A cell-based logit-opportunity taxi customer-search model

This paper proposes a cell-based model to predict local customer-search movements of vacant taxi drivers, which incorporates the modeling principles of the logit-based search model and the intervening opportunity model. The local customer-search movements were extracted from the global positioning system data of 460 Hong Kong urban taxis and inputted into a cell-based taxi operating network to calibrate the model and validate the modeling concepts. The model results reveal that the taxi drivers’ local search decisions are significantly affected by the (cumulative) probability of successfully picking up a customer along the search route, and that the drivers do not search their customers under the random walk principle. The proposed model helps predict the effects of the implementation of the policies in adjusting the taxi fleet size and the changes in passenger demand on the customer-search distance and time of taxi drivers.     

Nonlinear pricing of taxi services

This paper examines the effects of nonlinear fare structures in taxi markets using an extended taxi model with an explicit consideration of perceived profitability. The expected profit, defined as the profit per unit time (inclusive of both occupied and vacant taxi times), that a taxi driver expects to receive from picking up a customer in a particular zone or location, has great impact on the taxi driver’s choice of location in the search for customers. The fare structure directly governs the profitability of taxi rides of different distances originating from different locations. With these explicit considerations, the extended model is intended to look into the market effects of adopting a nonlinear fare structure with declining incremental charges. The proposed nonlinear fare structure could help restore a level-playing field for taxi operators whose businesses have been affected by some taxi drivers who resort to practices such as offering fare discounts or accepting requests for discounted fares from passengers for long-haul trips. Analysis of sensitivity of social welfare and profit gain as well as taxi/customer wait/search times is conducted with respect to the parameters in the nonlinear fare structure for the Hong Kong taxi market, and Pareto-improving nonlinear fare amendments are identified that neither disadvantage any customer nor reduce the taxi operators’ profits.     

Dynamic modeling and control of taxi services in large-scale urban networks: A macroscopic approach

Taxis are increasingly becoming a prominent mobility mode in many major cities due to their accessibility and convenience. The growing number of taxi trips and the increasing contribution of taxis to traffic congestion are cause for concern when vacant taxis are not distributed optimally within the city and are unable to find unserved passengers effectively. A way of improving taxi operations is to deploy a taxi dispatch system that matches the vacant taxis and waiting passengers while considering the search friction dynamics. This paper presents a network-scale taxi dispatch model that takes into account the interrelated impact of normal traffic flows and taxi dynamics while optimizing for an effective dispatching system. The proposed model builds on the concept of the macroscopic fundamental diagram (MFD) to represent the dynamic evolution of traffic conditions. The model considers multiple taxi service firms operating in a heterogeneously congested city, where the city is assumed to be partitioned into multiple regions each represented with a well-defined MFD. A model predictive control approach is devised to control the taxi dispatch system. The results show that lack of the taxi dispatching system leads to severe accumulation of unserved taxi passengers and vacant taxis in different regions whereas the dispatch system improves the taxi service performance and reduces traffic congestion by regulating the network towards the undersaturated condition. The proposed framework demonstrates sound potential management schemes for emerging mobility solutions such as fleet of automated vehicles and demand-responsive transit services.     

Conflict‐free time‐based trajectory planning for aircraft taxi automation with refined taxiway modeling

To mitigate airport congestion caused by increasing air traffic demand, the trajectory‐based surface operations concept has been proposed to improve surface movement efficiency while maintaining safety. It utilizes decision support tools to provide optimized time‐based trajectories for each aircraft and uses automation systems to guide surface movements and monitor their conformance with assigned trajectories. Whether the time‐based trajectories can be effectively followed so that the expected benefits can be guaranteed depends firstly on whether these trajectories are realistic. So, this paper first deals with the modeling biases of the network model typically used for taxi trajectory planning via refined taxiway modeling. Then it presents a zone control‐based dynamic routing and timing algorithm upon the refined taxiway model to find the shortest time taxi route and timings for an aircraft. Finally, the presented algorithm is integrated with a sequential planning framework to continuously decide taxi routes and timings. Experimental results demonstrate that the solution time for an aircraft can be steadily around a few milliseconds with timely cleaning of expired time windows, showing potential for real‐time decision support applications. The results also show the advantages of the proposed methodology over existing approaches. Copyright © 2015 John Wiley & Sons, Ltd.     

Modeling urban taxi services in road networks: Progress,problem and prospect

Traditionally, many economists have examined the models and economics of urban taxi services under various types of regulation such as entry restriction and price control in an aggregate way. Only recently have we modeled urban taxi services in a network context. A realistic method has been proposed to describe vacant and occupied taxi movements in a road network and taxi drivers' search behavior for customers. A few extensions have been made to deal with demand elasticity and congestion effects together with development of efficient solution algorithms. Calibration and validation of the network taxi service models have been conducted towards their practical applications. This paper presents an overview of the research that has been carried out by the authors to develop network equilibrium models and solution algorithms for urban taxi services, and offers perspectives for future researches.     

Customers’ selections between premium electric taxis and liquefied petroleum gas taxis

Reducing roadside emissions is a common challenge in metropolitan cities. In Hong Kong, conventional liquefied petroleum gas taxis are one of the main contributors to roadside emissions as they operate on the streets 24 h a day with a long daily driving mileage. Moreover, these taxis suffer from a severely poor service reputation. To enhance the environmental friendliness and service quality of the taxi industry, this study explores the market potential of operating premium electric taxis in the dispatching mode. A stated preference survey was conducted to 1410 taxi customers about their taxi-riding choices between premium electric taxis and conventional liquefied petroleum gas taxis. In total, 5640 observations were obtained and used to develop a series of binary logistic regression models with different model formulations for the determination of the significant factors influencing customers’ selections. The findings indicate that walk time to and wait time for taxis were the most critical concerns to the customers, and they were more willing to take premium taxis if their journey distance was longer and their desired improvement on taxi service quality was greater. The socio-demographic status of taxi customers also influences their choices. The associated policy implications are discussed for promoting taxis with better service quality and fewer roadside emissions. The findings provide some policy insights to other international cities that have a similar taxi market to Hong Kong.     

The use of a hazard-based duration model for imputation of missing personal income data

This paper suggests using a proportional hazard model to predict personal income, for the purpose of imputing missing income data in household travel surveys. The model has a hazard function that comprises two multiplicative components: (1) a non-parametric baseline hazard function that is dependent only on the income level and (2) a function that is dependent only on the other personal attributes of the survey respondents (excluding income). To estimate and validate the model, data is drawn from a travel characteristics survey conducted in Hong Kong in year 2001. The model is found to have a much higher accuracy when compared with a conventional ordered probit model based on the assumption that the logarithm of income is normally distributed.

Safety impacts of signalized lane merge control at highway work zones

Lane closures due to highway work zones present many challenges to the goal of ensuring smooth traffic operations and a safe environment for both drivers and workers. Late merge behavior at a work zone closure is a dangerous behavior that impacts the traffic conflicts upstream of work zone closures. This paper analyzes the safety impacts of using a signalized lane control strategy at the work zone merge points. To achieve the objective of this research, a field study has been conducted at a highway work zone to collect traffic and driver behavior data, and a two-stage, simulation-based approach is used to analyze the safety impacts of implementing a signalized lane merge control strategy at the studied work zone. In the first stage, micro-simulation models are developed and calibrated based on field data to generate vehicle trajectories. In the second stage, the U.S. Federal Highway Administration’s Surrogate Safety Assessment Model is employed to identify potential conflicts under different traffic conditions. The paper concludes that a proposed signal control device could significantly reduce lane-change conflicts at work zone merge points. In addition, recommendations on the signal cycle length and timing splits are provided.     

A macroscopic taxi model for passenger demand,taxi utilization and level of services

In most urban areas taxi services are subject to various types of regulation such as entry restriction and price control. However, effective intervention depends on generating and using suitable information on the demand-supply equilibrium of the taxi market. This paper develops a simultaneous equation system of passenger demand, taxi utilization and level of services based on a taxi service situation found in the urban area of Hong Kong over the last ten years. A set of variables is introduced including number of licensed taxis, taxi fare, disposable income, occupied taxi journey time as exogenous variables and daily taxi passenger demand, passenger waiting time, taxi availability, taxi utilization and average taxi waiting time as endogenous variables. These variables are coupled together through a system of nonlinear simultaneous equations whose parameters are estimated from survey data. The simultaneous equation system can be used to obtain useful regulatory information to assist with the decisions concerning the restriction over the number of taxi licenses and the fixing of the taxi fare structure as well as a range of service quality control. This revised version was published online in June 2006 with corrections to the Cover Date.     

Mining factors affecting taxi drivers’ incomes using GPS trajectories

Taxis provide essential transport services in urban areas. In the taxi industry, the income level remains a cause of concern for taxi drivers as well as regulators. Mining underlying factors affecting the income level will not only benefit the newcomers and low-income drivers but also assist in developing effective optimization algorithms for taxi operations. This paper intends to disclose the factors affecting incomes along with their quantitative influence by mining over 167 million GPS records from nearly 8000 taxis in Shanghai. We first identify a marked difference in drivers’ incomes and categorize drivers into three income levels accordingly. We next investigate the overall search-delivery process, thereby defining several factors that may affect the income level. We then develop a generalized multi-level ordered logit (GMOL) model to find the significant factors that influence incomes. Finally, we compute the elasticity for those significant factors and present their contributions, as well as challenge some preconceived ideas regarding how to earn high incomes.     

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

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.     

Taxi vacancy duration: a regression analysis

Taxi vacancy duration is a major efficiency measure for taxi services. A clear understanding of the various factors and their effect on vacancy duration is necessary for the optimal operational management of taxis. Previous research has only dealt with vacancy duration by assuming probability distributions and has not investigated heterogeneity in the data caused by various factors. We develop a parametric duration model using not only new operational characteristics but also variables associated with taxi demand, such as weather, land use, demographics, socioeconomic variables, and accessibility of public transportation. The model is applied to a large-scale New York City (NYC) taxi trip dataset that covers operations for 2013. The results show that all the attributes have significant associations with vacancy duration that follows a log-normal distribution. Our study is expected to help improve the efficiency of taxi operations by decreasing the time spent in vacant states.     

Equilibrium properties of taxi markets with search frictions

The equilibrium properties of an aggregate taxi market are investigated using a general bilateral searching and meeting function which characterizes the search frictions between vacant taxis and unserved customers. Three specific issues are analyzed for meeting functions that exhibit increasing, constant and decreasing returns to scale. Firstly, service quality in terms of customer wait/search time and average profit per taxi are examined jointly in relation to taxi fleet size, and a Pareto-improving win-win situation is identified, where an increase in taxi fleet size leads to improvements in both service quality and market profitability. Such a Pareto-improving situation is found to emerge if and only if the meeting functions show increasing returns to scale. Secondly, the properties of the socially optimal solution are examined. It is found that the taxi fleet size should be chosen such that the total cost of operating vacant taxis equals the total cost of customer waiting time multiplied by an asymmetric factor of the meeting function, and that taxi services should be subsidized at social optimum only when the meeting functions show increasing returns to scale. Thirdly, the Pareto-efficient services are examined for trade-offs between social welfare and profits in the light of partially conflicting objectives of the public sector and the private taxi firms using a bi-objective maximization approach. The taxi utilization rate and the customer wait/search time or service quality are proved to be constant along the Pareto frontier and equal to those at social optimum if the meeting functions show constant returns to scale. Extensions are made to the cases with increasing and decreasing returns to scale.     

Taxis in road pricing zone: should they pay the congestion charge?

This study aims at investigating the impact and feasibility of charging taxis with toll fee in the pricing zone when designing congestion pricing scheme. A bi‐level programming model is developed to compare the maximum social welfares before and after the congestion charge is imposed on taxis. The lower level is a combined network equilibrium model formulated as a variational inequality program, which considers the logit‐based mode split, route choice, elastic demand, and vacant taxi distributions. The upper level is to maximize the social welfare when toll rates vary. The bi‐level problem can be solved by the genetic algorithm, whereas the lower level is solved by the block Gauss–Seidel decomposition approach together with the method of successive averages and diagonalization algorithm. An application with numerical examples is conducted to demonstrate the effectiveness of the proposed model and algorithm and to reveal some interesting findings. Copyright © 2014 John Wiley & Sons, Ltd.     

Can Hong Kong price-manage its cross-harbor-tunnel congestion?

Hong Kong drivers face daily congestion, especially at the Cross Harbor Tunnel (CHT) whose tolls are substantially lower than those of the drivers’ other two tunnel options: the Eastern Harbor Crossing (EHC) and the Western Harbor Crossing (WHC). In 2013, the Hong Kong Special Administrative Region (HKSAR) Government issued a consultation paper, seeking public comments on three toll-change proposals that would raise the CHT’s tolls and lower the EHC’s tolls. The WHC’s tolls would remain unchanged due to its congested connecting roads. Using monthly crossing data available from the HKSAR’s Transport Department for 2000–2012, this paper uses a Generalized Leontief demand system to document that the usage patterns of the three tunnels is price-responsive. Hence, we conclude that the proposed toll changes are likely to be effective in transportation demand management, by shifting a portion of the CHT’s usage to the EHC and WHC, thereby relieving the CHT’s congestion.     

Modeling taxi drivers’ decisions for improving airport ground access: John F. Kennedy airport case

Taxi service is an important component of airport ground access, which affects the economic competitiveness of an airport and its potential positive impact on the surrounding region. Airports across the globe experience both taxi shortages and excesses due to various factors such as the airport’s proximity to the city center, timing and frequency of flights, and the fare structure. Since taxi drivers are independent entities whose decisions affect the taxi supply at airports, it is important to understand taxi drivers’ decision mechanisms in order to suggest policies and to maintain taxi demand and supply equilibrium at the airports. In this paper, New York City (NYC) taxi drivers’ decisions about airport pick-ups or cruising for customers at the end of each trip is modeled using logistic regression based on a large taxi GPS dataset. The presented approach helps to quantify the potential impacts of parameters and to rank their influence for policy recommendations. The results reveal that spatial variables (mainly related to proximity) have the highest impact on taxi drivers’ airport pickup decisions, followed by temporal, environmental and driver-shift related variables. Along with supplementary information from unstructured taxi driver interviews, the model results are used to suggest policies for the improvement of John F. Kennedy (JFK) airport’s ground access and passenger satisfaction, i.e. the implementation of taxi driver frequent airport server punch cards and a time-specific ride share program.     

Microscopic decision model for pedestrian route choice at signalized crosswalks

In this paper, two‐tier mathematical models were developed to simulate the microscopic pedestrian decision‐making process of route choice at signalized crosswalks. In the first tier, a discrete choice model was proposed to predict the choices of walking direction. In the second tier, an exponential model was calibrated to determine the step size in the chosen direction. First, a utility function was defined in the first‐tier model to describe the change of utility in response to deviation from a pedestrian's target direction and the conflicting effects of neighboring pedestrians. A mixed logit model was adopted to estimate the effects of the explanatory variables on the pedestrians' decisions. Compared with the standard multinomial logit model, it was shown that the mixed logit model could accommodate the heterogeneity. The repeated observations for each pedestrian were grouped as panel data to ensure that the parameters remained constant for individual pedestrians but varied among the pedestrians. The mixed logit model with panel data was found to effectively address inter‐pedestrian heterogeneity and resulted in a better fit than the standard multinomial logit model. Second, an exponential model in the second tier was proposed to further determine the step size of individual pedestrians in the chosen direction; it indicates the change in walking speed in response to the presence of other pedestrians. Finally, validation was conducted on an independent set of observation data in Hong Kong. The pedestrians' routes and destinations were predicted with the two‐tier models. Compared with the tracked trajectories, the average error between the predicted destinations and the observed destinations was within an acceptable margin. Copyright © 2016 John Wiley & Sons, Ltd.     

Evaluating parking reservation policy in urban areas: An environmental perspective

This paper investigates a parking reservation mechanism to reduce car cruising to find parking. To consider the benefits for drivers and parking facility providers, we charge drivers for making reservations in addition to parking fees, by introducing a reservation pricing model that makes reservation prices equivalent to the value of saved search time. By modeling the number of vacant spaces as a stochastic variable, and applying binomial pricing methods, parking reservation prices are obtained. Numerical examples based on the data for two parking facilities in Taiwan are given.     

Network equilibrium for congested multi‐mode networks with elastic demand

This paper proposes an elastic demand network equilibrium model for networks with transit and walking modes. In Hong Kong, the multi‐mode transit system services over 90% of the total journeys and the demand on it is continuously increasing. Transit and walking modes are related to each other as transit passengers have to walk to and from transit stops. In this paper, the multi‐mode elastic‐demand network equilibrium problem is formulated as a variational inequality problem where the combined mode and route choices are modeled in a hierarchical logit structures and the total travel demand for each origin‐destination pair is explicitly given by an elastic demand function. In addition, the capacity constraint for transit vehicles and the effects of bi‐directional flows on walkways are considered in the proposed model. All these congestion effects are taken into account for modeling the travel choices. A solution algorithm is developed to solve the multi‐mode elastic‐demand network equilibrium model. It is based on a Block Gauss‐Seidel decomposition approach coupled with the method of successive averages. A numerical example is used to illustrate the application of the proposed model and solution algorithm.     

A two-stage taxi scheduling strategy at airports with multiple independent runways

Long taxiing times at large airports lead to fuel wastage and dissatisfied passengers. This paper investigates the 4D taxi scheduling problem in airports to minimize the taxiing time. We propose an iterative two-stage scheduling strategy. In the first stage, all aircrafts in a current schedule period are assigned initial 4D routes. In the second stage, landing aircrafts that are unavailable to fulfil their initially assigned routes are rescheduled using a shortest path algorithm based approach. In this paper, the simplified model used in most existing literature, that depicts a runway as having a single entrance and a single exit or even sets only one point to represent both of them has been discarded. Instead, we model the fact that a runway has multiple entrance and exit points and use an emerging concept—Runway Exit Availability (REA)—to measure the probability of clearing a runway from a specific exit during a specific time interval so that the taxiing scheduling model can be much higher approximation to the practical operation. An integer programming (IP) model factoring REA is proposed for assigning 4D taxiing routes in the first stage. The IP model covers most practical constraints faced in airport taxiing procedures, such as the rear-end/head-on conflict constraint, runway-crossing constraint, take-off/landing separation constraint, and taxi-out constraint. Besides, flight holding patterns at intersections are much more realistically modelled. Furthermore, to accelerate the solving process of the IP model, we have refined the formulation using several tricks. Simulation results by proposed scheduling approach for operations at the Beijing Capital International Airport (PEK) for an entire day demonstrate a surprising taxiing time saving against the empirical data and simulation results based on a strategy similar to what being used now days while showing an acceptable running time of our approach, which supports that our approach may help in real operation in the future.