Morning commute problem considering route choice, user heterogeneity and alternative system optima

Liu, Yang; Zhou, Yuhang

doi:10.1016/j.trb.2010.11.003

Cited by 66 publications

(25 citation statements)

References 18 publications

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“…References [16,17] investigated a type of users with bounded rationality, specifically, "oblivious users. " References [18][19][20] studied the morning commute problem within the context of heterogeneous commuters who have different value-of-time or early/late arrival penalty parameters.…”

Section: Introductionmentioning

confidence: 99%

Agent-Based Modeling and Simulation for the Bus-Corridor Problem in a Many-to-One Mass Transit System

Xie

Jia

et al. 2014

Discrete Dynamics in Nature and Society

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With the growing problem of urban traffic congestion, departure time choice is becoming a more important factor to commuters. By using multiagent modeling and the Bush-Mosteller reinforcement learning model, we simulated the day-to-day evolution of commuters' departure time choice on a many-to-one mass transit system during the morning peak period. To start with, we verified the model by comparison with traditional analytical methods. Then the formation process of departure time equilibrium is investigated additionally. Seeing the validity of the model, some initial assumptions were relaxed and two groups of experiments were carried out considering commuters' heterogeneity and memory limitations. The results showed that heterogeneous commuters' departure time distribution is broader and has a lower peak at equilibrium and different people behave in different pattern. When each commuter has a limited memory, some fluctuations exist in the evolutionary dynamics of the system, and hence an ideal equilibrium can hardly be reached. This research is helpful in acquiring a better understanding of commuter's departure time choice and commuting equilibrium of the peak period; the approach also provides an effective way to explore the formation and evolution of complicated traffic phenomena. Hindawi Publishing Corporation

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Section: Introductionmentioning

confidence: 99%

Agent-Based Modeling and Simulation for the Bus-Corridor Problem in a Many-to-One Mass Transit System

Xie

Jia

et al. 2014

Discrete Dynamics in Nature and Society

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“…However, other functions, such as an exponential deterrence function, are compatible and could be used instead. For the modified friction function with arrival time penalties described by Equation ,

α = 1

β = 0.609

, and

γ = 2.38

were chosen based on value‐of‐time values for one of the vehicle classes analyzed by Liu and Nie (). Trips were distributed over the morning peak from 7 am (

t = 0

) to 9 am .…”

Section: Experimental Methodologymentioning

confidence: 99%

Demand Profiling for Dynamic Traffic Assignment by Integrating Departure Time Choice and Trip Distribution

Levin

Boyles

Duthie

et al. 2015

Computer aided Civil Eng

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One challenge in dynamic traffic assignment (DTA) modeling is estimating the finely disaggregated trip matrix required by such models. In previous work, an exogenous time distribution profile for trip departure rates is applied uniformly across all origin‐destination (O‐D) pairs. This article develops an endogenous departure time choice model based on an arrival time penalty function incorporated into trip distribution, which results in distinct demand profiles by O‐D pair. This yields a simultaneous departure time and trip choice making use of the time‐varying travel times in DTA. The required input is arrival time preferences, which can be disaggregated by O‐D pair and may be easier to collect through surveys than the demand profile. This model is integrated into the four‐step planning process with feedback, creating an extension of previous frameworks which aggregate over time. Empirical results from a network representing Austin, Texas indicate variation in departure time choice appropriate to the arrival time penalties and travel times. Our model also appears to converge faster to a dynamic trip table prediction than a time‐aggregated coupling of DTA and planning, potentially reducing the substantial computation time of combined planning models that solve DTA as a subproblem of a feedback process.

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“…For the purpose of verification, the same two-route example in Liu and Nie (2011) is used. The parameters of the two-route numerical experiment are provided in Table 4.…”

Section: Multi-route Examplementioning

confidence: 99%

“…Vickrey's original bottleneck model does not consider users who differ in their valuation of travel time and schedule delay. Such heterogeneity has since attracted much attention because of its potential impacts on the equilibrium solutions as well as the welfare effects of demand management policies (Small, 1982;Cohen, 1987;Arnott et al, 1994;Lindsey, 2004;Small et al, 2005;van den Berg and Verhoef, 2011b;Liu and Nie, 2011;Hall, 2013).…”

Section: Introductionmentioning

confidence: 99%

A semi-analytical approach for solving the bottleneck model with general user heterogeneity

Liu

Nie

Hall

2015

Transportation Research Part B: Methodological

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Morning commute problem considering route choice, user heterogeneity and alternative system optima

Cited by 66 publications

References 18 publications

Agent-Based Modeling and Simulation for the Bus-Corridor Problem in a Many-to-One Mass Transit System

Agent-Based Modeling and Simulation for the Bus-Corridor Problem in a Many-to-One Mass Transit System

Demand Profiling for Dynamic Traffic Assignment by Integrating Departure Time Choice and Trip Distribution

A semi-analytical approach for solving the bottleneck model with general user heterogeneity

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