Traffic Signal Settings Research Articles

Fast move: A prioritized vehicle rerouting strategy in smart city

Efficient and dynamic traffic management is an integral part of any smart city. Finding the shortest route considering congestion in real-time and managing traffic signals determine the efficiency of overall traffic flow. Route planning within a dynamic traffic environment remains an open challenge due to some essential unaddressed issues. Specially, considering priority vehicles to provide better traffic flow. For example, the routes of the vehicles need to be derived in such a way that higher priority vehicles like ambulances, police cars, etc. are provided efficient routes and green signals as per their given priority. To establish the solution we need to consider two factors. Vehicle rerouting to obtain shorter path and traffic signal optimization for lesser waiting time by a vehicle on a traffic signal. Existing works don't consider both factors in their work and tried to solve the issue reactively; upon request for clearance by a vehicle on a particular traffic signal. The proposed work seems to be a proactive approach that considers both factors. In this work, a dynamic real-time traffic environment with prioritized vehicles is modeled as a bi-level optimization problem. The solution ensures that the routes are offered to the vehicles in a way such that the unit travel time of a vehicle with higher priority must be less compared to vehicles with lesser priority. In addition, the traffic signal settings are optimized in a coordinated way to achieve the above-mentioned goal. Rigorous experimentation is done for validation of the proposed solution. Several traffic situations consisting of inherent dynamism are simulated through SUMO and the experimental findings substantiate our claims in terms of various traffic metrics.

Ecology based network traffic control: A bee colony optimization approach

The majority of fuel consumed in traffic on urban arterials is related to driving in congested traffic, characterized by frequent speed fluctuations and stops at signalized intersections. A range of traffic control strategies was suggested in the past to decrease fuel consumption and emissions in urban networks. The research presented in this study aims to fill the gap in the existing knowledge by proposing a novel combination of an ecology-based performance index and an evolutionary method for optimization of traffic signal settings. An optimization problem is defined to find the best values for traffic light control parameters on the street network. The ecology-based performance index is used as the criteria for optimization. The defined problem is solved by the Bee Colony Optimization (BCO) technique. The geometry of the subject network has been inserted into a Vissim model calibrated by using relevant traffic demand and field-measured travel times. The Vissim has been used as the tool for the evaluation of the proposed BCO, TRANSYT-7F (T7F) and field signal timing plans. The methodology is tested on the field-real-like network of the City of Kragujevac, Serbia. Results show that in the case of the overall network ecology performance index, BCO makes a decrease of 11.95 % and 8.47% compared to the signal timings from field and T7F, respectively.

Cooperation in the jaywalking dilemma of a road public good due to points guidance

Jaywalking is a dangerous illegal crossing behavior, which is common but difficult to govern. If road is a kind of public goods, jaywalking can be regarded as a completely uncooperative behavior in the game of the public goods. Jaywalking is a relatively broad concept, which includes both the behaviors of pedestrians running a red light at the crosswalks and the behaviors of pedestrians directly crossing the road regardless of the traffic rules outside the crosswalks. At the same time, the traffic signal settings in the road network include both the signal lights at the intersections and the signal lights in the mid-roadways. The jaywalking behavior outside the crosswalks in the mid-roadways may be more common and difficult to govern due to the lack of management. Therefore, this study aims at the governance of jaywalking behaviors outside the crosswalks in the mid-roadways. Clearly, time pressure has a huge impact on crossing decision-making processes of pedestrians, and even causes pedestrians to fall into a jaywalking dilemma. The points decision-making guidance mechanism (PDGM) established by us is proposed based on a crossing decision-making model and a points guidance system in this problem-oriented context, which takes time pressure as an important factor. The points rules that the points guidance system relies on mainly apply the Elo algorithm to realize the automatic update of the points. The decision-making processes of pedestrians crossing the road can be positively influenced by the PDGM, which adopts a multi-factor crossing decision-making model. Since our PDGM is an innovative soft strategy based on the development of future intelligent transportation systems, which has not yet been established, so the introduction of a simulation modeling method is very necessary. In particular, this paper establishes an agent-based model to describe the effects of various aspects of the PGDM, and further verifies its effectiveness and feasibility with quantitative methods. The PDGM is beneficial to reduce jaywalking behaviors of pedestrians and effectively promote cooperation between pedestrians and traffic rules. The establishment of the PDGM has been proved to be feasible and effective, which can significantly promote legal crossing and improve the level of crossing safety without affecting the operating efficiency of vehicles by a simulation modeling method. The PDGM, which achieves a good performance, can be pioneered and applied to induce pedestrians to cross the road cooperatively and legally. What's more, the PDGM has been proved to be effective and has great potential to be applied to more traffic scenarios. In summary, it is conducive to urban traffic road more efficient and safer through the study of the points guidance mechanism for pedestrians.

ESTIMATION METHOD OF LEFT TURN LANE CAPACITY UNDER THE INFLUENCE OF PEDESTRIANS AND CROSSWALK LAYOUT AT SIGNALIZED CROSSWALKS

The left turn lane capacity is highly influenced by the presence of pedestrians under shared signal phasing. Pedestrian crossing time can be highly influenced by pedestrian platoon maneuver under the influence of traffic signal settings, crosswalk length and bidirectional interactions of pedestrian, due to that left turning vehicles movement may be significantly affected. However, existing capacity estimation methods of left turn lanes did not consider those factors. In addition, the influence of crosswalk layout did not properly consider in the existing methods and researches. This study aims to propose a method to estimate the left turn lane capacity, considering the characteristics of crossing pedestrians and crosswalk layout variations. Waiting pedestrian presence-time is estimated by applying pedestrian presence probability model. In addition, the left turning vehicles discharge flow rate under different crosswalk layout and pedestrian demand condition are investigated and modeled. The left turn lane capacity estimation equation is proposed by characterizing the observed discharge flow rate of left turning vehicles under the influence of crossing pedestrians. It was found that the proposed capacity estimation method can represent the realistic influence of pedestrians and crosswalk layout on the left turn lane capacity at signalized crosswalks.

Traffic signal optimisation in disrupted networks, to improve resilience and sustainability

Transport has a critical role in economic development; an efficient transport system can enable economic growth and enhance social well-being. Road networks, as a part of a transport system, are among the most important lifeline systems. Urban road networks experience serious congestion because of infrequent major disruptions. Due to these disruptions the traffic system performance is reduced and the travel time and emissions in a road network are increased. This paper describes a method for optimising traffic signal settings (i.e. green times and offsets) to assist drivers to avoid partial or complete blockages, to minimise the travel time or carbon dioxide emissions in the case of disruptions in road networks. This method involves applying the Cross-Entropy optimisation method, along with a semi-dynamic approach, to optimise traffic signal control in disrupted road networks. This includes investigating two objective functions: minimising the travel time or minimising carbon dioxide emissions. To achieve this, short-term blockages are tested with different durations (a degradation for 4 minutes up to full hour) and level of capacity reductions (i.e. 0%, 25%, 50%, 75%, and 100%). The results for minimising the travel time, in the Cambridge (UK) network, show that applying signal optimisation reduces the travel time by almost 6% and carbon dioxide emissions by almost 8% for a complete capacity reduction at the most congested node, compared to not optimising the signal settings.

Lane-Based Traffic Signal Simulation and Optimization for Preventing Overflow

In the lane-based signal optimization model, permitted turn directions in the form of lane markings that guide road users to turn at an intersection are optimized with traffic signal settings. The spatial queue requirements of approach lanes should be considered to avoid the overdesigning of the cycle, effective red, and effective green durations. The point-queue system employed in the conventional modeling approach is unrealistic in many practical situations. Overflow conditions cannot be modeled accurately, while vehicle queues are accumulated that block back upstream intersections. In a previous study, a method was developed to manually refine the traffic signal settings by using the results of lane-based optimization. However, the method was inefficient. In the present study, new design constraint sets are proposed to control the effective red and effective green durations, such that traffic enters the road lanes without overflow. The reduced cycle times discharge the accumulated vehicles more frequently. Moreover, queue spillback and residual queues can be avoided. One of the most complicated four-arm intersections in Hong Kong is considered as a case study for demonstration. The existing traffic signal settings are ineffective for controlling the observed traffic demand, and overflow occurs in short lanes. The optimized traffic signal settings applied to the proposed optimization algorithm effectively avoided traffic overflow. The resultant queuing dynamics are simulated using TRANSYT 15 Cell Transmission Model (CTM) to verify the proposed model. The model application is extended to handle the difficult residual queue scenario. It is found that the proposed model can optimize the traffic signal settings in cases where there are short initial residual queues.

Recent developments in traffic flow modeling using macroscopic fundamental diagram

ABSTRACTThis paper presents an overview of the recent developments in traffic flow modelling and analysis using macroscopic fundamental diagram (MFD) as well as their applications. In recent literature, various aggregated traffic models have been proposed and studied to analyse traffic flow while enhancing network efficiency. Many of these studies have focused on models based on MFD that describes the relationship between aggregated flow and aggregated density of transport networks. The analysis of MFD has been carried out based on experimental data collected from sensors and GPS, as well as simulation models. Several factors are found to influence the existence and shape of MFD, including traffic demand, network and signal settings, and route choices. As MFD can well express the traffic dynamics of large urban transport networks, it has been extensively applied to traffic studies, including the development of network-wide control strategies, network partitioning, performance evaluation, and road pricing. This work also presents future extensions and research directions for MFD-based traffic modelling and applications.

Recent developments in traffic flow modelling using macroscopic fundamental diagram

ABSTRACT This paper presents an overview of the recent developments in traffic flow modelling and analysis using macroscopic fundamental diagram (MFD) as well as their applications. In recent literature, various aggregated traffic models have been proposed and studied to analyze traffic flow while enhancing network efficiency. Many of these studies have focused on models based on MFD that describes the relationship between aggregated flow and aggregated density of transport networks. The analysis of MFD has been carried out based on experimental data collected from sensors and GPS, as well as simulation models. Several factors are found to influence the existence and shape of MFD, including traffic demand, network and signal settings, and route choices. As MFD can well express the traffic dynamics of large urban transport networks, it has been extensively applied to traffic studies, including the development of network-wide control strategies, network partitioning, performance evaluation, and road pricing. This work also presents future extensions and research directions for MFD-based traffic modelling and applications.

Delay distribution estimation at a signalized intersection

Previous studies found that delay at signalized intersection accounted for more than one-third of total travel time. Different level of services tends to have different delay probability. An early assumption was made that multimodality occurs because of two traffic states experienced by the traveler; delay and non-delay at the signalized intersection. This study proposed a method to quantify delay distribution at a signalized intersection by analyzing the patterns in the speed time and speed distance profiles when passing two consecutive intersections and redrawing vehicle trajectory generated by ‘second by second’ GPS data. The searching algorithm was developed to search for the times when the vehicle enters and leaves the delay section by checking the ‘second by second’ speed data. To differentiate between the queue, move up and stop and go traffic, the algorithm searches for the idle time (i.e. when the speed less than 3.5 km/h). Along with Sydney Coordinates, Adaptive Traffic Systems (SCATS) degree of saturation and signal settings (green and red time) generating from SCATS systems at upstream loop detectors, a realistic delay probability model also was developed. This model used the General Additive Model for Location, Shape, and Scale (GAMLSS) which allows location, scale and shape parameter of selected distribution as a function of the explanatory variable. Signal settings and SCATS degrees of saturation were used as an explanatory variable. This model enables us to estimate delay experiencing by traveler depending on traffic parameters including traffic flow, signal settings and degree of saturation that are readily available on the site.

Innovative countermeasures for red light running prevention at signalized intersections: A driving simulator study

The change interval, which includes the yellow and all-red times, plays a crucial role in the safety and operation of signalized intersections. During this interval, drivers not only need to decide to stop or go but also have to interact with drivers both in front and behind, trying to avoid conflicting decisions. Red light running and inconsistent stopping behavior may increase the risk for angular and rear-end crashes. This study aims to investigate the effect of different innovative countermeasures on red light running prevention and safe stopping behavior at signalized intersections. Five different conditions were tested inviting sixty-seven volunteers with a valid driving license. The conditions include a default traffic signal setting (control condition), flashing green signal setting (F-green), red LED ground lights integrated with a traffic signal (R-LED), yellow interval countdown variable message sign (C-VMS), and red light running detection camera warning gantry (RW-gantry). Drivers in each condition were exposed to two different situations based on the distance from the stop line. In the first situation, drivers were located in the indecision zone while in the second situation they were located in the likely stopping zone. A series of logistic regression analyses and linear mixed models were conducted to investigate the overall safety effects of the different countermeasures. The probability of red light running (RLR) was significantly reduced for R-LED in both analyses (i.e. in the total sample, and in the sample of crossed vehicles). Moreover, a clearly inconsistent stopping behavior was observed for the flashing green condition. Furthermore, a unit increase in speed (kph) at the onset of yellow interval significantly increases the probability of RLR by 5.3 %.The study showed that R-LED was the most effective solution for improving red light running prevention and encouraging a consistent stopping behavior at the intersection. In conclusion, the R-LED and the RW-gantry treatments are recommended as effective tools to improve safety at signalized intersections.

Fitness landscapes analysis and adaptive algorithms design for traffic lights optimization on SIALAC benchmark

Finding optimal traffic light timings at road intersections is a mandatory step for urban planners wishing to achieve a sustainable mobility in modern cities. Increasing congestion situations constantly require urbanists to enhance traffic fluidity, while limiting pollutant emissions and vehicle consumption to improve inhabitants’ welfare. Various mono or multi-objective optimization methods, such as evolutionary algorithms, fuzzy logic algorithms or even particle swarm optimizations, help to reach optimal traffic signal settings. However, those methods are usually designed to tackle very specific transportation configurations.Here, we introduce an extended version of the sialac benchmark, bringing together several real-world-like study cases with various features related to population, working activities, or traffic light devices. We drive a fitness landscape analysis on these various benchmark instances, which helps to improve the design of optimization algorithms for this class of real-world mobility problems. Thereby, we propose a new adaptive optimization algorithm to tackle each scenario of the benchmark.

Optimization of signalized network configurations using the Lane-based method.

Vehicle movements at signalized intersections should follow the guidance of lane marking arrows. Turns are permitted or banned depending on the existence of lane marking arrows establishing network link connectivity. Lane markings are the interface that joins consecutive upstream and downstream intersections. Traffic flows from origins to destinations across intersections should be governed by lane markings. In this study, conventionally fixed lane markings are relaxed as binary variables to be optimized by maximizing the green bandwidths. The proposed methodology is innovative in that it extends the lane-based design framework to incorporate green band maximization for enhancing traffic signal coordination. Path flows are controlled to satisfy flow conservations and to compile turning flows at intersections. With these turning flows as inputs, lane markings can be optimized together with the coordinated traffic signal settings. Path flows, path travel times, and path choices are evaluated through new linear constraints. For path travel times, cruise times along lanes and total delays at the ends of lanes are evaluated. The non-linear total delays are approximated by the proposed linearized delay function. The model coefficients are calibrated by network data as in a previous study. The problem is formulated as a binary-mixed-integer-linear-program and solved by standard branch-and-bound techniques using a CPLEX solver. To avoid non-linearity in the problem formulation, the bandwidth maximization approach is adopted instead of minimizing the total network delay in the design of the signalized network. A network with four intersections is provided to demonstrate how optimized lane markings can create efficient network link configurations. The numerical results are promising compared with those obtained in previous studies and show that the overall network performance can be improved.

A Single Intersection Cooperative-Competitive Paradigm in Real Time Traffic Signal Settings Based on Floating Car Data

New technologies such as “connected” and “autonomous” vehicles are going to change the future of traffic signal control and management and possibly will introduce new traffic signal systems that will be based on floating car data (FCD). The use of floating car data to regulate traffic signal systems, in real time, has the potential for an increased sustainability of transportation in terms of energy efficiency, traffic safety and environmental issues. However, research has never explored how not “connected” vehicles would benefit by the implementation of such systems. This paper explores the use of floating car data to regulate traffic signal systems in real-time in a single intersection and in terms of cooperative-competitive paradigm between “connected” vehicles and conventional vehicles. In a dedicated laboratory, developed for testing regulation algorithms, results show that “invisible vehicles” for the system (which are not “connected”) in most simulated cases also benefit when real time traffic signal settings based on floating car data are introduced. Moreover, the study estimates the energy and air quality impacts of a single intersection signal regulation by evaluating fuel consumption and pollutant emissions. Specifically, the study demonstrates that significant improvements in air quality are possible with the introduction of FCD regulated traffic signals.

Bandwidth optimization for lane-based traffic signal settings with improved stopping criteria in non-linear TRANSYT delay

While assigning given OD demand flows onto network links, travel times along different routes could be varied depending on respective traffic volumes. To achieve equilibrium, all used routes should have the minimum and identical travel times. Such route travel times are composed by link travel times and end of link delay. Upstream and downstream traffic signals are coordinated through bandwidth maximization. Path flows and path travel times are modeled to be responsive to traffic signal settings to enable attractive path choices. Approximated linear function will be established to linearize the end of link delay in TRANSYT model. The problem is formulated as a Binary-Mixed-Integer-Linear-Program and could be solved by standard branch-and-bound method.

Lane-based optimization for signalized network configuration designs

Lane-based traffic signal design has been developed for designing signal-controlled intersections. Conventional designs take on fixed configurations as exogenous inputs to design traffic signal settings. The proposed study will be an extension to merge geometrical junction arrangement and signal controls together for network configuration designs. Design methodology would be directly extended from existing lane-based design method. New Path flows variables and new flow conservation constraints are required to ensure the users’ input OD flows could be assigned onto network paths through different signal-controlled intersections. This problem is new that involves binary variables and related linear constraints which is formulated as a BMILP. Standard technique could solve the optimum solution. A four-intersection network with two approach lane settings is optimized for demonstration purposes.

Graphical Solution for Arterial Road Traffic Flow Model Considering Spillover

This research proposes a graphical solution to arterial road dynamics simulation. An arterial road consists of channelized and upstream sections. Traffic flow is mixed in the upstream section (U-section) and operates without lateral interaction in the channelized section (C-section). Under over-saturated conditions, C-section spillover occurrence governs the traffic flow dynamics of the entire road. In order to capture the arterial road traffic flow dynamics, the proposed method takes advantage of the following components: 1) a decomposition mechanism that uniforms the analysis of each lane; 2) a red–green pair-based vehicle queue tracking component that describes traffic dynamics both temporally and spatially; and 3) a well-defined converted cumulative curve that is capable of generating a queue solution directly. The graphical method permits arbitrary traffic flow and signal settings input and can easily be automated, as demonstrated in the example.

Multi-Objective Optimization of Traffic Signal Settings for Isolated Intersections Considering Efficiency as well as Safety

Multi-Objective Optimization of Traffic Signal Settings for Isolated Intersections Considering Efficiency as well as Safety

Traffic Signal Optimisation in Disrupted Networks with Re-Routing

Abstract This paper describes a modified bi-level framework to simulate disruptive events in urban road networks with different levels of disruption severity and duration. This framework combines the Cross Entropy method to optimise traffic signals and the quasi-dynamic user equilibrium assignment model embedded in SATURN software package. This enables simulation of short-term closures with less computational effort and running time than fully dynamic models. We have applied this model to the Cambridge (UK) network and demonstrated how the degradation at one node affects the optimal signal settings at that node and nearby nodes. The computational results show that for different disruption severities, as traffic starts to divert to other routes, the optimal traffic signal settings changes, to minimise the travel time.

Modelling the Performance of Signalized Intersections Near Railway Crossings

Railway related pre-emption time, which refers to the time needed to clear a vehicle from the pathway of a train, isa necessary input for appropriate pre-emption traffic signal settings. It is, however, usually left to the judgment of the signal engineer, using assumptions not always based on hard evidence. The research reported here analysed the safety and performance at railway crossings in the vicinity of signalized intersections with the aid of micro traffic simulation modelling. The developed model was calibrated by comparing the time that the last vehicle on the railway tracks to be cleared. A location in Brisbane, Australia, was chosen to apply the proposed methodology. The case study was used to evaluate three settings, which were implemented using fixed signal time; pre-emption with actuated signal; and actuated signal only. The signal logic was developed with the aid of an external signal controller to replicate pre-emption technology. The resultsfrom the simulation model show that the use of the pre-emption benefits safety and driving performance by changing signals dynamically in accordance withconditions related to traffic flow, train frequency and the proportion of heavy goods vehicles.

A robust algorithm to solve the signal setting problem considering different traffic assignment approaches

AbstractIn this paper we extend a stochastic discrete optimization algorithm so as to tackle the signal setting problem. Signalized junctions represent critical points of an urban transportation network, and the efficiency of their traffic signal setting influences the overall network performance. Since road congestion usually takes place at or close to junction areas, an improvement in signal settings contributes to improving travel times, drivers’ comfort, fuel consumption efficiency, pollution and safety. In a traffic network, the signal control strategy affects the travel time on the roads and influences drivers’ route choice behavior. The paper presents an algorithm for signal setting optimization of signalized junctions in a congested road network. The objective function used in this work is a weighted sum of delays caused by the signalized intersections. We propose an iterative procedure to solve the problem by alternately updating signal settings based on fixed flows and traffic assignment based on fixed signal settings. To show the robustness of our method, we consider two different assignment methods: one based on user equilibrium assignment, well established in the literature as well as in practice, and the other based on a platoon simulation model with vehicular flow propagation and spill-back. Our optimization algorithm is also compared with others well known in the literature for this problem. The surrogate method (SM), particle swarm optimization (PSO) and the genetic algorithm (GA) are compared for a combined problem of global optimization of signal settings and traffic assignment (GOSSTA). Numerical experiments on a real test network are reported.