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.     

An exact modelling of the uniform control traffic delay in undersaturated signalized intersections

The average delay experienced by vehicles at a signalized intersection defines the level of service (LOS) at which the intersection operates. A major challenge in this regard is the ability to accurately estimate all the components underlying the overall control delay, including the uniform, incremental and initial queue delays. This paper tackles this challenging task by proposing a novel exact model of the uniform control delay component with a view to enhancing the accuracy of the existing approximate models, notably, the one reported in the Highway Capacity Manual 2010. Both graphical and analytical proofs are employed to derive exact closed‐form expressions for the uniform control delay at undersaturated signalized intersections. The high degree of accuracy of the proposed models is analysed through extensive simulations to demonstrate their abilities to exactly characterize the performance of real‐life intersections in terms of the resulting vehicle delay. Unlike the existing widely adopted uniform delay models, which tend to overestimate the LOS of real‐life intersections, the delay models introduced in this paper have the merit of exactly capturing such a LOS. Copyright © 2016 John Wiley & Sons, Ltd.     

Signalized intersections with variable flow rates: I analysis and simulation

One of the most common measures of signalized intersection operation is the amount of delay a vehicle incurs while passing through the intersection. Traditional models for estimating vehicle delay at intersections generally assume fixed signal timing and uniform arrival rates for vehicles approaching the intersection. One would expect that highly variable arrival rates would result in much longer delays than uniform arrival rates of the same average magnitude. Furthermore, one might expect that signal timing that is adjusted according to traffic volume would result in lower delay signal when variations in flow warrant such adjustable timing. This paper attempts to test several hypotheses concerning the effects of variable traffic arrival rates and adjusted signal timing through the use of simulation. The simulation results corroborate the hypothesis concerning the effect of varying arrival rates. As the variance of the arrival rate over time increases, the average delay per vehicle also increases. Signal timing adjustments based on traffic appear to decrease delay when flow rates vary greatly. As flow variations stabilize, the benefits of signal adjustments tend to diminish.     

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.     

Pedestrian delay estimation at signalized intersections in developing cities

This paper proposes a pedestrian delay model suitable for signalized intersections in developing cities, on the basis of a field study conducted in Xi’an, China. The field study consisted of two parts: Part I involved only one crosswalk, and the signal cycle was divided into 13 subphases; Part II involved 13 crosswalks, but the signal cycles were only divided into green phases and non-green phases. It was found that pedestrian arrival rates were not uniform throughout cycles; pedestrians arriving during green phases might also receive delays; pedestrian signal non-compliance was so severe that delays were greatly reduced, but non-complying pedestrians might still receive delays; and for pedestrians walking different directions, though the relationships between average delay and arrival subphase were different, the overall average delays were almost the same. On the basis of the field study results, some assumptions are made about the relationship between average pedestrian delay and arrival subphase, and a new model is developed to estimate pedestrian delays at signalized intersections. The model is validated using the field data, and the validation results indicate that in Xi’an the new model provides much more accurate estimation than the existing models.     

Derivation of delays based on improved macroscopic traffic models

Recent improved and rigorous mathematical models describing the formation and dissipation of queues at signalized intersections are employed for deriving delay and effective queue size. Analytical and numerical solutions are presented that are applicable for both isolated and coordinated intersections. Comparisons against results obtained from conventional models reveals significant differences. Further, it is demonstrated that the current practice of calculating delays from input-output analysis results in substantial overestimation of delays. Numerical examples supporting this finding are presented.     

Operational analysis of the contraflow left-turn lane design at signalized intersections in China

The primary objective of the study was to evaluate the impacts of an unconventional left-turn treatment called contraflow left-turn lane (CLL) on the operational performance of left-turn movement at signalized intersections. An analytical model was developed for estimating the capacity of left-turn movement at signalized intersections with the CLL design. The capacity model was calibrated and validated using field data collected at six approaches at five signalized intersections in the city of Handan, China. The results of field data analyses showed that the use of CLL design improved the capacity of left-turn movements. However, the capacity gains with the CLL design were quite stochastic considering the randomness in the arrivals of left-turning vehicles. Analytical delay models were proposed for estimating the delay to left-turning vehicles at intersections with the CLL design. A procedure was also proposed for optimizing the location of the upstream median opening and the green interval of the pre-signal. Simulation analyses were conducted to compare the delay experienced by the left-turning and through vehicles at signalized intersections with the conventional left-turn lane, the CLL and another unconventional left-turn treatment entitled “tandem design”. The results showed that both CLL and tandem designs outperformed conventional left-turn lane design; and the CLL design generated less delay to both the left-turning and through vehicles as compared with the tandem design.     

Review on Theoretical Delay Estimation Model for Signalized Intersections

Traffic delay is an effective index for estimating the performance of a signalized intersection. In this study, we provide a comprehensive review of the theoretical delay estimation model over the last ca. 90 years. For fixed-time signalized intersections, we classified the estimation development process into three stages. Stage 1 covered 1920s–1970s, when approaches based on steady-state theory were derived. These methods obtain accurate predictions with low degrees of saturation, but overestimate the delay with higher saturation and cannot provide reasonable results for oversaturated conditions. To accommodate high saturation, time-dependent models were proposed and improved in Stage 2, 1970s–2000s, using coordination transformation techniques. Progression factors to account for the filtering impact from upstream intersections were also introduced during this period. Due to inaccurate approximation of certain specific traffic conditions, some modified approaches and supplementary terms were derived from 2000 onwards (Stage 3), which facilitate the evolution of the delay estimation method and improved approximation results. Some new techniques, including artificial intelligence algorithms, were also introduced into delay estimation in this era. We also describe theoretical delay measurement methods for actuated control intersections with a similar time line. From our summary of the evolution of theoretical delay models, we highlight some deficiencies and future research directions.     

Real-time estimation of turning movement counts at signalized intersections using signal phase information

A variety of sensor technologies, such as loop detectors, traffic cameras, and radar have been developed for real-time traffic monitoring at intersections most of which are limited to providing link traffic information with few being capable of detecting turning movements. Accurate real-time information on turning movement counts at signalized intersections is a critical requirement for applications such as adaptive traffic signal control. Several attempts have been made in the past to develop algorithms for inferring turning movements at intersections from entry and exit counts; however, the estimation quality of these algorithms varies considerably. This paper introduces a method to improve accuracy and robustness of turning movement estimation at signalized intersections. The new algorithm makes use of signal phase status to minimize the underlying estimation ambiguity. A case study was conducted based on turning movement data obtained from a four-leg signalized intersection to evaluate the performance of the proposed method and compare it with two other existing well-known estimation methods. The results show that the algorithm is accurate, robust and fairly straightforward for real world implementation.     

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.     

台州市信号灯交叉口碳排放测算及优化策略

近年来随着小汽车保有量的不断增多,机动车尾气成为碳排放的主要组成部分。文中以信号灯控制交叉口运行的小汽车为研究对象,通过研究小汽车在交叉口减速、怠速、加速三种工况下车辆的排放特性,将信号灯交叉口小汽车温室气体排放量量化。本文以台州市市府大道-中心大道交叉口为例,通过实地调查该交叉口当前平峰期和高峰期信号灯配时特性、交通运行特性等实际参数,对二氧化碳排放量进行测算,最终得出该交叉口在平峰期和高峰期的二氧化碳小时排放量,为后续该交叉口采取优化策略后在碳排放指标方面的量化效果提供参考依据,同时为台州市信号灯交叉口碳排放量测算提供参考方法。     

Using connected vehicle technology to improve the efficiency of intersections

Information from connected vehicles, such as the position and speed of individual vehicles, can be used to optimize traffic operations at an intersection. This paper proposes such an algorithm for two one-way-streets assuming that only a certain percentage of cars are equipped with this technology. The algorithm enumerates different sequences of cars discharging from the intersection to minimize the objective function. Benefits of platooning (multiple cars consecutively discharging from a queue) and signal flexibility (adaptability to demand) are also considered. The goal is to gain insights about the value (in terms of delay savings) of using connected vehicle technology for intersection control.Simulations are conducted for different total demand values and demand ratios to understand the effects of changing the minimum green time at the signal and the penetration rate of connected cars. Using autonomous vehicle control systems, the signal could rapidly change the direction of priority without relying on the reaction of drivers. However, without this technology a minimum green time is necessary. The results of the simulations show that a minimum green time increases the delay only for the low and balanced demand scenarios. Therefore, the value of using cars with autonomous vehicle control can only be seen at intersections with this kind of demand patterns, and could result in up to 7% decrease in delay. On the other hand, using information from connected vehicles to better adapt the traffic signal has proven to be indeed very valuable. Increases in the penetration rate from 0% up to 60% can significantly reduce the average delay (in low demand scenarios a decrease in delay of up to 60% can be observed). That being said, after a penetration rate of 60%, while the delays continue to decrease, the rate of reduction decreases and the marginal value of information from communication technologies diminishes. Overall, it is observed that connected vehicle technology could significantly improve the operation of traffic at signalized intersections, at least under the proposed algorithm.     

Coordinated transit signal priority supporting transit progression under Connected Vehicle Technology

In this paper, a person-delay-based optimization method is proposed for an intelligent TSP logic that enables bus/signal cooperation and coordination among consecutive signals under the Connected Vehicle environment. This TSP logic, called TSPCV-C, provides a method to secure the mobility benefit generated by the intelligent TSP logic along a corridor so that the bus delay saved at an upstream intersection is not wasted at downstream intersections. The problem is formulated as a Binary Mixed Integer Linear Program (BMILP) which is solved by standard branch-and-bound method. Minimizing per person delay has been adopted as the criterion for the model. The TSPCV-C is also designed to be conditional. That is, TSP is granted only when the bus is behind schedule and the grant of TSP causes no extra total person delay.The logic developed in this research is evaluated using both analytical and microscopic traffic simulation approaches. Both analytical tests and simulation evaluations compared four scenarios: without TSP (NTSP), conventional TSP (CTSP), TSP with Connected Vehicle (TSPCV), and Coordinated TSP with Connected Vehicle (TSPCV-C). The measures of effectiveness used include bus delay and total travel time of all travelers. The performance of TSPCV-C is compared against conventional TSP (CTSP) under four congestion levels and five intersection spacing cases. The results show that the TSPCV-C greatly reduces bus delay at signalized intersection for all congestion levels and spacing cases considered. Although the TSPCV is not as efficient as TSPCV-C, it still demonstrates sizable improvement over CTSP. An analysis on the intersection spacing cases reveals that, as long as the intersections are not too closely spaced, TSPCV can produce a delay reduction up to 59%. Nevertheless, the mechanism of TSPCV-C is recommended for intersections that are spaced less than 0.5 mile away. Simulation based evaluation results show that the TSPCV-C logic reduces the bus delay between 55% and 75% compared to the conventional TSP. The range of improvement corresponding to the four different v/c ratios tested, which are 0.5, 0.7, 0.9 and 1.0, respectively. No statistically significant negative effects are observed except when the v/c ratio equals 1.0.     

Pre-timed control for an under-saturated and over-saturated isolated intersection: a Bee Colony Optimization approach

In this paper we study the problem of determining the optimum cycle and phase lengths for isolated signalized intersections. Calculation of the optimal cycle and green phase lengths is based on the minimization of the average control delay experienced by all vehicles that arrive at the intersection within a given time period. We consider under-saturated as well as over-saturated conditions at isolated intersections. The defined traffic signal timing problem, that belongs to the class of combinatorial optimization problems, is solved using the Bee Colony Optimization (BCO) metaheuristic approach. The BCO is a biologically inspired method that explores collective intelligence applied by honey bees during the nectar collecting process. The numerical experiments performed on some examples show that the proposed approach is competitive with other methods. The obtained results show that the proposed approach is capable of generating high-quality solutions within negligible processing times.     

Using stop bar detector information to determine turning movement proportions in shared lanes

Turning vehicle volumes at signalized intersections are critical inputs for various transportation studies such as level of service, signal timing, and traffic safety analysis. There are various types of detectors installed at signalized intersections for control and operation. These detectors have the potential of producing volume estimates. However, it is quite a challenge to use such detectors for conducting turning movement counts in shared lanes. The purpose of this paper was to provide three methods to estimate turning movement proportions in shared lanes. These methods are characterized as flow characteristics (FC), volume and queue (VQ) length, and network equilibrium (NE). FC and VQ methods are based on the geometry of an intersection and behavior of drivers. The NE method does not depend on these factors and is purely based on detector counts from the study intersection and the downstream intersection. These methods were tested using regression and genetic programming (GP). It was found that the hourly average error ranged between 4 and 27% using linear regression and 1 to 15% using GP. A general conclusion was that the proposed methods have the potential of being applied to locations where appropriate detectors are installed for obtaining the required data. Copyright © 2016 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.     

Optimization of pedestrian phase patterns at signalized intersections: a multi‐objective approach

This paper presents a multi‐objective optimization model and its solution algorithm for optimization of pedestrian phase patterns, including the exclusive pedestrian phase (EPP) and the conventional two‐way crossing (TWC) at an intersection. The proposed model will determine the optimal pedestrian phase pattern and the corresponding signal timings at an intersection to best accommodate both vehicular traffic and pedestrian movements. The proposed model is unique with respect to the following three critical features: (1) proposing an unbiased performance index for comparison of EPP and TWC by explicitly modeling the pedestrian delay under the control of TWC and EPP; (2) developing a multi‐objective model to maximize the utilization of the available green time by vehicular traffic and pedestrian under both EPP or TWC; and (3) designing a genetic algorithm based heuristic algorithm to solve the model. Case study and sensitivity analysis results have shown the promising property of the proposed model to assist traffic practitioners, researchers, and authorities in properly selecting pedestrian phase patterns at signalized intersections. Copyright © 2013 John Wiley & Sons, Ltd.     

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.     

Speed,travel time and delay for intersections and road segments in the Montreal network using cyclist Smartphone GPS data

Very little is known about cyclist speeds and delays at the disaggregate level of each road segment and intersection in an entire city network. Speeds and delays serve as vital information for planning, navigation and routing purposes including how they differ for different times of the day and across road and bicycle facility types, after controlling for other factors. In this work, we explore the use of recent GPS cyclist trip data, from the Mon RésoVélo Smartphone application, to identify different performance measures such as travel time, speed and delay at the level of the entire network of roads and intersections on the island of Montreal. Also, a linear regression model is formulated to identify the geometric design and built environment characteristics affecting cyclist speeds on road segments. Among other results, on average, segment speeds are greater along arterials than on local streets and greater along segments with bicycle infrastructure than those without. Incorporating different measures of cyclist personality in the models revealed that the following characteristics all affect cyclist speeds along segments, each cyclist’s average speed on uphill, downhill and level segments as well as geometric design and built environment characteristics. The model results also identify that the factors that increase cyclist speeds along segments include, segments which have cyclists biking for work or school related purposes, segments used during morning peak and segments which do not have signalized intersections at either end.