A multi-criteria decision support methodology for implementing truck operation strategies

This study proposes a multi-criteria decision support methodology to enable the prioritization of potential alternative transportation system operations strategies and then demonstrates the effectiveness of the methodology using a case study involving truck operations. The primary feature of this methodology is its ability to help policymakers consider economic, public, and private sector standpoints simultaneously. The economic criterion is cost to the public sector where four criteria related to truck impacts on the transportation system are incorporated. These are traffic congestion, safety hazards, air pollution, and pavement damage. In addition, reliability and productivity are regarded as metrics representing the private sector viewpoint since they can significantly affect profitability. The methodology combines qualitative and quantitative aspects of these standpoints. In order to demonstrate the applicability of this methodology, a corridor with some of the highest truck traffic in the US is selected as a case study and three forms of left lane restrictions for trucks are considered. For qualitative analysis, survey data were collected from two groups classified as public agency and transportation industry professionals who are experts in trucking. In addition, a micro traffic simulation model was used to produce various performance measurements that can describe quantitative impacts. As a result, the methodology provides a rational argument for prioritizing potential alternative truck strategies.     

A spatial decision support system for retail plan generation and impact assessment

Current geographic information systems typically offer limited analytical capabilities and lack the flexibility to support spatial decision making effectively. Spatial decision support systems aim to fill this gap. Following this approach, this paper describes an operational system for integrated land-use and transportation planning called Location Planner. The system integrates a wide variety of spatial models in a flexible and easy-to-use problem solving environment. Users are able to construct a model out of available components and use the model for impact analysis and optimization. Thus, in contrast to existing spatial decision support systems, the proposed system allows users to address a wide range of problems. The paper describes the architecture of the system and an illustrative application. Furthermore, the potentials of the system for land-use and transportation planning are discussed.     

A decision support system for integrated hazardous materials routing and emergency response decisions

Hazardous materials routing constitutes a critical decision in mitigating the associated transportation risk. This paper presents a decision support system for assessing alternative distribution routes in terms of travel time, risk and evacuation implications while coordinating the emergency response deployment decisions with the hazardous materials routes. The proposed system provides the following functionalities: (i) determination of alternative non-dominated hazardous materials distribution routes in terms of cost and risk minimization, (ii) specification of the hazardous materials first-response emergency service units locations in order to achieve timely response to an accident, and (iii) determination of evacuation paths from the impacted area to designated shelters and estimation of the associated evacuation time. The proposed system has been implemented, used and evaluated for assessing alternative hazardous materials routing decisions within the heavily industrialized area of Thriasion Pedion of Attica, Greece. The implementation of the aforementioned functionalities is based on two new integer programming models for the hazardous materials routing and the emergency response units location problems, respectively. A simplified version of the routing model is solved by an existing heuristic algorithm developed by the authors. A new Lagrangean relaxation heuristic algorithm has been developed for solving the emergency response units location problem. The focus of this paper is on the exposition of the proposed decision support system components and functionalities. Special emphasis is placed on the presentation of the two new mathematical models and the new solution method for the location model.     

A decision support approach to the computerisation of some operational decision problems in community transport

Community Transport (CT) in the UK operates a diverse range of services, and organisations are computerising management and operational functions. This paper describes the approach which has been taken to computerising four operational decision making functions.

The paper considers models of human decision making and problem solving, with particular reference to an information processing view of cognitive activity and to perception and memory. The design of decision support systems is also discussed.

Four decision problems are considered. For each, the paper considers how people tackle the problem, how computers can be used to tackle it and the approach which has been adopted.

For allocating trips to vehicles using a diary, the approach has been to provide a representation on screen of a manual diary. For vehicle brokerage, vehicles are presented to the operator allocating a booking in an order based on the Sequence Number, an index of how ‘difficult to book’ a vehicle is, and the distance of the vehicle's base from the start point of the trip. For the sorting of passenger pick‐ups into an efficient tour, traditional solutions to the travelling salesperson problem have been rejected in favour of a solution using spacefilling curves. Finally, for allocating dial‐a‐ride passenger trips to vehicle shifts an approach has been chosen which presents the operator with appropriate information rather than attempting to automate the scheduling.

The paper concludes that the approach to the diary has been successful and accepted by operators, although the similar approach to the dial‐a‐ride scheduling has not, as the system has not yet been able to replace manual scheduling aids. The facility to order passenger pick‐ups is little used by operators. Finally, it is suggested that the vehicle brokerage problem may be an appropriate use of fuzzy logic.     

Using GIS in Denmark for traffic planning and decision support

This paper presents current efforts at the Technical University of Denmark for developing concepts for a Geographic Information System for the whole traffic planning process. Such a system (GIS-T) will consist of five model for collection of data, determination of alternate solutions, estimation of future traffic flows, impact analyses and selection of a solution. Furthermore, the system will contain procedures for evaluation and quality control of data and results. Such an integrated GIS-T system will not only ease the specific work, but also gather and strengthen the process of traffic planning. The paper deals mainly with conceptual problems. The theoretical discussions, however, are supplemented by practical examples of traffic models, models for impact analyses and models for data management and quality control, which were implemented in GIS and tested on several real size problems in Denmark. The final part of the paper outlines the promising perspective of future work with GIS-T.     

A decision analysis framework for intermodal transport: Comparing fuel price increases and the internalisation of external costs

This paper presents the impact of fuel price increases on the market area of intermodal transport terminals. Aim of this research is to determine whether an increase in fuel prices is sufficient enough to raise the market area of intermodal transport to the same degree that would be accomplished by stimulating intermodal transport through policy instruments. Therefore, several fuel price scenarios are analysed in order to verify the impact of different fuel price evolutions on the market area of unimodal road transport compared to intermodal transport in Belgium. The LAMBIT-model (Location Analysis for Belgian Intermodal Terminals), which is a GIS-based model (Macharis and Pekin, 2008), is used to analyse the different fuel price increases and enables a visualisation of the impact on the market area. The LAMBIT model incorporates the different network layers for each transport mode by setting up a GIS network that includes four different layers: the road network, the rail network, the inland waterways network and the final haulage network. The geographic locations of the intermodal terminals and the port of Antwerp are added as nodes in the network and the Belgian municipality centres are defined and connected to the different network layers. Based on the different fuel price scenarios representing respectively a fuel price increase with 10% (low price case), 50% (business as usual case) and 90% (high price case), the results of the LAMBIT model show that the market areas rise in favour of intermodal barge/road and intermodal rail/road. Depending on the scenario, the degree of modal shift however differs. Additionally, in order to compare policy measures with the effect of a fuel price increase, the internalisation of the external costs is analysed with the LAMBIT model. For some years, the European Commission is supporting the idea that transportation costs should reflect the true impacts on environment and society, and is relentlessly pushing towards the so called ‘internalisation of external costs’ as a policy instrument in order to establish fair and efficient pricing of different transport modes. This requires monetarizing the external effects of transport and adding them to the already internalized costs in order to give the correct price signals. Results of this comparative analysis performed with the LAMBIT model are also presented in this paper.     

Transportation agencies experiences with decision support systems for airport ground access planning

This article reports on a field investigation into the ways that transportation agencies use quantitative and qualitative information for making strategic decisions regarding airport ground access. The study analyzes the value of this information for planning airport ground access improvements at seven major international airport sites.The major finding of the research is that quantitative modeling for strategic decision support is very difficult, costly and time consuming. Modelers are confident that the models are accurate and reliable but executives generally lack confidence in the results. Transportation officials believe that the information supplied is flawed by a number of defects that minimize its value for strategic decision makers. The information defects described in this article provide an analysis of the structural difficulty of using quantitative modeling for transportation problems of strategic importance. To date, qualitative information is not frequently used, but some transportation agencies are considering its application to designing transportation services. Although this study is limited to airport ground access, the authors feel that this evidence, in conjunction with the evidence from other studies in the transportation area, dictates a need for wariness in the development of decision support systems for transportation planners. Developers of decision support systems for transportation planners must be aware of modeling costs and defects and consider how to improve the timeliness, relevance and credibility of information quantitative models provide transportation executives. Fundamentally it is important to recognize that decision makers tend, either singularly or in concert with other individuals or groups, to be the champions of a long-term vision for the community. When modeling produces inconsistent or wide ranging results that contradict their position, decision makers may not only discard modeling activities, but lose confidence in the models altogether. As a consequence, transportation planners are faced with the challenge of how to improve quantitative modeling. The most reliable and effective means for improvement is incorporation of qualitative techniques which provide greater understanding of customer perceptions and human behavior.     

Real-time tracking of activity scheduling/schedule execution within a unified data collection framework

One of the major foci in transport research is the identification of the temporal–spatial decision making structure embedded in activity scheduling and its linkage to actual activity execution. The latter part of the research in question has not been explored explicitly in real life situations due to the lack of effective data collection means. This paper presents a real-time activity scheduling, activity/travel survey system that incorporates the extraction of activity scheduling and the execution information within one unified data collection framework. These “revealed” data can be used for explicitly defining the mechanism of how people’s activity schedules dynamically adapt to social-demographic and temporal–spatial constraints and finally lead to the observed activity-travel patterns.     

Analyzing commuter train user behavior: a decision framework for access mode and station choice

The purpose of the current research effort is to develop a framework for a better understanding of commuter train users’ access mode and station choice behavior. Typically, access mode and station choice for commuter train users is modeled as a hierarchical choice with access mode being considered as the first choice in the sequence. The current study proposes a latent segmentation based approach to relax the hierarchy. In particular, this innovative approach simultaneously considers two segments of station and access mode choice behavior: Segment 1—station first and access mode second and Segment 2—access mode first and station second. The allocation to the two segments is achieved through a latent segmentation approach that determines the probability of assigning the individual to either of these segments as a function of socio-demographic variables, level of service (LOS) parameters, trip characteristics, land-use and built environment factors, and station characteristics. The proposed latent segment model is estimated using data from an on-board survey conducted by the Agence Métropolitaine de Transport for commuter train users in Montreal region. The model is employed to investigate the role of socio-demographic variables, LOS parameters, trip characteristics, land-use and built environment factors, and station characteristics on commuter train user behavior. The results indicate that as the distance from the station by active forms of transportation increases, individuals are more likely to select a station first. Young persons, females, car owners, and individuals leaving before 7:30 a.m. have an increased propensity to drive to the commuter train station. The station model indicates that travel time has a significant negative impact on station choice, whereas, presence of parking and increased train frequency encourages use of the stations.     

An integrated transportation decision support system for transportation policy decisions: The case of Turkey

From the point of view of the feasibility of providing growth in road capacity parallel to the predicted growth in traffic as well in terms of impact on the environment and health, current trends in transportation are unsustainable. Transport problems are expected to worsen due to the fact that worldwide automobile ownership tripled between 1970 and 2000, and the movement of goods is projected to increase by 50% by 2010. Similar trends can be seen in an even more dramatic way in Turkey. The Turkish transport network has not followed a planned growth strategy, due to political factors. There is no transportation master plan which aims to integrate the transport modes in order to provide a balanced, multimodal system. This study proposes a decision support system that guides transportation policy makers in their future strategic decisions and facilitates analysis of the possible consequences of a specific policy on changing the share of transportation modes for both passenger and freight transportation. For this purpose, based on the wide spectrum of critical issues encountered in the transportation sector, several scenarios have been built and analysed.     

A framework for urban freight policy analysis

This paper provides an overview of the urban freight process, in the context of the supply and demand aspects of freight. A framework for analysis is developed, and within that framework, particular aspects of the urban freight process are described. Issues of concern from a public policy viewpoint are highlighted.

Seven main instruments related to public policy are introduced and their application described — taxes and subsidies, regulations, investment, operational instruments, planning, public ownership and research.

It is concluded that the importance of urban freight to the community and its relevance to urban transport justifies a higher level of attention in transport planning and policy formulation, and that there are a wide range of policy instruments available to enable this to be done. The objective of such planning and policy making needs to be specified in each specific context.     

A simulation model of reliable schedule design for a fixed transit route

This paper describes a simulation model of schedule design for a fixed transit route adopting the holding control strategy. The model is capable of determining the locations of time points and the amount of slack time allocated to each time point by minimizing the total cost associated with the schedule. The optimization is carried out through a process, which combines a heuristic search, enumeration, and population ranking and selection techniques. Examples showing applications and potential savings of the proposed model are given. It is shown that the model can serve as a practical tool for designing reliable, economical as well as operational transit schedules.     

A stochastic passenger loading model of airline schedule performance

The passenger loading problem is defined as that of determining the distribution of passengers that will be carried on each flight in a given market over the course of the day. This problem is stochastic in nature, and must take into account the fact that as some flights become booked up, passengers may spill to adjacent flights, or may choose not to fly on that airline. A precise model of the loading process is developed and solved using an efficient numerical procedure. Several approximations are introduced and tested which further improve the overall efficiency. The model represents a more rigorous solution approach than has appeared previously in the literature, and as such could be used to evaluate simpler approximations. It is fast enough, however, to be used as an interactive schedule evaluation and design tool.     

A network option portfolio management framework for adaptive transportation planning

A real option portfolio management framework is proposed to make use of an adaptive network design problem developed using stochastic dynamic programming methodologies. The framework is extended from Smit’s and Trigeorgis’ option portfolio framework to incorporate network synergies. The adaptive planning framework is defined and tested on a case study with time series origin-destination demand data. Historically, OD time series data is costly to obtain, and there has not been much need for it because most transportation models use a single time-invariant estimate based on deterministic forecasting of demand. Despite the high cost and institutional barriers of obtaining abundant OD time series data, we illustrate how having higher fidelity data along with an adaptive planning framework can result in a number of improved management strategies. An insertion heuristic is adopted to run the lower bound adaptive network design problem for a coarse Iran network with 834 nodes, 1121 links, and 10 years of time series data for 71,795 OD pairs.     

A threshold model of social contagion process for evacuation decision making

Individual evacuation decisions are often characterized by the influence of one’s social network. In this paper a threshold model of social contagion, originally proposed in the network science literature, is presented to characterize this social influence in the evacuation decision making process. Initiated by a single agent, the condition of a cascade when a portion of the population decides to evacuate has been derived from the model. Simulation models are also developed to investigate the effects of community mixing patterns and the initial seed on cascade propagation and the effect of previous time-steps considered by the agents and the strength of ties on average cascade size. Insights related to social influence include the significant role of mixing patterns among communities in the network and the role of the initial seed on cascade propagation. Specifically, faster propagation of warning is observed in community networks with greater inter-community connections.     

A framework for analyzing rank-ordered data with application to automobile demand

In this paper, we develop a general random utility framework for analyzing data on individuals’ rank-orderings. Specifically, we show that in the case with three alternatives one can express the probability of a particular rank-ordering as a simple function of first choice probabilities. This framework is applied to specify and estimate models of household demand for conventional gasoline cars and alternative fuel vehicles in Shanghai based on rank-ordered data obtained from a stated preference survey. Subsequently, the framework is extended to allow for random effects in the utility specification to allow for intrapersonal correlation in tastes across stated preference questions. The preferred model is then used to calculate demand probabilities and elasticities and the distribution of willingness-to-pay for alternative fuel vehicles.     

A conceptual and methdological framework for the generation of activity-travel patterns

This paper develops a conceptual framework for the generation of activity and travel patterns in the context of more general structures and presents an integrated model system as a step toward development of an improved travel demand forecasting model system. We propose a two-stage structure to model activity and travel behavior. The first stage, the stop generation and stop/auto allocation models, consists of the choices for the number of household maintenance stops and the allocation of stops and autos to household members. The second stage, the tour formation model, includes the choices for the number of tours and the assignment of stops to tours for each individual, conditional on the choices in the first stage. Empirical results demonstrate that individual and household socio-demographics are important factors affecting the first stage choices, the generation of maintenance stops and the allocation of stops and autos among household members, and the second stage choices, the number of tours and the assignment of stops to tours. This revised version was published online in June 2006 with corrections to the Cover Date.     

A hybrid model of fuzzy and AHP for handling public assessments on transportation projects

Having an effective public participation in transportation planning and project development processes has been a major concern for developed countries. In the United States, for instance, all state Departments of Transportation are subject to the Transportation Equity Act (TEA-21) that formally requires public involvement in transportation planning. Since transportation planning involves public resources and values, judgments by the public should play a key role in determining final decisions. Therefore, all these agencies are required not only to disseminate information to the public, but also to solicit and consider public opinion in forming transportation policy. This work presents a decision support model, with public involvement and public oversight, to help policy makers select appropriate transportation projects for implementation. Since focus groups will face multiple objectives and inexact information in the process, a hybrid model of fuzzy logic and analytical hierarchy process (AHP) is proposed. A set of ‘if–then’ rules based on Weber’s psycho-physical law of 1834 is presented to reason from fuzzy numbers to capture essential subjective preferences, pairwise, among the alternatives. The AHP is then incorporated to estimate preference allotments among alternatives. An example application of the suggested method is provided seeking public approval of an appropriate public bus transportation system choosing between one run by municipal authorities and one run by private agencies to show how this procedure works.

A framework for robustness analysis of road networks for short term variations in supply

There is a growing awareness that road networks, are becoming more and more vulnerable to unforeseen disturbances like incidents and that measures need to be taken in order to make road networks more robust. In order to do this the following questions need to be addressed: How is robustness defined? Against which disturbances should the network be made robust? Which factors determine the robustness of a road network? What is the relationship between robustness, travel times and travel time reliability? Which indicators can be used to quantify robustness? How can these indicators be computed? This paper addresses these questions by developing a consistent framework for robustness in which a definition, terms related to robustness, indicators and an evaluation method are included. By doing this, policy makers and transportation analyst are offered a framework to discuss issues that are related to road network robustness and vulnerability which goes beyond the disconnected definitions, indicators and evaluation methods used so far in literature. Furthermore, the evaluation method that is presented for evaluating the robustness of the road network against short term variations in supply (like incidents) contributes to the problem of designing robust road networks because it has a relatively short computation time and it takes spillback effects and alternative routes into account.     

Application of genetic algorithm for scheduling and schedule coordination problems

The problems on scheduling and schedule co‐ordination usually have conflicting objectives related to user's cost and operator's cost. Users want to spend less time to wait, transfer and travel by public buses. Operators are interested in profit making by lesser vehicle operating cost and having a minimum number of buses. As far as level of service is concerned users are interested in lesser crowing while operators are concerned with maximizing profit and thus to have higher load factors. In schedule co‐ordination problems transfer time plays an important role. Users are interested in coordinating services with in acceptable waiting time whereas operators prefer to have lesser services and want to meet higher demands, which invariably increases waiting time. These problems have multiple conflicting objectives and constraints. It is difficult to determine optimum solution for such problems with the help of conventional approaches. It is found that Genetic Algorithm performs well for such multi objective problems.