A time-dependent logit-based taxi customer-search model

Szeto, W.Y.; Wong, R.C.P.; Wong, Stephen C. P.; Yang, Hai

doi:10.1080/12265934.2013.776292

Cited by 34 publications

(24 citation statements)

References 34 publications

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“…These findings were consistent with those in another similar study [14]. Szeto et al [28] introduced a time-dependent logit model to model vacant taxi movements and indicated significant impacts of demand, earned fare, and time of day, utilizing GPS data from about 460 taxicabs. Wong et al [12,29] extended the simple logit-based structure to the sequential processes (i.e., a series of decisions along the vacant taxi routes) and showed that the customer searching behaviors were significantly influenced by the probability of successfully picking up a customer along their movement routes.…”

Section: Literature Reviewsupporting

confidence: 88%

Modeling the Taxi Drivers’ Customer-Searching Behaviors outside Downtown Areas

2018

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A popular phenomenon in the street-hailing taxi system is the imbalanced mobility services between city central and outside downtown areas, which leads to unmet demand outside downtown areas and competitions in city central areas. Understanding taxi drivers' customer-searching behaviors is crucial to addressing the phenomenon and redistributing the taxi supply. However, the current literature ignores or simply models the taxi drivers' behaviors, in particular, lacks the in-depth discussions on individuals' heterogeneity. This study introduces the latent class model to identify the internal and external factors influencing the taxi drivers' destination choice after the last drop-offs. Beyond the influencing factors, the modeling structure captures the heterogeneity in vacant taxicab drivers through introducing latent classes. The proposed model outperforms other discrete choice models, for instance, multinomial logit, nested logit, and mixed logit, based on the two study cases developed from the New York City yellow taxicab system. The empirical results first statistically indicate the existence of latent classes, which further empirically prove the heterogeneity in the choices by vacant taxicab drivers while searching customers. Moreover, we obtain a set of internal and external factors influencing the customer searching behaviors. For example, the taxicab drivers are sensitive to the demand at the search destination areas and the distance from the last drop-off location to the search destination areas and behave identically in particular under the conditions of high demand and short search distance. On the other hand, the external variables have different impacts on customer searching behaviors across the different groups of drivers in the both study cases, including peak hours, weekday, holiday, earned fare from last occupied trip, raining hours, and flight arrivals at airports. In final, the proposed modeling structure and findings are useful as a sub-model of taxi system modeling while developing strategies, as well as as a regional planning tool for taxi supply estimations.

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Section: Literature Reviewsupporting

confidence: 88%

Modeling the Taxi Drivers’ Customer-Searching Behaviors outside Downtown Areas

2018

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“…They constructed various network models by considering customer OD patterns, congestions, model calibration efficiency, demand and supply equilibrium while taking into account the influence of spatial structure in the market; and (4) Route choice behaviors. A number of studies applied the logit and probability based models to analyze taxi drivers' behaviors in occupied situations [9] and customer searching behaviors in vacant situations [7]; [10], [11].…”

Section: Introductionmentioning

confidence: 99%

A Two-Layer Model for Taxi Customer Searching Behaviors Using GPS Trajectory Data

Tang

Jiang

et al. 2016

IEEE Trans. Intell. Transport. Syst.

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This paper proposes a two-layer decision framework to model taxi drivers' customer-search behaviors within urban areas. The first layer models taxi drivers' pickup location choice decisions, and a Huff model is used to describe the attractiveness of pickup locations. Then, a path size logit (PSL) model is used in the second layer to analyze route choice behaviors considering information such as path size, path distance, travel time, and intersection delay. Global Positioning System data are collected from more than 36 000 taxis in Beijing, China, at the interval of 30 s during six months. The Xidan district with a large shopping center is selected to validate the proposed model. Path travel time is estimated based on probe taxi vehicles on the network. The validation results show that the proposed Huff model achieved high accuracy to estimate drivers' pickup location choices. The PSL outperforms traditional multinomial logit in modeling drivers' route choice behaviors. The findings of this paper can help understand taxi drivers' customer searching decisions and provide strategies to improve the system services. Index Terms-Customer-search behavior, Huff model, path overlapping, path size logit model, taxi GPS traces.

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“…Szeto et al . further extended the consideration to every hour in a day, and Wong et al . extended by adopting the sequential logit approach to modeling sequential customer‐search decisions of vacant taxi drivers on finding customers at intermediate zones while heading to their designated zones.…”

Section: Introductionmentioning

confidence: 99%

“…Wong et al [26] calibrated and validated the logit models based on Global Positioning System (GPS) data from 460 urban taxis to predict the drivers' strategic zonal choice for searching for customers during both peak and off-peak periods. Szeto et al [27] further extended the consideration to every hour in a day, and Wong et al [28] extended [26] by adopting the sequential logit approach to modeling sequential customer-search decisions of vacant taxi drivers on finding customers at intermediate zones while heading to their designated zones. However, these behavioral studies of vacant taxi drivers focused on their zonal choices in search of customers.…”

Section: Introductionmentioning

confidence: 99%

Behavior of taxi customers in hailing vacant taxis: a nested logit model for policy analysis

Wong

Szeto

Wong

2015

J of Advced Transportation

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Summary This study models and examines the taxi customers' preferences for hailing vacant taxis on streets. A stated preference survey was conducted to randomly select and interview 1242 taxi customers at taxi stands and pedestrians on streets, who had experiences of taking taxis recently, about their choices under different given hypothetical scenarios. In total, 4968 observations were collected and used for developing the discrete choice models for the analysis. To account for the potential correlations among alternatives, two nested logit models are developed, calibrated, and compared with a standard multinomial logit model in the investigation. The results of likelihood ratio test demonstrate that one of the developed nested logit models is better than the standard multinomial logit model to describe the search behavior of taxi customers. The model results also show that the walking time to and the waiting time at the location for hailing taxis, the extra travel time to the destination because of local circulation for finding a way from the pickup location heading to a passenger's destination, as well as the taxi customers' perceptions for walking to and waiting at taxi stands were found as significant factors to influence their decisions. In addition, the results of market segmentation analysis illustrate the variations in taxi‐search strategies of taxi customers in different districts and regions. Some policy implications on introducing more taxi stands and improving the utilization rates of taxi stands are also discussed. We believe that the proposed models, findings, and discussion are useful for developing micro‐simulation models to evaluate the performance of road traffic networks with taxi services and developing simulation‐based optimization models to answer policy questions related to taxi services. Copyright © 2015 John Wiley & Sons, Ltd.

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A time-dependent logit-based taxi customer-search model

Cited by 34 publications

References 34 publications

Modeling the Taxi Drivers’ Customer-Searching Behaviors outside Downtown Areas

Modeling the Taxi Drivers’ Customer-Searching Behaviors outside Downtown Areas

A Two-Layer Model for Taxi Customer Searching Behaviors Using GPS Trajectory Data

Behavior of taxi customers in hailing vacant taxis: a nested logit model for policy analysis

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