Taxi System Research Articles

Migration-driven benefit in a two-species nutrient taxis system

A model describing the competition of two species for a common nutrient is studied. It is assumed that one of the competitors is motionless while the other has the ability to move upwards gradients of the nutrient density. It is proved that under suitable assumptions on the initial data, in the long time perspective the ability to move turns out to be a crucial feature providing competitive advantage irrespectively of a possible difference between the species with regard to their rates of proliferation and nutrient uptake.

Empty vehicle redistribution and fleet size in autonomous taxi systems

This study investigates empty vehicle redistribution algorithms for personal rapid transit and autonomous taxi services. The focus is on passenger service and operator cost. A new redistribution algorithm is presented in this study: index-based redistribution (IBR). IBR is a proactive method, meaning it takes into account both current demand and anticipated future demand, in contrast to reactive methods, which act based on current demand only. From information on currently waiting for passengers, predicted near-future demand and projected arrival of vehicles, IBR calculates an index for each vehicle station, and redistribution is done based on this index. Seven different algorithm combinations are evaluated using a test case in Paris Saclay, France (20 stations and 100 vehicles). A combination of simple nearest neighbours and IBR is shown to be promising. Its results outperform the other methods tested in peak and off-peak demand, in terms of average and maximum passenger waiting times as well as station queue length. The effect of vehicle fleet size on generalised cost is analysed. Waiting times, mileage and fleet size are taken into account while assessing this generalised cost.

Derivation of a bacterial nutrient-taxis system with doubly degenerate cross-diffusion as the parabolic limit of a velocity-jump process.

This paper is devoted to the justification of the macroscopic, mean-field nutrient taxis system with doubly degenerate cross-diffusion proposed by Leyva et al. (Phys A 392:5644-5662, 2013) to model the complex spatio-temporal dynamics exhibited by the bacterium Bacillus subtilis during experiments run in vitro. This justification is based on a microscopic description of the movement of individual cells whose changes in velocity (in both speed and orientation) obey a velocity jump process governed by a transport equation of Boltzmann type. For that purpose, the asymptotic method introduced by Hillen and Othmer (SIAM J Appl Math 61:751-775, 2000; SIAM J Appl Math 62:1222-1250, 2002) is applied, which consists of the computation of the leading order term in a regular Hilbert expansion for the solution to the transport equation, under an appropriate parabolic scaling and a first order perturbation of the turning rate of Schnitzer type (Schnitzer in Phys Rev E 48:2553-2568, 1993). The resulting parabolic limit equation at leading order for the bacterial cell density recovers the degenerate nonlinear cross diffusion term and the associated chemotactic drift appearing in the original system of equations. Although the bacterium B. subtilis is used as a prototype, the method and results apply in more generality.

Applications of the Bounded Total Variation Denoising Method to Urban Traffic Analysis

While it is believed that denoising is not always necessary in many big data applications, we show in this paper that denoising is helpful in urban traffic analysis by applying the method of bounded total variation denoising to the urban road traffic prediction and clustering problem. We propose two easy-to-implement methods to estimate the noise strength parameter in the denoising algorithm, and apply the denoising algorithm to GPS-based traffic data from Beijing taxi system. For the traffic prediction problem, we combine neural network and history matching method for roads randomly chosen from an urban area of Beijing. Numerical experiments show that the predicting accuracy is improved significantly by applying the proposed bounded total variation denoising algorithm. We also test the algorithm on clustering problem, where a recently developed clustering analysis method is applied to more than one hundred urban road segments in Beijing based on their velocity profiles. Better clustering result is obtained after denoising.

Combining taxi and social media data to explore urban mobility issues

Sensor networks, connected vehicles and mobile devices are currently used as data collectors in urban environments, data which can be used to better understand the cities’ dynamics. Specifically, the study of data-driven solutions to understand the behavior of cities and propose services to enhance the experiences of the citizens in their everyday life has become an active research topic. Many studies in this topic focus on exploring single data sources, and, to tackle this limitation we propose the SMAFramework to collect and integrate urban mobility data from heterogeneous sources. In this work, we propose a methodology that enables the standardization of spatiotemporal annotated data from sources such as Sensor Networks, Vehicular Networks, Social Media and the Web over a single data model (i.e., a Multi-Aspect Graph) and perform different analyses, such as the identification of taxi demand. To show the potential of this framework, we built and assessed a tool to evaluate spatiotemporal correlation of urban data from different sources. Real data collected from social media and a taxi system of the city of New York are used to evaluate this method. The obtained results allowed us to understand some of the applicabilities of the SMAFramework and also provided some insights on how to use it to resolve specific problems when analyzing mobility in urban environments. Using this methodology, we can obtain a better taxi positioning within the city by employing social media data.

Aircraft model for the automatic taxi directional control design

PurposeThis paper aims to present a concept of an automatic directional control system of remotely piloted aerial system (RPAS) during the taxiing phase. In particular, it shows the initial stages of the control laws synthesis-mathematical model and simulation of taxiing aircraft. Several reasons have emerged in recent years that make the automation of taxiing an important design challenge including decreased safety, performance and pilot workload.Design/methodology/approachThe adapted methodology follows the model-based design approach in which the control system and the aircraft are mathematically modelled to allow control laws synthesis. The computer simulations are carried out to analyse the model behaviour.FindingsChosen methodology and modelling technique, especially tire-ground contact model, resulted in a taxiing aircraft model that can be used for directional control law synthesis. Aerodynamic forces and moments were identified in the wind tunnel tests for the full range of the slip angle. Simulations allowed to compute the critical speeds for different taxiway conditions in a 90° turn.Practical implicationsThe results can be used for the taxi directional control law synthesis and simulation of the control system. The computed critical speeds can be treated as a safety limits.Originality/valueThe taxi directional control system has not been introduced to the RPAS yet. Therefore, the model of taxiing aircraft including aerodynamic characteristics for the full range of the slip angle has a big value in the process of design and implementation of the future auto taxi systems. Moreover, computed speed safety limits can be used by designers and standards creators.

Influencing factors and heterogeneity in ridership of traditional and app-based taxi systems

The growth of app-based taxi services has disrupted the urban taxi market. It has seen significant demand shift between the traditional and emerging app-based taxi services. This study explores the influencing factors for determining the ridership distribution of taxi services. Considering the spatial, temporal, and modal heterogeneity, we propose a mixture modeling structure of spatial lag and simultaneous equation model. A case study is designed with 6-month trip records of two traditional taxi services and one app-based taxi service in New York City. The case study provides insights on not only the influencing factors for taxi daily ridership but also the appropriate settings for model estimation. In specific, the hypothesis testing demonstrates a method for determining the spatial weight matrix, estimation strategies for heterogeneous spatial and temporal units, and the minimum sample size required for reliable parameter estimates. Moreover, the study identifies that daily ridership is mainly influenced by number of employees, vehicle ownership, density of developed area, density of transit stations, density of parking space, bike-rack density, day of the week, and gasoline price. The empirical analyses are expected to be useful not only for researchers while developing and estimating models of taxi ridership but also for policy makers while understanding interactions between the traditional and emerging app-based taxi services.

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

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.

Multiagent Spatial Simulation of Autonomous Taxis for Urban Commute: Travel Economics and Environmental Impacts

AbstractWith the likelihood of autonomous vehicle technologies in public transport and taxi systems increasing, their impact on commuting in real-world road networks is insufficiently studied. In t...

Shared Autonomous Taxi System and Utilization of Collected Travel-Time Information

Shared autonomous taxi systems (SATS) are being regarded as a promising means of improving travel flexibility. Each shared autonomous taxi (SAT) requires very precise traffic information to independently and accurately select its route. In this study, taxis were replaced with ride-sharing autonomous vehicles, and the potential benefits of utilizing collected travel-time information for path finding in the new taxi system examined. Specifically, four categories of available SATs for every taxi request were considered: currently empty, expected-empty, currently sharable, and expected-sharable. Two simulation scenarios—one based on historical traffic information and the other based on real-time traffic information—were developed to examine the performance of information use in a SATS. Interestingly, in the historical traffic information-based scenario, the mean travel time for taxi requests and private vehicle users decreased significantly in the first several simulation days and then remained stable as the number of simulation days increased. Conversely, in the real-time information-based scenario, the mean travel time was constant. As the SAT fleet size increased, the total travel time for taxi requests significantly decreased, and convergence occurred earlier in the historical information-based scenario. The results demonstrate that historical traffic information is better than real-time traffic information for path finding in SATS.

Mapping Rural Road Networks from Global Positioning System (GPS) Trajectories of Motorcycle Taxis in Sigomre Area, Siaya County, Kenya

Effective transport infrastructure is an essential component of economic integration, accessibility to vital social services and a means of mitigation in times of emergency. Rural areas in Africa are largely characterized by poor transport infrastructure. This poor state of rural road networks contributes to the vulnerability of communities in developing countries by hampering access to vital social services and opportunities. In addition, maps of road networks are incomplete, and not up-to-date. Lack of accurate maps of village-level road networks hinders determination of access to social services and timely response to emergencies in remote locations. In some countries in sub-Saharan Africa, communities in rural areas and some in urban areas have devised an alternative mode of public transport system that is reliant on motorcycle taxis. This new mode of transport has improved local mobility and has created a vibrant economy that depends on the motorcycle taxi business. The taxi system also offers an opportunity for understanding local-level mobility and the characterization of the underlying transport infrastructure. By capturing the spatial and temporal characteristics of the taxis, we could design detailed maps of rural infrastructure and reveal the human mobility patterns that are associated with the motorcycle taxi system. In this study, we tracked motorcycle taxis in a rural area in Kenya by tagging volunteer riders with Global Positioning System (GPS) data loggers. A semi-automatic method was applied on the resulting trajectories to map rural-level road networks. The results showed that GPS trajectories from motorcycle taxis could potentially improve the maps of rural roads and augment other mapping initiatives like OpenStreetMap.

Towards Smart Cities Development: A Study of Public Transport System and Traffic-related Air Pollutants in Malaysia

Increasing number of privately owned vehicles are depicting Malaysians preferred mode of mobility and lack of interest in the public transport system. In most developing countries such as Malaysia, motorized vehicles are the major contributors to air pollution in urban zones. Air pollution is a silent killer as it infiltrates the vital organs, leading to serious diseases and death. This research critically analyses the emissions of air pollutants such as CO, NO2, SO2, hydrocarbon, and PM from various sources in Malaysia with emphasis mainly on the emission of pollutants from motor vehicles. This research also discusses the public transport initiatives undertaken by the government of Malaysia such as enhancing the bus and rail system, transforming Malaysia’s taxi system, managing travel demand and enhancing the integration of urban public transport system. Furthermore, considering the smart cities initiatives, this research identified that weather, safety, security and inappropriate infrastructure are major barriers in Malaysia’s move towards the implementation of smart and eco-friendly mobility practices such as cycling, carpooling and car sharing.

A Cost-Oriented Optimal Model of Electric Vehicle Taxi Systems

This paper presents a cost optimal model of electric vehicle taxi systems based on the cost of electric vehicle taxi companies, charging or battery swap stations, passengers’ time, and emission costs. Considering the requirement of meeting passengers’ travel demands, an electric taxi demand model using transportation elasticity is formulated to optimize the number of electric taxis. The electric taxi demand model constitutes the measure of electric taxis, the cruise range, the amount of charging or battery swap stations, and other related factors. Simultaneously, to meet the charging requirements of electric taxis, a layout optimal model of EVSE (electric vehicle supply equipment) is designed using a Voronoi polygon method aimed at the cost of charging or battery swap stations and the range cost for changing. Finally, these aforementioned models are mixed to calculate the scale of electric taxis, the allocation of vehicle models, the optimizing level, and the site distribution of charging or battery swap stations. The key findings include the following: (1) the cost of the BEV(battery electric vehicle) taxi system is lower in the charging model than in the battery swap model, (2) the cost of the PHEV taxi system is lower than the BEV taxi system in the charging model, (3) in the Tongzhou District of Beijing, five charging or battery swap stations required being found to meet the charging demands of 5557 BEVs in the charging model or 5316 BEVs in the battery swap model, (4) according to the passengers’ travel demands and traffic conditions in Tongzhou, the BEV’s cruise range ought to be 250 km and BEV’s battery capacity should be 42.5 kW, the price of PHEV should be under 24,000 RMB and the electric-powered cruise range needs to be under 100 km, the daily operating time of EVs is around 16 h and the daily operating range is controlled under 380 km, and (5) a carbon tax is suggested to be imposed on ICEVs but the price should be under 20 RMB per ton.

Analysis of ground handling characteristic of aircraft with electric taxi system

Electric landing gear drive equipped with traction motors can provide taxi capability without the use of main engines or tractor. The ground handling characteristic of aircraft with electric taxi system is analyzed. The new mathematic model of aircraft ground maneuver is established, considering the 6-degree-freedom aircraft body and the flexible main strut and the powered wheel. Quasi-steady method is applied to calculate tire side forces and moments, to determine side slip. The simulation for the ground steering response of aircraft with electric taxi system is done by employing ADAMS and Simulink co-simulation platform. The dynamic responses of aircraft ground steering and landing gear spin-up and spring back are simulated. Different taxi conditions including powered nose wheel mode and powered main wheel mode are compared. Four conclusions are obtained: electric taxi system helps the aircraft turn on the spot and the turning radius is smaller than the aircraft using engines; differential powered main wheel mode has the minimum turning radius while turning-circle with uniform velocity, and it has smaller difference between two vertical loads of main landing gear than powered nose wheel mode; in the case of the same steering angle, the extreme velocity of differential powered main wheel mode before side slip is larger than powered nose wheel mode; and pre-rotation of powered main wheel decreases the spin-up drag load and spring back drag load.

Collective taxis in 1930s Paris: A contribution to an archaeology of ‘uberization’

The recent ‘uberization’ of Paris taxis has brought major, long-standing issues back to the surface: A historic analysis of how the Paris taxi system has functioned over the last century offers a clear explanation of why it is difficult to hail a taxi in the middle of the street, as opposed to New York for example. Paris taxis, which have been the subject of never-ending discussion, were associated during their early years with a heroic Great War mythology, and were connected to the Parisian car industry’s beginnings. Collective use of taxis existed in the 1930s; however, these services disappeared as a result of severe monopolistic regulation. Using different sources, this paper aims to define why and how collective taxis grew and failed in 1930s Paris.

Toward Urban Electric Taxi Systems in Smart Cities: The Battery Swapping Challenge

Despite the clear benefits of electric vehicles (EVs) in terms of reducing greenhouse gas emissions and traditional energy consumptions, the popularization of EVs remains a challenge in the short run. There are currently two major ways of refueling electric taxicabs (ETs): recharging and battery swapping. ETs usually choose battery swapping so as not to waste precious time during their daily work. While previous studies focused on planning battery swapping stations for private EVs, we investigate ways of supporting the upgrade of an entire urban taxi system, with demands differing both in scale and nature. Furthermore, most ETs are fully charged in the early morning and need to swap battery in approximately the same time period of the day, which results in a bottleneck for battery swapping and hurts the quality of service (QoS) of the taxicab fleet. With this insight, we model the ET fleet as a mobile sensor network, analyze the historical sensing data of taxi routes, and evaluate the battery swapping demand profile and the power consumption of individual taxis, as well as the driving time between positions in the road network. Based on these inputs, we propose a method to calculate an optimized battery swapping station scheme, then describe a real-time algorithm to schedule a subset of the unoccupied taxicabs to swap batteries early by giving them allowances to avoid congestion. Our strategies are then evaluated via a real-world 366-day, 3 976-taxi dataset. The results demonstrate that compared to uniform deployment, our planning scheme reduces the average time cost by 67.2%; and based on our deployment, our scheduling strategy decreases the in-station queuing time by 45.63%, 52.26%, and 29.57%, and the average driving time cost to the stations by 42.3%, 43.69%, and 28.77% compared to actual taxicab refueling, random scheduling, and a static heuristic strategy, respectively. Furthermore, our approach reduces the number of battery swapping that last more than 30 min by 40.8%, which is a significant improvement on the QoS of the whole system.

An Agent-Based Simulation Model for Shared Autonomous Taxi System

An Agent-Based Simulation Model for Shared Autonomous Taxi System

Investigation and design of an axial flux permanent magnet machine for a commercial midsize aircraft electric taxiing system

In this study, an electric taxiing drive system for a commercial midsize aircraft is proposed. Four electric motors are integrated in the main landing gears to enable electric drive of the aircraft during the taxiing process. To achieve the same performance, a system level analysis is conducted to investigate the drive cycle requirements. Based on the recorded aircraft taxiing data, a variety of taxiing drive cycles are used as inputs to size the powertrain components. An axial flux permanent magnet (AFPM) machine is then proposed in order to meet the compact space and high torque output requirement. Both analytical calculations and three-dimensional finite element model are applied to design and improve the machine performance. A wide range of simulations has been conducted and the results confirmed that the proposed AFPM machine fulfils the given requirements for an electric taxiing drive system.

The Impact of Green Taxiing Systems Using on Airport

The aircraft’s engine isn’t designed for taxiing on the ground. This article describes the green taxiing systems and compares their advantages and disadvantages. Setting the Beijing Capital International Airport as an example, the taxiing fuel consumption and pollutant emissions calculation model were established. This paper calculates the total fuel consumption and pollutant emissions of the different modes in one year. The results show that the green taxiing systems can significantly reduce fuel consumption and HC, CO, CO2, NOx emissions. TaxiBot is better for reducing fuel consumption and NOx emissions.

Mining the Relationship between Spatial Mobility Patterns and POIs

Passengers move between urban places for diverse interests and drive the metropolitan regions as the aggregation of urban places to group into network communities. This paper aims to examine the relationship between the spatial patterns (represented by the network communities) of mobility flows and places of interest (POIs). Furtherly, it intends to identify the categories of POIs that play the most significant role in shaping the spatial patterns of mobility flows. To achieve these purposes, we partition the study area into disjoint regions and construct the network with each partitioned region as a node and connection between them as links weighted by the mobility flows. The community detection algorithm is implemented on the network to discover spatial mobility patterns, and the multiclass classification based on the logistic regression method is adopted to classify spatial communities featured by POIs. Taking the taxi systems of Shanghai and Beijing as examples, we detect spatial communities based on the movement strengths among regions. Then we investigate their correlations with POIs. It finds that communities’ modularity correlates linearly with POIs; particularly governments, hotels, and the traffic facilities are of the most significance for generating the mobility patterns. This study can provide valuable insight into understanding the spatial mobility patterns from the perspective of POIs.