Computing Travel Time Reliability in Transportation Networks with Multistates and Dependent Link Failures

Al-Deek, Haitham; Emam, Emam B

doi:10.1061/(asce)0887-3801(2006)20:5(317)

Cited by 16 publications

(2 citation statements)

References 10 publications

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“…The former assumes that the road capacities and traffic demand obeying certain distribution patterns. The traffic flow assignment is repeatedly implemented using the deterministic or stochastic user equilibrium model to obtain massive amounts of sample data, based on which the Monte Carlo sampling is applied for travel time reliability estimation (e.g., Liu [22][23][24]. Although the travel time reliability under the present transportation conditions can be truly reflected by the above methods, there still are some defects.…”

Section: Prediction Methods Of Travel Time Reliabilitymentioning

confidence: 99%

Optimization of Airport Shuttle Bus Routes Based on Travel Time Reliability

Bao

et al. 2018

Mathematical Problems in Engineering

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An optimization model of airport shuttle bus routes is constructed by taking operational reliability maximization as a main goal in this paper. Also, a hybrid genetic algorithm is designed to solve this problem. Then the theoretical method is applied to the case of Nanjing Lukou International Airport. During the research, a travel time reliability estimation method is proposed based on back propagation (BP) neural network. Absolute error and regression fitting methods are used to test the measurement results. It is proved that this method has higher accuracy and is applicable to calculate airport bus routes reliability. In algorithm design, the hill-climbing algorithm with strong local search ability is integrated into genetic algorithm. Initial solution is determined by hill-climbing algorithm so as to avoid the search process falling into a local optimal solution, which makes the accuracy of calculation result improved. However, the calculation results show that the optimization process of hybrid genetic algorithm is greatly affected by both the crossover rate and mutation rate. A higher mutation rate or lower crossover rate will decrease the stability of the optimization process. Multiple trials are required to determine the optimal crossover rate and mutation rate. The proposed method provides a scientific basis for optimizing the airport bus routes and improving the efficiency of airport’s external transportation services.

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Section: Prediction Methods Of Travel Time Reliabilitymentioning

confidence: 99%

Optimization of Airport Shuttle Bus Routes Based on Travel Time Reliability

Bao

et al. 2018

Mathematical Problems in Engineering

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“…The daily TTV can be defined as a measure that shows how the TTR during the non-peak period differs from the TTR of other days during the same non-peak period. The daily TTV (U(Ω n )) was estimated by using the probabilistic method assuming the most n probable system states as in prior studies (Sumalee and Watling, 2003;Al-Deek and Emam, 2006):…”

Section: Daily Travel Time Variabilitymentioning

confidence: 99%

How automated speed enforcement may reduce travel time variability and result in travel time savings: The case study of the loop 101 speed enforcement program in Scottsdale, Arizona

2010

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The city of Scottsdale Arizona implemented the first fixed photo Speed Enforcement camera demonstration Program (SEP) on a US freeway in 2006. A comprehensive before-and-after analysis of the impact of the SEP on safety revealed significant reductions in crash frequency and severity, which indicates that the SEP is a promising countermeasure for improving safety. However, there is often a tradeoff between safety and mobility when safety investments are considered. As a result, identifying safety countermeasures that both improve safety and reduce Travel Time Variability (TTV) is a desirable goal for traffic safety engineers. This paper reports on the analysis of the mobility impacts of the SEP by simulating the traffic network with and without the SEP, calibrated to real world conditions. The simulation results show that the SEP decreased the TTV: the risk of unreliable travel was at least 23% higher in the 'without SEP' scenario than in the 'with SEP' scenario. In addition, the total Travel Time Savings (TTS) from the SEP was estimated to be at least '569 vehicle-hours/year.' Consequently, the SEP is an efficient countermeasure not only for reducing crashes but also for improving mobility through TTS and reduced TTV.

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