A combined distribution, hierarchical mode choice, and assignment network model with multiple user and mode classes

Wong, Ka-Io; Wong, Stephen C. P.; Wu, Jianhui; Yang, Hai; Lam, William H. K.

doi:10.4337/9781845420536.00008

Cited by 12 publications

(8 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Generally, Taxi regulations are mainly concerned with two primary issues (price and entry controls) and many models have been extensively developed to tackle them. Although each model is analyzed from different points of view, the models to date can be grouped into two categories: aggregated models (e.g., [5][6][7][8][9][10][11][12][13][14]) and equilibrium models (e.g., a series of models presented by Yang and Wong during the period of 1997-2010 by studying the taxicab market in the network of Hong Kong) [15][16][17][18][19][20][21][22][23].…”

Section: Related Work On Modeling Taxi Marketmentioning

confidence: 99%

Modeling and Analyzing Taxi Congestion Premium in Congested Cities

Cao

Wei

et al. 2017

Journal of Advanced Transportation

View full text Add to dashboard Cite

Traffic congestion is a significant problem in many major cities. Getting stuck in traffic, the mileage per unit time that a taxicab travels will decline significantly. Congestion premium (or so-called low-speed fare) has become an increasingly important income source for taxi drivers. However, the impact of congestion premium on the taxicab market is not widely understood yet. In particular, modeling and analyzing of the taxi fare structure with congestion premium are extremely limited. In this paper, we developed a taxi price equilibrium model, in which the adjustment mechanism of congestion premium on optimizing the taxi driver's income, balancing the supply and demand, and eventually improving the level of service in the whole taxicab market was investigated. In the final part, we provided a case study to demonstrate the feasibility of the proposed model. The results indicated that the current taxi fare scheme in Beijing is suboptimal, since the gain from the raise of congestion premium cannot compensate for the loss from the demand reduction. Conversely, the optimal fare scheme suggested by our model can effectively reduce the excessive demand and reach the supply-demand equilibrium, while keeping the stability of the driver's income to the maximum extent.

show abstract

Section: Related Work On Modeling Taxi Marketmentioning

confidence: 99%

Modeling and Analyzing Taxi Congestion Premium in Congested Cities

Cao

Wei

et al. 2017

Journal of Advanced Transportation

View full text Add to dashboard Cite

show abstract

“…An interesting discussion on various user classes with different values of time can be found in Wong et al (2004). Many studies have obtained specific values for the VoT of the citizens by trip purpose, trip length, income and others.…”

Section: Trip Costmentioning

confidence: 99%

“…They presented and analyzed the complex case where customers have to wait until the first occupied taxi is available, increasing the waiting time and reducing the LoS. In the hailing market, Wong et al (2004) use the number of vacant taxis and the size of the area of service for calculating the waiting time, assuming a continuous taxi stand distribution. Using a more statistical approach, the waiting time is equal to the time that the user must wait until the first free taxi reaches the customer, starting from a random moment when the user decides to take a taxi.…”

Section: Access and Waiting Timementioning

confidence: 99%

Aggregated Modeling of Urban Taxi Services

Grau

Estrada

Amat

2014

Procedia - Social and Behavioral Sciences

View full text Add to dashboard Cite

Models are an indispensable tool for decision makers when defining the principal policy measures of the taxi services, such as fleet size, fares or operational modes of the services within the city. Various models have been developed for calculating the variables that characterize the taxi services in urban regions. This paper presents an extensive review of the presented formulations for the modeling of taxi services in urban areas. The variables of the problem are identified and analyzed, presenting the different formulations proposed in the literature for each one of the three operational modes (hailing, stand and dispatching).

show abstract

“…Friesz (1981) provided an equivalent optimization problem for combined multiclass distribution, assignment, and model split which obviates symmetry restrictions. Wong et al (2004) proposed an optimization model for combining distribution, hierarchical mode choice, and assignment network with multiple user and mode classes. Safwat and Magnanti (1988) developed a combined model by integrating all four steps in sequential demand forecasting based on random utility theory.…”

Section: Introductionmentioning

confidence: 99%