Overlapping phase and split phase are two typical phase patterns at signalized intersections in practice. The existing bandwidth-oriented progression control schemes mainly focus on overlapping phase to adopt the various layout of intersections and volumes rather than split phase. To address this issue, a two-way signal progression model, namely Pband, is developed to simultaneously optimize phase pattern choice from overlapping phase or split phase, phase sequence, and offsets. Also, the proposed Pband is formulated with a mixed integer nonlinear programming technique to guarantee an optimal solution. A numerical test based on a field arterial from the county of Jiashan, Jiaxing, China is employed to validate Pband under designed traffic patterns and signal timings. Numerical results have indicated that the Pband can show promise in increasing progression bandwidths and reducing average travel delay and the number of stops via traffic simulation experiments compared with the conventional Multiband model.

The rapid development of traffic theory and information technology has provided diversified and large-scale traffic data resources for traffic research and urban traffic management. At the same time, these data also present many challenges, such as missing data and deviations in data collection. Many researchers have reported that inaccurate or incomplete measurements of traffic variables can be corrected based on either traditional traffic flow theory, which ignores the randomness of traffic, or are performed using machine learning methods, which emphasize data quantity, but do not make effective use of domain knowledge. This paper proposes a Traffic Factor State Network framework defined by traffic factors and their links to represent the relationships between traffic factors; this framework includes not only obvious traffic factors like volume and speed, but also hidden traffic factors such as the environmental impact factor, which is a variable used to represent complex road conditions. This variable is used to describe the influence of non-traffic flow parameters such as road condition and environmental factors, and is estimated by the EM (Expectation Maximization) algorithm based on historical data. This study used a high-order multivariate Markov model to implement the TFSN, which was then used to establish a stochastic model of speed and related factors. A large amount of historical data was used to calculate and calibrate the strength of the links between the model factors. Finally, a stochastic model of speed prediction was established. The verification results compared with actual cases demonstrate the validity and applicability of the proposed model.

Progression bandwidth maximization is one of the most important signal coordination strategies for urban arterial signal control. MAXBAND and MULTIBAND have implemented a weighting factor that is capable of adjusting the bandwidth according to unbalanced bandwidth demands in a two-way bandwidth maximization problem. The maximum bandwidth solution may not be achieved with certain values of weighting factors; therefore, users may need to have a well-developed idea about what weighting factor to use in order to not compromise the total bandwidth. In this paper, we propose a new two-way bandwidth maximization model that not only maximizes the total bandwidth, but also introduces a bandwidth proration impact factor. This impact factor allows the user to control the importance of satisfying the target bandwidth demand ratio. Numerical examples have demonstrated that the new model has the following advantages: (1) when two-way progression solution is not physically possible, the model first guarantees ma...

An optimisation model for network progression coordinated control under the signal design mode of split phasing in unsaturated traffic conditions was proposed in this study. Considering the characteristics of the cyclical variation relationship between the bidirectional progression coordinated control effect and intersection spacing, a cosine function of the time difference between the actual green centre point and the ideal green centre point was defined as the evaluation index. The constraints of the common signal cycle, phase time, and phase sequence were introduced in the model, and the phase time allocation was discussed in this study. The model enables the phase time and phase sequence of each intersection to be freely valued within the solution space, and realises the comprehensive optimisation of the phase time, as well as common signal cycle, phase sequence, and offset. The case study demonstrates that the scheme optimised by this model can provide significant progression coordinated control effects for all the through movements on each artery. This method is effective when applied to network progression coordinated control.

An optimization model of regional green wave coordination control for the coordinated path set is proposed based on the network’s directional and asymmetric actual coordination control demands. The model in this paper selects the coordinated path set as the optimization object and takes the best regional coordination control effect as the optimization objective. By selecting signal timing parameters, such as stage time, stage center point, offset, and cycle length, as optimization variables, the relationship between signal timing parameters and the effect of green wave coordination was established. The stage time of the coordinated stage at the upstream and downstream intersections is used to calculate the evaluation index of the coordination control benefit of the whole road network. The case study demonstrates that this model can optimize coordinated path chains with left-turn traffic flows under green wave coordination management. In terms of network performance, compared with Transyt and Synchro, the signal control scheme obtained by the proposed model can reduce the average delay by about 30% and the average number of stops by about 40%. To meet the requirements of regional green wave coordination control, the proposed model can optimize different signal timing parameters to obtain a wide range of applications of green wave coordinated control in road networks.