Modular route bus design – A method of meeting transport operation and vehicle manufacturing requirements

This research examines the problem of route bus specification and vehicle manufacturability. In order for bus operators to provide transport services, a range of vehicle configurations must be available from bus manufacturers, generating variety which has a negative impact on the manufacturing process. Larger part inventories, uncontrolled labour tasks and more troublesome maintenance are known impacts of this variety. This research identifies the functional necessities in route bus interior design and reduces the problems in bus manufacture and operation caused by specification diversity by proposing a modularised system of bus design. In particular, it makes recommendations as to how bus configuration should be carried out, ensuring an optimum mix of operational and manufacturing needs:

• 1.Determine user needs before the bus specification process.
• 2.Designs to be developed by the manufacturer in response to user needs.
• 3.This design should be standardised where possible, as suggested by the user needs.
• 4.Where user needs dictate product variations, apply a mass customisation approach to accommodate these needs.

The recommendations are communicated in design proposals for a modular bus interior, demonstrated by four cases designed to meet the present status quo of bus interior design and predictions for the future of the field.     

A partial differential equation formulation of Vickrey’s bottleneck model,part I: Methodology and theoretical analysis

This paper is concerned with the continuous-time Vickrey model, which was first introduced in Vickrey (1969). This model can be described by an ordinary differential equation (ODE) with a right-hand side which is discontinuous in the unknown variable. Such a formulation induces difficulties with both theoretical analysis and numerical computation. Moreover it is widely suspected that an explicit solution to this ODE does not exist. In this paper, we advance the knowledge and understanding of the continuous-time Vickrey model by reformulating it as a partial differential equation (PDE) and by applying a variational method to obtain an explicit solution representation. Such an explicit solution is then shown to be the strong solution to the ODE in full mathematical rigor. Our methodology also leads to the notion of generalized Vickrey model (GVM), which allows the flow to be a distribution, instead of an integrable function. As explained by Han et al. (in press), this feature of traffic modeling is desirable in the context of analytical dynamic traffic assignment (DTA). The proposed PDE formulation provides new insights into the physics of The Vickrey model, which leads to a number of modeling extensions as well as connection with first-order traffic models such as the Lighthill–Whitham–Richards (LWR) model. The explicit solution representation also leads to a new computational method, which will be discussed in an accompanying paper, Han et al. (in press).     

Boundedly rational user equilibria (BRUE): Mathematical formulation and solution sets

Boundedly rational user equilibria (BRUE) represent traffic flow distribution patterns where travellers can take any route whose travel cost is within an ‘indifference band’ of the shortest path cost. Those traffic flow patterns satisfying the above condition constitute a set, named the BRUE solution set. It is important to obtain all the BRUE flow patterns, because it can help predict the variation of the link flow pattern in a traffic network under the boundedly rational behavior assumption. However, the methodology of constructing the BRUE set has been lacking in the established literature. This paper fills the gap by constructing the BRUE solution set on traffic networks with fixed demands. After defining ε-BRUE, where ε is the indifference band for the perceived travel cost, we formulate the ε-BRUE problem as a nonlinear complementarity problem (NCP), so that a BRUE solution can be obtained by solving a BRUE–NCP formulation. To obtain the BRUE solution set encompassing all BRUE flow patterns, we propose a methodology of generating acceptable path set which may be utilized under the boundedly rational behavior assumption. We show that with the increase of the indifference band, the acceptable path set that contains boundedly rational equilibrium flows will be augmented, and the critical values of indifference band to augment these path sets can be identified by solving a family of mathematical programs with equilibrium constraints (MPEC) sequentially. The BRUE solution set can then be obtained by assigning all traffic demands to the acceptable path set. Various numerical examples are given to illustrate our findings.     

A statistical approach to the traveling salesman problem

A statistical approach is shown to be adaptable to the N-city traveling salesman problem by considering route distances to be random variables which are continuous and normally distributed. A solution to the shortest route distance and path can be approximated by utilizing a Monte Carlo simulation to obtain a representative sample of possible journeys. The approach involves recursive statistical inference which is used to select next-city visits leading to the most probable minimum route path. A statistical selection of the minimum route path is computationally efficient and computer run time increases in proportion to the square of the number of cities as opposed to an (N - 1)! increase for a deterministic approach. The accuracy of the statistical approach is directly proportional to the number of Monte Carlo simulations.     

Prediction of vehicle CO2 emission and its application to eco-routing navigation

Transportation sector accounts for a large proportion of global greenhouse gas and toxic pollutant emissions. Even though alternative fuel vehicles such as all-electric vehicles will be the best solution in the future, mitigating emissions by existing gasoline vehicles is an alternative countermeasure in the near term. The aim of this study is to predict the vehicle CO₂ emission per kilometer and determine an eco-friendly path that results in minimum CO₂ emissions while satisfying travel time budget. The vehicle CO₂ emission model is derived based on the theory of vehicle dynamics. Particularly, the difficult-to-measure variables are substituted by parameters to be estimated. The model parameters can be estimated by using the current probe vehicle systems. An eco-routing approach combining the weighting method and k-shortest path algorithm is developed to find the optimal path along the Pareto frontier. The vehicle CO₂ emission model and eco-routing approach are validated in a large-scale transportation network in Toyota city, Japan. The relative importance analysis indicates that the average speed has the largest impact on vehicle CO₂ emission. Specifically, the benefit trade-off between CO₂ emission reduction and the travel time buffer is discussed by carrying out sensitivity analysis in a network-wide scale. It is found that the average reduction in CO₂ emissions achieved by the eco-friendly path reaches a maximum of around 11% when the travel time buffer is set to around 10%.     

Electric vehicles in multi-vehicle households

The suitability of an electric vehicle of a given range to serve in place of a given conventional vehicle is not limited by the daily travel over distances within that that range, but rather by the occasional inconvenience of finding alternative transport for longer trips. While the frequency of this inconvenience can be computed from usage data, the willingness of individual users to accept that replacement depends on details of available transportation alternatives and their willingness to use them. The latter can be difficult to assess. Fortunately, 65% of US households have access to the most convenient alternative possible: a second car. In this paper we describe an analysis of prospective EV acceptance and travel electrification in two-car households in the Puget Sound region. We find that EVs with 60 miles of useful range could be acceptable (i.e. incur inconvenience no more than three days each year) to nearly 90% of two-car households and electrify nearly 55% of travel in those households (32% of all travel). This compares to 120 miles range required to achieve the same fraction of electrified travel via one-for-one replacement of individual vehicles. Even though only one third of personal vehicles in the US may be replaced in this paradigm, the ‘EV as a second-car’ concept is attractive in that a significant fraction of travel can be electrified by vehicles with modest electric range and virtually no dependence on public charging infrastructure.     

Recursive estimation of origin-destination matrices from input/output counts

The application of recursive prediction error techniques to the problem of estimating origin-destination patterns from input and output volume counts is described. Each algorithm deals with the special case where route choice between origin and destination can be ignored. A gradient algorithm developed by Cremer and Keller (1983) turns out to be a special case of a family of methods described by Ljung and Söderström (1983). After describing how the methods developed in Ljung and Söderström (1983) could be modified so that the resulting estimates satisfy natural constraints, a number of algorithm possibilities are tested. Generally, those algorithms employing Gauss-Newton search directions appear superior to gradient-based methods, while the constraining procedures improve accuracy.     

A survey of Hungarian transport policy

Abstract

In its introductory part this article discusses the principles of the transport policy approved in 1968, followed by the reasons behind the advances on this policy approved in 1978.

It then goes on to review the Hungarian transport pattern and organization, including the roles played by the railways, the road transport companies, the state‐owned enterprises as well as cooperatives, urban transport, shipping, air transport, pipelines, and private transport.

In discussing the division of labour (or market sharing) in transport it concludes that passenger transport is increasing slowly, while the proportion of private transport is continuing to rise. A moderate increase is expected in goods transport with a decline in the share of the railways and a rise in that of the other transport branches. This division of labour is being influenced by economic, not administrative, means.

The main target of the advanced transport policy is to shape a transport system which corresponds to socioeconomic requirements. This means that goods transport capacities must be put to more efficient use, which involves improving development, organizational and planning operations. In passenger transport priority must go to public transport while the proportion of private transport must be defined in keeping with demand and economic possibilities.

In the development of the infrastructure and investments, the need to improve energy use and protect the environment must be stressed.

The rest of the article presents the detailed reasoning behind the measures already taken and scheduled to be taken to achieve these main targets.     

Access control policies without inside queues: Their properties and public policy implications

An access control policy that eliminates all queues beyond the entry points to a network has obvious benefits, which include smooth travel and predictable travel times inside the network. Yet it has never been proven, to the best of our knowledge, whether excluding inside queues yields sub-optimal network performance or, in other words, allowing inside queues can actually further reduce the system travel cost. Moreover, it is not clear whether an optimal control policy derived from efficiency considerations can also be a fair policy to all road users. This paper provide answers to these questions in the context of a monocentric network. By analyzing the structure of the access control problem considering all feasible policies (with/without inside queues), we show that the minimal system cost realizable by access control can be obtained without directly solving a non-convex optimization program, and can indeed always be achieved by a control policy excluding all of the inside queues. These optimal policies are defined by a polyhedral set and a Finite Generation Algorithm can be applied to derive the analytical form of this set. The optimal policies are not unique in general, thus making it possible to achieve both minimal system cost and fairness simultaneously.     

Development and testing of a fully Adaptive Cruise Control system

Adaptive Cruise Control systems have been developed and introduced into the consumer market for over a decade. Among these systems, fully-adaptive ones are required to adapt their behaviour not only to traffic conditions but also to drivers’ preferences and attitudes, as well as to the way such preferences change for the same driver in different driving sessions. This would ideally lead towards a system where an on-board electronic control unit can be asked by the driver to calibrate its own parameters while he/she manually drives for a few minutes (learning mode). After calibration, the control unit switches to the running mode where the learned driving style is applied. The learning mode can be activated by any driver of the car, for any driving session and each time he/she wishes to change the current driving behaviour of the cruise control system.The modelling framework which we propose to implement comprises four layers (sampler, profiler, tutor, performer). The sampler is responsible for human likeness and can be calibrated while in learning mode. Then, while in running mode, it works together with the other modelling layers to implement the logic. This paper presents the overall framework, with particular emphasis on the sampler and the profiler that are explained in full mathematical detail. Specification and calibration of the proposed framework are supported by the observed data, collected by means of an instrumented vehicle. The data are also used to assess the proposed framework, confirming human-like and fully-adaptive characteristics.     

How to Capture the Passengers’ Point of View on a Transit Service through Rating and Choice Options

Abstract

In this paper, a methodology for capturing the transit passenger’s point of view by using both rating and choice options is proposed. For this purpose, some discrete choice logit models are introduced; the models allow the probability of choice of some alternative transit services to be calculated, and the importance of each service aspect to be determined. The models are calibrated by using data collected by a survey in which a stated preferences experiment was proposed to a sample of passengers, and some judgements were expressed by them about their transit services, in terms of perceptions and expectations. The introduced methodology provides a relevant contribution from a practical viewpoint because it allows the identification of the most important aspects on overall service quality; it is useful to the transit operators for measuring service quality and for investing on the various service aspects in order to effectively improve transit services.     

Prospects for computer aided railway scheduling: perspectives from users and parallels from mass transit

Railway scheduling faces new challenges as competition and, in many parts of the world, privatisation require ever better results, both in terms of minimising the resources used and maximising the performance achieved by those resources. It is therefore surprising that in practice railway scheduling tasks appear to be performed largely without the use of optimizing models. This paper takes two different perspectives, a case study of user needs from the UK railway industry and a comparative analysis with mass transit scheduling systems, to consider why this might be and assesses what the future prospects are for computer aided railway scheduling.

A number of conclusions are drawn: that optimization models need to be integrated with software packages that meet schedulers' data management needs; that researchers need to work with commercial developers to achieve this integration; that there needs to be an emphasis on extending models to cover more real‐life circumstances; and that solutions with international applicability should be sought.     

Manual vs. adaptive cruise control – Can driver’s expectation be matched?

The role of the driver in the longitudinal car following control task will change from operator to supervisor with most of manual control replaced by automation as adaptive cruise control (ACC) technologies become commonplace. The extent to which manual control can be replaced by ACC will be determined by many factors. An important issue is the compatibility between ACC performance and the driver’s expectations.This paper describes the results of a simulation study of the performance of ACC relative to driver expectation. Driver’s expectation is quantitatively defined as the expected deceleration rate for several time-to-collision (TTC) levels, and an absolute minimum TTC that drivers tried to avoid in all cases. A two-level ACC algorithm was used to simulate the performance of an ACC equipped vehicle in various scenarios, and the result was compared to the driver’s expectations. The investigation has focused on scenarios which ACC is able to manage technically, but where driver expectations might be breached.By systematically changing variables such as the parameters of the ACC algorithms, traffic scenarios and time-headway settings, a large number of situations have been tested. The results have revealed that whilst appropriate ACC settings can be found which will meet the driver’s expectations, the ACC settings that are most capable in a range of traffic conditions are not necessarily the most user-friendly. A discussion on the implications of the findings is also presented.     

Activity patterns in space and time: calculating representative Hagerstrand trajectories

Daily activity diaries can be recorded as sequences of characters representing events and their contexts as they unfold during the day. Dynamic programming algorithms as used in bioinformatics have been used by a number of researchers to measure the similarities and differences between travel patterns on the basis of temporal sequencing of events, activity transition, and total activity time. The resultant similarity matrices have been shown to be more effective in classifying sequential patterns than classifications based on alternative similarity indices. The basic algorithms can be amended to include the geographic coordinates of events by a suitable amendment to the definition of distance. This permits quantitative classification of Hagerstrand-type activity trajectories on the basis of both activity and spatial similarity. Such a classification can be used to group similar trajectories and to identify representative trajectories that are analogous to measures of central tendency in univariate statistics, giving more concrete meaning to the concept of the activity pattern than any other method now available. The paper illustrates the effect of considering both events and locations in the classification of daily activity patterns using activity diary data gathered in the town of Reading. The algorithm has been implemented in the Clustal_TXY alignment software package.

Man and his transport behaviour Part 4a. User response to price changes: application of the ‘threshold’ concept

Summary

(1) The response of an individual consumer to change in such characteristics as price will be to change behaviour at a critical point, a ‘threshold’ at which a change of behaviour is perceived to be beneficial.

(2) Most choices can be viewed as binary, for example, between pairs of transport modes. A cumulative normal distribution of responses will give an S‐shaped curve, the mid‐point being at the average threshold value.

(3) An aggregate demand curve should show the response of a given group of people to a range of price changes at one point in time. Most curves derived from revealed behaviour do not permit this. To some extent, a demand curve must be derived from interviews and other tests, giving hypothetical behaviour. Such methods are used in non‐transport consumer tests, and work by Brög et al. gives a similar picture for transport users, supporting the concept of the S‐shaped curve.

(4) Allowance for frequency of trip‐making modifies this picture, suggesting that a smoother curve may be appropriate for some conditions, such as non‐work trips. These approaches may be combined by use of catastrophe theory, with two control factors. The hysteresis effect is found around the threshold where repeated changes in the basic stimulus produce successively smaller responses.

(5) There is some evidence of symmetrical response by public transport users to real increases and reductions in cash‐paid graduated fares, but this is not the case where different forms of pricing are involved.

(6) An example of threshold effects in private transport may be found in the monitoring of tolls on the Itchen Bridge by Atkins. Demand became particularly sensitive to price in a certain range.

(7) In the public transport field, there is similar evidence from the experience of introducing flat or zonal fares where graduated fares previously applied. Where travelcards are sold, the effect is much greater, and cases such as the West Midlands show little if any effect on sales despite real price increases. Here, trips are about 7% higher than would have been expected for the same revenue target, had graduated fares been retained. However, it may well be possible to exceed the threshold, especially where fares simplification and increases are combined, as the Trondheim experience suggests.     

Optimal scheduling of public transport fleet at network level

This paper deals with the development of a strategic approach for optimizing the operation of public transport system that considers both user's objective and operator's objective. Passengers of public transport are assumed to seek a minimum wait time to conduct the trips, while on the other hand, operators are concerned with the efficient operation such as minimum fleet size. The average minimum wait time is to be achieved by creating an optimal despatching policy for each vehicle from the terminal. As for efficient operation the utilisation of vehicle should be maximised by having a minimum number of vehicles in operation. User's and operator's objectives are optimized within certain operational constraints such as vehicle capacity to maintain acceptable level of service. The i‐model is contructed in a bi‐level programming form in which the user's objective is minimized by dynamic programming and the operator's objective is minimized by various routing strategies. Furthermore, an algorithm and a contrived example are developed to solve and see the performance of the approach.     

An empirical assessment of the feasibility of battery electric vehicles for day-to-day driving

Driven by sustainability objectives, Australia like many nations in the developed world, is considering the option of battery electric vehicles (BEVs) as an alternative to conventional internal combustion engine vehicles (ICEVs). In addition to issues of capital and running costs, crucial questions remain over the specifications of such vehicles, particularly the required driving range, recharge time, re-charging infrastructure, performance, and other attributes that will be of importance to consumers. With this in mind, this paper assesses (hypothetically) the extent to which current car travel needs could be met by BEVs for a sample of motorists in Sydney assuming a home-based charging set-up, which is likely to be the primary option for early adopters of the technology. The approach uses five weeks of driving data recorded by GPS technology and builds up home-home tours to assess the distances between (in effect) charging possibilities. An energy consumption model based on characteristics of the vehicle, and the speeds recorded by the GPS is adapted to determine the charge used, while a battery recharge function is used to determine charging times based on the current battery level. Among the most pertinent findings are that over the five weeks, (i) BEVs with a range as low as 60 km and a simple home-charge set-up would be able to accommodate well over 90% of day-to-day driving, (ii) however the incidence of tours requiring out-of-home charging increases markedly for vehicles below 24 kWh (170 km range), (iii) recharge time in itself has little impact on the feasibility of BEVs because vehicles spend the majority of their time parked and (iv) effective range can be dramatically impacted by both how a vehicle is driven and use of electrical auxiliaries, and (v) while unsuitable for long, high-speed journeys without some external re-charging options, BEVs appear particularly suited for the majority of day-to-day city driving in big cities where average journey speeds of 34 km/h are close to optimal in terms of maximising vehicle range. The paper has implications for both policy-makers and auto manufacturers in breaking down some of the (perceived) barriers to greater uptake of BEVs in the future.     

Locating inspection facilities in traffic networks: an artificial intelligence approach

Abstract

In order for traffic authorities to attempt to prevent drink driving, check truck weight limits, driver hours and service regulations, hazardous leaks from trucks, and vehicle equipment safety, we need to find answers to the following questions: (a) What should be the total number of inspection stations in the traffic network? and (b) Where should these facilities be located? This paper develops a model to determine the locations of uncapacitated inspection stations in a traffic network. We analyze two different model formulations: a single-objective optimization problem and a multi-objective optimization problem. The problems are solved by the Bee Colony Optimization (BCO) method. The BCO algorithm belongs to the class of stochastic swarm optimization methods, inspired by the foraging habits of bees in the natural environment. The BCO algorithm is able to obtain the optimal value of objective functions in all test problems. The CPU times required to find the best solutions by the BCO are found to be acceptable.     

Valorization of carbon dioxide by conversion into fuel using renewable energy in Algeria

Reducing the emissions of the main anthropogenic greenhouse gases, such as carbon dioxide (CO₂), is one of the major challenges of this century. A partial solution to these environmental problems could be the capture and the conversion of carbon dioxide. The main objective of the present work is to study the opportunities and prospects of recycling carbon dioxide to produce synthetic fuel, particularly methanol, which is a complementary technology to carbon capture and storage (CCS). This methanol will be produced by using several renewable energies, such as solar, wind and geothermal, for the purpose of using it in the transportation sector in Algeria. In 2013, Algeria’s total amount of CO₂ emissions (created by energy consumption) was 143 million tonnes. It is estimated that 44.4 million tonnes of CO₂ can be captured from the exhaust of stationary units (factories and power stations) and converted to methanol every year. By adopting this process, approximately 32 million tonnes of methanol can be produced with an energy value of 580,000 TJ. The methanol produced from CO₂ can be used as an alternative transportation fuel. For this reason, the Geographical Information System (GIS) is used to present the spatial distribution of the methanol demand in short and long terms, based on market penetration rates, vehicle fleet and population data. An analysis of the energy balance, environment and economics of CO₂ recycling process is presented. In terms of environmental performance, the reduction in carbon dioxide emissions that come from the transport sector was remarkable in 2045.     

Instrumented city database analysts using multi-agents

The Instrumented City (iC) database is a multi-purpose, transport-related database facility for use by the entire academic transport research community. Data from the UK Leicester City Council and Nottinghamshire County Council Traffic Management Computers is logged and archived on a continuous basis, by the Leeds University’s Institute for Transport Studies. Since its inception in 1992, the iC database has been used for various real-time applications such as air quality and noise monitoring, modelling and forecasting. This paper describes the framework that demonstrates the feasibility of using multi-agents as information analysts to process and manage the iC database. The agents are adaptive, interactive and personal. They can be trained via the interactions with the users to be personalised for individual preferences. These agents are designed to be responsible for (1) data clean-up to remove outliers; (2) missing data substitutions; (3) statistical data analysis; (4) data mining to enhance the understanding of the relationships between traffic and air quality, noise and health; and (5) knowledge discovery by identifying unknown but potentially important patterns.