Incorporating Dynamic Bus Stop Simulation into Static Transit Assignment Models

Owais, Mahmoud; Hassan, Taher S.

doi:10.1007/s40999-016-0064-8

Cited by 20 publications

(13 citation statements)

References 32 publications

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“…The solution methodology begins with creating the incident matrix as in Figure 2. Each link is assigned a weight equal Journal of Advanced Transportation 5 2,3,5,6,7,8,9,10,11,12,13,14,15,17,18,22,23,25,26,27,28,31,32,34,35,37,38,39,40,41,42,43,44,45,46,48,51,53,55,56,57,59,60,61,62,63,64,65,66,67,68,69,71,73,74,75,…”

Section: Methodsmentioning

confidence: 99%

“…In [15], four location rules are stated as a rule of thumb to judge the quality of a number of counting sensors set if used to estimate the O/D matrix. To find the optimum sensors number and locations that achieve these rules, different metaheuristics are used such as genetic algorithms [16], greedy algorithms [17], distancebased genetic algorithm [18], compressed sensing [19], and randomized priority search [20][21][22][23][24][25].…”

Section: State-of-the-artmentioning

confidence: 99%

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Location Strategy for Traffic Emission Remote Sensing Monitors to Capture the Violated Emissions

Owais

2019

Journal of Advanced Transportation

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Air contamination becomes an urgent problem to be considered as a result of the rapid growth in traffic all over the world. Traffic emissions differ from vehicle to vehicle depending on the vehicle type, production year, fuel octane number, and periodical maintenance of the vehicle. The majority of drivers do not revise their harmful vehicles emissions regularly. Therefore, effective tracking of high-emitting vehicles can be an important solution for reducing traffic air pollution. This study proposes a location strategy for vehicle remote sensing monitors aided with ID-plate recognizer to capture any violated vehicle emissions. The problem is formulated into a graph theory problem, and then a novel adapted metaheuristic algorithm is used to solve the problem. The methodology, using a benchmark problem, has managed to solve the problem to the optimality. Moreover, its robustness is measured statistically.

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Section: Methodsmentioning

confidence: 99%

Section: State-of-the-artmentioning

confidence: 99%

Location Strategy for Traffic Emission Remote Sensing Monitors to Capture the Violated Emissions

Owais

2019

Journal of Advanced Transportation

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“…e formation of the rail corrugation is the result of coaction of the wheel-rail interaction, rolling contact mechanics, and the wear properties of wheel-rail materials. e source of complexity often prevents finding the optimal solution [13][14][15][16][17][18]. Due to the complex and diverse causes of rail corrugation, there is currently no appropriate theoretical system that can give a reasonable explanation for all the rail corrugation observed on railway tracks [19].…”

Section: Literature Reviewmentioning

confidence: 99%

Applying System Dynamics of Discrete Supported Track to Analyze the Rail Corrugation Causation on Curved Urban Railway Tracks

Yin

Wei

Zheng

2021

Discrete Dynamics in Nature and Society

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Urban rail corrugation on curved tracks with small radii causes strong howling during operation, which has been bothering subway operating companies for many years. Therefore, revealing its causes and growth is important for the comfort and safety of subway operation. Current studies believe that the occurrence of rail corrugation is largely due to the resonant vibration of the wheel-rail system. However, little attention has been paid to the key causes of the track resonance and the practical prediction of the occurrence probability of rail corrugation on the certain track. This paper intends to solve these above issues. Firstly, the practical model of predicting the rail corrugation growth is proposed based on the wheel-rail coupling interaction, the key causes of corrugation are investigated, and the sensitivity analysis is carried out, while the corrugation superposition model is introduced to the analyze the corrugation evolution as well as to validate the corrugation growth from the aspect of material friction and wear. Secondly, the impact of the key causes on the initiation and development of the rail corrugation is investigated based on the cosimulation. Finally, case studies validate the proposed theory model and method. The results show that the practical prediction model for the rail corrugation growth proposed in this paper is able to estimate the occurrence possibility of rail corrugation on a specific track, and the superharmonic resonance of the track directly excited by passing vehicles eventually leads to rail corrugation. It is also found that shortwave corrugation develops more rapidly, and adjusting the support stiffness or sleeper spacing leads to fluctuations in the corrugation wavelength and its wear rate.

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“…Starting with prior constructed routes and then storing them for on-line use is possible with new advances in computer servers. For the planning part, the expected network conditions could be reflected by successive demand simulation [3].…”

Section: State Of the Artmentioning

confidence: 99%

“…Operators do not bother themselves to transport each user in the shortest path, but alternatively, they ensure the overall harmony of the network. This appears apparently in the design of transit routes as found in [1]- [3]. On the other side, users need the generated routes to be the fastest way to transport them from their origins to the desired destinations.…”

Section: Introductionmentioning

confidence: 99%

Pareto Optimal Path Generation Algorithm in Stochastic Transportation Networks

Owais

Alshehri

2020

IEEE Access

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Routing problems play a crucial part in urban transportation network operation and management. This study addresses the problem of finding a set of non-dominated shortest paths in stochastic transportation networks. Instead of the previous practice of assuming the travel time variability to be tracked by a known probability density function, it is extracted from the existing correlation between the traffic flow and the corresponding links' time. The time horizon is divided into time intervals/slots in which the network is assumed to experience a static traffic equilibrium with different traffic conditions for each slot. Starting with Priori demand information, prior generated paths, and a chosen traffic assignment method, the proposed methodology conducts successive simulations to the network intervals. It manages to draw both links and paths probability distribution of their travel time considering the correlation among them. Then, multi-objective analysis is conducted on the generated paths to produce the Pareto-optimal set for each demand node pair in the network. Numerical studies are conducted to show the methodology efficiency and generality for any network. The expected travel time and the reliability could be drawn for each path in the network.

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Incorporating Dynamic Bus Stop Simulation into Static Transit Assignment Models

Cited by 20 publications

References 32 publications

Location Strategy for Traffic Emission Remote Sensing Monitors to Capture the Violated Emissions

Location Strategy for Traffic Emission Remote Sensing Monitors to Capture the Violated Emissions

Applying System Dynamics of Discrete Supported Track to Analyze the Rail Corrugation Causation on Curved Urban Railway Tracks

Pareto Optimal Path Generation Algorithm in Stochastic Transportation Networks

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