government introduced an idling stop policy for vehicles in early 2007. This paper seeks to quantify the environmental benefits of the policy based on a stated preference analysis. Motorcyclists were surveyed at urban intersections in Taiwan, to identify the amount of time they would be willing to turn off their engines while waiting at traffic lights (the WTO). A contingent valuation framework based on stated preference questions was designed to determine the WTO. Results obtained from the Spike model showed that the average motorcyclist’s WTO is 82 s. In another analysis, in which other variables were taken into consideration, such as the possibility that the policy will be enacted as legislation, the expected WTO increased to 101 s. In both cases, an idling stop policy would have positive environmental effects, reducing gasoline usage by 1021 L per hour and reducing CO₂ emissions by 0.56 metric tons per hour at the intersection studied during peak periods.     

Statistical characteristics of transitional queue conditions in signalized arterials

The performance of signalized arterials is related to queuing phenomena. The paper investigates the effect of transitional traffic flow conditions imposed by the formation and dissipation of queues. A cross-recurrence quantification analysis combined with Bayesian augmented networks are implemented to reveal the prevailing statistical characteristics of the short-term traffic flow patterns under the effect of transitional queue conditions. Results indicate that transitions between free-flow conditions, critical queue conditions that exceed the detector’s length, as well as the occurrence of spillovers impose a set of prevailing traffic flow patterns with different statistical characteristics with respect to determinism, nonlinearity, non-stationarity and laminarity. The complexity in critical queue conditions is further investigated by introducing two supplementary regions in the critical area before spillover occurrence. Results indicate that the supplementary information on the transitional conditions in the critical area increases the accuracy of the predictive relations between the statistical characteristics of traffic flow evolution and the occurrence of transitions.     

The simple platoon advancement model of its technologies applied to vehicle control at signalised intersections

The Simple Platoon Advancement (SPA) Model describes a conceptual system whose principal objective is to increase the throughput of vehicles at signalised intersections. This is achieved through a novel combination of Intelligent Transport System (ITS) technologies including Automatic Cruise Control, Lane Departure Avoidance, and Collision Avoidance. These are combined in SPA so that vehicles are progressed through signalised intersections under automated control. All of the vehicles in a stationary queue are moved instantly at the start‐of‐green as a closely‐spaced platoon. Dispersion occurs after all vehicles are in motion. Throughput of the SPA model is determined analytically and comparisons are made between the SPA model and a valid representation of current road traffic behaviour. These comparisons show that theoretically a SPA system can progress nearly twice as many vehicles past the stopline as can be seen in today's road network. Other benefits of a conceptual SPA system are improved safety and a reduction in delay per vehicle.