Video vehicle detection at signalised junctions: a simulation-based study

Many existing advanced methods of traffic signal control depend on information about approaching traffic provided by inductive loop detectors at particular points in the road. But analysis of images from CCTV cameras can in principle provide more comprehensive information about traffic approaching and passing through junctions, and cameras may be easier to install and maintain than loop detectors, and some systems based on video detection have already been in use for some time. Against this background, computer simulation has been used to explore the potential of existing and immediately foreseeable capability in automatic on-line image analysis to extract information relevant to signal control from images provided by cameras mounted in acceptable positions at signal-controlled junctions. Some consequences of extracting relevant information in different ways were investigated in the context of an existing detailed simulation model of vehicular traffic moving through junctions under traffic-responsive signal control, and the development of one basic and one advanced algorithm for traffic-responsive control. The work was confined as a first step to operation of one very simple signalcontrolled junction. Two techniques for extraction of information from images were modelled - a more ambitious technique based on distinguishing most of the individual vehicles visible to the camera, and a more modest technique requiring only that the presence of vehicles in any part of the image be distinguished from the background scene. In the latter case, statistical modelling was used to estimate the number of vehicles corresponding to any single area of the image that represents vehicles rather than background. At the simple modelled junction, each technique of extraction enabled each of the algorithms for traffic-responsive control of the signals to achieve average delays per vehicle appreciably lower than those given by System D control, and possibly competitive with those that MOVA would give, but comparison with MOVA was beyond the scope of the initial study. These results of simulation indicate that image analysis of CCTV pictures should be able to provide sufficient information in practice for traffic-responsive control that is competitive with existing techniques. Ways in which the work could be taken further were discussed with practitioners, but have not yet been progressed

Signal Phasing Strategies for Intersections with an Exclusive Bicycle Path

Over the past few years in the United States, there has been a gradual increase among many public agencies installing experimental exclusive bicycle traffic signals in conjunction with vehicular traffic signals. These signals, mostly found at intersections with protected two-way bicycle paths, may cause operational inefficiencies if unsatisfactory phasing strategies are used. The source of the issue stems from difficulty in developing a phasing strategy where simultaneous vehicular movement is to not come into conflict with any concurrent bicycle movement, particularly the vehicular right-turn movement adjacent to a bicycle path. Additionally, as a new signal type, there has been a lack of general guidelines on how to develop an efficient strategy that not only accommodate bicycle traffic signals, but also pedestrian signals. The goal of this research was to develop different strategies to accommodate bicycle traffic signals. The strategies are based on a case study intersection where a bicycle signal has been installed and is causing operational inefficiencies. Three strategies was developed for each split and lead-lag phasing using a combination of overlaps, dummy phases, and phase modifiers. Using the simulation software VISSIM, a model was developed based on the case study's intersection roadway geometry and signal timing. Each strategy is then implemented and evaluated for the capacity and delay of the right-turn lane by varying bicycle and pedestrian volumes. Analytical models based on Poisson distribution were developed for the capacity and delay of the right-turn lane and checked with simulation results for validation. The current intersection operation was also evaluated using current traffic volumes, and implementing all three split design strategies.The results from simulation showed low delays and high capacity for the vehicular right-turn lane at low bicycle and pedestrian volumes. Vice versa, higher delay and lower capacity for the vehicular right-turn lane at higher bicycle and pedestrian volumes resulted, which is expected. A reduction of the current operation's right-turn lane average delay was observed with the implementation of all three solutions. And finally, the results from simulation indicate that each strategy will be advantageous at different bicycle and pedestrian demands

Adaptive signal control using approximate dynamic programming

This paper presents a concise summary of a study on adaptive traffic signal controller for real time operation. The adaptive controller is designed to achieve three operational objectives: first, the controller adopts a dual control principle to achieve a balanced influence between immediate cost and long-term cost in operation; second, controller switches signals without referring to a preset plan and is acyclic; third, controller adjusts its parameters online to adapt new environment. Not all of these features are available in existing operational controllers. Although dynamic programming (DP) is the only exact solution for achieving the operational objectives, it is usually impractical for real time operation because of demand in computation and information. To circumvent the difficulties, we use approximate dynamic programming (ADP) in conjunction with online learning techniques. This approach can substantially reduce computational burden by replacing the exact value function of DP with a continuous linear approximation function, which is then updated progressively by online learning techniques. Two online learning techniques, which are reinforcement learning and monotonicity approximation respectively, are investigated. We find in computer simulation that the ADP controller leads to substantial savings in vehicle delays in comparison with optimised fixed-time plans. The implications of this study to traffic control are: the ADP controller meet all of the three operational objectives with competitive results, and can be readily implemented for operations at both isolated intersection and traffic networks; the ADP algorithm is computationally efficient, and the ADP controller is an evolving system that requires minimum human intervention; the ADP technique offers a flexible theoretical framework in which a range of functional forms and learning techniques can be further studied

Hybrid model predictive control for freeway traffic using discrete speed limit signals

HYCON2 Show day - Traffic modeling, Estimation and Control 13/05/2014 GrenobleIn this paper, two hybrid Model Predictive Control (MPC) approaches for freeway traffic control are proposed considering variable speed limits (VSL) as discrete variables as in current real world implementations. These discrete characteristics of the speed limits values and some necessary constraints for the actual operation of VSL are usually underestimated in the literature, so we propose a way to include them using a macroscopic traffic model within an MPC framework. For obtaining discrete signals, the MPC controller has to solve a highly non-linear optimization problem, including mixed-integer variables. Since solving such a problem is complex and difficult to execute in real-time, we propose some methods to obtain reasonable control actions in a limited computation time. The first two methods (-exhaustive and -genetic discretization) consist of first relaxing the discrete constraints for the VSL inputs; and then, based on this continuous solution and using a genetic or an exhaustive algorithm, to find discrete solutions within a distance of the continuous solution that provide a good performance. The second class of methods split the problem in a continuous optimization for the ramp metering signals and in a discrete optimization for speed limits. The speed limits optimization, which is much more time-consuming than the ramp metering one, is solved by a genetic or an exhaustive algorithm in communication with a non-linear solver for the ramp metering. The proposed methods are tested by simulation, showing not only a good performance, but also keeping the computation time reduced.Unión Europea FP7/2007–201

Analyzing the Diverging Diamond Interchange Using Discrete Event Simulation

The diverging diamond interchange (DDI) can improve traffic flow by limiting the number of phases in the traffic signals and improve safety by eliminating left turns. A few instillations of these interchanges have been constructed and there is great potential to construct more. In an effort to develop a methodology to evaluate these interchanges, this paper presents the development of a discrete event simulation model of the diverging diamond interchange (DDI). Specific emphasis is on using simulation to model the DDI, a description of the operation of the simulation model, and using simulation to understand the operation of the DDI. The paper concludes that the use of the simulation package allows for rapid evaluation of the DDI and demonstrates that this interchange design will not work in all locations

17-11 Evaluation of Transit Priority Treatments in Tennessee

Many big cities are progressively implementing transit friendly corridors especially in urban areas where traffic may be increasing at an alarming rate. Over the years, Transit Signal Priority (TSP) has proven to be very effective in creating transit friendly corridors with its ability to improve transit vehicle travel time, serviceability and reliability. TSP as part of Transit Oriented Development (TOD) is associated with great benefits to community liveability including less environmental impacts, reduced traffic congestions, fewer vehicular accidents and shorter travel times among others.This research have therefore analysed the impact of TSP on bus travel times, late bus recovery at bus stop level, delay (on mainline and side street) and Level of Service (LOS) at intersection level on selected corridors and intersections in Nashville Tennessee; to solve the problem of transit vehicle delay as a result of high traffic congestion in Nashville metropolitan areas. This study also developed a flow-delay model to predict delay per vehicle for a lane group under interrupted flow conditions and compared some measure of effectiveness (MOE) before and after TSP. Unconditional green extension and red truncation active priority strategies were developed via Vehicle Actuated Programming (VAP) language which was tied to VISSIM signal controller to execute priority for transit vehicles approaching the traffic signal at 75m away from the stop line. The findings from this study indicated that TSP will recover bus lateness at bus stops 25.21% to 43.1% on the average, improve bus travel time by 5.1% to 10%, increase side street delay by 15.9%, and favour other vehicles using the priority approach by 5.8% and 11.6% in travel time and delay reduction respectively. Findings also indicated that TSP may not affect LOS under low to medium traffic condition but LOS may increase under high traffic condition

Development of a micro-simulation model toevaluate shuttle-lane roadwork operations

This thesis focuses on the development of a micro-simulation model for urban shuttle-lane roadworks. The aim of this research is to study the effectiveness of shuttle-lane roadworks traffic management controls (i.e. operated by temporary traffic signals) on capacity, delays and safety.SIMSUR (SIMulation of Shuttle-lane Urban Roadworks) micro-simulation model is based on car-following and shuttle-lane rules, considers the various decisions undertaken whenapproaching temporary traffic signals at urban shuttle-lane roadworks (i.e. tailgating, crossingthrough amber or even violating the red light). Data from six different sources were collected(from 23 different sites with over 54 hours of traffic data video recordings). This includes data from visited roadworks sites, Individual Vehicle Data (IVD) from UK motorways anddata from typical signalised junctions.Temporary traffic signals operation modes, including Fixed Time (FT) and Vehicle Actuated (VA) signals, have been integrated within the developed micro-simulation model. Thedeveloped model has been verified, calibrated and validated using real traffic data.Various scenarios were tested using the developed simulation model such as the effect of various parameters on system capacity, delays and safety (i.e. site length, HGVs%,directional split, and drivers’ non-compliance with temporary traffic signals). The resultsrevealed that the maximum shuttle-lane roadworks capacity values which could be achieved(using existing temporary traffic signals settings) for two-way flow are 1,860 and 2,060veh/hr for FT and VA signals, respectively. Regression analysis was also carried out usingdifferent factors and could be used in analytical models to provide a more accurate estimationof system capacity compared to existing equations. Using improved signals settings, capacitycould be increased by about 3.5%. Making the assumption that Microwave Vehicle Detector(MVD) could be simulated within the model, various ranges were tested and the optimumrange was found to be 80m (rather than the existing 40m) which could result in an increase insystem capacity of 4.2%. Using speed reduction (i.e. speed hump) in advance of the stop linecould reduce the effect of dilemma zone by reducing the number of vehicles crossing at theonset of amber or violating the red light by about 33%