377 research outputs found

    Development of Cell Transmission Model for Traffic Signal Coordination

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    This research aims to develop a macroscopic traffic model to estimate delay at signalized intersections by considering queue forming and dissipation in the presence of pre-timed signal. Cell Transmission Model (CTM) was set up with basic traffic input parameters to estimate delay and level of service (LOS) and the results are compared to computational analysis run by SIDRA (Signalized and Unsignalized Intersection Design and Research Aid) software. To optimize the traffic flow condition, traffic signal coordination is carried. It was found that optimized traffic signal setting reduces delay by 25.5% and 17% in Intersection A and Intersection B after a second run by CTM

    Stochastic modeling for vehicle platoons: 1, Dynamic grouping behavior and online platoon recognition

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    A vehicle platoon is a group of vehicles traveling together at approximately the same speed. Traffic platooning is an important phenomenon that can substantially increase the capacity of roads. This two-part paper presents a new approach to stochastic dynamic modeling for vehicle platoons. In part I, we develop a vehicle platoon model with two interconnected components: a Markov regime-switching stochastic process that is used to model the dynamic behavior of platoon-to-platoon transitions, and a state space model that is employed to describe individual vehicles’ dynamic movements within each vehicle platoon. On the basis of the developed stochastic dynamic model, we then develop an algorithm for online platoon recognition. The proposed stochastic dynamic model for vehicle platoons also provides a new approach to vehicle speed filtering for traffic with a platoon structure

    Accounting for midblock pedestrian activity in the HCM 2010 urban street segment analysis

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    The Urban Street segment analysis Chapter of the 2010 Highway Capacity Manual (HCM 2010) provides a methodology for analyzing automobile performance on signalized roadway segments within an urban roadway network. The methodology involves applying a platoon dispersion model to: a) predict the vehicle arrival flow profiles at a downstream signalized intersection; b) use the predicted arrivals to compute the proportion of vehicle arrivals on green; and c) subsequently estimate the delay, travel speed and Level of Service (LOS) under which the segment operates. Vehicles arriving during the red interval at a signalized intersection generally accumulate and form a platoon. When the signal turns green, the platoon of vehicles is discharged from the upstream intersection to the downstream intersection. As vehicle speeds fluctuate, the platoon will disperse before it arrives at the downstream intersection. This is called Platoon dispersion. Notwithstanding its importance and application in evaluating the performance of urban roadway segments, the predictive ability of the HCM 2010 platoon dispersion model under friction and non-friction traffic conditions has not been evaluated. Friction traffic conditions include midblock pedestrian activity, on-street parking activity, and medium to high truck volume. Furthermore, one key limitation of the methodology for evaluating automobile performance on urban street segment is that it does not account for the delay incurred by platoon vehicles due to pedestrian activity at midblock (or mid-segment) crosswalks Therefore, the first objective of this research is to evaluate the predictive performance of the HCM 2010 platoon dispersion model under friction and non-friction traffic conditions using field data collected at four urban street segments. The second and primary objective is to develop an integrated deterministic-probabilistic (stochastic) model that estimates the delay incurred by platoon vehicles due to midblock pedestrian activity on urban street segments. Results of the statistical model evaluation show statistically significant difference between the observed and predicted proportion of arrivals on green under traffic. The results, however, show no statistically significant difference between the observed and predicted proportion of vehicle arrivals on under no traffic friction condition. In addition, the developed delay model was validated using field measured data. Results of the statistical validation show the developed midblock delay model performs well when compared to delays measured in the field. Sensitivity analysis is also performed to study the relationship between midblock delay and certain model parameters and variables. The model parameters are increased and decreased by 50% of their baseline values

    Real-Time Prediction of Lane-Based Queue Lengths for Signalized Intersections

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    Queue length is one of the most important traffic evaluation indexes for traffic signal control at signalized intersections. Most previous studies have focused on estimating queue length, which cannot be predicted effectively. In this paper, we applied the Lighthill–Whitham–Richards shockwave theory and Robertson’s platoon dispersion model to predict the arrival of vehicles in advance at intervals of 5 seconds. This approach fully described the relationship between disparate upstream traffic arrivals (as a result of vehicles making different turns) and the variation of incremental queue accumulation. It also addressed the shortcomings of the uniform arrival assumption in previous research. In addition, to predict the queue length of multiple lanes at the same time, we integrated the prediction of the traffic volume proportions in each lane using the Kalman filter. We tested this model in a field experiment, and the results showed that the model had satisfactory accuracy. We also discussed the limitations of the proposed model in this paper. Document type: Articl

    A Dynamic Predictive Traffic Signal Control Framework in a Cross-Sectional Vehicle Infrastructure Integration Environment

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    With the development of modern wireless communication technology, especially the vehicle infrastructure integration (VII) technology, vehicles’ information such as identification, location, and speed can be readily obtained at upstream cross-section. This information can be used to support traffic signal timing optimization in real time. A dynamic predictive traffic signal control framework for isolated intersections is proposed in a cross-sectional VII environment, which has the ability to predict vehicle arrivals and use this to optimize traffic signals. The proposed dynamic predictive control framework includes a dynamic platoon dispersion model (DPDM) which uses the vehicles’ speed data from the cross-sectional VII environment, as opposed to traditional vehicle passing/existing data, to predict the arriving flow distribution at the downstream stop-line. Then, a dynamic programming algorithm based on the exhaustive optimization of phases (EOP) is proposed working in rolling optimization (RO) scheme with a 2s time horizon. The signal timings are continuously optimized by regarding the minimization of intersection delay as the optimization objective, and setting the green time duration of each phase as a constraint. In the end, the proposed dynamic predictive control framework is tested in a simulated cross-sectional VII environment and a case study carried out based on a real road network. The results show that the proposed framework can reduce the average delay and queue length by up to 33% and 35%, respectively, compared with the traditional full-actuated control

    AN INTEGRATED CONTROL MODEL FOR FREEWAY INTERCHANGES

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    This dissertation proposes an integrated control framework to deal with traffic congestion at freeway interchanges. In the neighborhood of freeway interchanges, there are six potential problems that could cause severe congestion, namely lane-blockage, link-blockage, green time starvation, on-ramp queue spillback to the upstream arterial, off-ramp queue spillback to the upstream freeway segments, and freeway mainline queue spillback to the upstream interchange. The congestion problem around freeway interchanges cannot be solved separately either on the freeways or on the arterials side. To eliminate this congestion, we should balance the delays of freeways and arterials and improve the overall system performance instead of individual subsystem performance. This dissertation proposes an integrated framework which handles interchange congestion according to its severity level with different models. These models can generate effective control strategies to achieve near optimal system performance by balancing the freeway and arterial delays. The following key contributions were made in this dissertation: 1. Formulated the lane-blockage problem between the movements of an arterial intersection approach as an linear program with the proposed sub-cell concept, and proposed an arterial signal optimization model under oversaturated traffic conditions; 2. Formulated the traffic dynamics of a freeway segment with cell-transmission concept, while considering the exit queue effects on its neighboring through lane traffic with the proposed capacity model, which is able to take the lateral friction into account; 3. Developed an integrated control model for multiple freeway interchanges, which can capture the off-ramp spillback, freeway mainline spillback, and arterial lane and link blockage simultaneously; 4. Explored the effectiveness of different solution algorithms (GA, SA, and SA-GA) for the proposed integrated control models, and conducted a statistical goodness check for the proposed algorithms, which has demonstrated the advantages of the proposed model; 5. Conducted intensive numerical experiments for the proposed control models, and compared the performance of the optimized signal timings from the proposed models with those from Transyt-7F by CORSIM simulations. These comparisons have demonstrated the advantages of the proposed models, especially under oversaturated traffic conditions

    A Review of Models of Urban Traffic Networks (With Particular reference to the Requirements for Modelling Dynamic Route Guidance Systems)

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    This paper reviews a number of existing models of urban traffic networks developed in Europe and North America. The primary intention is to evaluate the various models with regard to their suitability to simulate traffic conditions and driver behavior when a dynamic route guidance system is in operation
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