Incorporating Driver Behaviors in Network Design Problems: Challenges and Opportunities

The goal of a network design problem (NDP) is to make optimal decisions to achieve a certain objective such as minimizing total travel time or maximizing tolls collected in the network. A critical component to NDP is how travelers make their route choices. Researchers in transportation have adopted human decision theories to describe more accurate route choice behaviors. In this paper, we review the NDP with various route choice models: the random utility model (RUM), random regret-minimization (RRM) model, bounded rationality (BR), cumulative prospect theory (CPT), the fuzzy logic model (FLM) and dynamic learning models. Moreover, we identify challenges in applying behavioral route choice models to NDP and opportunities for future research.     

Eco-design of transportation in sustainable supply chain management: A DEA-like method

This study addresses the issue of eco-design for transportation in sustainable supply chain management (SSCM). Data envelopment analysis (DEA) is adopted and extended to construct a model for this application. This proposed model, together with the tractable algorithm developed in this research, can provide stakeholders with a Pareto Optimal transportation strategy. This derived transportation strategy can help stakeholders realize certain transportation goals with less resource consumption and pollution emission. The discussion presented leads to a heuristic Joint Transportation Policy and concludes with two useful suggestions for putting the strategy into practice. The proposed model was used in an empirical study of design sustainable transportation mechanism for one air-condition manufacturer in China to transport its products as well, the analysis further demonstrating the theoretical and practical value of this research.     

Intermodal hub-and-spoke network design: Incorporating multiple stakeholders and multi-type containers

This paper develops a mathematical program with equilibrium constraints (MPEC) model for the intermodal hub-and-spoke network design (IHSND) problem with multiple stakeholders and multi-type containers. The model incorporates a parametric variational inequality (VI) that formulates the user equilibrium (UE) behavior of intermodal operators in route choice for any given network design decision of the network planner. The model also uses a cost function that is capable of reflecting the transition from scale economies to scale diseconomies in distinct flow regimes for carriers or hub operators, and a disutility function integrating actual transportation charges and congestion impacts for intermodal operators. To solve the MPEC model, a hybrid genetic algorithm (HGA) embedded with a diagonalization method for solving the parametric VI is proposed. Finally, the comparative analysis of the HGA and an exhaustive enumeration algorithm indicates a good performance of the HGA in terms of computational time and solution quality. The HGA is also applied to solve a large-scale problem to show the applicability of the proposed model and algorithm.     

Optimization of a feeder-bus route design by using a multiobjective programming approach

This paper presents a feeder-bus route design model, capable of minimizing route length, minimizing maximum route travel time of planned routes, and maximizing service coverage for trip generation. The proposed model considers constraints of route connectivity, subtour prevention, travel time upper bound of a route, relationships between route layout and service coverage, and value ranges of decision variables. Parameter uncertainties are dealt with using fuzzy numbers, and the model is developed as a multiobjective programming problem. A case study of a metro station in Taichung City, Taiwan is then conducted. Next, the programming problem in the case study is solved, based on the technique for order preference by similarity to ideal solution approach to obtain the compromise route design. Results of the case study confirm that the routes of the proposed model perform better than existing routes in terms of network length and service coverage. Additionally, increasing the number of feeder-bus routes decreases maximum route travel time, increases service coverage, and increases network length. To our knowledge, the proposed model is the first bus route design model in the literature to consider simultaneously various stakeholder needs and support for bus route planners in developing alternatives for further evaluation efficiently and systematically.     

A set-covering model for a bidirectional multi-shift full truckload vehicle routing problem

This paper introduces a bidirectional multi-shift full truckload transportation problem with operation dependent service times. The problem is different from the previous container transport problems and the existing approaches for container transport problems and vehicle routing pickup and delivery are either not suitable or inefficient. In this paper, a set covering model is developed for the problem based on a novel route representation and a container-flow mapping. It was demonstrated that the model can be applied to solve real-life, medium sized instances of the container transport problem at a large international port. A lower bound of the problem is also obtained by relaxing the time window constraints to the nearest shifts and transforming the problem into a service network design problem. Implications and managerial insights of the results by the lower bound results are also provided.     

Development of control models for the planning of sustainable transportation systems

Planning of sustainable transportation systems requires integration of multiple systems while considering a holistic approach. A limited amount of research has been conducted that simultaneously considers all the transportation, economic activity, environmental and social effects. The proposed research envisages incorporating considerations related to sustainability and providing solutions to stakeholders in policy making. In this paper, a dynamic model for planning and development of sustainable transportation systems is presented. This is given by a system of three nonlinear differential equations representing the dynamics of the three independent states, namely, transportation, activity, and environmental systems. A policy scenario considering investment in energy efficient technologies and its effects on the states is discussed to assist making investment decisions. Optimal control techniques are used to design the controls. The results show that it is possible to formulate an optimal control to achieve the desired target. Numerical results, based on actual parameters, are presented to illustrate the long-term trends of the states. The methodology discussed in this paper will be helpful to decision makers in making optimal decisions. The contribution of this research work is the introduction of a systems and controls methodology to develop optimal policies for the design of sustainable systems.     

Time-dependent fuzzy random location-scheduling programming for hazardous materials transportation

The tremendous use of hazardous materials has promoted the economic development, which also brings about a growing risk causing a widespread concern. In this work, we consider a location-scheduling problem on hazardous materials transportation under the assumption that transportation risks are time-dependent fuzzy random variables. First, we formulate a scheduling optimization model and design a fuzzy random simulation based genetic algorithm to optimize the departure time and dwell times for each depot–customer pair. Then we establish an expected value model and design a modified particle swarm optimization algorithm to minimize the en route risks and site risks. Finally, numerical examples are given to illustrate the effectiveness of the proposed models and algorithms.     

Multi-agent simulation of individual mobility behavior in carpooling

Carpooling is an emerging alternative transportation mode that is eco-friendly and sustainable as it enables commuters to save time, travel resource, reduce emission and traffic congestion. The procedure of carpooling consists of a number of steps namely; (i) create a motive to carpool, (ii) communicate this motive with other agents, (iii) negotiate a plan with the interested agents, (iv) execute the agreed plans, and (v) provide a feedback to all concerned agents. In this paper, we present a conceptual design of an agent-based model (ABM) for the carpooling a that serves as a proof of concept. Our model for the carpooling application is a computational model that is used for simulating the interactions of autonomous agents and to analyze the effects of change in factors related to the infrastructure, behavior and cost. In our carpooling application, we use agent profiles and social networks to initiate our agent communication model and then employ a route matching algorithm, and a utility function to trigger the negotiation process between agents. We developed a prototype of our agent-based carpooling application based on the work presented in this paper and carried out a validation study of our results with real data collected in Flanders, Belgium.     

Transit network design with allocation of green vehicles: A genetic algorithm approach

The use of fossil fuels in transportation generates harmful emissions that accounts for nearly half of the total pollutants in urban areas. Dealing with this issue, local authorities are dedicating specific efforts to seize the opportunity offered by new fuels and technological innovations in achieving a cleaner urban mobility. In fact, authorities are improving environmental performances of their public transport fleet by procuring cleaner vehicles, usually called low and zero emission vehicles (LEV and ZEV, respectively). Nevertheless there seems to be a lack of methodologies for supporting stakeholders in decisions related to the introduction of green vehicles, whose allocation should be performed since the network design process in order to optimize their available green capacity.In this paper, the problem of clean vehicle allocation in an existing public fleet is faced by introducing a method for solving the transit network design problem in a multimodal, demand elastic urban context dealing with the impacts deriving from transportation emissions.The solving procedure consists of a set of heuristics which includes a routine for route generation and a genetic algorithm for finding a sub-optimal set of routes with the associated frequencies.     

Designing a route planner to facilitate and promote cycling in Metro Vancouver,Canada

With increasing fuel costs, greater awareness of greenhouse gas emissions and increasing obesity levels, cycling is promoted as a health promoting and sustainable transport mode. We developed a cycling route planner (http://cyclevancouver.ubc.ca) for Metro Vancouver, British Columbia, Canada, to facilitate cycling amongst the general public and to facilitate new route location by transportation planners. The geographical information system-based planner incorporates variables that influence choices to travel by bicycle (e.g., distance, elevation gain, safety, route features, air pollution and links to transit) in selecting the preferred routing. Using a familiar and user-friendly Google Maps interface, the planner allows individuals to seek optimized cycling routes throughout the region based on their own preferences. In addition to the incorporation of multiple user preferences in route selection, the planner is unique amongst cycling route planners in its use of topology to minimize data storage redundancy, its reliance on node/vertex index tables to increase efficiency of the route selection process, and the use of web services and asynchronous technologies for quick data delivery. Use of this tool can help promote bicycle travel as a form of active transportation and help lower greenhouse gas carbon dioxide (CO₂) and air pollutant emissions by reducing car trips.     

An integrated assessment of factors affecting modal choice: towards a better understanding of the causal effects of built environment

This paper discusses the methodological challenges in understanding causal relationships between urban form and travel behavior and uses a holistic quasi-experimental approach to investigate the separable marginal influence of each of several urban form factors on mode choice as well as the complex relationships between those factors and a wide range of personal traits. Data analysis and models are used to reveal the effect of such interactions on mode choice for both work and non-work trips in Rome, Italy. It is found that population density does not have a significant marginal positive effect on sustainable mode choice for work trips. Conversely, this factor decreases sustainable mode choice for non-work trips. Small scale street design quality alone increases sustainable mode choice for non-work trips. This is while presence of street network integration alone increases automobile use for all trip purposes. The results point to the importance of incorporating all the urban form factors of diversity, design and street network integration if the goal is to increase the use of more sustainable modes of transportation for both work and non-work trips, but also show that attitudes and preferences can modify the response to urban design factors. The findings suggest that thoughtful policies triggering certain attitudes (cost sensitivity, sensitivity to peer pressure regarding the value attributed to sustainable transportation, and transit preference) can be adopted to significantly increase sustainable mode choice even in the neighborhoods with specific physical restrictions.     

A GIS‐based method to identify cost‐effective routes for rural deviated fixed route transit

Deviated fixed route transit (DFRT) service connecting rural and urban areas is a growing transportation mode in the USA. Little research has been done to develop frameworks for route design. A methodology to explore the most cost‐effective DFRT route is presented in this paper. The inputs include potential DFRT demand distribution and a road network. A heuristic is used to build possible routes by starting at urban cores and extending in all network directions in certain length increments. All the DFRT routes falling in the length range desired by the users are selected. The cost effectiveness of those routes, defined by operating cost per passenger trip, is compared. The most cost‐effective route is selected and presented in a GIS map. A case study illustrates the methodology in several Tennessee metropolitan regions. The most cost‐effective route length is case specific; some routes (e.g. those out of our Nashville case) are most cost effective when short, while others (e.g. those out of Memphis) are most cost effective when long. Government agencies could use the method to identify routes with the lowest operating cost per passenger given a route length or an operating cost budget. Copyright © 2016 John Wiley & Sons, Ltd.     

A mixed logit model for predicting exit choice during building evacuations

Knowledge on human behaviour in emergency is crucial to increase the safety of buildings and transportation systems. Decision making during evacuations implies different choices, of which one of the most important concerns is the escape route. The choice of a route may involve local decisions on alternative exits from an enclosed environment. This study investigates the effect of environmental (presence of smoke, emergency lighting and distance of exit) and social factors (interaction with evacuees close to the exits and with those near the decision-maker) on local exit choice. This goal is pursued using an online stated preference survey carried out making use of non-immersive virtual reality. A sample of 1503 participants is obtained and a mixed logit model is calibrated using these data. The model shows that the presence of smoke, emergency lighting, distance of exit, number of evacuees near the exits and the decision-maker and flow of evacuees through the exits significantly affect local exit choice. Moreover, the model indicates that decision making is affected by a high degree of behavioural uncertainty. Our findings support the improvement of evacuation models and the accuracy of their results, which can assist in designing and managing building and transportation systems. The main aim of this study is to enrich the understanding of how local exit choices are made and how behavioural uncertainty affects these choices.     

Urban transportation in Chinese cities: An efficiency assessment

We use 2008 data for 34 Chinese cities to compare urban transportation systems. The results show stronger eastern and central cities focusing more on high capacity and less on sustainable modes of transportation, while western cities do the opposite. Chinese cities with more sustainable transportation are also more likely to have lower gross domestic product per capita, be smaller, are less urbanized and have higher bus usage. This model needs to change to align with China’s new policy priorities.     

Assessment of carbon emission costs for air cargo transportation

This study presents a set of models that calculate carbon emissions in individual phases of flight during air cargo transportation, investigates resultant carbon footprints by aircraft type and flight route, and estimates increases in transportation costs for airlines due to carbon taxes imposed by the EU ETS. The estimated results provide useful references for airlines in aircraft assignment on different routes and in aircraft selection for new purchases. Validation of the model is conducted by simulating the potential impact of the implementation of the EU ETS on costs of air cargo transportation for six routes and six types of aircraft. Results show that the impact may be subject to various factors including unit carbon emissions per aircraft, aviation emission allowances per airline, and carbon trading prices; and that increases in costs of air cargo transportation range from 0% to 5.27% per aircraft per route. Therefore, the implementation of the EU ETS may encourage airlines to cut down their operating costs by reducing their carbon emissions, thereby ameliorating greenhouse gas pollution caused by air cargo transportation.     

公路绿化与环保的研究分析

为推动公路建设水平,确保公路正常运营和沿线生态环境可持续发展,文章总结了公路绿化的特点和功能,从安全性、经济性、生物多样性、景观性等方面分析了公路绿化设计的原则,并探讨了公路中央分隔带、路基边坡、互通立交、服务区的绿化设计内容,从公路环保的重要性,认知公路环保的内容、功能及意义,并多方角度的加以分析和采取措施,达到预期效果,把建设和环境紧密协调统一。并对公路环保的设计理念、评价指标、评价方法及施工阶段的环保措施进行了论述。     

宽容性理念在路侧设计的具体体现

在交通问题中,路侧安全问题尤为突出。文章将宽容性设计理念引入路侧设计中,分析目前我国路侧设施存在的问题,汲取国外宽容性设计研究成果,提出适合我国的路侧设施的人性化合理设置方法,为今后的路侧设计提供参考。     

Adaptive traffic signal control with equilibrium constraints under stochastic demand

This study develops a methodology to model transportation network design with signal settings in the presence of demand uncertainty. It is assumed that the total travel demand consists of commuters and infrequent travellers. The commuter travel demand is deterministic, whereas the demand of infrequent travellers is stochastic. Variations in demand contribute to travel time uncertainty and affect commuters’ route choice behaviour. In this paper, we first introduce an equilibrium flow model that takes account of uncertain demand. A two-stage stochastic program is then proposed to formulate the network signal design under demand uncertainty. The optimal control policy derived under the two-stage stochastic program is able to (1) optimize the steady-state network performance in the long run, and (2) respond to short-term demand variations. In the first stage, a base signal control plan with a buffer against variability is introduced to control the equilibrium flow pattern and the resulting steady-state performance. In the second stage, after realizations of the random demand, recourse decisions of adaptive signal settings are determined to address the occasional demand overflows, so as to avoid transient congestion. The overall objective is to minimize the expected total travel time. To solve the two-stage stochastic program, a concept of service reliability associated with the control buffer is introduced. A reliability-based gradient projection algorithm is then developed. Numerical examples are performed to illustrate the properties of the proposed control method as well as its capability of optimizing steady-state performance while adaptively responding to changing traffic flows. Comparison results show that the proposed method exhibits advantages over the traditional mean-value approach in improving network expected total travel times.     

广西路网工程路线设计方法

文章结合广西路网工程建设背景、路网工程建设程序、路线设计步骤,介绍了以公路运行安全、新征用土地数量、工程造价、地形地物、方便施工等为原则控制路线的设计方法,同时针对当前路网工程路线设计中存在的主要问题,提出了相关的处理措施。