Optimal subwork zone operational strategy for short‐term work zone projects in four‐lane two‐way freeways

Roadside trees in Singapore are regularly trimmed for the purpose of traffic safety and roadside tree‐trimming project is one typical type of short‐term work zone projects. To implement such a short‐term work zone project, contractors usually divide an entire work zone into multiple subwork zones with the uniform length. This paper aims to determine an optimal subwork zone strategy for the short‐term work zone projects in four‐lane two‐way freeways with time window and uniform subwork zone length constraints. The deterministic queuing model is employed to estimate total user delay caused by the work zone project by taking into account variable traffic speeds. Based on the user delay estimations, this paper proceeds to build a minimization model subject to time window and uniform length constraints for the optimal subwork zone strategy problem. This paper also presents a variation of the minimization model to examine the impact of unequal subwork zone length constraint. Since these minimization models belong to the mixed‐integer non‐differentiable optimization problems, an iterative algorithm embedding with the genetic simulated annealing method is thus proposed to solve these models. Finally, a numerical example is carried out to investigate the effectiveness of the proposed models. Copyright © 2010 John Wiley & Sons, Ltd.     

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.     

Real time queue length estimation for signalized intersections using travel times from mobile sensors

We study how to estimate real time queue lengths at signalized intersections using intersection travel times collected from mobile traffic sensors. The estimation is based on the observation that critical pattern changes of intersection travel times or delays, such as the discontinuities (i.e., sudden and dramatic increases in travel times) and non-smoothness (i.e., changes of slopes of travel times), indicate signal timing or queue length changes. By detecting these critical points in intersection travel times or delays, the real time queue length can be re-constructed. We first introduce the concept of Queue Rear No-delay Arrival Time which is related to the non-smoothness of queuing delay patterns and queue length changes. We then show how measured intersection travel times from mobile sensors can be processed to generate sample vehicle queuing delays. Under the uniform arrival assumption, the queuing delays reduce linearly within a cycle. The delay pattern can be estimated by a linear fitting method using sample queuing delays. Queue Rear No-delay Arrival Time can then be obtained from the delay pattern, and be used to estimate the maximum and minimum queue lengths of a cycle, based on which the real-time queue length curve can also be constructed. The model and algorithm are tested in a field experiment and in simulation.     

Optimal location of advance warning for mandatory lane change near a two-lane highway off-ramp

Improper mandatory lane change (MLC) maneuvers in the vicinity of highway off-ramp will jeopardize traffic efficiency and safety. Providing an advance warning for lane change necessity is one of the efficient methods to perform systematic lane change management, which encourages smooth MLC maneuvers occurring at proper locations to mitigate the negative effects of MLC maneuvers on traffic flow nearby off-ramp. However, the state of the art indicates the lack of rigorous methods to optimally locate this advance warning so that the maximum benefit can be obtained. This research is motivated to address this gap. Specifically, the proposed approach considers that the area downstream of the advance warning includes two zones: (i) the green zone whose traffic ensures safe and smooth lane changes without speed deceleration (S-MLC); the start point of the green zone corresponding to the location of the advance warning; (ii) the yellow zone whose traffic leads to rush lane change maneuvers with speed deceleration (D-MLC). An optimization model is proposed to search for the optimal green and yellow zones. Traffic flow theory such as Greenshield model and shock wave analysis are used to analyze the impacts of the S-MLC and D-MLC maneuvers on the traffic delay. A grid search algorithm is applied to solve the optimization model. Numerical experiments conducted on the simulation model developed in Paramics 6.9.3 indicate that the proposed optimization model can identify the optimal location to set the advance MLC warning nearby an off-ramp so that the traffic delay resulting from lane change maneuvers is minimized, and the corresponding capacity drop and traffic oscillation can be efficiently mitigated. Moreover, the experiments validated the consistency of the green and yellow zones obtained in the simulation traffic flow and from the optimization model for a given optimally located MLC advance warning under various traffic regimes. The proposed approach can be implemented by roadside mobile warning facility or on-board GPS for human-driven vehicles, or embedded into lane change aid systems to serve connected and automated vehicles. Thus it will greatly contribute to both literature and engineering practice in lane change management.     

Development of a delay model for unsignalized intersections applicable to traffic assignment

Abstract

This paper develops a model for estimating unsignalized intersection delays which can be applied to traffic assignment (TA) models. Current unsignalized intersection delay models have been developed mostly for operational purposes, and demand detailed geometric data and complicated procedures to estimate delay. These difficulties result in unsignalized intersection delays being ignored or assumed as a constant in TA models.

Video and vehicle license plate number recognition methods are used to collect traffic volume data and to measure delays during peak and off-peak traffic periods at four unsignalized intersections in the city of Tehran, Iran. Data on geometric design elements are measured through field surveys. An empirical approach is used to develop a delay model as a function of influencing factors based on 5- and 15-min time intervals. The proposed model estimates delays on each approach based on total traffic volumes, rights-of-way of the subject approach and the intersection friction factor. The effect of conflicting traffic flows is considered implicitly by using the intersection friction factor. As a result, the developed delay model guarantees the convergence of TA solution methods.

A comparison between delay models performed using different time intervals shows that the coefficients of determination, R ², increases from 43.2% to 63.1% as the time interval increases from 5- to 15-min. The US Highway Capacity Manual (HCM) delay model (which is widely used in Iran) is validated using the field data and it is found that it overestimates delay, especially in the high delay ranges.     

A stochastic model of traffic flow: Theoretical foundations

In a variety of applications of traffic flow, including traffic simulation, real-time estimation and prediction, one requires a probabilistic model of traffic flow. The usual approach to constructing such models involves the addition of random noise terms to deterministic equations, which could lead to negative traffic densities and mean dynamics that are inconsistent with the original deterministic dynamics. This paper offers a new stochastic model of traffic flow that addresses these issues. The source of randomness in the proposed model is the uncertainty inherent in driver gap choice, which is represented by random state dependent vehicle time headways. A wide range of time headway distributions is allowed. From the random time headways, counting processes are defined, which represent cumulative flows across cell boundaries in a discrete space and continuous time conservation framework. We show that our construction implicitly ensures non-negativity of traffic densities and that the fluid limit of the stochastic model is consistent with cell transmission model (CTM) based deterministic dynamics.     

Control strategies for departure process delays at airport passenger terminals

This paper explores the characteristics of process delays at airport passenger terminals and establishes a queuing model for both passengers and baggage served by different connecting type facilities. The impact of delay propagation on other processes and flights is investigated using an analytical approach. In addition, the extra costs incurred on passengers, process operators, and airlines are examined using the delay cost functions. To reduce the impact of process delays, various delay-controlled strategies are proposed, such as setting scheduled times for completion of a process, increasing the number of service counters, and priority service for emergent flights. Taoyuan International Airport in Taiwan is used as a case study when facing special events. Results showed that the model can effectively and efficiently estimate delay propagation and its costs. In addition, processes that are not consecutive allow more buffer time between different operations, which helps ease propagation of delays caused by previous services.     

Feedback control strategy of a new car-following model based on reducing traffic accident rates

ABSTRACT

To reduce the traffic accident death rate effectively and alleviate the traffic congestion phenomenon, this study proposes a new type of car-following model under the influence of drivers’ time-varying delay response time. Based on Lyapunov function theory, this paper reduces the traffic accident rate problem to the stability issues of the new model. By constructing suitable Lyapunov functions and using the linear matrix inequality method, the stability problem of the new car-following model is studied. The model, under the action of the controller, can effectively restrain traffic congestion. Using the traffic accident rate model proposed by Solomon, compared with the car-following model without the controller, the model under the controller shows a stronger convergence. This also means that the traffic congestion phenomenon has been effectively suppressed while greatly reducing the mortality rate of traffic accidents.     

Modeling delay at signalized intersections with channelized right‐turn lanes considering the impact of blockage

This paper presents a probabilistic delay model for signalized intersections with right‐turn channelization lanes considering the possibility of blockage. Right‐turn channelization is used to improve the capacity and to reduce delay at busy intersections with a lot of right‐turns. However, under heavy traffic conditions the through vehicles will likely block the channelization entrance that accrues delay to right‐turn vehicles. If the right‐turn channelization gets blocked frequently, its advantage in reducing the intersection delay is neglected and as a result the channelization lane becomes inefficient and redundant. The Highway Capacity Manual (HCM) neglects the blockage effect, which may be a reason for low efficiency during peak hours. More importantly, using HCM or other standard traffic control methods without considering the blockage effects would lead to underestimation of the delay. To overcome this issue, the authors proposed delay models by taking into account both deterministic and random aspects of vehicles arrival patterns at signalized intersections. The proposed delay model was validated through VISSIM, a microscopic simulation model. The results showed that the proposed model is very precise and accurately estimates the delay. In addition, it was found that the length of short‐lane section and proportion of right‐turn and through traffic significantly influence the approach delay. For operational purposes, the authors provided a step‐by‐step delay calculation process and presented approach delay estimates for different sets of traffic volumes, signal settings, and short‐lane section lengths. The delay estimates would be useful in evaluating adequacy of the current lengths, identifying the options of extending the short‐lane section length, or changing signal timing to reduce the likelihood of blockage. Copyright © 2016 John Wiley & Sons, Ltd.     

Analytical model for calibrating delay at congested bus stops

Abstract

A model is proposed to calculate the overall operating and delay times spent at bus stops due to passenger boarding and alighting and the time lost to queuing caused by bus stop saturation. A formula for line demand at each stop and the interaction between the buses themselves is proposed and applied to different bus stops depending on the number of available berths. The application of this model has quantified significant operational delays suffered by users and operator due to consecutive bus arrival at stops, even with flows below bus stop capacity.     

Speed-flow relations and cost functions for congested traffic: Theory and empirical analysis

A dynamic ‘car-following’ extension of the conventional economic model of traffic congestion is presented, which predicts the average cost function for trips in stationary states to be significantly different from the conventional average cost function derived from the speed-flow function. When applied to a homogeneous road, the model reproduces the same stationary state equilibria as the conventional model, including the hypercongested ones. However, stability analysis shows that the latter are dynamically unstable. The average cost function for stationary state traffic coincides with the conventional function for non-hypercongested traffic, but rises vertically at the road’s capacity due to queuing, instead of bending backwards. When extending the model to include an upstream road segment, it predicts that such queuing will occur under hypercongested conditions, while the general shape of the average cost function for full trips does not change, implying that hypercongestion will not occur on the downstream road segment. These qualitative predictions are verified empirically using traffic data from a Dutch bottleneck. Finally, it is shown that reduced-form average cost functions, that relate the sum of average travel cost and average schedule delay costs to the number of users in a dynamic equilibrium, certainly need not have the intuitive convex shape, but may very well be concave – despite the fact that the underlying speed-flow function may be convex.     

An improved cellular automata model for heterogeneous work zone traffic

This paper aims to develop an improved cellular automata (ICA) model for simulating heterogeneous traffic in work zone. The proposed ICA model includes the forwarding rules to update longitudinal speeds and positions of work zone vehicles. The randomization probability parameter used by the ICA is formulated as a function of the activity length, the transition length and the volumes of different types of vehicles traveling across work zone. Compared to the existing cellular automata models, the ICA model possesses a novel and realistic lateral speed and position updating rule so that the simulation of vehicle’s lateral movement in work zone is close to the reality. The ICA model is calibrated and validated microscopically and macroscopically by using the real work zone data. Comparisons of field data and ICA for trajectories, speed and speed–flow relationship in work zone show very close agreement. Finally, the proposed ICA model is applied to estimate traffic delay occurred in work zone.     

Stochastic prediction of train delays in real-time using Bayesian networks

In this paper we present a stochastic model for predicting the propagation of train delays based on Bayesian networks. This method can efficiently represent and compute the complex stochastic inference between random variables. Moreover, it allows updating the probability distributions and reducing the uncertainty of future train delays in real time under the assumption that more information continuously becomes available from the monitoring system. The dynamics of a train delay over time and space is presented as a stochastic process that describes the evolution of the time-dependent random variable. This approach is further extended by modelling the interdependence between trains that share the same infrastructure or have a scheduled passenger transfer. The model is applied on a set of historical traffic realisation data from the part of a busy corridor in Sweden. We present the results and analyse the accuracy of predictions as well as the evolution of probability distributions of event delays over time. The presented method is important for making better predictions for train traffic, that are not only based on static, offline collected data, but are able to positively include the dynamic characteristics of the continuously changing delays.     

Multi-stage stochastic program to optimize signal timings under coordinated adaptive control

In the wake of traffic congestion at intersections, it is imperative to shorten delays in corridors with stochastic arrivals. Coordinated adaptive control can adjust green time flexibly to deal with a stochastic demand, while maintaining a minimum through-band for coordinated intersections. In this paper, a multi-stage stochastic program based on phase clearance reliability (PCR) is proposed to optimize base timing plans and green split adjustments of coordinated intersections under adaptive control. The objective is to minimize the expected intersection delay and overflow of the coordinated approach. The overflow or oversaturated effect is explicitly addressed in the delay calculation, which greatly increases the modeling complexity due to the interaction of overflow delays across cycles. The notion of PCR separates the otherwise related green time settings of consecutive cycles into a number of stages, in which the base timing plan and actual timing plan in different cycles are handled sequentially. We then develop a PCR based solution algorithm to solve the problem, and apply the model and the solution algorithm to actual intersections in Shanghai to investigate its performance as compared with Allsop’s method and Webster’s method. Preliminary results show the PCR-based method can significantly shorten delays and almost eliminates overflow for the coordinated approaches, with acceptable delay increases of the non-coordinated approaches. A comparison between the proposed coordinated adaptive logic and a coordinated actuated logic is also conducted in the case study to show the advantages and disadvantages.     

Estimating link travel time functions for heterogeneous traffic flows on freeways

Oversized vehicles, such as trucks, significantly contribute to traffic delays on freeways. Heterogeneous traffic populations, that is, those consisting of multiple vehicles types, can exhibit more complicated travel behaviors in the operating speed and performance, depending on the traffic volume as well as the proportions of vehicle types. In order to estimate the component travel time functions for heterogeneous traffic flows on a freeway, this study develops a microscopic traffic‐simulation based four‐step method. A piecewise continuous function is proposed for each vehicle type and its parameters are estimated using the traffic data generated by a microscopic traffic simulation model. The illustrated experiments based on VISSIM model indicate that (i) in addition to traffic volume, traffic composition has significant influence on the travel time of vehicles and (ii) the respective estimations for travel time of heterogeneous flows could greatly improve their estimation accuracy. Copyright © 2016 John Wiley & Sons, Ltd.     

The development of taiwan arterial traffic‐adaptive signal control system and its field test: A taiwan experience

This Taiwan traffic‐adaptive arterial signal control model borrowed its traffic flow framework mainly from a British traffic‐adaptive control model with a cyclic traffic progression function, i.e. SCOOT (Split Cycle Office Optimisation Technique). The new arterial control model can take into account delays of both major and minor streets and make real‐time signal timing decisions with optimal two‐way signal offsets, so as to create the best arterial signal operation performance. It has been developed to be an online real‐time software for both simulation testing and field validation. Through simulation, it was found that the performance when operating this newly developed real‐time arterial traffic‐adaptive model was significantly better than when using the optimal fixed‐time arterial timing plan. On the aspect of field testing, three signalized intersections located in East District, Tainan City, Taiwan were selected to be the test sites. Fairly good traffic control performance has been demonstrated in that it can effectively reduce travel delays of the control arterial as a whole. Additional discussions about how to combine travel delay and the total number of vehicle stops into a new control performance index have also been included to make the new traffic‐adaptive model more flexible and reasonable to meet the expectations of different driver groups in the arterial system.     

Signalized intersections with variable flow rates: I analysis and simulation

One of the most common measures of signalized intersection operation is the amount of delay a vehicle incurs while passing through the intersection. Traditional models for estimating vehicle delay at intersections generally assume fixed signal timing and uniform arrival rates for vehicles approaching the intersection. One would expect that highly variable arrival rates would result in much longer delays than uniform arrival rates of the same average magnitude. Furthermore, one might expect that signal timing that is adjusted according to traffic volume would result in lower delay signal when variations in flow warrant such adjustable timing. This paper attempts to test several hypotheses concerning the effects of variable traffic arrival rates and adjusted signal timing through the use of simulation. The simulation results corroborate the hypothesis concerning the effect of varying arrival rates. As the variance of the arrival rate over time increases, the average delay per vehicle also increases. Signal timing adjustments based on traffic appear to decrease delay when flow rates vary greatly. As flow variations stabilize, the benefits of signal adjustments tend to diminish.     

Design of single-track rail line for high-speed trains

This paper presents a method for designing a single-track rail line for a reliable high-speed passenger train service. We first consider deterministic train performance and describe a general method for finding the best location and length of the passing tracks. The design is then modified to include slack, which is necessary to ensure on-time performance for trains encountering unexpected delay. An analysis of the robustness of the system to small delays is presented. Robustness to large train delays and slower traffic is incorporated through the provision of additional sidings. Finally, simulation results are presented which compare the performance of a single-track line to a fully double-tracked equivalent.     

Microscopic modeling of large‐scale pedestrian–vehicle conflicts in the city of Madinah,Saudi Arabia

This paper presents a micro‐simulation modeling framework for evaluating pedestrian–vehicle conflicts in crowded crossing areas. The framework adopts a simulation approach that models vehicles and pedestrians at the microscopic level while satisfying two sets of constraints: (1) flow constraints and (2) non‐collision constraints. Pedestrians move across two‐directional cells as opposed to one‐dimensional lanes as in the case of vehicles; therefore, extra caution is considered when modeling the shared space between vehicles and pedestrians. The framework is used to assess large‐scale pedestrian–vehicle conflicts in a highly congested ring road in the City of Madinah that carries 20 000 vehicles/hour and crossed by 140 000 pedestrians/hour after a major congregational prayer. The quantitative and visual results of the simulation exhibits serious conflicts between pedestrians and vehicles, resulting in considerable delays for pedestrians crossing the road (9 minutes average delay) and slow traffic conditions (average speed <10 km/hour). The model is then used to evaluate the following three mitigating strategies: (1) pedestrian‐only phase; (2) grade separation; and (3) pedestrian mall. A matrix of operational measures of effectiveness for network‐wide performance (e.g., average travel time, average speed) and for pedestrian‐specific performance (e.g., mean speed, mean density, mean delay, mean moving time) is used to assess the effectiveness of the proposed strategies. Copyright © 2012 John Wiley & Sons, Ltd.     

A probabilistic model for traffic at actuated control signals

Vehicle actuated controls are designed to adapt green and red times automatically, according to the actual dynamics of the arrival, departure and queuing processes. In turn, drivers experience variable delays and waiting times at these signals. However, in practice, delays and waiting times are computed at these systems with models that assume stationariety in the arrival process, and that are capable of computing simply expectation values, while no information is given on the uncertainty around this expectation. The growing interest on measures like travel time reliability, or network robustness motivates the development of models able to quantify the variability of traffic at these systems.This paper presents a new modeling approach for estimating queues and signal phase times, based on probabilistic theory. This model overcomes the limitations of existing models in that it does not assume stationary arrival rates, but it assumes any temporal distribution as input, and allows one to compute the temporal evolution of queue length and signal sequence probabilities. By doing so, one can also quantify the uncertainty in the estimation of delays and waiting times as time-dependent processes. The results of the probabilistic approach have been compared to the results of repeated microscopic simulations, showing good agreement. The smaller number of parameters and shorter computing times required in the probabilistic approach makes the model suitable for, e.g., planning and design problems, as well as model-based travel time estimation.