Optimal control strategies with an extended cell transmission model for massive vehicular‐pedestrian mixed flows in the evacuation zone

Zhang, Xin; Chang, Gang‐Len

doi:10.1002/atr.1243

Cited by 14 publications

(10 citation statements)

References 43 publications

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“…On the other hand, motivated by the widely used LWR theory (traffic flow theory proposed by Lighthill, Whitham and Richards) [24] [25] and the cell transmission model [26] [27] [28] in highway traffic modeling, Menon et al derive an aggregate air traffic model by using a baseline Eulerian model, where aircraft are also aggregated into control centers [29]. The derived one-dimensional model is extended to a two-dimensional one by aggregating aircraft into small grids of surface elements discretized from the realistic airspace with a computer-aided methodology, which is computationally expensive [30].…”

Section: Bloem Et Al Extend the Previous Model By Adapting Quadraticmentioning

confidence: 99%

A network based dynamic air traffic flow model for en route airspace system traffic flow optimization

Chen

Zhang

et al. 2017

Transportation Research Part E: Logistics and Transportation Re

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Section: Bloem Et Al Extend the Previous Model By Adapting Quadraticmentioning

confidence: 99%

A network based dynamic air traffic flow model for en route airspace system traffic flow optimization

Chen

Zhang

et al. 2017

Transportation Research Part E: Logistics and Transportation Re

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“…In MCTM, the nonuniform cell lengths are acceptable. Also, the pedestrian CTM has been developed to simulate the pedestrian flow in public facilities and the accuracy results about LOS [34] can be obtained [35]; the CTM was also used to control the vehicular-pedestrian mixed flows in the evacuation zone [36]. All above works indicate that the CTM can simulate the traffic flow in roadway network as well as the pedestrian flow in the network of corridors.…”

Section: Network-wide Pedestrian Flow Modelmentioning

confidence: 99%

Level-of-Service Based Hierarchical Feedback Control Method of Network-Wide Pedestrian Flow

Zhang

Jia

Qin

2016

Mathematical Problems in Engineering

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Pedestrian flow control is usually used to manage the crowd motion in public facilities to avoid congestion. We propose a network-wide pedestrian flow model based on the modified cell transmission model which describes the link flow as ordinary differential equations. The network flow control model (NFCM) is proposed to limit the number of pedestrians in a network according to the level-of-service requirements; however, the NFCM cannot ensure the uniform link density which is a premise of using NFCM. As a solution, the link flow control model (LFCM) is proposed to adjust the walking speed of pedestrians to realize the uniform link density. The NFCM provides the inputs for the LFCM and the LFCM compensates the deficiency of NFCM. Both NFCM and LFCM control the pedestrian flow in a cooperative way, and thus they form the hierarchical feedback control model (HFCM) of network-wide pedestrian flow. At last, the proposed HFCM is applied to control the crowd of a hall and the comparison of the simulation results in the controlled and uncontrolled scenarios shows that the proposed HFCM has the capability to suggest the optimal link inflows and walking speeds in real time to meet the LOS requirement.

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“…To count the number of the aircraft in a specified airspace, for example, the sector being monitored by the controller, the continuity model established in the preceding texts should be discretized both in time and space. Considering the air traffic density and speed variation both in time and space, the airspace system can be treated as a dynamic system, where the space division concept of cell transmission model is introduced to describe the dynamics of air traffic flow by using the airspace control volumes [16,17]. According to the dynamic network presented in section 2, several interconnected directed edges make up an air route, where one directed edge, that is, a segment, corresponds to one control volume.…”

Section: Dynamic Model For En Route Air Trafficmentioning

confidence: 99%

“…The other point is that the split parameters cause the diffusion and dispersion problem, which may result in inaccurate predictions [13]. On the other hand, motivated by the widely used LWR theory (traffic flow theory proposed by Lighthill, Whitham and Richards) [14,15] and the cell transmission model [16,17] in highway traffic modelling, Menon et al derived the aggregate air traffic model from the Eulerian model [18]. Then, the derived one-dimension model is extended to a largedimensional one by modelling the realistic airspace involving multiple traffic streams with computer-aided methodology, which is computationally expensive [19].…”

mentioning

confidence: 99%

A network‐based dynamic air traffic flow model for short‐term en route traffic prediction

Chen

et al. 2016

J of Advced Transportation

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This paper presents a dynamic network-based approach for short-term air traffic flow prediction in en route airspace. A dynamic network characterizing both the topological structure of airspace and the dynamics of air traffic flow is developed, based on which the continuity equation in fluid mechanics is adopted to describe the continuous behaviour of the en route traffic. Building on the network-based continuity equation, the space division concept in cell transmission model is introduced to discretize the proposed model both in space and time. The model parameters are sequentially updated based on the statistical properties of the recent radar data and the new predicting results. The proposed method is applied to a real data set from Shanghai Area Control Center for the short-term air traffic flow prediction both at flight path and en route sector level. The analysis of the case study shows that the developed method can characterize well the dynamics of the en route traffic flow, thereby providing satisfactory prediction results with appropriate uncertainty limits. The mean relative prediction errors are less than 0.10 and 0.14, and the absolute errors fall in the range of 0 to 1 and 0 to 3 in more than 95% time intervals respectively, for the flight path and en route sector level. airport conditions, airline operation and human factors. [4]. Furthermore, the dimension of the model depends on the number of aircraft under consideration, which demands a huge computational cost in real context to resolve. Thus, in practice, it is difficult to make sound online air traffic control strategies based on the trajectory-based model due to the short forecast horizon and the expensive computational cost.Efficient ATFM requires reasonable prediction of the whole traffic flow situations in the specified airspace, rather than the temporal-spatial information of individual aircraft. Therefore, the aggregate air traffic flow models are introduced recently, which focus on the overall distribution of the air traffic flow in the airspace volumes of interest [5][6][7][8][9][10][11][12][13][18][19][20][21][22][23][24]. Because the aircrafts in the airspace volumes are spatially aggregated, the dimension of the aggregated model depends solely on the number of airspace volumes rather than the total number of aircrafts in the airspace, which will reduce the computational cost significantly. In addition, because the behaviour of the individual aircraft is not taken into account in the aggregated model, it is less sensitive to the uncertainty factors related to individual aircraft, such as the departure delay and the weather, and thus, a longer forecast time horizon with less prediction errors can be achieved.Recently, the aggregated approach is widely discussed in the literatures [5][6][7][8][9][10][11][12][13][18][19][20][21][22][23][24]. A stochastic framework with linear dynamic system model was developed by Sridhar et al., where the dimension of the model depends on the number of control volumes by introducing split parameters to d...

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Optimal control strategies with an extended cell transmission model for massive vehicular‐pedestrian mixed flows in the evacuation zone

Cited by 14 publications

References 43 publications

A network based dynamic air traffic flow model for en route airspace system traffic flow optimization

A network based dynamic air traffic flow model for en route airspace system traffic flow optimization

Level-of-Service Based Hierarchical Feedback Control Method of Network-Wide Pedestrian Flow

A network‐based dynamic air traffic flow model for short‐term en route traffic prediction

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