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Spatiotemporal Characteristics of Ride-sourcing Operation in Urban Area

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Abstract

The emergence of ride-sourcing platforms has brought an innovative alternative in transportation, radically changed travel behaviors, and suggested new directions for transportation planners and operators. This paper provides an exploratory analysis on the operations of a ride-sourcing service using large-scale data on service performance. Observations over multiple days in Singapore suggest reproducible demand patterns and provide empirical estimates of fleet operations over time and space. During peak periods, we observe significant increases in the service rate along with surge price multipliers. We perform an in-depth analysis of fleet utilization rates and are able to explain daily patterns based on drivers' behavior by involving the number of shifts, shift duration, and shift start and end time choices. We also evaluate metrics of user experience, namely waiting and travel time distribution, and explain our empirical findings with distance metrics from driver trajectory analysis and congestion patterns. Our results of empirical observations on actual service in Singapore can help to understand the spatiotemporal characteristics of ride-sourcing services and provide important insights for transportation planning and operations.

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Book
The MATSim (Multi-Agent Transport Simulation) software project was started around 2006 with the goal of generating traffic and congestion patterns by following individual synthetic travelers through their daily or weekly activity programme. It has since then evolved from a collection of stand-alone C++ programs to an integrated Java-based framework which is publicly hosted, open-source available, automatically regression tested. It is currently used by about 40 groups throughout the world. This book takes stock of the current status. The first part of the book gives an introduction to the most important concepts, with the intention of enabling a potential user to set up and run basic simulations.The second part of the book describes how the basic functionality can be extended, for example by adding schedule-based public transit, electric or autonomous cars, paratransit, or within-day replanning. For each extension, the text provides pointers to the additional documentation and to the code base. It is also discussed how people with appropriate Java programming skills can write their own extensions, and plug them into the MATSim core. The project has started from the basic idea that traffic is a consequence of human behavior, and thus humans and their behavior should be the starting point of all modelling, and with the intuition that when simulations with 100 million particles are possible in computational physics, then behavior-oriented simulations with 10 million travelers should be possible in travel behavior research. The initial implementations thus combined concepts from computational physics and complex adaptive systems with concepts from travel behavior research. The third part of the book looks at theoretical concepts that are able to describe important aspects of the simulation system; for example, under certain conditions the code becomes a Monte Carlo engine sampling from a discrete choice model. Another important aspect is the interpretation of the MATSim score as utility in the microeconomic sense, opening up a connection to benefit cost analysis. Finally, the book collects use cases as they have been undertaken with MATSim. All current users of MATSim were invited to submit their work, and many followed with sometimes crisp and short and sometimes longer contributions, always with pointers to additional references. We hope that the book will become an invitation to explore, to build and to extend agent-based modeling of travel behavior from the stable and well tested core of MATSim documented here.
Article
The paper defines the field of Freight Demand Management (FDM), and positions it as an important component of transportation policy and management. To establish the rationale for FDM, the paper studies the effects of the agent interactions at the core of supply chains, and identifies the important role played by the receivers of supplies in determining when and how deliveries are made. The paper classifies the various modalities of FDM, and summarizes the real-life experiences of their implementation. To illustrate the potential of FDM, the paper analyzes Receiver-Led Consolidation (RLC) programs. The paper provides background on consolidation programs, and estimates a behavioral model to shed light on the factors explaining receivers’ interest in cargo consolidation. The resulting model is used to estimate expected participation in a RLC program in New York City. These results are complemented with freight-trip generation analyses, and a behavioral micro-simulation to estimate potential reductions in freight traffic and vehicle-miles-traveled. The results show that RLC programs could bring significant benefits to large metropolitan areas, reducing freight vehicle-miles-traveled and congestion levels.
Article
This paper develops procedures to identify and quantify the role played by large urban freight traffic generators as contributors of truck traffic in metropolitan areas. Although ports, container terminals, and other industrial sites are usually associated with large generations of truck trips, they only represent a small proportion of the total trips produced and attracted in large metropolitan areas. This paper analyzes the importance of other facilities such as ordinary businesses or buildings that individually or collectively (clusters) generate a large proportion of truck traffic. The paper discusses the opportunities of these large traffic generators for city logistics initiatives. In addition, the paper introduces two effective and complementary procedures to identify these generators using freight trip generation models estimated by the authors.
Article
A key element to enhance urban distribution is the adequate management of parking space, particularly for loading and unloading operations. An in-advance booking system able to be adjusted to users needs can be a very useful tool for city councils. Such a tool should be fed with criteria for allocating requests to time slots. In this paper we discuss alternative criteria for the parking slot assignment problem for urban distribution and we propose the use of mathematical programming formulations to model them. Several models are proposed, analyzed and compared among them. Extensive computational experience is presented with a detailed analysis and comparison, which provides quantitative indicators of the quality of each of the proposed models.
Article
The planning of freight transportation activities creates benefits as well as costs. Among those costs, some of them, namely externalities, fall on other people/society that have no direct relevance to the operations of transportation. Such externalities are accrued expenses which should be addressed by actual pricing policies to enable an efficient and sustainable freight transportation system. This paper reviews externalities in quantitative terms, and then provides pricing studies of these costs per unit of freight transported along with the most recent estimations. The associated negative externalities are structured by transportation mode (road, rail, maritime, and air).
Article
This paper investigates transport providers’ preferences for alternative loading bays and pricing policies. It estimates the importance of loading bays, the probability of finding them free and offers strategically relevant information to policy makers. The results underline the relevance of both preference heterogeneity and non-linear attribute effects. Three classes of agents are detected with substantially different preferences also characterized by non-linear sensitivity to attribute level variations. The specific freight sector, frequency of accesses and number of employees are all relevant covariates explaining different preferences for alternative transport providers’ categories. The implications of the results obtained are illustrated by simulating alternative policy scenarios. In conclusion, the paper underlines the need for rigorous policy analysis if the correct policy outcomes are to be estimated with an adequate level of accuracy.
Article
The provision and management of loading-unloading spaces for pickup-delivery vehicles are important issues in busy urban areas.In areas without loading-unloading spaces, delivery vehicles often park on the roadway lanes and this generates negative impacts in terms of road capacity and safety. The model described in this paper can be classified as a facility location problem. It determines the optimal location of loading-unloading spaces by minimizing the total cost that is comprised of delay penalty, fixed cost, operation cost, parking fee and waiting cost of both pickup-delivery vehicles as well as passenger cars. Furthermore this model takes into account both the behavior of pickup-delivery vehicles and that of passenger cars.
Article
This paper reviews the literature on parking with an emphasis on economic issues. Parking is not just one of the most important intermediate goods in the economy; it is also a vast use of land. Many theoretical and empirical papers analyze the quantity and pricing of parking by concentrating on particular aspects of the issue. The aspects covered in this review are cruising for parking, spatial competition, (minimum and maximum) parking requirements, parking pricing and road pricing in the bottleneck model, and temporal-spatial pricing. Various forms of parking, including residential parking, shopping mall parking, and employer-provided parking, are also reviewed before identifying understudied topics that should be on the research agenda.
Article
Significance Recent advances in information technologies have increased our participation in “sharing economies,” where applications that allow networked, real-time data exchange facilitate the sharing of living spaces, equipment, or vehicles with others. However, the impact of large-scale sharing on sustainability is not clear, and a framework to assess its benefits quantitatively is missing. For this purpose, we propose the method of shareability networks, which translates spatio-temporal sharing problems into a graph-theoretic framework that provides efficient solutions. Applying this method to a dataset of 150 million taxi trips in New York City, our simulations reveal the vast potential of a new taxi system in which trips are routinely shareable while keeping passenger discomfort low in terms of prolonged travel time.
Article
Urban freight (UF) operations include deliveries, pickups and transfers of physical goods within urban areas. A significant issue in UF operations is the need for law enforcement to deter non-freight vehicles from occupying loading/unloading bays. This paper aims to evaluate the level of service (LoS) of the loading/unloading bay infrastructure (i.e., the number of establishments/bay within a walking range) and the scale of illegal parking. A zone in Lisbon was selected as a case study and was analyzed, according to the relative locations of bays and establishments, as well as the establishment size and Number of Equivalent Commercial Stores (NECS). A higher LoS was expected for zones with a potentially higher UF parking demand. A Point Density and Commercial Homogeneity analysis provided an overview of the concentration of establishments. Clusters were confirmed with Global and Local Statistics of Spatial Association. The LoS was calculated for four commerce clusters, identified as likely areas of higher demand. Main clusters did not show an improved LoS. The usage of loading/unloading bays by all vehicles was observed for 17 days in a street with near-optimal spatial distribution of bays. The observed occupation of bays by non-freight vehicles was 80% of the freight vehicle demand.
Article
In this paper we present and analyze a queueing-theoretical model for autonomous mobility-on-demand (MOD) systems where robotic, self-driving vehicles transport customers within an urban environment and rebalance themselves to ensure acceptable quality of service throughout the entire network. We cast an autonomous MOD system within a closed Jackson network model with passenger loss. It is shown that an optimal rebalancing algorithm minimizing the number of (autonomously) rebalancing vehicles and keeping vehicles availabilities balanced throughout the network can be found by solving a linear program. The theoretical insights are used to design a robust, real-time rebalancing algorithm, which is applied to a case study of New York City. The case study shows that the current taxi demand in Manhattan can be met with about 8,000 robotic vehicles (roughly 60% of the size of the current taxi fleet). Finally, we extend our queueing-theoretical setup to include congestion effects, and we study the impact of autonomously rebalancing vehicles on overall congestion. Collectively, this paper provides a rigorous approach to the problem of system-wide coordination of autonomously driving vehicles, and provides one of the first characterizations of the sustainability benefits of robotic transportation networks.
Article
Carsharing programs that operate as short-term vehicle rentals (often for one-way trips before ending the rental) like Car2Go and ZipCar have quickly expanded, with the number of US users doubling every 1–2 years over the past decade. Such programs seek to shift personal transportation choices from an owned asset to a service used on demand. The advent of autonomous or fully self-driving vehicles will address many current carsharing barriers, including users’ travel to access available vehicles.This work describes the design of an agent-based model for shared autonomous vehicle (SAV) operations, the results of many case-study applications using this model, and the estimated environmental benefits of such settings, versus conventional vehicle ownership and use. The model operates by generating trips throughout a grid-based urban area, with each trip assigned an origin, destination and departure time, to mimic realistic travel profiles. A preliminary model run estimates the SAV fleet size required to reasonably service all trips, also using a variety of vehicle relocation strategies that seek to minimize future traveler wait times. Next, the model is run over one-hundred days, with driverless vehicles ferrying travelers from one destination to the next. During each 5-min interval, some unused SAVs relocate, attempting to shorten wait times for next-period travelers.Case studies vary trip generation rates, trip distribution patterns, network congestion levels, service area size, vehicle relocation strategies, and fleet size. Preliminary results indicate that each SAV can replace around eleven conventional vehicles, but adds up to 10% more travel distance than comparable non-SAV trips, resulting in overall beneficial emissions impacts, once fleet-efficiency changes and embodied versus in-use emissions are assessed.