Daisik Nam

Analysis of Grid Cell–Based Taxi Ridership with Large-Scale GPS Data

Understanding the spatial variation of taxi ridership is of critical importance to many government agencies and taxi companies because taxis’ location dependency on spatial pattern of passenger demand results in spatially unbalanced taxi demand and supply. This study presents an analysis of the spatial distribution of taxi ridership by using large-scale GPS taxi trip data collected from Seoul, South Korea. To capture the spatial variations better in taxi ridership, GPS entities were disaggregated into units of a uniform size with a grid cell decomposition method. A geographically weighted spatial regression was applied to model spatial correlations of factors associated with transit and urban density to taxi ridership. Results from the proposed method demonstrated a higher relationship between taxi and subway ridership in the regions where lower accessibility to subway stations existed. In these regions, taxis were found to perform as a complementary mode to subway. In residential and commercial districts, this analysis showed that population and employment were highly related to taxi ridership. In contrast, in central business districts it was the building area (floor space), rather than population and employment, that was highly related to taxi ridership.

Promoting Peer-to-Peer Ridesharing Services as Transit System Feeders

Peer-to-peer (P2P) ridesharing is a recently emerging travel alternative that can help accommodate the growth in urban travel demand and at the same time alleviate problems such as excessive vehicular emissions. Prior ridesharing projects suggest that the demand for ridesharing is usually shifted from transit, but its true benefits are realized when the demand shifts from single-occupancy vehicles. This study investigated the potential of shifting demand from private autos to transit by providing a general modeling framework that found routes for private vehicle users that were a combination of P2P ridesharing and transit. The Los Angeles Metro Red Line in California was considered for a case study because it has recently shown declining ridership trends. For successful implementation of a ridesharing system, strategically selecting locations for individuals to get on and off the rideshare vehicles is crucial, along with an appropriate pricing structure for the rides. The study conducted a parametric analysis of the application of real-time P2P ridesharing to feed the Los Angeles Metro Red Line with simulated demand. A mobile application with an innovative ride-matching algorithm was developed as a decision support tool that suggested transit-rideshare and rideshare routes.

Origin-destination trip table estimation based on subarea network OD flow and vehicle trajectory data

ABSTRACT Identifying accurate origin-destination (O-D) travel demand is one of the most important and challenging tasks in the transportation planning field. Recently, a wide range of traffic data has been made available. This paper proposes an O-D estimation model using multiple field data. This study takes advantage of emerging technologies – car navigation systems, highway toll collecting systems and link traffic counts – to determine O-D demand. The proposed method is unique since these multiple data are combined to improve the accuracy of O-D estimation for an entire network. We tested our model on a sample network and found great potential for using multiple data as a means of O-D estimation. The errors of a single input data source do not critically affect the model’s overall accuracy, meaning that combining multiple data provides resilience to these errors. It is suggested that the model is a feasible means for more reliable O-D estimation.

Peer-to-peer ridesharing with ride-back on high-occupancy-vehicle lanes: Toward a practical alternative mode for daily commuting

This paper presents a matching and pricing mechanism for a peer-to-peer ridesharing system that ensures a ride-back for matched riders. This service is thus presented as an alternative to driving alone for daily commuting. The matching algorithm is formulated as a minimum-cost, maximum-flow problem that is exact and quickly solvable on polynomial time. The mechanism modeling is based on the Vickrey–Clarke–Groves (VCG) mechanism that is known to be efficient, incentive compatible, and individually rational. However, VCG runs on a budget deficit in a ridesharing setting. To address this issue, participants were classified into drivers and riders in accordance with a novel multiparameter reserve price that fixes the revenue shortage problem and makes the system financially self-sustainable but in detriment of no longer being efficient. Agents’ utility functions include cost-sharing savings and high-occupancy-vehicle (HOV) travel time savings. The parametric study uses origin–destination demand data from the Southern California Association of Governments, and travel times are extracted from a professional web mapping service. Results show the method has a revenue surplus over most of the reserve-price parameter space and offers high matching rates attributable to the inclusion of HOV travel time savings and reserve-price structure. The reserve prices are drawn from empirical distributions of value of time and unit distance cost.

Determining locations of charging stations for electric taxis using taxi operation data

ABSTRACT The adequate provision of charging infrastructure is critical for the effective deployment of electric taxis. This study attempts to locate charging stations for electric taxis reflecting real-world taxi travel patterns identified from taxis equipped with digital tachographs. Data for one week are processed in order to estimate their charge demand. The estimated temporal distribution of charge demand indicates that it varies day-by-day and hour-by-hour. The maximum set covering model is applied for determining the locations of charging stations. The results show that the pre-specified service distance and service coverage rate (defined by the proportion of total demand served) can be critical factors for determining the number and location of charging stations. These factors should be carefully specified by considering the tradeoff between operational efficiency of charging facilities and user convenience.

Designing a Transit-Feeder System using Multiple Sustainable Modes: Peer-to-Peer (P2P) Ridesharing, Bike Sharing, and Walking

Peer-to-peer (P2P) ridesharing is a relatively new concept that aims to provide a sustainable method for transportation in urban areas. Previous studies have demonstrated that a system that incorporates both P2P ridesharing and transit would enhance mobility. We develop schemes to provide travel alternatives, routes and information across multiple modes, which includes P2P ridesharing, transit, city bike-sharing and walking, within the network. This study includes a case study of the operation of the multimodal system that includes P2P ridesharing participants (both drivers and riders), the Los Angeles Metro Red line subway rail, and the Los Angeles downtown bike-share system. The study conducts a simulation, enhanced by an optimization layer, of providing travel alternatives to passengers during morning peak hours. The results indicate that a multi-modal network expands the coverage of public transit, and that ride- and bike-sharing could be effective transit feeders when properly designed and integrated into the transit system.

Determination of Representative Path Set from Vehicle Trajectory Samples

AbstractThe representative path set between an origin and destination (OD) pair is useful for various transportation areas such as traffic assignment, travel information service, and traffic management. With the development of telecommunication technology, a car navigation system now collects trajectory-type data that can show the routes generated by drivers. Thus, the travel paths of individual travelers are available for the transportation study. Unfortunately, the availability of individual path data cannot guarantee direct application to the transportation model because it does not give us the significant path set between the OD pairs. Every driver in the real world has different starting and finishing points, yet these points are in a same origin and destination zone. In this study, a new methodology to determine the representative path set between an OD pair based on vehicle trajectory data is developed. This new model is tested with simulation data and compares various results according to clusteri...