Jointly optimizing cost, service, and environmental performance in demand-responsive transit scheduling

In certain fleet systems, the environmental impacts of operation are, to some extent, a controllable function of vehicle routing and scheduling decisions. However, little prior work has considered environmental impacts in fleet vehicle routing and scheduling optimization, in particular, where the impacts were assessed systematically utilizing life-cycle impact assessment methodologies such as those described by the Society of Environmental Chemistry and Toxicology. Here a methodology is presented for the joint optimization of cost, service, and life-cycle environmental consequences in vehicle routing and scheduling, which we develop for a demand-responsive (paratransit or dial-a-ride) transit system. We demonstrate through simulation that, as a result of our methodology, it is possible to reduce environmental impacts substantially, while increasing operating costs and service delays only slightly.     

International experience with speed limits during and prior to the energy crisis of 1973–4

This paper presents an artificial neural network (ANN) based method for estimating route travel times between individual locations in an urban traffic network. Fast and accurate estimation of route travel times is required by the vehicle routing and scheduling process involved in many fleet vehicle operation systems such as dial‐a‐ride paratransit, school bus, and private delivery services. The methodology developed in this paper assumes that route travel times are time‐dependent and stochastic and their means and standard deviations need to be estimated. Three feed‐forward neural networks are developed to model the travel time behaviour during different time periods of the day‐the AM peak, the PM peak, and the off‐peak. These models are subsequently trained and tested using data simulated on the road network for the City of Edmonton, Alberta. A comparison of the ANN model with a traditional distance‐based model and a shortest path algorithm is then presented. The practical implication of the ANN method is subsequently demonstrated within a dial‐a‐ride paratransit vehicle routing and scheduling problem. The computational results show that the ANN‐based route travel time estimation model is appropriate, with respect to accuracy and speed, for use in real applications.     

The use of GIS and relational database management systems to improve the scheduling operations of paratransit

The scheduling operations of many paratransit agencies in the United States are undertaken manually. Those customers who are eligible to travel call in their requests the day before the trip is needed. As the trip requests are received, they are entered into a list of unscheduled trips. In order to schedule these trips, the scheduler must first determine the number of drivers and shuttle buses that are available as well as the time of availability of each. The scheduler must then try to match the rides that are in “similar” areas around the “same” time to place together on the driver's schedule. As new trip requests are made, the schedulers must adjust the trips that are already scheduled to try and schedule as many trips as possible in the most efficient way.

By developing a system that would improve the scheduling system operations of, in this case, DART (Delaware Administration for Regional Transit) First State Paratransit, customers can expect to receive better service that will improve their ability to travel throughout the community. Some devices that could also improve the operations of paratransit agencies are described in this paper, such as satellite‐based Global Positioning System (GPS), radio communication systems, mobile computers, radio frequency‐based data communication systems, internet web pages, automated paratransit information systems, and card‐based data storage and transfer media. However, because paratransit systems are difficult to operate cost‐efficiently, the optimum and most cost‐efficient device must be selected. The system chosen for DART First State Paratransit includes the use of a relational database management system (RDMS) and a transportation Geographic Information System (GIS). RDMS keeps track of the database information as well as the scheduled trips and the GIS is ideal for analyzing both geographic and temporal data. This system is shown to be superior to the manual system.     

Solving the User Optimum Privately Owned Automated Vehicles Assignment Problem (UO-POAVAP): A model to explore the impacts of self-driving vehicles on urban mobility

Interest in vehicle automation has been growing in recent years, especially with the very visible Google car project. Although full automation is not yet a reality there has been significant research on the impacts of self-driving vehicles on traffic flows, mainly on interurban roads. However, little attention has been given to what could happen to urban mobility when all vehicles are automated. In this paper we propose a new method to study how replacing privately owned conventional vehicles with automated ones affects traffic delays and parking demand in a city. The model solves what we designate as the User Optimum Privately Owned Automated Vehicles Assignment Problem (UO-POAVAP), which dynamically assigns family trips in their automated vehicles in an urban road network from a user equilibrium perspective where, in equilibrium, households with similar trips should have similar transport costs. Automation allows a vehicle to travel without passengers to satisfy multiple household trips and, if needed, to park itself in any of the network nodes to benefit from lower parking charges. Nonetheless, the empty trips can also represent added congestion in the network. The model was applied to a case study based on the city of Delft, the Netherlands. Several experiments were done, comparing scenarios where parking policies and value of travel time (VTT) are changed. The model shows good equilibrium convergence with a small difference between the general costs of traveling for similar families. We were able to conclude that vehicle automation reduces generalized transport costs, satisfies more trips by car and is associated with increased traffic congestion because empty vehicles have to be relocated. It is possible for a city to charge for all street parking and create free central parking lots that will keep total transport costs the same, or reduce them. However, this will add to congestion as traffic competes to access those central nodes. In a scenario where a lower VTT is experienced by the travelers, because of the added comfort of vehicle automation, the car mode share increases. Nevertheless this may help to reduce traffic congestion because some vehicles will reroute to satisfy trips which previously were not cost efficient to be done by car. Placing the free parking in the outskirts is less attractive due to the extra kilometers but with a lower VTT the same private vehicle demand would be attended with the advantage of freeing space in the city center.     

Fuel economy,cost, and greenhouse gas results for alternative fuel vehicles in 2011

This paper presents in-service data collected from over 300 alternative fuel vehicles and over 80 fueling stations to help fleets determine what types of applications and alternative fuels may help them reduce their environmental impacts and fuel costs. The data were compiled in 2011 by over 30 organizations in New York State using a wide variety of commercial vehicle types and technologies. Fuel economy, incremental vehicle purchase cost, fueling station purchase cost, greenhouse gas reductions, and fuel cost savings data clarifies the performance of alternative fuel vehicles and fuel stations. Data were collected from a range of vehicle types, including school buses, delivery trucks, utility vans, street sweepers, snow plows, street pavers, bucket trucks, paratransit vans, and sedans. CNG, hybrid, LPG, and electric vehicles were tracked.     

Optimization of headways with stop‐skipping control: a case study of bus rapid transit system

Bus rapid transit system is designed to provide high‐quality and cost‐efficient passenger transportation services. In order to achieve this design objective, effective scheduling strategies are required. This research aims at improving the operation efficiency and service quality of a BRT system through integrated optimization of its service headways and stop‐skipping strategy. Based on cost analysis for both passengers and operation agencies, an optimization model is established. A genetic algorithms based algorithm and an application‐oriented solution method are developed. Beijing BRT Line 2 has been chosen as a case study, and the effectiveness of the optimal headways with stop‐skipping services under different demand levels has been analyzed. The results has shown that, at a certain demand level, the proposed operating strategy can be most advantageous for passengers with an accepted increase of operating costs, under which the optimum headway is between 3.5 and 5.5 min for stop‐skipping services during the morning peak hour depending on the demand with the provision of stop‐skipping services. The effectiveness of the optimal headways with stop‐skipping services is compared with those of existing headways and optimal headways without stop‐skipping services. The results show that operating strategies under the optimal headways with stop‐skipping services outperforms the other two operating strategies with respect to total costs and in‐vehicle time for passengers. Copyright © 2014 John Wiley & Sons, Ltd.     

A simulation model for evaluating advanced dial-a-ride paratransit systems

This paper presents a simulation system that has been developed to model a variety of technology-oriented dial-a-ride paratransit systems operated in an urban environment. The latest advances in information technologies such as automatic vehicle location (AVL), digital telecommunication and computers have afforded a unique opportunity for public transit agencies to integrate these technologies in their paratransit systems for improved productivity and reliability. This opportunity has also prompted wide spread interest in quantifying the actual benefits that can be attained from such technological enhancement. The primary objective of the simulation model described in this paper was to facilitate the evaluation of the potential effects that these technologies may bring on a paratransit system. The paper discusses the general concepts, models and computational techniques applied in the simulation system, focusing on how various components are modeled and how they interact with each other in the overall simulation framework. The simulation system is applied to evaluate the potential operational improvement that may be attained from the application of automatic vehicle location technology.     

Transport innovation and passenger needs — changing perspectives on the role of Dial‐a‐Ride systems

The changing role of Dial‐a‐Ride systems in the period 1969 to 1985 is reviewed as a case study in transport innovation. The first phase Dial‐a‐Ride systems were conceived and planned as transport services to complement and even replace conventional transit. However, their failure to attract any sizeable part of the public transport market combined with their high operating costs led to their demise in the mid‐1970s, to be superseded by the second phase Dial‐a‐Ride systems as paratransit services to the elderly and handicapped. These later systems were often initiated by community‐based transport agencies which have demonstrated their ability as transport innovators in meeting passenger needs. It is suggested that other transport services could learn valuable lessons from the experiences of community Dial‐a‐Ride, and that Dial‐a‐Ride itself will prove historically to be an important transitional agent in the reorganization of passenger transport services in the post‐deregulation environment of the late 1980s and 1990s.     

Anatomy of a systems failure: Dial-a-ride in Santa Clara County,California

Late in 1974 and early in 1975 the Santa Clara County Transit District initiated, operated, and then discontinued a demand responsive dial-a-ride system within a -month span. This systems failure was primarily the result of poor systems planning. Specifically, four major mistakes were made that led to the death of the system. They were: (1) Inadequate Customer Communication System, (2) Starting the Entire System at Once, (3) Inadequate Number of Vehicles, and (4) Taxicab Buyout.Each of these four mistakes is discussed in detail. Recommendations for instituting dial-a-ride systems are made. Getting through the difficulties of the start-up period is emphasized. Costs are discussed, and some relevant cost data are presented.     

Improving the efficiency of demand-responsive paratransit services

State agencies responsible for ADA-eligible paratransit services are increasingly under pressure to contain costs and maximize service quality. Many do not operate vehicles themselves; instead, they contract out the provision of services. Contractors are paid for each hour of service. They are responsible for hiring crew, forming routes, dispatching, and operating and maintaining agency-owned vehicles. In the Twin Cities of Minneapolis and Saint Paul, Metro Mobility, the agency responsible for providing paratransit services, requires contractors to use agency-approved software for booking trips dynamically and sets parameters that guide contractors’ practices. Customer trips booked in this fashion may not utilize capacity in the most efficient manner. Therefore, beginning with the daily trip schedules generated by the software, this paper proposes two approaches for improving the efficiency of paratransit operations and estimates the benefit of using these approaches via experiments that utilize Metro Mobility data. The first approach re-optimizes routes developed at the end of each day. The second approach evaluates the benefit to state agencies of selectively using non-dedicated service providers such as taxis. Both approaches are tested on actual data obtained from Metro Mobility. The study shows that a conservative estimate of savings from re-optimization would be approximately 5% of Metro Mobility’s operating costs. Savings from the use of taxis are smaller and in the range of hundreds of dollars per day.     

What is paratransit worth?

Paratransit is a flexible demand-responsive form of public transportation intended for transporting mobility impaired individuals. This is the first study that estimates both demand and cost functions for publicly provided paratransit in the United States and the first to conduct a benefit-cost analysis for this mode. We find that the benefits of paratransit far exceed its associated costs. The results suggest that paratransit riders have few transportation alternatives available to them. We also find that the level of service matters in the demand for paratransit.     

Segmentation of paratransit users based on service quality and travel behaviour in Bandung,Indonesia

Using a data-set collected among paratransit users in Bandung, Indonesia, this paper explores the impacts of paratransit users' negative experiences and dissatisfactions with their paratransit usage pattern. Segmentation and ordered probit analyses are used to examine the impacts of users' opinions on service quality on their trip-making behaviour. The results indicate that users are divided into six segments – namely, the unlucky, the young user, the experienced, the adapter, the infrequent user and the captive. The results further indicate that paratransit users, especially women, perceive negative experiences related to on-time performance (departure and arrival time) and security issues related to vehicles. Despite these dissatisfactions and negative experiences, they are still likely to use paratransit as part of their daily life. Two paratransit market segments (the adapter and the captive) are also likely to result in more trips using paratransit. The study offers several strategies and recommendations that can improve the current paratransit system so that it can better serve local needs.     

Autonomous vehicles: who will use them,and will they share?

ABSTRACT

The advent of road transport automation is suggested to be one of four key technological transitions that could amount to a major transformation in mobility practices. Specifically, fully Automated Vehicles (AVs) might replace the current private car owner user model with fleets of on-demand synchronously-shared automated taxis. However, significant barriers to this vision becoming the norm remain. This paper examines two critical user-acceptance aspects of the transition: willingness to adopt AVs, and willingness to share an AV with others, particularly strangers. Our novel survey (n?=?899) included a choice experiment featuring four future full automation transport services (private, synchronously/asynchronously shared, and public). Cluster analysis examined respondents' preferences and their demographic and psycho-social characteristics. We uncover significant uncertainty about willingness to adopt automation and sharing, and important differences between clusters within our sample. For example, under 50% of participants report willingness to use an AV over their normal mode, or would prefer an automated option to a current human-driven option. Our findings raise critical questions for policymakers and transport authorities. Not least, how can AV technologies help realise the environmental and social benefits of widespread vehicle sharing in a context of a travelling public that still prefers its privacy on-the-move?     

Development of computerized vehicle scheduling system for specialized transportation: delaware case

A computer‐aided vehicle scheduling system is developed for Delaware's state‐wide specialized transportation system for elderly and handicapped persons. This paper presents the model, computer program package, system implementation, evaluation and the lessons learned from the project. The project which spanned two and a half years consists of five phases: (1) examine the manual method of vehicle scheduling (prior to the computerization); (2) develop a scheduling model; (3) develop a computer program package for the operation of the model; (4) install and operate the system; and (5) evaluate the system performance. The scheduling model consolidates passengers by block of time, origin and destination zones and along the direction of vehicle travel, first; second, minimizes the empty vehicle travel; and, lastly, assigns drivers to route considering assignment priority among the types of drivers and passengers. The product of the model is a set of driver log‐sheets which specify the sequence of passenger pick‐ups and drop‐offs. The computer program package includes necessary auxiliary data management functions such as registration of trip reservation, operating statistics and parameter value changes, as well as the execution of the model. It also allows the dispatcher to override the computer generated log‐sheet based on his discretion. The system has been operational for more than one year and it has brought about a number of changes in the operation and the role of the dispatcher. A before‐and‐after comparison of the operation and the lessons learned are also shown.     

Calibrating trust through knowledge: Introducing the concept of informed safety for automation in vehicles

There has been an increasing focus on the development of automation in vehicles due its many potential benefits like safety, improved traffic efficiency, reduced emissions etc. One of the key factors influencing public acceptance of automated vehicle technologies is their level of trust. Development of trust is a dynamic process and needs to be calibrated to the correct levels for safe deployment to ensure appropriate use of such systems. One of the factors influencing trust is the knowledge provided to the driver about the system’s true capabilities and limitations. After a 56 participants driving simulator study, the authors found that with the introduction of knowledge about the true capabilities and limitations of the automated system, trust in the automated system increased as compared to when no knowledge was provided about the system. Participants experienced two different types of automated systems: low capability automated system and high capability automated system. Interestingly, with the introduction of knowledge, the average trust levels for both low and high capability automated systems were similar. Based on the experimental results, the authors introduce the concept of informed safety, i.e., informing the drivers about the safety limits of the automated system to enable them to calibrate their trust in the system to an appropriate level.     

Transit system evaluation: Guideway bus vs. light rail transit

This paper describes a set of specialized spreadsheets that model the cost and performance of transit system options including light rail transit, guideway bus, express bus, and ride sharing. These spreadsheets are demonstrated by comparing a guideway bus (GWB) transit system and a light rail transit (LRT) system proposed for construction in an active rail corridor. The comparisons for assumed levels of transit ridership include guideway geometry, travel time, headways, vehicle requirements, grade crossing protection, and capital and operating costs. The planned GWB system runs on an exclusive dual guideway in the rail right-of-way, and the alternative LRT system operates on the existing rails with new bridges and track as needed for a dual guideway system. The analysis compares the two options for mode splits between 0.5% and 50%. Results show that while both options have approximately the same travel time, the GWB system costs approximately 30% less than the LRT system. The cost difference results primarily from lower GWB vehicle purchase and operating costs. The spreadsheets are available through the McTrans Center at the University of Florida, Gainesville, Florida.     

Influential vectors in fuel consumption by an urban bus operator: Bus route,driver behavior or vehicle type?

Energy costs account for an important share of the total costs of urban and suburban bus operators. The purpose of this paper is to expand empirical research on bus transit operation costs and identify the key factors that influence bus energy efficiency of the overall bus fleet of one operator and aid to the management of its resources.We estimate a set of multivariate regression models, using cross-section dataset of 488 bus drivers operating over 92 days in 2010, in 87 routes with different bus typologies, of a transit company operating in the Lisbon’s Metropolitan Area (LMA), Rodoviária de Lisboa, S.A.Our results confirm the existence of influential variables regarding energy efficiency and these are mainly: vehicle type, commercial speed, road grades over 5% and bus routes; and to a lesser extent driving events such as: sudden longitudinal decelerations and excessive engine rotation. The methodology proved to be useful for the bus operator as a decision-support tool for efficiency optimization purpose at the company level.     

Automatic identification of risky weather objects in line of flight (AIRWOLF)

Adverse weather conditions are hazardous to flight and contribute to re-routes and delays. This has a negative impact on the National Airspace System (NAS) due to reduced capacity and increased cost. In today’s air traffic control (ATC) system there is no automated weather information for air traffic management decision-support systems. There are also no automatic weather decision-support tools at the air traffic controller workstation. As a result, air traffic operators must integrate weather information and traffic information manually while making decisions. The vision in the Next Generation Air Transportation System (NextGen) includes new automation concepts with an integration of weather information and decision-making tools. Weather-sensitive traffic flow algorithms could automatically handle re-routes around weather affected areas; this would optimize the capacity during adverse conditions. In this paper, we outline a weather probe concept called automatic identification of risky weather objects in line of flight (AIRWOLF). The AIRWOLF operates in two steps: (a) derivation of polygons and weather objects from grid-based weather data and (b) subsequent identification of risky weather objects that conflict with an aircraft’s line of flight. We discuss how the AIRWOLF concept could increase capacity and safety while reducing pilot and air traffic operator workload. This could translate to reduced weather-related delays and reduced operating costs in the future NAS.     

A practice-ready relocation model for free-floating carsharing systems with electric vehicles – Mesoscopic approach and field trial results

This paper introduces a relocation model for free-floating Carsharing (FFCS) systems with conventional and electric vehicles (EVs). In case of imbalances caused by one-way trips, the approach recommends profit maximizing vehicle relocations. Unlike existing approaches, two types of relocations are distinguished: inter zone relocations moving vehicles between defined macroscopic zones of the operating area and intra zone relocations moving vehicles within such zones. Relocations are combined with the unplugging and recharging of EVs and the refueling of conventional vehicles. In addition, remaining pure service trips are suggested. A historical data analysis and zone categorization module enables the calculation of target vehicle distributions. Unlike existing approaches, macroscopic optimization steps are supplemented by microscopic rule-based steps. This enables relocation recommendations on the individual vehicle level with the exact GPS coordinates of the relocation end positions. The approach is practice-ready with low computational times even for large-scale scenarios.To assess the impact of relocations on the system’s operation, the model is applied to a FFCS system in Munich, Germany within three real world field tests. Test three shows the highest degree of automation and represents the final version of the model. Its evaluation shows very promising results. Most importantly, the profit is increased by 5.8% and the sales per vehicle by up to 10%. The mean idle time per trip end is decreased by 4%.     

Intermodal Transit System Coordination

In urban areas where transit demand is widely spread, passengers may be served by an intermodal transit system, consisting of a rail transit line (or a bus rapid transit route) and a number of feeder routes connecting at different transfer stations. In such a system, passengers may need one or more transfers to complete their journey. Therefore, scheduling vehicles operating in the system with special attention to reduce transfer time can contribute significantly to service quality improvements. Schedule synchronization may significantly reduce transfer delays at transfer stations where various routes interconnect. Since vehicle arrivals are stochastic, slack time allowances in vehicle schedules may be desirable to reduce the probability of missed connections. An objective total cost function, including supplier and user costs, is formulated for optimizing the coordination of a general intermodal transit network. A four-stage procedure is developed for determining the optimal coordination status among routes at every transfer station. Considering stochastic feeder vehicle arrivals at transfer stations, the slack times of coordinated routes are optimized, by balancing the savings from transfer delays and additional cost from slack delays and operating costs. The model thus developed is used to optimize the coordination of an intermodal transit network, while the impact of a range of factors on coordination (e.g., demand, standard deviation of vehicle arrival times, etc) is examined.