Network Signal Setting Design: Meta-heuristic optimisation methods

This paper aims to investigate the application of meta-heuristic optimisation methods to Network Signal Setting Design. The adopted approaches are (i) three step optimisation, in which first the stage matrix (stage composition and sequence), the green timings at each single junction are optimised, then the node offsets are computed in three successive steps; (ii) two step optimisation, in which the stage matrix is defined at a first step, then the green timings and the node offsets are computed at a second step. In both approaches the stage matrix optimisation is carried out through explicit complete enumeration.In the first approach multi-criteria optimisation is followed for single junction signal setting design (green timings), whilst the coordination (node offsets) is approached through mono-criterion optimisation, as well as for the synchronisation (green timings and offsets) in the second approach.A new traffic flow model mixing CTM and PDM has been applied. This model allows to explicitly represent horizontal queuing phenomena as well as dispersion along a link. Some meta-heuristic algorithms (i.e. Genetic Algorithms, Hill Climbing and Simulated Annealing) are investigated in order to solve the two problems.The proposed strategies are applied to two different layouts (a two junction arterial vs. a four junction network) and their effectiveness is evaluated by comparing the obtained results with those from benchmark approaches implementing mono-criterion optimisation only.     

Network traffic control based on a mesoscopic dynamic flow model

The paper focuses on Network Traffic Control based on aggregate traffic flow variables, aiming at signal settings which are consistent with within-day traffic flow dynamics. The proposed optimisation strategy is based on two successive steps: the first step refers to each single junction optimisation (green timings), the second to network coordination (offsets). Both of the optimisation problems are solved through meta-heuristic algorithms: the optimisation of green timings is carried out through a multi-criteria Genetic Algorithm whereas offset optimisation is achieved with the mono-criterion Hill Climbing algorithm. To guarantee proper queuing and spillback simulation, an advanced mesoscopic traffic flow model is embedded within the network optimisation method. The adopted mesoscopic traffic flow model also includes link horizontal queue modelling. The results attained through the proposed optimisation framework are compared with those obtained through benchmark tools.     

Optimal operation of displaced left-turn intersections: A lane-based approach

Displaced left-turn (DLT) intersections that resolve the conflict between left-turn and opposing-through movements at the pre-signal are probably the most extensively used innovative intersection designs. The DLT intersection concept can be extended to ten different types according to the location of the left-turn transition area, the number of DLT approaches, and the possible setting of the bypass right-turn lane. This paper presents a generalized lane-based optimization model for the integrated design of DLT intersection types, lane markings, the length of the displaced left-turn lane, and the signal timings. The optimization is formulated as a mixed-integer non-linear program. This program is further transformed to a series of mixed-integer linear programming problems that can be solved by the standard branch-and-bound technique. Results from extensive numerical analyses reveal the effectiveness of the proposed method, as well as the promising property of assisting transportation professionals in the proper selection of DLT intersection types, and the design of geometric layout and signal timings.     

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.     

Operation of signalized diamond interchanges with frontage roads using dynamic reversible lane control

Signalized diamond interchanges (SDI), connecting major highways and surface streets in urban and suburban areas, are probably the most widely used interchange patterns. The limited storage space between the two closely joined intersections coupled with heavy traffic volumes may easily oversaturate the facility and cause spillback problems, especially with the presence of frontage roads. This paper presents an innovative design and operational model for SDI by dynamically reversing certain lanes in the internal link on a regular basis with the deployment of overhead reversible lane control signs. A Binary-Mixed-Integer-Linear-Program (BMILP) is formulated to simultaneously optimize lane markings, dynamic usage of the reversible lane, and signal timings for the new SDI system. Results from extensive numerical analyses reveal the promising property of the proposed design and operational model in expanding capacity and reducing congestion at the SDI with frontage roads.     

Bus Priority Using pre-signals

The need to provide efficient public transport services in urban areas has led to the implementation of bus priority measures in many congested cities. Much interest has recently centred on priority at signal controlled junctions, including the concept of pre-signals, where traffic signals are installed at or near the end of a with-flow bus lane to provide buses with priority access to the downstream junction. Although a number of pre-signals have now been installed in the U.K., particularly in London, there has been very little published research into their design, operation and optimisation. This paper addresses these points through the development of analytical procedures which allow pre-implementation evaluation of specific categories of pre-signals. The paper initially sets out three categories of pre-signal, which have different operating characteristics, different requirements for signalling and different impacts on capacity and delay. Key issues concerning signalling arrangements for these categories are then discussed, together with a summary of the analytical approach adopted and the assumptions required. Equations are developed to allow appropriate signal timings to be calculated for pre-signalised intersections. Further equations are then developed to enable delays to priority and non-priority traffic, with and without pre-signals, to be estimated with delay being taken here as the key performance criterion. The paper concludes with three application examples illustrating how the equations are applied and the impacts of pre-signals in different situations.The analyses confirm the potential benefits of pre-signals, where these signals apply to non-priority traffic only. Where buses are also subject to a pre-signal, it is shown that disbenefits to buses can often occur, unless bus detectors are used to gain priority signalling.     

Traffic performance of shared lanes at signalized intersections based on cellular automata modeling

Shared lanes at signalized intersections are designed for use by vehicles of different movement directions. Shared lane usage increases the flexibility of assigning lane grouping to accommodate variable traffic volume by direction. However, a shared lane is not always beneficial as it can at time result in blockage that leads to both capacity and safety constraints. This paper establishes a cellular automata model to simulate traffic movements at signalized intersections with shared lanes. Several simulation experiments are carried out both for a single shared lane and for an approach with a shared lane. Simulation of a single shared lane used by straight‐through and right‐turn (as similar to left‐turn in the USA) vehicles suggests that the largest travel delay occurs when traffic volumes (vehicles/lane) of the two movement streams along the shared lane are at about the same level. For a trial lane‐group with a shared lane, when traffic volumes of the two movement streams are quite different, the shared lane usage is not efficient in terms of reduction in traffic delay. The simulation results are able to produce the threshold traffic volume to arrange a shared lane along an approach. Copyright © 2013 John Wiley & Sons, Ltd.     

Combining driver response with cyclical queue optimisation over selected corridors

A case study located in Auckland, New Zealand, was used to quantify the magnitude of savings that may result if the SCATS adaptive traffic control system contains an explicitly combined queue estimation and offset adjustment on a cycle‐by‐cycle basis. A validated SATURN traffic model was used to evaluate five scenarios that represent the short‐run and long‐run efficiency gains resulting from progressive signal adaption with an objective of queue minimisation on the main corridors. Optimisation was applied both area‐wide, and on selected arterial corridors, using a combined split/offset optimisation routine with responsive driver behaviour to achieve a network‐wide and corridor‐specific efficiency gain. The modelling heuristic evaluates the efficiency of both the Equisat and P₀ optimisation policies that would mimic a more progressive adaption of signals under SCATS. Results for the long‐run area‐wide optimisation can produce network‐wide travel‐time savings in the order of 20% and a reduction in transient queues of 28% if only selected corridors are optimised, with a 5% reduction in journey time over an average 8‐min journey. Copyright © 2016 John Wiley & Sons, Ltd.     

Multi-objective signal control of urban junctions – Framework and a London case study

This paper presents an approach to multi-objective signal control using fuzzy logic. The signal control uses fuzzy logic where the membership functions are optimised according to the Bellman–Zadeh principle of fuzzy decision-making. This approach is both practical for the decision-maker and efficient, as it leads directly to a Pareto-optimal solution. Signal control priorities are ultimately a political decision. Therefore the tool developed in this research allows the traffic engineer to balance the objectives easily by setting acceptability and unacceptability thresholds for each objective. Particular attention is given in the example to pedestrian delays. The membership functions of the fuzzy logic are optimised by a genetic algorithm coupled to the VISSIM microscopic traffic simulator. The concept is illustrated with a case study of the Marylebone Road–Baker Street intersection in London at which pedestrians as well as vehicle flows are high. The results prove the feasibility of the framework and show the vehicle delays for a more pedestrian friendly signal control strategy.     

Modeling speed-flow relationship and merging behavior in work zone merging areas

This paper aims to investigate the speed-flow relationship and drivers’ merging behavior in work zone merging areas. It first proposes lane-based speed-flow models, incorporating traffic conflicts among the lanes. It proceeds to develop a desired merging location model determining where drivers start to consider merging and a binary logit model that is applied to estimate the probabilities that drivers will merge into current adjacent gaps. A merging distance model is also proposed to find the 85th percentile of the merging distance. Finally, real work zone traffic data in Singapore are used to calibrate and evaluate the developed models. The findings show that the speed-flow relationship in the through lane is affected by the merge lane traffic under uncongested circumstances. Satisfactory results indicate that the merging behavioral models can competently predict drivers’ merging behavior and that the merging distance model could provide accurate information for traffic engineers to calculate the merge lane length.     

Integrated optimization of transit priority operation at isolated intersections: A person-capacity-based approach

In this paper, a person-capacity-based optimization method for the integrated design of lane markings, exclusive bus lanes, and passive bus priority signal settings for isolated intersections is developed. Two traffic modes, passenger cars and buses, have been considered in a unified framework. Person capacity maximization has been used as an objective for the integrated optimization method. This problem has been formulated as a Binary Mixed Integer Linear Program (BMILP) that can be solved by a standard branch-and-bound routine. Variables including, allocation of lanes for different passenger car movements (e.g., left turn lanes or right turn lanes), exclusive bus lanes, and passive bus priority signal timings can be optimized simultaneously by the proposed model. A set of constraints have been set up to ensure feasibility and safety of the resulting optimal lane markings and signal settings. Numerical examples and simulation results have been provided to demonstrate the effectiveness of the proposed person-capacity-based optimization method. The results of extensive sensitivity analyses of the bus ratio, bus occupancy, and maximum degree of saturation of exclusive bus lanes have been presented to show the performance and applicable domain of the proposed model under different composition of inputs.     

Traffic signal timing problems with environmental and equity considerations

Traffic signal timings in a road network can not only affect total user travel time and total amount of traffic emissions in the network but also create an inequity problem in terms of the change in travel costs of users traveling between different locations. This paper proposes a multi‐objective bi‐level programming model for design of sustainable and equitable traffic signal timings for a congested signal‐controlled road network. The upper level of the proposed model is a multi‐objective programming problem with an equity constraint that maximizes the reserve capacity of the network and minimizes the total amount of traffic emissions. The lower level is a deterministic network user equilibrium problem that considers the vehicle delays at signalized intersections of the network. To solve the proposed model, an approach for normalizing incommensurable objective functions is presented, and a heuristic solution algorithm that combines a penalty function approach and a simulated annealing method is developed. Two numerical examples are presented to show the effects of reserve capacity improvement and green time proportion on network flow distribution and transportation system performance and the importance of incorporating environmental and equity objectives in the traffic signal timing problems. Copyright © 2013 John Wiley & Sons, Ltd.     

Lane-based real-time queue length estimation using license plate recognition data

License plate recognition (LPR) data are emerging data sources that provide rich information in estimating the traffic conditions of urban arterials. While large-scale LPR system is not common in US, last few years have seen rapid developments and implementations in many other parts of world (e.g. China, Thailand and Middle East). Due to privacy issues, LPR data are seldom available to research communities. However, when available, this data source can be valuable in estimating real-time operational metrics in transportation systems. This paper proposes a lane-based real-time queue length estimation model using the license plate recognition (LPR) data. In the model, an interpolation method based on Gaussian process is developed to reconstruct the equivalent cumulative arrival–departure curve for each lane. The missing information for unrecognized or unmatched vehicles is obtained from the reconstructed arrival curve. With the complete arrival and departure information, a car-following based simulation scheme is applied to estimate the real-time queue length for each lane. The proposed model is validated using ground truth information of the maximum queue lengths from the city of Langfang in China. The results show that the model can capture the variations in queue lengths in the ground truth data, and the maximum queue length for each signal cycle can be estimated with a reasonable accuracy. The estimated queue length information using the proposed model can serve as a useful performance metric for various real-time traffic control applications.     

Increase of metro line capacity by optimisation of track circuit length and location: In a distance to go system

The signalling system affects the type of service that can be provided on any particular railway line. The aims set when it comes to designing these systems to operate a railway line are: to ensure safety of operation and to ensure flexible and efficient running. When building a line capacity optimisation algorithm, it must reach a compromise solution between two parameters: minimise the interval between trains and keep journey time as low as possible. This paper aims to describe the algorithm developed between METRO DE MADRID and CITEF (Railway Technology Research Centre of the Universidad Politécnica de Madrid – UPM) that allows the capacity of an underground line equipped with ATP Distance To Go systems to be studied and optimised. This algorithm facilitates the tasks of signalling design and optimisation. Copyright © 2010 John Wiley & Sons, Ltd.     

The optimization of lane assignment and signal timing at the tandem intersection with pre‐signal

This paper presents an integrated model for optimizing lane assignment and signal timing at tandem intersection, which is introduced recently. The pre‐signal is utilized in the tandem intersection to reorganize the traffic flow; hence, the vehicles, regardless of whether left‐turns or through vehicles, can be discharged in all the lanes. However, the previous work does not consider the extra traffic disruption and the associated delay caused by the additional pre‐signal. In the paper, the extra delay aroused by the coordination is incorporated in a lane assignment and signal timing optimization model, and the problem is converted into a mixed‐integer non‐linear programming. A feasible directions method is hence introduced to solve the mixed‐integer non‐linear programming. The result of the optimization shows that the performance of the tandem intersection is improved and the average delay is minimized. The comparison between the tandem and the conventional configuration is presented, and the results verify that the former shows better performance than the latter. In addition, the optimal sequence corresponding to the turning proportion and the optimal lane assignment at the upstream approach of the pre‐signal are presented. Furthermore, if the number of lanes is equal in all arms, the paper proves that the average delay will be reduced if lane assignment is proportional to the turning proportion and the vehicles with low proportion are discharged in advance. Copyright © 2013 John Wiley & Sons, Ltd.     

New approach for developing warrants of protected left-turn phase at signalized intersections

The research embodied in this paper presents a new approach for the development of guidelines for the installation of a protected left-turn phase at signalized intersections when permissive-only left-turn operation is present. This approach is based on maintaining intersection traffic operation at optimum efficiency. Three analyses were presented and discussed and they involved the use of the new approach on some hypothetical basic scenarios at a four-legged intersection with single lane in each approach. The first scenario involved exclusive left-turn lane operation while the other two scenarios involved shared-lane operation. Exhaustive signal optimization analyses were conducted using a signal optimization software package called “Signal Expert”. Regression models were developed from optimization results that allow the analyst to make the decision on protected left-turn phase installation using the basic input data of signal timing design without the need to perform field measurements. The regression results showed that the transition from permissive to protected/permissive left-turn operation, based on system optimization, is mainly a function of traffic conditions and that this transition (interface) is predictable. The results also suggested that these warrants are of reasonable accuracy when compared with those in the current practice.     

An online speed profile generation approach for efficient airport ground movement

The precise guidance and control of taxiing aircraft based on four-dimensional trajectories (4DTs) has been recognised as a promising means to ensure safe and efficient airport ground movement in the context of ever growing air traffic demand. In this paper, a systematic approach for online speed profile generation is proposed. The aim is to generate fuel-efficient speed profiles respecting the timing constraints imposed by routing and scheduling, which ensures conflict-free movement of aircraft in the planning stage. The problem is first formulated as a nonlinear optimisation model, which uses a more flexible edge-based speed profile definition. A decomposed solution approach (following the framework of matheuristic) is then proposed to generate feasible speed profiles in real time. The decomposed solution approach reduces the nonlinear optimisation model into three tractable constituent problems. The control point arrival time allocation problem is solved using linear programming. The control point speed allocation problem is solved using particle swarm optimisation. And the complete speed profile between control points is determined using enumeration. Finally, improved speed profiles are generated through further optimisation upon the feasible speed profiles. The effectiveness and advantages of the proposed approach are validated using datasets of real-world airports.     

Establishing speed–flow–density relationships for exclusive motorcycle lanes

Abstract

The motorcycle is a popular mode of transport in Malaysia and developing Asian countries, but its significant representation in the traffic mix results in high rates of motorcycle accidents. As a result, the Malaysian Government decided to segregate motorcycle traffic along its new federal roads as an engineering approach to reduce accidents. However, traffic engineers needed to know the maximum traffic a motorcycle lane could accommodate. Despite substantial literature related to speed–flow–density relationships and capacities of various transport facilities, there is a knowledge gap regarding motorcycle lanes. This paper establishes motorcycle speed–flow–density relationships and capacities of exclusive motorcycle lanes in Malaysia. Observations of motorcycle flows and speeds were conducted along existing and experimental motorcycle lanes. Motorcycle speed–density data were aggregated and plotted for two types of observable motorcycle riding behaviour patterns that were influenced by the widths of a motorcycle lane: the headway pattern (lane width ≤ 1.7 m) and the space pattern (lane width > 1.7 m). For both riding patterns, regression analysis of motorcycle speed–density data best fits the logarithmic model and consequently the motorcycle flow–density and speed–flow models are derived. Motorcycle lane capacities for headway and space riding patterns are estimated as 3300 mc/hr/lane and 2200 mc/hr/m, respectively.     

An investigation of multiplier effects generated by implementing queue jump lanes at multiple intersections

This paper investigates the combination effects of queue jump lanes (QJLs) on signalised arterials to establish if a multiplier effect exists, that is, the benefit from providing QJLs at multiple intersections is higher than the sum of benefits from providing them individually at each of those intersections. To explore the combination effects on bus delay and total person delay, a delay estimation model is developed using kinematic wave theory, kinematic equations and Monte Carlo simulation. In addition, to investigate the combination effects in offset settings optimised for bus delay or total person delay, offset optimisation models are proposed. Validation results using traffic micro‐simulation indicate the effectiveness and computational efficiency of the proposed models. Results of a modelling test bed suggest that providing QJLs at multiple intersections can create a multiplier effect on one‐directional bus delay savings with signal offsets that provide bus progression. Furthermore, optimising offsets to minimise bus delay tends to create a multiplier effect on one‐directional bus delay savings, particularly when variations in dwell times are not high. The reason for the multiplier effect may be that providing QJLs reduces variations in bus travel times, which makes signal coordination for buses perform more effectively. From a policy perspective, the existence of a multiplier effect suggests that a corridor‐wide scale implementation of QJLs has considerable merit. Copyright © 2016 John Wiley & Sons, Ltd.     

Modelling dual carriageway lane changing using neural networks

Neural networks offer a potential alternative method of modelling driver behaviour within road traffic systems. This paper explores the application of neural networks to modelling the lane-changing decisions of drivers on dual carriageways. Two approaches are considered. The first, preliminary approach uses a prediction type of neural network with a single hidden layer and the back propagation learning algorithm to model the behaviour of an individual driver. A series of consecutive time-scan traffic patterns, which describe the driver's environment and changes over time as the selected vehicle travels along a link, are input to the neural network, which then predicts the new lane and position of the vehicle. Training data are collected from a human subject using an interactive driving simulation. The trained neural network successfully exhibited the rudiments of driving behaviour in terms of lane and speed changes. A major disadvantage of this approach was the difficulty in recording real-life data, which are required to train the neural network, for individual drivers. The second approach concentrates specifically on lane changing and makes use of a learning vector quantization classification type of neural network. Input to the neural network still consists primarily of time-scan traffic patterns, but the format is changed to facilitate the possibility of data acquisition using image processing. The neural network output classifies the input data by determining the new lane for the vehicle concerned. Performance in both testing and training was very good for data generated by the rule-based driver-decision model of a microscopic simulation. Performance in testing was less satisfactory for data taken directly from a road and highlighted the need for extensive data sets for successful training.