Dynamic vehicular delay comparison between a police-controlled roundabout and a traffic signal

Effects of queues on motorists during rush hours are severe at intersections controlled by roundabouts. Traffic police are frequently used in order to optimize the traffic flow and to control queue length at such intersections. However, the question as to how efficient such system is, compared with traffic signal, is not clear from the dynamic delay point of view. In this study a criterion is being developed based on vehicular delays as the motorist join the queues and cross the stop-line. The adopted method avoids oversimplification of reality and prevents unrealistic assumptions. The data required for the study were mainly collected through video filming technique. The results, for a given set of geometric and traffic characteristics, indicate that both a police-controlled roundabout and a traffic signal act in a similar manner in terms of vehicular delay at a certain critical value. This critical value is considered to be the point of intersection between the curves representing traffic signal and roundabout on a delay–space diagram for the vehicles as they join the tail end of the queue until they cross the stop-line. Beyond the critical value, the effect of delays and buildup of queues at roundabouts will be excessive, compared to traffic signals. Before the critical value the delays at traffic signals are quite high compared to roundabouts. The study will assist the concerned authorities to operate the existing conditions, particularly the roundabouts, more efficiently. It will also be beneficial for the traffic planners and policy makers in making judicious decisions regarding control type at intersections.     

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.     

Estimating traffic volumes for signalized intersections using connected vehicle data

Recently connected vehicle (CV) technology has received significant attention thanks to active pilot deployments supported by the US Department of Transportation (USDOT). At signalized intersections, CVs may serve as mobile sensors, providing opportunities of reducing dependencies on conventional vehicle detectors for signal operation. However, most of the existing studies mainly focus on scenarios that penetration rates of CVs reach certain level, e.g., 25%, which may not be feasible in the near future. How to utilize data from a small number of CVs to improve traffic signal operation remains an open question. In this work, we develop an approach to estimate traffic volume, a key input to many signal optimization algorithms, using GPS trajectory data from CV or navigation devices under low market penetration rates. To estimate traffic volumes, we model vehicle arrivals at signalized intersections as a time-dependent Poisson process, which can account for signal coordination. The estimation problem is formulated as a maximum likelihood problem given multiple observed trajectories from CVs approaching to the intersection. An expectation maximization (EM) procedure is derived to solve the estimation problem. Two case studies were conducted to validate our estimation algorithm. One uses the CV data from the Safety Pilot Model Deployment (SPMD) project, in which around 2800 CVs were deployed in the City of Ann Arbor, MI. The other uses vehicle trajectory data from users of a commercial navigation service in China. Mean absolute percentage error (MAPE) of the estimation is found to be 9–12%, based on benchmark data manually collected and data from loop detectors. Considering the existing scale of CV deployments, the proposed approach could be of significant help to traffic management agencies for evaluating and operating traffic signals, paving the way of using CVs for detector-free signal operation in the future.     

A reverse causal-effect modeling approach for signal control of an oversaturated intersection

A novel approach is presented in which signalized intersections are treated as normal highway bottlenecks for improved computational efficiency. It is unique in two ways. First, it treats the signalized intersections as common freeway bottlenecks by a reversed cause and effect modeling approach. Both traffic arrivals and departures are modeled by smooth continuous functions of time as if there were no interruptions to traffic flows from signals. The use of smooth continuous functions for departure curves instead of commonly used step functions makes it easy to apply differential calculus in optimization and future extension to a system of intersections. Second, a dynamic linear programming (LP) model is then developed to maximize the total vehicular output from the intersection during the entire period of congestion subject to prevailing capacity and other operational constraints. The continuous optimal departure flow rate (the effect) is then converted to signal timing parameters (the cause) that can be readily implemented. Two numerical examples are presented to demonstrate the properties of the proposed algorithm and examine its performance.     

The evaluation of active bus-priority signal routes

In an attempt to provide priority facilities for high occupancy vehicles, many cities have investigated or installed active bus priority signals at selected intersections. This paper describes one such installation at the intersection of Bell Street and Oriel Road in Heidelberg, Victoria, Australia. In particular, it describes the impact of the signals on bus performance levels and on non-priority traffic performance levels. An evaluation is performed taking account of the costs of the installation, the changes in the amount of fuel consumed and the changes in the perceived, budgeted delay of people passing through the intersection. Perceived, budgeted delay is defined so as to take account of the variability of delay and the perception of small delay changes. The evaluation at this site showed that, for various reasons, it was difficult to justify the priority signals at this isolated intersection.The evaluation is then extended to the concept of a route of bus priority signal intersections. A simple model is built to simulate the performance of such a priority route and the evaluation repeated. As a result of using perceived delay as a measure of performance, it is then shown that although the priority intersections along the route may not be individually justifiable, the priority route as a whole may show considerable net benefits. These benefits will occur given that there are greater than a critical number of priority intersections on the route. This critical number will depend on the assumptions made in the priority route model.It is concluded that re-evaluation of bus priority signal intersections along the lines suggested in the paper may yield a number of viable bus priority intersections and bus priority routes which were previously considered to be non-viable.     

Paradoxes of reservation-based intersection controls in traffic networks

Reservation-based intersection control is a revolutionary idea for using connected autonomous vehicle technologies to improve intersection controls. Vehicles individually request permission to follow precise paths through the intersection at specific times from an intersection manager agent. Previous studies have shown that reservations can reduce delays beyond optimized signals in many demand scenarios. The purpose of this paper is to demonstrate that signals can outperform reservations through theoretical and realistic examples. We present two examples that exploit the reservation protocol to prioritize vehicles on local roads over vehicles on arterials, increasing the total vehicle delay. A third theoretical example demonstrates that reservations can encourage selfish route choice leading to arbitrarily large queues. Next, we present two realistic networks taken from metropolitan planning organization data in which reservations perform worse than signals. We conclude with significantly positive results from comparing reservations and signals on the downtown Austin grid network using dynamic traffic assignment. Overall, these results indicate that network-based analyses are needed to detect adverse route choices before traffic signals can be replaced with reservation controls. In asymmetric intersections (e.g. local road-arterial intersections), reservation controls can cause several potential issues. However, in networks with more symmetric intersections such as a downtown grid, reservations have great potential to improve traffic.     

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.     

Analytical model of traffic delays under bus signal preemption: Theory and application

Major emphasis has been placed in recent years on the improvement of the operations of existing transportation facilities, using Transportation Systems Management strategies. Accordingly, preferential treatment of high occupancy vehicles is playing an increasing role in transportation projects. This paper deals with one of these strategies, the priority treatment of buses at signalized intersections. Such treatment is aimed at improving the capacity of intersections. The paper develops an analytical model of delays at signalized intersections under a bus preemption scheme. The analysis is presented for the simplest case, i.e., two intersecting one-way streets. The results suggests that the benefits of bus preemption can be increased by properly adjusting several design parameters such as cycle and phase duration of the preempted phases as well as the non-preempted parameters. The model outlined in this paper is applicable to any situation in which stochastic variation is introduced into the signal cycle as well as to bus preemption. Consequently, other potential applications of the model include the design/analysis of traffic actuated signals, and pedestrian actuated signals.     

Real-time estimation of lane-based queue lengths at isolated signalized junctions

In this study, we develop a real-time estimation approach for lane-based queue lengths. Our aim is to determine the numbers of queued vehicles in each lane, based on detector information at isolated signalized junctions. The challenges involved in this task are to identify whether there is a residual queue at the start time of each cycle and to determine the proportions of lane-to-lane traffic volumes in each lane. Discriminant models are developed based on time occupancy rates and impulse memories, as calculated by the detector and signal information from a set of upstream and downstream detectors. To determine the proportions of total traffic volume in each lane, the downstream arrivals for each cycle are estimated by using the Kalman filter, which is based on upstream arrivals and downstream discharges collected during the previous cycle. Both the computer simulations and the case study of real-world traffic show that the proposed method is robust and accurate for the estimation of lane-based queue lengths in real time under a wide range of traffic conditions. Calibrated discriminant models play a significant role in determining whether there are residual queued vehicles in each lane at the start time of each cycle. In addition, downstream arrivals estimated by the Kalman filter enhance the accuracy of the estimates by minimizing any error terms caused by lane-changing behavior.     

Traffic conflict models to evaluate the safety of signalized intersections at the cycle level

The safety of signalized intersections has often been evaluated at an aggregate level relating collisions to annual traffic volume and the geometric characteristics of the intersection. However, for many safety issues, it is essential to understand how changes in traffic parameters and signal control affect safety at the signal cycle level. This paper develops conflict-based safety performance functions (SPFs) for signalized intersections at the signal cycle level. Traffic video-data was recorded for six signalized intersections located in two cities in Canada. A video analysis procedure is proposed to collect rear-end conflicts and various traffic variables at each signal cycle from the recorded videos. The traffic variables include: traffic volume, maximum queue length, shock wave characteristics (e.g. shock wave speed and shock wave area), and the platoon ratio. The SPFs are developed using the generalized linear models (GLM) approach. The results show that all models have good fit and almost all the explanatory variables are statistically significant leading to better prediction of conflict occurrence beyond what can be expected from the traffic volume only. Furthermore, space-time conflict heat maps are developed to investigate the distribution of the traffic conflicts. The heat maps illustrate graphically the association between rear-end conflicts and various traffic parameters. The developed models can give insight about how changes in the signal cycle design affect the safety of signalized intersections. The overall goal is to use the developed models for the real-time optimization of signalized intersection safety by changing the signal design.     

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.     

Optimization of mixed cycle length traffic signals

Mixed cycle length operation has been recommended for networks where individual intersections process considerably different traffic volumes. The signals to operate at lower or higher cycle lengths are determined heuristically. This paper demonstrates that the use of mixed cycle lengths as given by the heuristic is inferior to operation under a common cycle length. This contradicts findings in earlier studies, and the difference in conclusion is due to the use of updated optimization methodology. A procedure for incorporating the allocation of mixed cycle lengths into the global optimization of all signal timing variables by a genetic algorithm is proposed. The mixed cycle length timing plans obtained from this procedure are an improvement over those determined heuristically. Mixed cycle length operation is found to be of a more limited application than indicated in previous studies. Copyright © 2012 John Wiley & Sons, Ltd.     

A network flow model for lane-based evacuation routing

Most traffic delays in regional evacuations occur at intersections. Lane-based routing is one strategy for reducing these delays. This paper presents a network flow model for identifying optimal lane-based evacuation routing plans in a complex road network. The model is an integer extension of the minimum-cost flow problem. It can be used to generate routing plans that trade total vehicle travel-distance against merging, while preventing traffic crossing-conflicts at intersections. A mixed-integer programming solver is used to derive optimal routing plans for a sample network. Manual capacity analysis and microscopic traffic simulation are used to compare the relative efficiency of the plans. An application is presented for Salt Lake City, Utah.     

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.     

Extensions of theoretical capacity models to account for special conditions

The computational procedures used to analyze two-way stop-controlled intersections were extended in the National Cooperative Highway Research Project 3-46 to account for a number of effects commonly observed at actual unsignalized intersections. This paper presents theoretical extensions that can account for commonly observed phenomena, such as two-stage gap acceptance when median storage is available; right-turn “sneakers” at flared minor-street approaches; non-random arrivals caused by upstream signals; impedance due to pedestrian crossings; and delay to major-street through vehicles using shared left-turn and through lanes. The individual effects are then combined into an analytical framework suitable for inclusion in the Unsignalized Intersections procedures of the 1997 “Highway Capacity Manual”. ©     

A continuous-flow-intersection-lite design and traffic control for oversaturated bottleneck intersections

Oversaturation has become a severe problem for urban intersections, especially the bottleneck intersections that cause queue spillover and network gridlock. Further improvement of oversaturated arterial traffic using traditional mitigation strategies, which aim to improve intersection capacity by merely adjusting signal control parameters, becomes challenging since exiting strategies may (or already) have reached their “theoretical” limits of optimum. Under such circumstance, several novel unconventional intersection designs, including the well-recognized continuous flow intersection (CFI) design, are originated to improve the capacity at bottleneck intersections. However, the requirement of installing extra sub-intersections in a CFI design would increase vehicular stops and, more critically, is unacceptable in tight urban areas with closed spaced intersections. To address these issues, this research proposes a simplified continuous flow intersection (called CFI-Lite) design that is ideal for arterials with short links. It benefits from the CFI concept to enable simultaneous move of left-turn and through traffic at bottleneck intersections, but does not need installation of sub-intersections. Instead, the upstream intersection is utilized to allocate left-turn traffic to the displaced left-turn lane. It is found that the CFI-Lite design performs superiorly to the conventional design and regular CFI design in terms of bottleneck capacity. Pareto capacity improvement for every traffic stream in an arterial system can be achieved under effortless conditions. Case study using data collected at Foothill Blvd in Los Angeles, CA, shows that the new design is beneficial in more than 90% of the 408 studied cycles. The testing also shows that the average improvements of green bandwidths for the synchronized phases are significant.     

Mobility and environment improvement of signalized networks through Vehicle-to-Infrastructure (V2I) communications

Traffic signals, even though crucial for safe operations of busy intersections, are one of the leading causes of travel delays in urban settings, as well as the reason why billions of gallons of fuel are burned, and tons of toxic pollutants released to the atmosphere each year by idling engines. Recent advances in cellular networks and dedicated short-range communications make Vehicle-to-Infrastructure (V2I) communications a reality, as individual cars and traffic signals can now be equipped with communication and computing devices. In this paper, we first presented an integrated simulator with V2I, a car-following model and an emission model to simulate the behavior of vehicles at signalized intersections and calculate travel delays in queues, vehicle emissions, and fuel consumption. We then present a hierarchical green driving strategy based on feedback control to smooth stop-and-go traffic in signalized networks, where signals can disseminate traffic signal information and loop detector data to connected vehicles through V2I communications. In this strategy, the control variable is an individual advisory speed limit for each equipped vehicle, which is calculated from its location, signal settings, and traffic conditions. Finally, we quantify the mobility and environment improvements of the green driving strategy with respect to market penetration rates of equipped vehicles, traffic conditions, communication characteristics, location accuracy, and the car-following model itself, both in isolated and non-isolated intersections. In particular, we demonstrate savings of around 15% in travel delays and around 8% in fuel consumption and greenhouse gas emissions. Different from many existing ecodriving strategies in signalized road networks, where vehicles’ speed profiles are totally controlled, our strategy is hierarchical, since only the speed limit is provided, and vehicles still have to follow their leaders. Such a strategy is crucial for maintaining safety with mixed vehicles.     

Joint optimization of tram timetables and signal timing adjustments at intersections

This paper explores at the planning level the benefits of coordinating tram movements and signal timings at controlled intersections. Although trams may have dedicated travel lanes, they mostly operate in a mixed traffic environment at intersections. To ensure tram progression, pre-set signal timings at intersections are adjusted by activating Transit Signal Priority (TSP) actions, which inevitably add delays to the auto traffic. A mixed integer program is proposed for jointly determining tram schedules for a single tram line and modifying signal timings at major controlled intersections. The objective is to minimize the weighted sum of the total tram travel time and TSP’s negative impacts on other traffic. A real-world case study of Line 5 of the Shenyang Hunnan Modern Tramway shows that by extending the dwell time or link travel time we can significantly reduce the TSP’s negative impacts on the auto traffic while only slightly increasing tram travel times.     

Evaluating effects of traffic and vehicle characteristics on vehicular emissions near traffic intersections

Urban air quality is generally poor at traffic intersections due to variations in vehicles’ speeds as they approach and leave. This paper examines the effect of traffic, vehicle and road characteristics on vehicular emissions with a view to understand a link between emissions and the most likely influencing and measurable characteristics. It demonstrates the relationships of traffic, vehicle and intersection characteristics with vehicular exhaust emissions and reviews the traffic flow and emission models. Most studies have found that vehicular exhaust emissions near traffic intersections are largely dependent on fleet speed, deceleration speed, queuing time in idle mode with a red signal time, acceleration speed, queue length, traffic-flow rate and ambient conditions. The vehicular composition also affects emissions. These parameters can be quantified and incorporated into the emission models. There is no validated methodology to quantify some non-measurable parameters such as driving behaviour, pedestrian activity, and road conditions