Optimising traffic signal settings for periods of time-varying demand

Han, Bin

doi:10.1016/0965-8564(95)00018-6

Cited by 15 publications

(9 citation statements)

References 4 publications

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“…The gradual transitioning algorithm studied by Ross [6] is developed heuristically and the step size as well as the number of steps are not necessarily optimal; as noted in Reference [9], its performance depended on the distribution of the traffic volume in the network. Another similar approach is that of Reference [10] in which the co-ordination parameters for different time-varying demands are optimized using a sequential optimization technique. The method of [10] addresses a single junction only and hence is not well suited for an arterial network addressed here; however, it is possible to apply it in a network that uses traffic responsive control systems.…”

Section: Introductionmentioning

confidence: 98%

“…Another similar approach is that of Reference [10] in which the co-ordination parameters for different time-varying demands are optimized using a sequential optimization technique. The method of [10] addresses a single junction only and hence is not well suited for an arterial network addressed here; however, it is possible to apply it in a network that uses traffic responsive control systems.…”

Section: Introductionmentioning

confidence: 98%

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Application of LQ modelling and optimization in urban traffic control

Selekwa

Mussa

Chiteshe

2003

Optim Control Appl Methods

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SUMMARYThe increasing congestion on urban streets demands traffic control signal timing to be well co-ordinated and optimized even during the transition between timing patterns used in different periods of time-of-day (TOD). The TOD timing plans, defined by fixed-time co-ordination parameters, need to change from one TOD period to another. The current methods used in transitioning are aimed at achieving quick transition rather than optimizing traffic flow during the transition period. As a result, they generally cause increased vehicle delays during the transition period particularly for vehicles on the minor street, which face lengthened red times. This paper proposes a quadratic optimization method that can be used to reduce disutility measures to motorists during the transition period. The transition is modeled as a linear dynamic process, and the disutility measures are modeled as the sum of squares of the deviations of the co-ordination parameters}that is, cycle length, phase split, and offset}from the optimal values during the transition. A linear quadratic (LQ) optimization technique of optimal control is used to determine the step size and the number of steps necessary to complete the transition with minimum disutility. The proposed transition period optimization method has the advantage that the user need not specify minimum and maximum cycle length to achieve optimization, as is the case with current methods.Simulation results for three co-ordinated intersections showed that the proposed method reduces total vehicle delay when compared to the 'immediate' transition method embedded in CORSIM traffic simulation software. This is due to the fact that vehicles on the minor street approaches get proportional green time without significantly affecting green times on the major street approach green phase. However, the method showed a slight increase in total delay for vehicles on the major street.

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Section: Introductionmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 98%

Application of LQ modelling and optimization in urban traffic control

Selekwa

Mussa

Chiteshe

2003

Optim Control Appl Methods

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“…The static approach to the problem can be found in Allsop (1977), Smith (1979a,b), Dafermos (1980Dafermos ( , 1982, Fisk and Nguyen (1982), Florian and Spiess (1982), Gartner (1983), Meneguzzer (1990Meneguzzer ( , 1995, Smith and Van Vuren (1993), Lee and Hazelton (1996) and Cascetta et al (1999). Some papers focus on the dynamic approach; see for instance Han (1996), Hu and Mahmassani (1997) and Lo et al (2001). In and Gartner and Stamatiadis (2002), the traffic signal coordination parameters are also involved in the problem.…”

Section: Introductionmentioning

confidence: 99%

Models and algorithms for the optimization of signal settings on urban networks with stochastic assignment models

2006

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In this paper models and algorithms for the optimization of signal settings on urban networks are proposed. Two different approaches to the solution of the problem may be identified: a global approach (optimization of intersection signal settings on the whole network) and a local approach (optimization of signal settings intersection by intersection). For each approach a different optimization model and some solution algorithms are proposed; both models and algorithms are based on the assumptions of within-day static system and stochastic user equilibrium assignment models. The paper includes numerical results on test networks and a comparison between the two approaches.

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“…This SP model takes the risk-neutral planning strategy that minimizes the expected total vehicle delay of the intersection, subject to the intersection capacity and other operational constraints. Instead of solving a complex optimization problem of signal timing plans of several consecutive cycles like Han (1996), we recursively solve a series of two-stage stochastic programs, each for the signal timing plan of two consecutive cycles. We choose to use recursive two-stage stochastic programs rather than multistage stochastic programs for several consecutive cycles based on historical traffic statistics.…”

Section: Introductionmentioning

confidence: 99%