In arterial coordination, high traffic volume at large intersections often requires a long cycle length to achieve good two-way progression. This long cycle length, however, often causes excessive delay at some minor intersections where the traffic volume is low on cross streets. To address this issue, this paper describes a multi-objective optimization method to optimize uneven double cycling (UDC) enabled coordination timing plans. The control scheme adopts UDC at some of the minor intersections where a background cycle has two sub-cycles of different lengths. The multi-objective UDC modeling in this paper considers two basic objectives, maximal variable bandwidth and minimal cross street through delay at UDC intersections, to enable the UDC control scheme. The modeling also considers minimal arterial through delay and number of stops at UDC intersections to investigate if additional optimization strategies can improve the modeling results. Four optimization strategies yield four models all of which are a mixed integer quadratic programming (MIQP) problem. Results of numerical experiments and simulation in the case study indicate that maximal bandwidth and minimal cross street through delay at UDC intersections are two conflicting objectives. Minimal arterial through delay and stops at UDC intersections also contradict with each other in the UDC model optimizing all four objectives. Overall, optimizing the additional objectives improves the modeling results in different ways, but additionally minimizing arterial through stops without also minimizing through delay at UDC intersections may not provide satisfactory results.

The traffic congestion in transportation networks is spatially correlated in adjacent roads and can propagate with some finite speed in time and space. Therefore, we proposed a method to quantify the intersection’s importance which reflects the congestion by considering both road network topology and traffic flow characteristics. The priority order in traffic signal timings is the sorting results of intersection’s importance. The proposed method consists of two consecutive algorithms to sort the signalized intersections’ importance in a transportation network. Firstly, the graph connectivity of network is defined based on the shortest path distance and spatial connectivity between intersections. Secondly, a model of importance is developed based on the idea of Sorting Model of Optimization Order (SMOO). The proposed sorting method is applied in a 6 by 8 grid artificial network based on micro-simulation and simulated data. The results show the effectiveness of the proposed method compared with SMOO, saturation method and volume method.

A fundamental objective of traffic signal operations is the development of phasing plans that reduce delays while maintaining a high level of safety. One issue of concern is the treatment of left-turn phasing, which can operate as a protected movement, a permitted movement yielding to conflicting traffic, or a combination protected-permitted movement. Protected-only movements can improve safety of the turning movement, but they can also increase delays and congestion at intersections. Most states use criteria for left-turn phasing selection based on a threshold crash values and do not account for traffic volumes or intersection features that may influence crash frequency. This research leverages conflict points as an indicator of potential safety estimation to assist in the selection of the left-turn phasing and relates them to historical crash records. Prediction models of potential conflicts were developed through microsimulation for 200 existing intersections; hourly volume data resulted in approximately 2,300 hours of observations. The number of left-turn-related conflicts was obtained through SSAM and related to the number of crashes at each intersection. The proposed models offer a simple but realistic approach for determining the boundary conditions that influence safety when left-turn decisions are required. The models can be used to develop nomographs, which practicing traffic engineers can use for left-turn phasing decisions.

Adjusting traffic signal timings is a practical way for agencies to manage urban traffic without the need for significant infrastructure investments. Standard practice in signal timing optimization is to select signal timings that minimize the total control delay experienced at the intersection. However, there are many other possible objectives to consider, some of which may be in conflict with others. The goal of this research is to develop a tool for traffic engineers to optimize signal timings that simultaneously considers the various objectives that might exist. The research proposes the use of a new multi-objective optimization visualization technique to easily quantify and identify significant tradeoffs between objectives using the set of Pareto-optimal solutions that are normally provided by multi-objective optimization (MOO) algorithms. Methods are also proposed to remove redundant or unnecessary objectives that do not have any significant tradeoffs with others. Unfortunately, MOO procedures will still be needed if more than one objective remains, and MOO algorithms do not also provide a single recommended solution. To alleviate this concern, two methods are proposed here to rank the set of Pareto-optimal solutions based on how well they balance between the competing objectives to provide a final recommendation. The methods proposed will allow agencies to obtain signal timings that provide the best tradeoff between competing objectives that are defined for any particular location.

The coordinated-actuated operation mode is a type of signal control where the minor approaches are placed with the detectors to develop actuated phasing while the major movements are coordinated without the use of detection systems. In such a traffic signal control, the unused green time of the non-coordinated phases, resulting from gap-out or phase skip, are transferred to the coordinated phases. Considering this concept leads us to propose a cost-effective approach for generating a new timing plan in which the green splits of non-coordinated phases are multiplied by a factor greater than one. In the meantime, the amount of green time added to the non-coordinated phases is subtracted from the coordinated phases to keep the cycle length constant. Thus, if the traffic demand on the side streets exceeds the expected traffic flow, the added time in the non-coordinated phase enables the non-coordinated phases to accommodate the additional traffic demand. A regression analysis is implemented so as to identify the optimal value of the mentioned factor, called Actuated Factor (ActF). The response variable is the average delay reduction (seconds/vehicle) of the simulation runs under the proposed signal timing plan compared to the simulation runs under the basic timing plan, obtained through the macroscopic signal optimization tools. External traffic movements, left-turn percentage, and ActF are the explanatory variables in the model. Results reveal that the ActF is the only significant variable with the optimal value of 1.15 that is applicable for a wide range of traffic volumes. 

The tandem intersection is an unconventional signalized intersection that has the potential to improve the capacity of intersections. To enhance tandem intersection performance, the vehicular delay models were first established based on the analysis of special traffic flow characteristics (braking and starting-up twice) for three phase plans. The average error of the proposed delay model was found to be 6.54%. On this basis, the optimal-cycle-length model was established with the objective of minimizing vehicular delay. This model was further simplified by using data fitting for various numbers of arms in tandem strategy conditions. The accuracy of the proposed optimal-cycle-length model was then verified and compared with those of the existing models. A case study was used to verify the suitability of application of the proposed model. The results show that the accuracy of the proposed optimal-cycle-length model is higher than those of the Webster and Highway Capacity Manual cycle length model by 34.56% and 14.53%, respectively. A short cycle length is recommended for the tandem intersection, and it was found that a 35.59% reduction in delay could be achieved for the tested tandem intersection as compared with that of the original signal timing.

High crash rate is a major concern for traffic signal operation during nighttime, with speeding as one of the main causing factors. For nighttime signal operation, existing practice mainly includes red/red flashing and yellow/red flashing operation. However, neither operation is satisfactory, as the former operation leads to large delay, while the latter leads to high crash rates. Considering such, many traffic management agencies are switching to regular traffic signal operation. However, existing signal optimization models primarily focus on efficiency without consideration of safety. To fill in this gap, this paper proposes a new signal optimization program, namely SAFEBAND, for signal operation during nighttime. Built upon the classical MAXBAND model, the proposed model aims to reduce vehicle speeding while ensuring certain level of progression for nighttime traffic. The difference between SAFEBAND and MAXBAND is analyzed in the paper. A case study is conducted to illustrate and test the proposed model, based on real-world data collected from the Safety Pilot Model Deployment project, the world’s first large-scale connected vehicle deployment project. Simulation shows that the proposed model is effective in reducing vehicle speeding. Trade-off between safety and efficiency is also analyzed.

Controlling speed on urban arterials is important for safety; however, conventional traffic calming techniques cannot usually be applied on arterials, and many jurisdictions prohibit automated speed enforcement. Moreover, unlike unidirectional arterials, bidirectional arterials with short intersection spacing are not amenable to green waves that can remove the incentive to speed. This research explores the ways that coordinated traffic signal control creates – or limits – speeding opportunities on bidirectional arterials. Two measures of speeding opportunity are proposed: number of unconstrained vehicles, meaning vehicles arriving at a stopline on green and with no vehicle less than 5 s ahead of them, and number of speeders in a traffic microsimulation in which 20 percent of the vehicles have been assigned a desired speed in the “speeding” range. Theoretical analysis, confirmed by two case studies, show how speeding opportunities are related to degree of saturation, cycle length, specified progression speed (as in input to signal timing software), intersection spacing, and degree of recall. The important role of clusters of intersections with near-simultaneous greens, a byproduct of bi-directional coordination with short intersection spacing, is examined, and large clusters are shown to create a strong speeding incentive. Case studies show that it is sometimes possible to substantially reduce speeding opportunities with little or no increase in vehicular delay by lowering cycle length, lowering progression speed, and reducing the size of coordination zones. At the same time, it is shown that small reductions in progression speed can have no impact at all.

Person-based traffic signal timing optimization frameworks have recently been proposed to minimize total passenger delays experienced at an intersection. These frameworks implicitly prioritize transit vehicle movements over car movements due to their higher passenger occupancies while considering conflicts that might exist between transit vehicles on conflicting approaches. However, previous analytical approaches to person-based signal timing optimization consider only fixed phase sequences, which limits their flexibility. This paper extends the existing algorithms to consider phase rotations in which phase sequences may change within a cycle. The phase rotation is accommodated using an enumeration approach that is possible due to the algorithm’s computational efficiency. The proposed strategies are tested using numerical simulations of an intersection in State College, PA. The results reveal phase rotation reduces total passenger delays significantly at a high bus flow of 80 buses per hour. These reduced passenger delays are obtained by significantly reducing bus passenger delay in favor of car passenger delays. The benefits of phase rotation are highest when applied to signals with fixed cycle lengths and diminish as the cycle length is allowed to vary. This suggests that the benefits of phase rotation are not added with the benefits of flexible cycle lengths. Furthermore, the simulation tests reveal that phase rotation works best when bus flows at the intersection are higher.

Currently, arterial traffic signals adjacent to freeway on-ramps operate independent of freeway on-ramp metering. During the peak periods, the traffic signals employ long signal cycles to maximize the intersection capacity. This approach often results in long platoons of freeway-bound traffic advancing toward the on-ramp in a short duration, which quickly fills up the on-ramp and causes spillback on the surface streets. Queue override is typically employed to prevent the queue spillback by suspending ramp metering or relaxing the metering rates. Unfortunately, this reverses the objective of on-ramp metering, which is to prevent capacity drop at freeway merge bottlenecks.

Significant benefits can be realized by integrating arterial signal timing with the adjacent ramp metering system. A signal control strategy was developed and evaluated in this study. The algorithm takes available on-ramp storage and freeway ramp metering rate into account and dynamically adjusts the cycle length to prevent on-ramp queue spillback and activation of queue override. The proposed algorithm was tested through simulation and the results show that the proposed strategy reduces the freeway, arterial, and system-wide delay, at a modest penalty on on-ramp bound traffic.

Most progression band optimization methods are focused on providing uninterrupted flow along arterial streets. For arterials with significant traffic streams joining and leaving from side streets, these approaches often generate poor traffic signal control performance. To address this deficiency, an Origin Destination (OD) information based progression band optimization model, OD-BAND, was formulated to coordinate signals for arterials with major side-street traffic streams. This paper aims to further extend the OD-BAND model to address the O-D based traffic signal coordination problem in multi-arterial grid networks.  The extended model is able to create separate progression bands for each major OD stream in the network. In this expanded model, individual arterials are connected with loop constraints to ensure that offsets derived via different paths for a particular intersection are equal.  The new model is formulated as a mixed integer linear program that maximizes the sum of each major OD stream’s progression bandwidth. OD-NETBAND can optimize simultaneously cycle length, offsets and phase sequences for the entire network. Performance of the new model is evaluated with AIMSUN microscopic simulation and is compared to MAXBAND-86 and Synchro results.

Setting traffic lights at intersections reasonably can improve the traffic efficiency, improve traffic safety and reduce traffic pollution. The environmental impact control is one of the most important problems in urban areas. However, the existing signal warrant studies are rarely considering the noise pollution. Hence, this paper presents a framework of the intersection traffic signal warrant considering traffic noise control with the critical flow bi-level planning model. In order to establish the bi-level planning model, the traffic efficiency model and the simplified noise model are given. The field experiments were conducted at two intersections in Harbin, China. The results showed that the bi-level planning model was applicable in the practice and we can ensure the signal warrant through the critical traffic flow curve. This paper may give guidance for signal setting and traffic control, and establish a theoretical basis for traffic signal warrant considering efficiency and noise issues, which gives a reference to the future study.

 Keywords: Intersection traffic noise, Traffic signal warrant, Critical flow, Traffic Efficiency, Bi-level planning

Emergency vehicles (EVs) are provided priority at traffic signals via emergency vehicle preemption (EVP) mechanisms. EVP interrupts the normal operation of traffic signals along the EV path, one at a time, causing each intersection to fall out of coordination. This procedure can cause major increase in overall traffic delay. New GPS-based preemption systems are currently emerging and being piloted at several locations in the US. There is a need to study EVP issues to determine: (1) the conditions under which one GPS-systems are recommended for use and (2) the optimal configuration of the selected system. There is currently no existing simulation/optimization software that can meet this need. Starting from the functional requirements, the research team developed a Broad Area-wide & Distance-wise Agent-based Signal-optimization System (BADASS) to assist engineers in selecting and optimizing signal timing in conjunction with optimized EVP system parameters. BADASS produces total delay time and reliability-related output (histograms of travel times). In addition, the research team developed a dynamic model based on the BADASS output using experimental design and regression models and showed potential savings in travel time of about 15%. Saving in delay can be much higher, depending on the pre-existing timing plans and PE configuration parameters.

Various traffic sensors are available for traffic data collection, which are mostly based on measuring the variation in characteristics such as pressure, sound, vibration, magnetic flux, frequency of waves such as radar or infrared, background characteristics in a video etc. Out of all the available sensors, inductive loop detectors (ILD), that measure the change in inductance of a conductor due to the presence of vehicles, have been widely deployed due to their reliable performance and low cost. The main components of ILDs include the loops buried below the road surface, the connecting cables from the loops to the roadside pull box/Data Acquisition System (DAQ) or detector cards, connection from the pull box to the control unit that process the signals to traffic data and some communication mechanism to transmit the data to the remote traffic centers. At present, for lane by lane detection, the ILDs require separate connecting cables for each loop (each lane) and separate DAQs or detector channels to process them. This gets problematic with limited conduit and cabinet space. In most cases, transportation agencies use loops connected in series to avoid these constraints, in which case the lane-by-lane information gets lost. However, research has shown that lane by lane detection can lead to safer and more efficient operations at signalized intersections. In order to ease the application of lane-by-lane detection, the current study proposes a solution by reducing the requirements for conduits space and DAQs. The study uses electronic circuit modification to convert the existing serially connected loops to do lane by lane detection. The paper also proposes an improved loop design, for future installations, to enable vehicle classification, wrong way detection and lane by lane detection for serially connected configuration.