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The roles of ‘conventional’ (fixed-route and fixed-timetable) bus services is examined and compared to demand-responsive services, taking rural areas in England as the basis for comparison. It adopts a ‘rural’ definition of settlements under a population of 10,000.

Evidence from the National Travel Survey, technical press reports and academic work is brought together to examine the overall picture.

Inter-urban services between towns can provide a cost-effective way of serving rural areas where smaller settlements are suitably located. The cost structures of both fixed-route and demand-responsive services indicate that staff time and cost associated with vehicle provision are the main elements. Demand-responsive services may enable larger areas to be covered, to meet planning objectives of ensuring a minimum of level of service, but experience often shows high unit cost and public expenditure per passenger trip. Economic evaluation indicates user benefits per passenger trip of similar magnitude to existing average public expenditure per trip on fixed-route services. Considerable scope exists for improvements to conventional services through better marketing and service reliability.

The main issue in England is the level of funding for rural services in general, and the importance attached to serving those without access to cars in such areas.

The boundary between fixed-route and demand-responsive operation may lie at relatively low population densities.

The chapter uses statistical data, academic research and operator experience of enhanced conventional bus services to provide a synthesis of outcomes in rural areas.

In many cases it is not appropriate to utilise a system of daily route scheduling. This paper looks at the situation where a fixed route system is required and the demand characteristics of the customers must be matched to the system.

The purpose of this paper is to create a flight route optimization for all flights that aims to minimize the total cost consists of fuel cost, ground delay cost and air delay cost over the fixed route and free route airspaces.

Efficient usage of current available airspace capacity becomes more and more important with the increasing flight demands. The efficient capacity usage of an airspace is generally in contradiction to optimum flight efficiency of a single flight. It can only be achieved with the holistic approach that focusing all flights over mixed airspaces and their routes instead of single flight route optimization for a single airspace. In the scope of this paper, optimization methods were developed to find the best route planning for all flights considering the benefits of all flights not only a single flight. This paper is searching for an optimization to reduce the total cost for all flights in mixed airspaces. With the developed optimization models, the determination of conflict-free optimum routes and delay amounts was achieved with airway capacity and separation minimum constraints in mixed airspaces. The mathematical model and the simulated annealing method were developed for these purposes.

The total cost values for flights were minimized by both developed mathematical model and simulated annealing algorithm. With the mathematical model, a reduction in total route length of 4.13% and a reduction in fuel consumption of 3.95% was achieved in a mixed airspace. The optimization algorithm with simulated annealing has also 3.11% flight distance saving and 3.03% fuel consumption enhancement.

Although the wind condition can change the fuel consumption and flight durations, the paper does not include the wind condition effects. If the wind condition effect is considered, the shortest route may not always cause the least fuel consumption especially under the head wind condition.

The results of this paper show that a flight route optimization as a holistic approach considering the all flight demand information enhances the fuel consumption and flight duration. Because of this reason, the developed optimization model can be effectively used to minimize the fuel consumption and reduce the exhaust emissions of aircraft.

This paper develops the mathematical model and simulated annealing algorithm for the optimization of flight route over the mixed airspaces that compose of fixed and free route airspaces. Each model offers the best available and conflict-free route plan and if necessary required delay amounts for each demanded flight under the airspace capacity, airspace route structure and used separation minimum for each airspace.

The purpose of this study is to develop an operational level decision support system model for air traffic controllers (ATCos) within the framework of the Flexible Use of Airspace (FUA) concept to enable more efficient use of airspace capacity. This study produces a systematic solution to the route selection process so that the ATCo can determine the most efficient route with an operational decision support system model using Dijkstra’s Shortest Path Algorithm.

In this study, a new decision support system model for ATCos in decision-making positions was recommended and used. ATCos use this model as a main model for determining the shortest and safest route for aircraft as an operational-level decision support system. Dijkstra Algorithm, used in the model, is defined step by step and then explained with the pseudocode.

It has been determined that when the FUA concept and DSS are used while the ATCo chooses a route, significant fuel, time and capacity savings are achieved in flight operations. Emissions resulting from the negative environmental effects of air transportation are reduced, and significant capacity increase can be achieved. The operational level decision support system developed in the study was tested with 55 scenarios on the Ankara–Izmir flight route compared to the existing fixed route. The results for the proposed most efficient route were achieved at 11.22% distance (nm), 9.36%-time (min) savings and 837.71 kg CO₂ emission savings.

As far as the literature is reviewed, most studies aimed at increasing airspace efficiency produce solutions that try to improve rather than replace the normal process. Considering the literature positioning of this study compared to other studies, the proposed model provides a new systematic solution to the problems that cause human-induced route inefficiency within the framework of the FUA concept.

This paper describes a benchmarking framework applied to medium-sized urban public bus agencies in the United States, which has overcome the challenges of data quality, comparability, and understanding.

The benchmarking methodology described in this paper is based on lessons learned through seven years of development of a fixed-route key performance indicator (KPI) system for the American Bus Benchmarking Group (ABBG). Founded in 2011, the ABBG is a group of public medium-sized urban bus agencies that compare performance and share best practices with peers throughout the United States. The methodology is adapted from the process used within international benchmarking groups facilitated by Imperial College and consists of four main elements: peer selection, KPI system development, processes to achieve high-quality data, and processes to understand relative performance and change.

The four main elements of the ABBG benchmarking methodology consist of 18 subelements, which when applied overcome three main benchmarking challenges: comparability, data quality, and understanding. While serving as examples for the methodology elements, the paper provides specific insights into service characteristics and performance among ABBG agencies.

The benchmarking approach described in this paper requires time and commitment and thus is most suitably applied to a concise group of agencies.

This methodology provides transit agencies, authorities, and benchmarking practitioners a framework for effective benchmarking. It will lead to high-quality comparable data and a strong understanding of the performance context to serve as a basis for organizational changes, whether for policy, planning, operations, stakeholder communication, or program development.

The methodology, while consistent with recommendations from literature, is unique in its scale, in-depth validation and analysis, and holistic and multidimensional approach.

This chapter applies the Consortium for Advanced Management, International (CAM-I) Activity-Based Cost Management (ABC/M) tool to paratransit. The intent is to enable agencies sponsoring rides to save money through sharing rides and vehicle-time.

Several paratransit cost-allocation models from Transit Cooperative Research Program (TCRP) and other sources are reviewed and one is adapted to the ABC/M methodology, based upon the author’s previous work proportionately allocating ride time among sponsoring agencies at a consolidated human service transportation agency and the price sheets used in contracted operations to minimize financial risk.

Through application of the principles of ABC/M, paratransit providers can properly allocate costs, determine the costs of providing proposed new services, plan for future vehicle acquisitions, and motivate their customers to tailor their transportation needs in a manner that will save them money and boost efficiency.

University-based transportation studies programs may be motivated to apply these strategies to urban and rural paratransit providers that serve several customer agencies.

If agencies sponsoring paratransit rides understand that funds can purchase more rides during off-peak hours or if rides are shared with clients of other agencies, then paratransit resources can be used more efficiently and to the benefit of more individuals.

By enabling the provision of more rides, a greater number of riders will be enabled to reach necessary services and participate in community life.

This is the first application of the ABC/M methodology to paratransit (and transit) and possibly to social services.

With the growing preference of the generation of ageing baby boomers to age in place, mobility has played an increasingly important role in their continued physical and mental well-being. As older adults drive less, their ability to travel freely where and when they desire becomes increasingly limited. Consequences of this include the cessation of various activities and services that are necessary for daily living. Transportation immobility is known to negatively impact the quality of life through physical, mental, and social isolation. For any initiative or policy to be put in place, an assessment of the current state of transportation services, specifically for older adults, needs to be carried out. The purpose of this paper is to assess the access to public transit in the Greater Lansing, Michigan region, which has a population density of about 2,042 people per square kilometre, available to ageing adults, especially when they have to stop driving.

The study uses a spatial approach through the use of geographical information systems to assess the transit infrastructure available for use by older adults in the Greater Lansing region.

This paper finds a considerable gap in available options and that some of these can be addressed by quite simple actions and initiatives.

Because the data were drawn from the US Census, the spatial analysis is limited to block-level data. The US Census (2011) defines blocks as “statistical areas bounded by visible features such as roads, streams, and railroad tracks, and by nonvisible boundaries such as property lines, city, township, school district, county limits and short line-of-sight extensions of roads”. More detailed geographical data would have enabled a more comprehensive analysis.

This study area is typical of many small towns in the USA and underlines the need for more policy- and community-led transit initiatives to address this critical barrier to optimal ageing.

This paper fulfils an identified need to study the transit infrastructure of a range of urban areas and ascertain whether it currently fulfils mobility needs of older adults who do not drive.

The free roving robot in the form of a computer controlled industrial truck is now technically possible. The use of small on‐board computers and navigation aids frees the robot from dependence on fixed route marking. Conventional vehicles such as fork lift trucks may be modified for autonomous or semi‐autonomous control.

The problems which are inherent in designing sophisticated systems that are actually used by the intended user, for the originally‐intended purpose, and at approximately the intended level of effectiveness and efficiency have become vividly clear throughout society in the last decade. Millions have been spent on complex systems such as the “personal rapid transit” system in Morgantown, West Virginia, with the result that shortly after it was operating, serious consideration was given to spending additional millions to dismantle the system because it did not perform as intended. The Bay Area Rapid Transit (BART) system cost hundreds of millions and still has not changed the transit habits of the residents of the area; autos still clog the freeways at rush hour and travellers are heard to complain that the fixed routes of BART are not sufficiently convenient to lure them away from their cars. Business firms and other organisations have similarly spent millions developing computerised control systems only to find that employees develop their own informal systems because of a lack of “trust” in the system.