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This paper proposes and analyzes a new transit system that integrates the traditional fixed-route service with a demand-adaptive service. The demand-adaptive service connects passengers from their origin/destination to the fixed-route service in order to improve accessability. The proposed hybrid design is unique in that it operates the demand-adaptive service with a stable headway to cover all stops along a paired fixed-route line. Pairing demand-adaptive vehicles with a fixed-route line simplifies the complexity of on-demand routing, because the vehicles can follow a more predictable path and can be dispatched on intervals coordinated with the fixed-route line. The design of the two services are closely coupled to minimize the total system cost, which incudes both the transit agency’s operating cost and the user cost. The optimal design model is formulated as a mixed integer program and solved using a commercially available metaheuristic. Numerical experiments are conducted to compare the demand adaptive paired-line hybrid transit (DAPL-HT) system with two related transit systems that may be considered its special cases: a fixed-route system and a flexible-route system. We show that the DAPL-HT system outperforms the other two systems under a wide range of demand levels and in various scenarios of input parameters. A discrete-event simulation model is also developed and applied to confirm the correctness of the analytical results. [ABSTRACT FROM AUTHOR]

Integration of demand response (DR) programs and battery energy storage system (BESS) in microgrids are beneficial for both microgrid owners and consumers. The intensity of DR programs and BESS size can alter the operation of microgrids. Meanwhile, the optimal size for BESS units is linked with the uncertainties associated with renewable energy sources and load variations. Similarly, the participation of enrolled customers in DR programs is also uncertain and, among various other factors, uncertainty in market prices is a major cause. Therefore, in this paper, the impact of DR program intensity and BESS size on the operation of networked microgrids is analyzed while considering the prevailing uncertainties. The uncertainties associated with forecast load values, output of renewable generators, and market price are realized via the robust optimization method. Robust optimization has the capability to provide immunity against the worst-case scenario, provided the uncertainties lie within the specified bounds. The worst-case scenario of the prevailing uncertainties is considered for evaluating the feasibility of the proposed method. The two representative categories of DR programs, i.e., price-based and incentive-based DR programs are considered. The impact of change in DR intensity and BESS size on operation cost of the microgrid network, external power trading, internal power transfer, load profile of the network, and state-of-charge (SOC) of battery energy storage system (BESS) units is analyzed. Simulation results are analyzed to determine the integration of favorable DR program and/or BESS units for different microgrid networks with diverse objectives. [ABSTRACT FROM AUTHOR]

The autonomous road vehicle (AV) technology implies significant alteration of urban mobility services. The identified transit modes based on AVs are the individual cars, the demand-responsive public transportation with small or medium sized pods and the high capacity public transportation on arterial routes. The introduction of the telematics-based, shared, demand responsive mobility service requires new information management methods. Accordingly, the aim of our research was to model the structure and the operation of this rather complex information system considering both the operators and the users. Since the passenger functions are the keys of the advanced information service the conceptual plan of the mobile application with personalized functions has been also elaborated. The research questions were: how the architecture and the functions of the information system are to be modelled, what the novel information management functions of passengers and operators are, what data structure is needed and how it is related to the functions as well as what kind of functions are to be realized in the mobile application. The results are applicable as foundations for innovation and development projects aiming realization of either the back-end or the front-end components and for planning information management processes. [ABSTRACT FROM AUTHOR]

Demand response and distributed generation are key components of power systems. Several challenges are raised at both technical and business model levels for integration of those resources in smart grids and microgrids. The implementation of a distribution network as a test bed can be difficult and not cost-effective; using computational modeling is not sufficient for producing realistic results. Real-time simulation allows us to validate the business model's impact at the technical level. This paper comprises a platform supporting the real-time simulation of a microgrid connected to a larger distribution network. The implemented platform allows us to use both centralized and distributed energy resource management. Using an optimization model for the energy resource operation, a virtual power player manages all the available resources. Then, the simulation platform allows us to technically validate the actual implementation of the requested demand reduction in the scope of demand response programs. The case study has 33 buses, 220 consumers, and 68 distributed generators. It demonstrates the impact of demand response events, also performing resource management in the presence of an energy shortage. [ABSTRACT FROM AUTHOR]

In the dial-a-ride services, customers specify pickup and drop-off locations and their times for transport. The operator aims at constructing cheap itineraries while minimizing customer inconvenience. This problem has been studied as the Dial-a-Ride Problem (DARP), which consists of both spatial and temporal factors. This article studies the impact of spatial and temporal variation on multivehicle DARP using route construction heuristics. Our work highlights the impact of these variations on the customer disutility and transportation cost. The study will help the service operators in selecting an appropriate construction heuristic while expanding the DARP service in terms of service area, service duration, or planning for a sudden growth in the number of customers. The results show that if the operator is planning to expand the area of service, the Saving Heuristic is more appropriate for larger operators while Insertion Heuristic with spatial sorting scheme is better for smaller operators with limited number of vehicles. If the operator is expanding the service in terms of service duration, from 8 to 24 hours daily, for instance, or preparing for a growth in the number of customers, the Saving Heuristic is better for both smaller and larger service operators. [ABSTRACT FROM AUTHOR]

Transport models are used to evaluate new infrastructure and public transport services, varied levels of demand, and new ideas for demand management. Exploring these proposals virtually is easier than implementation and testing in situ. However, existing models are based around traditional forms of transportation. As part of a feature analysis using a case study approach, three different simulation packages (a simple custom-developed package, traffic microsimulation, and agent-based simulation) are used to develop and demonstrate simulations of demand-responsive transportation (DRT) and analyze the advantages and disadvantages of each simulation approach for evaluating DRT. While the simulations display some relational replication (meaning they produce similar relational patterns with respect to certain variables), they do not show distributional replication (that is, the value of the results is not statistically similar), meaning that under- or over-estimation of predicted travel could occur. Recommendations for the application of each modeling approach are made. [ABSTRACT FROM PUBLISHER]

Abstract: Demand responsive collective transportation might be a solution to serve thin flows that occur when the average demand per time unit for travel between particular locations is small. Small capacity and/or specially equipped vehicles are deployed to serve low population density areas and mobility impaired passengers. The variability of the demand and the low vehicle capacity require daily optimal planning of routes. The cost for daily tours heavily depends on the temporal and spatial distribution of the demand. This paper proposes a co-simulation model to evaluate the profitability of thin flow service providers over multiple years of operation under specific condition of public compensation (subsidizing). [ABSTRACT FROM AUTHOR]

The Brazilian Electricity Regulatory Agency (ANEEL) presented a proposal to revise the tariff structure of distribution companies in Brazil. One of the main approved suggestions was to establish a mechanism called Tariff Flags, which aims to foster a Demand Response Program in Brazil via an increase in the energy tariff. In this work, the proposed mechanism is reviewed in detail and the expected results of its application are simulated and analyzed under different perspectives. This paper shows that the system operation directly impacts the Demand Response Program, since the spot prices will define which Tariff Flag should be triggered. In order to encompass and assess the main consequences of its application, this paper presents the expected effects on energy spot prices, system operating costs, probability of triggering each flag, investment recovery for utilities and finally, the impact for the final consumers. The case studies presented in this paper were developed using real information about the Brazilian electrical system for each economic sector and the price-demand elasticity is discussed using the literature for this application. Finally, some conclusions and guidelines are provided to improve the application of the mechanism. [ABSTRACT FROM AUTHOR]

Demand response (DR) can be counted as an effective congestion management method in power systems. However, appointing the optimal buses for the demand response programs (DRPs) implementation is one of the main challenges for the power system operators. In this paper, a new procedure has been developed by which the optimal locations and times of DRPs implementation are determined. Optimal buses are identified based on the power transfer distribution factors (PTDFs), available transfer capability, and dynamic dc optimal power flow problem. Applying the developed method results in reducing lines’ congestion, increasing customers, and independent system operator's benefits, improving load curve's characteristics, preventing line outages and black outs, and consequently increasing the network reliability. The proposed method has been applied on the IEEE 39-bus New England test system. Results indicate the effectiveness and practical benefits of the proposed method. [ABSTRACT FROM AUTHOR]

• Overall user experience is crucial for adoption of new automated on-demand ride pooling services with flexible stops. • The novel concept of virtual stops as virtual traffic infrastructure and user-centered HMI is introduced to support users in pick-up scenarios. • The first HMI prototype for virtual stops shows high pragmatic quality and addresses user pain points by providing information efficiently. • Design guidelines are derived to iteratively develop augmented reality prototypes for hand held devices onwards. Sustainable and connected mobility concepts for the future are increasingly sought-after. Among many factors, providing high service quality is key to their commercial success. In pick-up scenarios of shared automated mobility on-demand (SAMOD), the new concept of virtual stops (vStop) improves control and planning, and the human-machine interface (HMI) associated with it aims to increase usability for users. This paper elaborates on the new concept in-depth and presents two user-centered online-interview studies. The objectives were 1) capturing users' information requirements when using SAMOD, and 2) evaluating an early-stage vStop HMI prototype in terms of user experience. Results show that the HMI prototype's high pragmatic quality corresponds to the user's desire for distinctive information. This aspect becomes especially valuable to users when picked up at unfamiliar traffic locations. Conclusions from both studies lead to initial design guidelines for a vStop HMI, which could be implemented using mobile augmented reality. This work is a starting point for user-centered HMI development for vStops. It contributes to widespread deployment of SAMOD in the future and fosters the change towards more sustainable mobility solutions. [ABSTRACT FROM AUTHOR]

• A model is proposed for modular vehicle-based routing with platooning and transfers. • A Steiner-tree inspired large neighborhood search heuristic is proposed. • Experiments conducted on Anaheim network with up to 75 vehicles and 150 requests. • Platooning can save up to 52% in vehicle travel cost and 41% passenger service time. • Modular vehicles benefit most from serving "enclave pairs" as dynamic hub-and-spoke. Modular vehicles (MV) possess the ability to physically connect/disconnect with each other and travel in platoon with less energy consumption. A fleet of demand-responsive transit vehicles with such technology can serve passengers door to door or have vehicles deviate to platoon with each other to travel at lower cost and allow for en-route passenger transfers before splitting. A mixed integer linear programming (MILP) model is formulated to solve this "modular dial-a-ride problem" (MDARP). A heuristic algorithm based on Steiner-tree-inspired large neighborhood search is developed to solve the MDARP for practical scenarios. A set of small-scale synthetic numerical experiments are tested to evaluate the optimality gap and computation time between exact solutions of the MDARP using commercial software and the proposed heuristic. Large-scale experiments are conducted on the Anaheim network with up to 75 vehicles and 150 requests considering 378 candidate join/split nodes to further explore the potentials and identify the ideal operation scenarios of MVs. The results show that MV technology can save up to 52% in vehicle travel cost, 41% in passenger service time, and 29% in total cost against existing on-demand mobility services in the scenarios tested. Results suggest that MVs best benefit from platooning by serving "enclave pairs" as a hub-and-spoke service. [ABSTRACT FROM AUTHOR]

Dial-a-ride (DAR) is a shared-ride service that provides mobility to transportation-disadvantaged individuals who are unable to use public transit. While most DAR studies focus on optimizing operations, our research explores the feasibility and benefits of outsourcing outlier trips to transportation network companies (TNCs) to minimize the combined service delivery cost. To achieve this goal, we formulate a multi-vehicle DAR problem (DARP) with trip outsourcing to TNCs, which can be solved optimally for small scale instances. To solve larger instances, we propose a two-stage solution framework to improve DAR routes from commercially available software. Firstly, we develop an integer programming model to re-optimize individual routes with trip outsourcing. Secondly, we design a multi-vehicle heuristic that considers reinserting trips initially designated for outsourcing back into the DAR fleet, as well as reinsertion and exchange of remaining trips among routes. We apply the approach to a medium-sized DAR operator in Maryland and achieve cost reductions of 7%-13% depending on the TNC volume discount negotiated by the DAR company. • We formulate a multi-vehicle DARP with trip outsourcing to ridesourcing companies. • A two-stage framework is proposed to improve DAR routes from commercial software. • A single-vehicle DARP with trip outsourcing re-optimizes individual routes. • A multi-vehicle heuristic considers reinserting trips selected for outsourcing. • Real-world case study on a DAR operator shows 7%-13% operational cost reductions. [ABSTRACT FROM AUTHOR]

Access to public transport is widely recognized as a welfare and livelihood issue. In sub-Saharan Africa (SSA), public transport is predominately paratransit which holds the largest modal share. Paratransit services are often accessed through their terminals and service routes, critical elements which directly distribute the service to populations. However, the allocation of paratransit terminals and routes is rarely equitable in SSA, where they are often erratic, dedicated to profitable routes, and vehicles not available on some routes and at certain times of the day (e.g. night time). Consequently, this study evaluates the allocation of paratransit terminals and routes, their access to populations, and overall coverage in the Oforikrom Municipality of Ghana. This was achieved by compiling General Transit Feed Specification (GTFS)-like data, conducting a nearest neighbor analysis and a service area estimation, and evaluating the allocation of paratransit service routes. The findings show that paratransit allocation is highly inefficient being associated with fragmented routes and poor connectivity, where the travel distance to paratransit service ranges from 1 to 2800 m, and existing routes can be reduced considerably by 53%. A close matching with an R-square of 0.977 was found between the proportion of the population served by paratransit and the coverage of the land area where they live. Economic status based on the relative wealth index was found to be moderately related to the travel distance to paratransit services, the population served, and the land area covered. While paratransit operators and driver unions have their roles, the inefficient configuration of terminals and routes is a direct outcome of the existing systemic structural arrangement with paratransit operators mostly built on underlying political economy, social injustice, labor exploitation, and lack of investment. It is recommended that enhanced paratransit allocation be co-formulated, co-developed, and co-enforced by all stakeholders, especially local governments, driver unions, paratransit operators, passengers, and pedestrians. [ABSTRACT FROM AUTHOR]

The Dial-a-Ride problem can contain various constraints for pickup-delivery requests, such as time windows and ride time constraints. Given a tour as a sequence of pickups and deliveries, there exist polynomial time algorithms to find a schedule respecting these constraints (provided that there exists one). However, if no such schedule exists, it is natural to ask for a schedule minimising constraint violations. We model a generic fixed-sequence scheduling problem, which we call Min Pickup-Delivery Scheduling , that allows violation of time window constraints (by late visits) and ride time constraints, both penalised with linear penalty functions. Although our model only considers these two types of time constraints, we show that it can express other common time constraints such as earliness and waiting times. We prove that Min Pickup-Delivery Scheduling is APX -hard, even in the very restrictive case where only the ride time constraints can be violated and the time windows have the same length. Conversely, when only the time window constraints can be violated (by late visits), we present a polynomial time algorithm to solve the problem. Then we focus on instances with some specific structural properties and present two polynomial-time algorithms: one for the case where all the ride time constraints are bounded by a constant, and a second one for the case where all the pickups precede all the deliveries in the sequence of stops. [ABSTRACT FROM AUTHOR]

[Display omitted] In most cities, transit consists solely of fixed-route transportation, whence the inherent limited Quality of Service for travellers in suburban areas and during off-peak periods. On the other hand, completely replacing fixed-route (FR) with demand-responsive (DR) transit would imply a huge operational cost. It is still unclear how to integrate DR transportation into current transit systems to take full advantage of it. We propose a Continuous Approximation model of a transit system that gets the best from fixed-route and DR transportation. Our model allows deciding whether to deploy a FR or a DR feeder, in each sub-region of an urban conurbation and each time of day, and to redesign the line frequencies and the stop spacing of the main trunk service. Since such a transit design can adapt to the spatial and temporal variation of the demand, we call it Adaptive Transit. Numerical results show that, with respect to conventional transit, Adaptive Transit significantly improves user-related cost, by drastically reducing access time to the main trunk service. Such benefits are particularly remarkable in the suburbs. Moreover, the generalized cost, including agency and user cost, is also reduced. These findings are also confirmed in scenarios with automated vehicles. Our model can assist in planning future-generation transit systems, able to improve urban mobility by appropriately combining fixed and DR transportation. [ABSTRACT FROM AUTHOR]

In this paper, bilateral contracting and selling price determination problems for an electricity retailer in the smart grid environment under uncertainties have been considered. Multiple energy procurement sources containing pool market (PM), bilateral contracts (BCs), distributed generation (DG) units, renewable energy sources (photovoltaic (PV) system and wind turbine (WT)) and energy storage system (ESS) as well as demand response program (DRP) as virtual generation unit are considered. The scenario-based stochastic framework is used for uncertainty modeling of pool market prices, client group demand and variable climate condition containing temperature, irradiation and wind speed. In the proposed model, the selling price is determined and compared by the retailer in the smart grid in three cases containing fixed pricing, time-of-use (TOU) pricing and real-time pricing (RTP). It is shown that the selling price determination based on RTP by the retailer leads to higher expected profit. Furthermore, demand response program (DRP) has been implemented to flatten the load profile to minimize the cost for end-user customers as well as increasing the retailer profit. To validate the proposed model, three case studies are used and the results are compared. [ABSTRACT FROM AUTHOR]

Demand responsive Pelican Crossing has been used widely at midblock pedestrian crossing. However this controller has not been tested in mixed traffic conditions, where the traffic streams are heterogeneous, lack of lane discipline and high proportion of motorcycles. This paper describes an evaluation of the performance of demand responsive Pelican Crossing using Extension Principle (PC VAC-EP) under mixed traffic conditions. An investigation was carried out to find the most appropriate extension time for the PC VAC-EP that was suitable for mixed traffic. The best performance of the PC VAC-EP was, then, compared with the Pelican Crossing Conventional (PC C) on validated simulated pedestrian crossing. The effectiveness of the proposed PC VAC-EP and PC C were evaluated by the simulation program VISSIM. [ABSTRACT FROM AUTHOR]

While providing essential access for large portions of city populations, the quality of paratransit services in Sub-Saharan African cities is poor. Poor quality of service can be attributed to two features of the paratransit business operating model: driver remuneration on the basis of a daily ‘target system’; and cash-based business management in which vehicle depreciation is ignored as an operating expense. In Kenya, the voluntary organisation of fragmented inter-city matatu businesses into Savings and Credit Cooperatives (SACCOs) has resulted in improved service, regulatory compliance and technology adoption, but little is known of how they operate. The aim of this paper is to gain insight into how the Kenyan inter-city matatu SACCOs are organised and have improved services, and to explore the transferability of this experience and the lessons it offers. The exploratory nature of the study, and constrained resources, necessitated that the research adopt a qualitative case study method. It was found that most of the case study SACCOs have addressed the root causes of poor service quality by shifting the remuneration of drivers from daily cash targets to salaries, and by requiring vehicle depreciation costing through compulsory contributions to the cooperative's capital savings from which vehicle acquisition and repair loans can be derived. Due to the particular shuttle-like nature of inter-city services and the considerable institutional support that exists in Kenya for cooperatives, the direct transfer of successes to other contexts is likely to prove difficult. Identifying the features of the inter-city SACCO model that have led to paratransit service improvements, and attempting to replicate these, may therefore be more effective than attempting to replicate the model in its entirety. These features are argued to be operator consolidation, accompanied by salaried drivers, systematic vehicle monitoring and compulsory vehicle depreciation costing. They can be adopted in other forms of paratransit organisation and regulation, but will require considerable adaptation to context. [ABSTRACT FROM AUTHOR]

This paper explores the use of combination of flexible alternating current transmission system (FACTS) devices, demand response (DR) programs, and generation redispatch (GR) in short-term congestion management as well as minimization of operation costs under contingency conditions in power systems. To achieve this, a multi-stage market clearing procedure is formulated. At the first stage, the market is cleared based on generation cost minimization, without considering network constraints. Market clearing formulation for the second stage is developed considering congestion and generation costs, in which FACTS device (Thyristor Controlled Series Capacitor) and DR programs (Direct Load Control besides Time-Of-Use) are optimally coordinated with GR in the presence of network constrains, to manage the congestion at minimum costs. In addition, to make conditions more realistic, the operational conditions spanning for a year (four seasons, day by day) are considered in this study. Finally, the paper prioritizes utilizing these approaches for different contingencies. The proposed formulation is verified on IEEE 14-bus and IEEE 30-bus test systems with supporting numerical and graphical results. Results show that applying GR with DR programs is the prioritized strategy in relieving congestion and reducing generation costs in the outage of the most sensitive lines contingency. [ABSTRACT FROM AUTHOR]

The Heterogeneous Dial-a-Ride Problem (HDARP) is an important problem in reduced mobility transportation. Recently, several extensions have been proposed towards more realistic applications of the problem. In this paper, a new variant called the Multi-Depot Multi-Trip Heterogeneous Dial-a-Ride Problem (MD-MT-HDARP) is considered. A mathematical programming formulation and three metaheuristics are proposed: an improved Adaptive Large Neighborhood Search (ALNS), Hybrid Bees Algorithm with Simulated Annealing (BA-SA), and Hybrid Bees Algorithm with Deterministic Annealing (BA-DA). Extensive experiments show the effectiveness of the proposed algorithms for solving the underlying problem. In addition, they are competitive to the current state-of-the-art algorithm on the MD-HDARP. [ABSTRACT FROM AUTHOR]

Dial-a-ride services provide disabled and elderly people with a personalized mode of transportation to preserve their mobility. Typically, several users with different pickup and dropoff locations are transported on a vehicle simultaneously. The focus in dial-a-ride problems (DARPs) is mainly on minimizing routing cost. Service quality has been taken into account in the models by imposing time windows and limiting the maximum ride time of each user. We extend the classical DARP by an additional feature of service quality referred to as driver consistency. Customers of dial-a-ride services are often sensitive to changes in their daily routine. This aspect includes the person who is providing the transportation service, i.e., the driver of the vehicle. Our problem, called the driver consistent dial-a-ride problem (DC-DARP), considers driver consistency by bounding the maximum number of different drivers that transport a user over a multi-period planning horizon. We propose different formulations of the problem and examine their efficiency when applied in a Branch-and-Cut fashion. Additionally, we develop a large neighborhood search algorithm that generates near-optimal solutions in a short amount of time. Over 1000 instances are generated with close reference to real world scenarios. Extensive computational experiments are conducted in order to assess the quality of the solution approaches and to provide insights into the new problem. Results reveal that the cost of offering driver consistency varies greatly in magnitude. Depending on the instance, the cost of assigning one driver to each user can be up to 27.98% higher compared to a low-cost solution. However, routing cost increases by not more than 5.80% if users are transported by at least two drivers. [ABSTRACT FROM AUTHOR]

This paper develops empirical models for evaluating the service quality (SQ) of paratransit. Specifically, several models are developed based on structural equation modeling (SEM) using twenty-four SQ variables. To calibrate those models, a data set of 2008 paratransit users of Dhaka City are utilized, who were interviewed with a structured questionnaire to know their experience, level of satisfaction and opinion about the existing service as well as their expectations. SEM reveals the observed and latent SQ variables and their relationship with the overall SQ of paratransit. Among the different models developed, the best one is selected using statistical parameters and resemblance with real life expectations. Out of twenty-four SQ variables, ‘Punctuality and Reliability’ and ‘Service Features’ are respectively found to be the observed and latent variables having the greatest influence on the paratransit SQ. Moreover, the effect of heterogeneity among users on the performance of the best model is investigated. All the study findings support the data collected from the paratransit users. The research outcomes can be utilized by the city transportation officials of developing countries to improve the overall paratransit performance to attract new users as well as retain the current ones. [ABSTRACT FROM AUTHOR]

The operating cost of a demand responsive transit (DRT) system strictly depends on the quality of service that it offers to its users. An operating agency seeks to minimize operating costs while maintaining the quality of service while users experience costs associated with scheduling, waiting, and traveling within the system. In this paper, an analytical model is employed to approximate the agency's operating cost for running a DRT system with dynamic demand and the total generalized cost that users experience as a result of the operating decisions. The approach makes use of Vickrey's (1969) congestion theory to model the dynamics of the DRT system in the equilibrium condition and approximate the generalized cost for users when the operating capacity is inadequate to serve the time-dependent demand over the peak period without excess delay. The efficiency of the DRT system can be improved by optimizing one of three parameters that define the agency's operating decision: (1) the operating capacity of the system, (2) the number of passengers that have requested a pick-up and are awaiting service, and (3) the distribution of requested times for service from the DRT system. A schedule management strategy and dynamic pricing strategies are presented that can be implemented to manage demand and reduce the total cost of the DRT system by keeping the number of waiting requests optimized over the peak period. In the end, proposed optimization strategies are compared using a numerical example. [ABSTRACT FROM AUTHOR]

Door-to-door transportation service for elderly and persons with disabilities is often called dial-a-ride (DAR), and is usually provided by transit agencies through private contractors. Growth in DAR ridership is reported across the United States and this tendency will likely continue due to aging population. Such trends encourage development of models that can provide decision support in planning new DAR systems or expanding existing ones. Several statistical models were previously developed to predict the required DAR system capacity, given various characteristics of the service region, level-of-service requirements and operator constraints. Our work contributes to this line of research by proposing statistical and machine learning approaches that provide more accurate predictions over a wider range of scenarios. This is accomplished through transformation of variables and application of generalized linear model and support vector regression. Proposed models are built into an online tool that can help transit planners and policy makers: (a) estimate the capacity and operating cost of a DAR system needed to provide the desired level of service, (b) explore tradeoffs between system costs and levels of service, and (c) compare the cost of providing DAR service with other transportation alternatives (e.g., taxi, conventional transit). [ABSTRACT FROM AUTHOR]

On-demand transport services in the form of dial-a-ride and taxis are crucial parts of the transport infrastructure in all major cities. However, not all on-demand transport services are equal: not-for-profit dial-a-ride services with coordinated drivers significantly differ from profit-motivated taxi services with uncoordinated drivers. In fact, there are two key threads of work on efficient scheduling, routing, and pricing for passengers: dial-a-ride services; and taxi services. Unfortunately, there has been only limited development of algorithms for joint optimization of scheduling, routing, and pricing; largely due to the widespread assumption of fixed pricing. In this paper, we introduce another thread: profit-motivated on-demand transport services with coordinated drivers. To maximize provider profits and the efficiency of the service, we propose a new market mechanism for this new thread of on-demand transport services, where passengers negotiate with the service provider. In contrast to previous work, our mechanism jointly optimizes scheduling, routing, and pricing. Ultimately, we demonstrate that our approach can lead to higher profits and reduced passenger prices, compared with standard fixed price approaches, while also improving efficiency. [ABSTRACT FROM AUTHOR]

In today’s world, due to rapid increase in population, there is a need for efficient public transportation system, as the increased population increases the burden on public transportation like bus, etc. (Manini Kumbhar et al., 2015). The main objective of this paper is to carry out a research on city bus tracking in Demand Responsive Transit (DRT) using RS485 LAN, in order to make it much more efficient, reliable and less expensive. This research is not the only way to develop this kind of system and by no means suggested as the best solution, but it can definitely be one of the best alternatives we have today and can be used in many areas where there are no 3G, WiFi or other long-range wireless technologies available. This study will also help to understand the potential of city bus enquiry and make the bus commuter’s life easy. Till now, RS485 is being used as in-house or in-vehicle technology, but this study brings in the idea of using RS485 as communication tool for Inter-Vehicle and Vehicle to Infrastructure. [ABSTRACT FROM AUTHOR]

The most formidable challenge in assembling a smart grid is the integration of a high penetration of renewables. Demand response (DR), a largely promising concept, is increasingly discussed as a means to cope with the intermittent and uncertain renewables. In this paper, we propose a dynamic market mechanism (DMM) that reaches the market equilibrium through continuous negotiations between key market players. In addition to incorporating renewables, this market mechanism also incorporates a quantitative taxonomy of DR devices, based on the inherent magnitude, runtime, and integral constraints of demands. The DMM is evaluated on an IEEE 118 bus system, a high-fidelity simulation model of the midwestern U.S. power grid. The results show how the proposed mechanism can be utilized to determine combinations of DR devices in the presence of intermittent and uncertain renewables with varying levels of penetration so as to result in a desired level of social welfare. [ABSTRACT FROM AUTHOR]

Low volume traveler flows cause problems for public transportation (PT) providers. The Smart-PT project aims to find out how such flows can be combined to increase the service provider viability. The capability to conceive multi-modal trips is fundamental in that context and is modeled by the Trip Sequence Composer (TSC) concept. A TSC is an essential component of the traveler's brain, of the customer support operated by collective transport providers, of trip advisers in websites etc. We present a simulation model design to evaluate the effect of cooperating TSCs on the viability of demand responsive collective transport providers. While obeying specific regulations, specialized services targeting mobility impaired people can also serve regular requests in order to save fleet and personnel costs. All stakeholders are assumed to optimize their private objectives and none of them has global perfect knowledge. [ABSTRACT FROM AUTHOR]

In this article, I map subaltern mobilities: practices of movement that I define as flexible, vernacular, and specific to postcolonial subjects. I do so through a six-month ethnography of "dollar cabs" used by Caribbean immigrants in Brooklyn, New York--taxis recognized not by exterior color or medallion but by the way they blow their horns, the familiarity between driver and passengers, and other diacritics this article critically attends to. These discursive geographies and practices allow Caribbean immigrants to navigate the U.S. urban landscape and to interact with each other in unique ways. Because dollar cabs often operate outside of dominant structures of licensure, they have been studied primarily as informal paratransit systems. This article offers a critique of the framework of informality as it relates to mobilities of subaltern subjects and argues that, given their focus on systems rather than practices, scholars have foreclosed on the analytical possibilities of fully understanding the social within these geographies of mobility. Through this ethnography I make a significant theoretical and methodological intervention by showing how both international and local subaltern movements and flows have disrupted, produced, and been affected by the global city. [ABSTRACT FROM AUTHOR]

This paper addresses the Dial-A-Ride Problem (DARP) which is used to model on-demand transportation services. This kind of transportation is quickly becoming an essential service for modern public mobility or logistics providers. In the DARP, a set of transportation requests has to be handled by a fleet of vehicles. Each request corresponds to a client to be transported from a pickup point to a delivery point. The routing costs have to be minimized, while respecting a set of constraints including time windows on nodes, maximum riding time per client and a maximal total duration of trips. An Evolutionary Local Search (ELS) based approach is proposed to solve this problem. A new greedy randomized heuristic to compute initial solutions is developed. A dynamic probabilities management mechanism is used in the local search to improve the convergence. The method is benchmarked on a classic set of instances from the literature and it is compared against state of the art methods. The numerical results show the effectiveness of this approach. [ABSTRACT FROM AUTHOR]

Renewable power generation will increase and more heat pumps (HP) will be installed in the UK causing challenges regarding balancing electricity supply and demand. Demand Response (DR) can help overcoming this issue. This paper investigates how DR with HP can be used for efficient grid operation and which potential exists in the UK. A model has been developed. It allows estimating the impact of introducing HP on the half-hourly load profile on both single dwelling and UK grid level. In the base case scenario it has been shown that grid peak loads would increase by about 6 GW in the winter. On household level, peak loads would approximately triple. DR has the potential to avoid the new peak loads on grid level. On household level, new peak loads can only be reduced. In an ideal case, in the winter peak loads would rise by 2 GW on grid level. In single dwellings peak loads would increase by one quarter. In both cases DR can avoid the new peak loads. The findings confirm results of previous studies regarding future challenges for grid operators. DR can be one of several solutions that help overcoming these obstacles and it should thus be promoted. [ABSTRACT FROM AUTHOR]

This paper deals with a combinatorial optimization problem that models situations of both dynamic ride-sharing and taxi-sharing. Passengers who want to share a taxi or a ride, use an app to specify their current location, destination and further information such as the earliest departure time, the latest arrival time and the maximum cost they are willing to pay for the ride. Car owners also specify their origin, destination, the leaving time and the maximum accepted delay. Taxi drivers report their location and the time they will start and end the service. All drivers need to define a price per kilometer. The problem is to compute routes, matching requests to vehicles in such a way that ride-sharing is allowed as long as some restrictions are satisfied, such as: the capacity of the vehicle, maximum trip cost of each passenger and maximum delay. The problem is dynamic since new requests arrive on-line and routes can be modified in order to attend them. To solve this dynamic problem, the day is divided in time periods. For each period, an instance of a static problem is created and solved by a greedy randomized adaptive search procedure (GRASP). Experiments with instances based on real data were made to evaluate the heuristics and the proposed method. In our simulations with taxis, passengers paid, on average, almost 30% less than they would pay on private rides. [ABSTRACT FROM AUTHOR]

Demand Responsive Transport (DRT) services are frequently offered in the context of door-to-door transportation of elderly and persons with disabilities (PWD), but are expensive to provide. Therefore, the present study aims to determine the impact of different policy decisions on the resource requirements of a DRT system, in terms of vehicles and drivers required and kilometers traveled. A number of policy scenarios are analyzed in the case study of Flanders for the prediction years 2015, 2020 and 2030: a base scenario assuming a geographically covering subsidized DRT system; a more economical scenario limiting the subsidized DRT services; a more accessible public transport; more flexibility of the users of the DRT system; an increase in the service area of the DRT service providers; and a doubling of the current supply of transport by volunteers. A microscopic simulation of the demand of elderly and PWD for transportation was performed in order to obtain a detailed overview of all transportation requests that need to be processed. Next, each simulated transportation request was assigned to a specific service provider and a separate vehicle routing plan was created, taking into account heterogeneous users (persons with different severity and type of disabilities), heterogeneous vehicles (regular and wheelchair adapted vehicles) and multiple geographically distributed depots. Resource requirements were calculated for each of the considered scenarios. The results show that changing the modal split (the mix between the different DRT providers), as well as the realization of adequate public transport and an improved flexibility, seem to be key elements in Flanders to minimize the resource requirements of a DRT system. Our applied methodology can easily be transferred to other regions or areas, as the flexibility of the model allows to easily modify the input criteria based on the specific context. This information can be used by governments for the optimization of their DRT system. [ABSTRACT FROM AUTHOR]

Non-myopic dial-a-ride problem and other related dynamic vehicle routing problems often ignore the need for non-myopic pricing under the assumption of elastic demand, which leads to an overestimation of the benefits in level of service and resulting inefficiencies. To correct this problem, a new dynamic dial-a-ride policy is introduced, one that features non-myopic pricing based on optimal tolling of queues to fit with the multi-server queueing approximation method proposed by Hyttiä et al. (2012) for large-scale systems. By including social optimal pricing, the social welfare of the resulting system outperforms the marginal pricing assumed for previous approaches over a range of test instances. In the examples tested, improvements in social welfare of the non-myopic pricing over the myopic pricing were in the 20–31% range. For a given demand function, we can derive the optimal fleet size to maximize social welfare. Sensitivity tests to the optimal price confirm that it leads to an optimal social welfare while the marginal pricing policy does not. A comparison of single passenger taxis to shared-taxis shows that system cost may reduce at the expense of decreased social welfare, which agrees with the results of Jung et al. (2013). [ABSTRACT FROM AUTHOR]

In this paper we study a realistic dial-a-ride problem which simultaneously considers multiple trips, heterogeneous vehicles, multiple request types, configurable vehicle capacity and manpower planning. All of these features originate from practical applications in recent years. To formulate the problem, we propose two mathematical models that use different methods to deal with requests associated with the depot. To further strengthen the models, we propose eight families of valid inequalities, and based on them, we propose a branch-and-cut algorithm to solve the problem. The branch-and-cut algorithm was extensively tested on a set of instances generated according to the data of a real world application. The computational results showed that seven families of inequalities can improve the lower bounds substantially and the branch-and-cut algorithm can solve instances with up to 22 requests within 4 h. [ABSTRACT FROM AUTHOR]

Developing demand responsive transit systems are important with regard to meeting the travel needs for elderly people. Although Dial-a-ride Problems (DARP) have been discussed for several decades, most researchers have worked to develop algorithms with low computational cost under the minimal total travel costs, and fewer studies have considered how changes in travel time might affect the vehicle routes and service sequences. Ignoring such variations in travel time when design vehicle routes and schedules might lead to the production of inefficient vehicle routes, as well as incorrect actual vehicle arrival times at the related nodes. The purpose of this paper is to construct a DARP formulation with consideration of time-dependent travel times and utilizes the traffic simulation software, DynaTAIWAN, to simulate the real traffic conditions in order to obtain the time-dependent travel time matrices. The branch-and-price approach is introduced for the time-dependent DARP and tested by examining the sub-network of Kaohsiung City, Taiwan. The numerical results reveal that the length of the time window can significantly affect the vehicle routes and quantitative measurements. As the length of the time window increases, the objective value and the number of vehicles will reduce significantly. However, the CPU time, the average pickup delay time, the average delivery delay time and the average actual ride time (ART)/direct ride time (DRT) will increase significantly as the length of the time window increases. Designing the vehicle routes to reduce operating costs and satisfy the requirements of customers is a difficult task, and a trade-off must be made between these goals. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper identifies some of the characteristics of trips and pick-up and drop-off locations that are associated with paratransit's travel time reliability. Following convention, reliability has been defined as the inverse of variability. Four measures of travel time variability have been used to examine reliability: Standard Deviation, Percent Variation, Misery Index, and Buffer Index. Regression models have been used to estimate these four variables with trip data from Access Link, the paratransit service provided by NJ TRANSIT pursuant to the Americans with Disabilities Act (ADA). A number of characteristics of the pick-up and drop-off locations as well as selected characteristics of the trips were used as independent variables of the models. The statistical significance of the independent variables varied depending on which measure of reliability was estimated, but a few variables were consistently associated with reliability in all four models. These variables were trip distance, booking type, winter season, density of motor vehicle crashes in pick-up and drop-off locations, and whether pick-ups occurred in suburban bus corridors or urban core areas. Because of the significance of the variables on motor vehicle crash density in pick-up and drop-off locations, an additional regression model was used to examine the effect of crash incidents on trip duration by considering drop-offs that occurred in locations immediately after a crash. The model showed that trips take 4 to 5% longer when crashes occur in locations prior to a drop off. Planning implications of the findings are discussed. [ABSTRACT FROM AUTHOR]

In light of the need to make better use of existing transport infrastructure, demand-responsive transportation (DRT) systems are gaining traction internationally. However, many systems fail due to poor implementation, planning, and marketing. Being able to realistically simulate a system to evaluate its viability before implementation is important. This review investigates the application of agent-based simulation for studying DRT. We identify that existing simulations are strongly focused on the optimisation of trips, usually in favour of the operator, and rarely consider individual preferences and needs. Agent-based simulations, however, permit incorporation of the latter, as well as capture the interactions between operators and customers. Several areas of future research are identified in order to unify future research efforts. [ABSTRACT FROM PUBLISHER]

This is the preliminary finding of a study elaborating the total energy consumption when paratransits in Bandung are altered into electric and the scenario to fulfill it. Therefore, there are lots to be done further concerning result of this initial research, of which will be discussed in another publication. In this paper calculation was done to find out the volume of power needed to fuel electric paratransits in Bandung. Steps carried out include computing total energy consumption for all paratransits, clustering stations from classified routes established by local Department of Transport, and estimating the electricity demand in every clustered station. Data used for this study was acquired from Badan Pusat Statistik Kota Bandung and PT PLN DJA APD Jawa Barat and Banten. A total demand of 61.12 MWh per month will surface to charge the total of 5,521 paratransits from 38 available routes in 15 clustered stations under the assumptions that all paratransits only make 6 return travels per day, operate 30 days per month, and use batteries with 50% State of Charge. [ABSTRACT FROM AUTHOR]

This paper reports on a system developed to address the dial-a-ride problem and an implementation for Maryland where real-world practical constraints are considered in providing customized vehicle routing and scheduling for about 450 trip requests daily. The system, called Mobile Resource Management System (MRMS), allows for dispatch operators to quickly study different operational scenarios and, in a strategic setting, explore tradeoffs between level-of-service and various system characteristics, including fleet composition, fleet size and dispatch rules. Such insights play a key role in making long-term investment decisions or estimating cost of servicing contracts that have service level agreements. Test comparison of manual and MRMS-based routes indicated an estimated annual operational expense reduction of $0.82 million, or about 18% of the total annual expense. In addition to the cost benefits, improved quality of service and the reduction in total vehicle-kilometers traveled leading to environmental benefits are demonstrated. [ABSTRACT FROM AUTHOR]