A closer look at urban development under the emergence of autonomous vehicles: Traffic,land use and air quality impacts

Autonomous vehicles (AVs) hold great promise for increasing the capacity of existing roadways and intersections, providing more mobility to a wider range of people, and are likely to reduce vehicle crashes. However, AVs are also likely to increase travel demand which could diminish the potential for AVs to reduce congestion and cause emissions of greenhouse gases (GHG) and other air pollutants to increase. Therefore, understanding how AVs will affect travel demand is critical to understanding their potential benefits and impacts. We evaluate how adoption of AVs affects travel demand, congestion and vehicle emissions over several decades using an integrated travel demand, land-use and air quality modeling framework for the Albuquerque, New Mexico metropolitan area. We find that AVs are likely to increase demand and GHG emissions as development patterns shift to the region's periphery and trips become longer. Congestion declines along most roadways as expanded capacity from more efficient AV operation outpaces increasing demand. Most of the population can also expect a reduction in exposure to toxic vehicle emissions. Some locations will experience an increase in air pollution exposure and traffic congestion from changes in land-use and traffic patterns caused by the adoption of AVs.     

Integrated transportation and energy sector CO2 emission control strategies

This paper analyses the mutual benefits of integrating strategies for future energy and transport CO₂ emissions control. The paper illustrates and quantifies the mutual benefits of integrating the transport and the energy sector in the case of Denmark. Today this issue is very relevant in Denmark due to the high share of fluctuating renewable energy produced in the country. In the future, such issue will apply to other countries who plan to use a high share of renewable energy. In short, the energy sector can help the transport sector to replace oil by renewable energy and combined heat and power production (CHP), while the transport sector can assist the energy system in integrating a higher degree of intermittent energy and CHP. Two scenarios for partial conversion of the transport fleet have been considered. One is battery cars combined with hydrogen fuel cell cars, while the other is the use of biofuel (ethanol) and synthetic fuel (methanol) for internal combustion cars. An increase in the fraction of electricity delivered by fluctuating sources like wind power will lead to excess electricity production and the two aforementioned scenarios have a substantial effect on the decrease of the excess production.     

Telecommuting and other trips: an English case study

This paper investigates the importance of non-work travel to the growing population of telecommuters and the implications of this for sustainable travel patterns. Previous research has identified a link between increased online access to work and reduced proximity between residential and workplace locations. These studies raise concerns that as more people split their work activities between home and external workplace, whilst living in more dispersed locations, more unsustainable transport impacts will be generated, including higher vehicle mileage, car dependency, and less physical activity. This paper counters that the implications of telecommuting and other flexible working practices for sustainable travel behaviours may be more dependent upon the number and type of non-work journeys and the accessibility of amenities for these purposes rather than on the distance to the workplace for less frequent commuting journeys. Using the National Travel Survey for England, the travel behaviours of those who identify themselves not as home workers but as working from home at least once a week are compared to other working adults by measuring and modelling the number and purpose of trips within a week's travel diary, independent of distance or mode. Telecommuters record fewer commute trips, more trips for other purposes, and the marginal utility of additional non-work trips to telecommuters is greater than for many other socio-economic characteristics. Thus, addressing the accessibility of non-work destinations proactively through local planning has the potential to optimise the sustainability benefits of telecommuting.     

Modelling and evaluation of road pricing in Paris

This article describes the impacts of road pricing in Ile-de-France, a region that includes Paris. The morning peak is studied using METROPOLIS: a dynamic network simulator that treats endogenously travellers' mode, departure time and route-choice decisions. Time-independent tolls on selected links, time-varying cordon tolls, and a network-wide toll proportional to travel time are considered. Welfare gains from the link and cordon tolls are relatively small. The comprehensive travel-time-based toll yields much higher benefits. In all cases, benefits to users amount to a large fraction of toll revenues and exceed the monetised value of reductions in noise, accidents and vehicle emissions.     

TRIBUTE: Trip-based urban transportation emissions model for municipalities

This research aims at developing modeling and scenario-comparison tools to explore the impacts of various transportation and land use planning policies on changing travel behavior and eventually greenhouse gas (GHG) emissions. A Trip-Based Urban Transportation Emissions (TRIBUTE) model is developed. Data required for TRIBUTE comes from household travel surveys and emissions inventories, which is a major advantage in cases where a detailed transportation network model is unavailable. TRIBUTE is composed of two main parts: a mode choice model and an emissions forecasting model. The mode choice model is responsible for estimating modal shares of alternative modes of travel in response to changes in personal, modal, and land use attributes. The emissions forecasting model translates the modal shares into vehicle kilometers traveled, and subsequently GHG emissions. TRIBUTE is a macroscopic model intended to assist municipalities evaluate alternative transportation and land use policy scenarios and eventually select the one(s) that help them meet their future GHG emission targets. This paper reports on the conceptual framework of the developed model and presents a case study.     

Analysis of active school transportation in hilly urban environments: A case study of Dresden

This paper analyses the way students travel to school and examines the influence of environmental conditions on travel patterns. More specifically, it studies how topographic changes affect the likelihood of choosing cycling as a transport mode. We use mode choice data on students' home-to-school commuting trips from a previous study by Müller et al. (2008). The results show that models perform better when they account for the topographic conditions of the urban environment. We included this information in the model by introducing the “energy exerted” variable, which significantly improves the model and the results. The implications of this study are manifold; it guides the consolidation or expansion of school-based transportation network planning in Germany and prompts further analysis of active transportation systems, such as bike, pedelec and e-bike sharing systems. Overall, transportation policy should seek to foster active transportation, as it provides the greatest benefits for society and has a direct impact on people's well-being, while notably reducing the negative environmental and socioeconomic impacts of motorized transport.     

Greening transportation fleets: Insights from a two-stage game theoretic model

The greening of organizational transportation fleets, especially trucks and automobiles, has gained increasing attention by companies in a variety of industrial sectors. The reasons for this concern and attention are due to regulatory and competitive pressures, but also increasing costs of fossil-fuels. Surprisingly the amount of research and modeling for fleet management overall has been rather limited, with the focus on managing green vehicle investments virtually non-existent. In this study we develop a two-stage game theoretic model that helps evaluate, from both policy and organizational perspectives, the implications of greening of transportation fleets. Various parameters are evaluated including factors such as innovations in green vehicle technology, levels of service differences, cost of fuel, adjusting tax policy, regulatory compliance requirements, and adaptation costs. This evaluation provides practical insights into actions that could be considered by regulators and organizations to encourage environmental investments.     

How vehicle ownership affect time utilization on study,leisure, social activities,and academic performance of university students? A case study of engineering freshmen in a rural university in Thailand

This study aims to investigate how the ownership of a private vehicle influences time utilization of university students, and whether it impacts their academic performance. This research analyzes travel/activity patterns of 130 engineering freshman students at a rural university in Thailand. An analysis of travel/activity data shows that vehicle ownership seems to play an important role in university student’s time utilization on various activities. It was found that those students who own a vehicle tend to spend less time for academic purposes, and more on leisure and social activities than non-owner students. Nevertheless, a further study using regression analysis on academic performance shows that the ownership of a vehicle does not seem to have a significant impact on the grade point average of students, once the cognitive ability and gender are accounted for. The findings imply that campus policies/measures that restrict the ownership or usage of a private vehicle in rural universities would improve the campus learning environment by influencing university students to put more attention on school-related activities, but such policies do not seem to impact on the academic performance of the college students.     

Key research themes on urban space,scale, and sustainable urban mobility

abstract

Land-use policies are frequently proposed as a means of reducing the negative impacts of transport on the environment, such as emissions of CO₂ and pollutants, and noise nuisance. In this article we discuss whether land-use policies make sense as a strategy for reducing vehicle travel and lessening environmental impacts. We conclude that they do, but that the greatest benefits may come from the enhancement of accessibility. We argue that land-use policies should be evaluated across a much broader range of benefits than is generally done at present.     

Time-use data, analysis and modeling: toward the next generation of transportation planning methodologies

This paper argues that transportation planning methodologies must be built on the central thesis of the activity-based approach to travel demand modeling, namely, that travel is a derived demand that reflects people's desire and need to participate in activities. The paper discusses why this foundation for transportation planning methodologies is necessary to address contemporary planning and policy analysis issues. The paper also argues that the introduction of time-use data, analysis and modeling is a key element in the development of the next generation of transportation planning methodologies. Following a brief review of time-use studies, the paper discusses a number of planning and policy analysis areas in which time-use data will be of particular value, including the evaluation of induced or suppressed travel demand. The concepts advanced in the paper are illustrated with two brief numerical examples. These examples show how model systems based on time-use data can be used to (i) estimate the number of induced trips that would result from a reduction in commute travel time, and (ii) evaluate the impacts of alternative transportation improvement projects.     

Fuel consumption for various driving styles in conventional and hybrid electric vehicles: Integrating driving cycle predictions with fuel consumption optimization*

Improving fuel economy and lowering emissions are key societal goals. Standard driving cycles, pre-designed by the US Environmental Protection Agency (EPA), have long been used to estimate vehicle fuel economy in laboratory-controlled conditions. They have also been used to test and tune different energy management strategies for hybrid electric vehicles (HEVs). This paper aims to estimate fuel consumption for a conventional vehicle and a HEV using personalized driving cycles extracted from real-world data to study the effects of different driving styles and vehicle types on fuel consumption when compared to the estimates based on standard driving cycles. To do this, we extracted driving cycles for conventional vehicles and HEVs from a large-scale U.S. survey that contains real-world GPS-based driving records. Next, the driving cycles were assigned to one of three categories: volatile, normal, or calm. Then, the driving cycles were used along with a driver-vehicle simulation that captures driver decisions (vehicle speed during a trip), powertrain, and vehicle dynamics to estimate fuel consumption for conventional vehicles and HEVs with power-split powertrain. To further optimize fuel consumption for HEVs, the Equivalent Consumption Minimization Strategy (ECMS) is applied. The results show that depending on the driving style and the driving scenario, conventional vehicle fuel consumption can vary widely compared with standard EPA driving cycles. Specifically, conventional vehicle fuel consumption was 13% lower in calm urban driving, but almost 34% higher for volatile highway driving compared with standard EPA driving cycles. Interestingly, when a driving cycle is predicted based on the application of case-based reasoning and used to tune the power distribution in a hybrid electric vehicle, its fuel consumption can be reduced by up to 12% in urban driving. Implications and limitations of the findings are discussed.     

New method to estimate local and system-wide effects of level rail crossings on network traffic flow

This paper makes local and aggregate estimates of the effects of 152 level crossings in the Melbourne metropolitan area, Australia on traffic congestion in the morning peak period (7 am–9 am). A new method, including micro-simulation of a range of rail crossing configurations, is used to inform a network model which makes aggregate estimates of impacts on all traffic.Relationships between train frequency and percentage change in vehicle travel time and volume were identified. These equations can predict change in travel time/traffic flow caused by rail level crossings based on rail crossing closures and train frequency.Overall, Melbourne's level crossings result in an average increase in travel time of 16.1% for vehicle traffic on links with a level crossing. However on average a level crossing reduces the volume of vehicles on these links by 5.9% as a result of traffic diversion. These values are higher in middle suburbs where train arrivals and crossing closure times at level crossings are more frequent.The aggregate effect of all 152 level rail crossings on all traffic in Melbourne is a travel time change from 1.81 to 1.82 min/km (an increase of around 0.3%). The number of congested links in Melbourne increases by 0.9% while the total delay increases by 0.7%. These network wide effects are not large compared to localised effects because road links affected directly by crossings represent a very small part of the overall network. Additionally, network effects also include traffic diversion impacts which will counteract some of the immediate impacts on a localised scale. However, it is significant that the very small element of the system can have even a measurable effect on aggregate traffic congestion.     

Benefits of in-vehicle consolidation in less than truckload freight transportation operations

Researchers and public agencies have proposed consolidation policies as an alternative to increase truck payload utilization and mitigate externalities produced by freight transportation. Understanding and enhancing the economic mechanisms that lead to freight consolidation can ease the implementation of these strategies, increase profits for shippers and carriers, and reduce freight-related negative externalities. An important mechanism that has recently been studied for cost reduction in the freight industry is combinatorial auctions. In these auctions, a shipper invites a set of carriers to submit bids for freight lane contracts. Carriers can bid for individual lanes or bundles of them according to their operational characteristics. These bids are constructed considering direct shipments (Truckload operations) and several biding advisory models have been proposed for this purpose. However, there are economies of scale that can be achieved if shipments are consolidated inside vehicles, which have not been explored in the construction of competitive bids. This paper investigates such benefits and provides insights on the competitiveness and challenges associated to the development of consolidated bids (suitable for Less-Than-Truckload operations). Consolidated bids are constructed using a multi-commodity one-to-one pickup-and-delivery vehicle routing problem that is solved using a branch-and-price algorithm. The numerical experiment shows that non-consolidated bids are dominated by consolidated bids, which implies that this type of operation can increase the likelihood of a carrier to win auctioned lanes, while increasing its profits margins over truckload companies (non-consolidated bids), and keeping the reported benefits that combinatorial auctions represent for shippers.     

A comprehensive relationship marketing model between airlines and travel agencies: The case of Taiwan

This study aims to examine how airlines' relationship selling, relational benefits, and relationship quality affect voluntary performance of travel agencies. Hypotheses on the relationship among these constructs were created based on relevant literature and validation using structural equation modeling was carried out. A questionnaire survey was conducted using stratified sampling on comprehensive travel agencies and Class A travel agencies in Taiwan. Among the 1000 copies of the questionnaire, 169 valid copies were collected and used to perform data analysis. Empirical results show that relational benefits and relationship selling can influence voluntary performance of travel agencies through the mediation of relationship quality, although neither has a direct effect on the latter, whereas, relationship quality has a significant and positive impact on voluntary performance of travel agencies towards airlines. It is evident that relationship quality plays an indispensable role in the connection between relationship marketing constructs (relationship selling and relational benefits) and voluntary performance. Results of this study may provide some insights for airlines in developing relationship management strategies towards travel agencies.     

A large neighborhood search heuristic to establish an optimal ad-hoc hubbing strategy in the wake of a large-scale airport outage

Abrupt airport outages can cause diversions and fuel-critical situations for flights, leading to costly passenger misconnections. We develop a large neighborhood search heuristic to optimize the rerouting of flights bound for a disrupted airport to a hub airport that is not disrupted, with the goal of accommodating passengers on existing flights departing the non-disrupted hub. The objective of the heuristic is to identify and reroute flights to the ad-hoc hub(s) – non-disrupted hub airport(s) – that minimize the sum of passenger travel time and wait time. We minimize the passenger cost as the sum of passenger travel time to the diversion airport and wait time for a connecting flight at the ad-hoc hub airport, subject to on-board fuel and diversion airport capacity constraints. We use the heuristic to determine how a coordinated traffic management strategy could have diverted flights immediately following a real-world airport outage.     

Shaping carpool policies under rapid motorization: the case of Chinese cities

Rapid motorization and fuel cost hike over the past few years have made carpool a new mode of travel in Chinese cities. But transportation policy makers have been rather ambivalent, if not indifferent, about carpool. Unlike cities in highly motorized societies, little is known about carpooling behavior in emerging economies such as China. This paper provides an initial discussion of carpooling in China by exploring a series of questions. What are the current practice and issues of carpool in Chinese cities? How do carpools in China compare with those in the motorized Western cities? Can carpools help Chinese cities mitigate the negative impacts of rapid motorization? Are foreign policies such as High-Occupancy-Vehicle (HOV) lanes transferable to China? Acknowledging the social benefits of voluntary carpooling, this paper argues: (1) bus lanes may be a better choice than HOV lanes when converting general motor vehicle lanes; (2) policies subsidizing carpoolers cannot be justified on either efficiency or equity grounds because a marginal carpooler is more likely transitioning from a transit user or non-motorized traveler than from a driver. Policy suggestions are proposed to Chinese decision makers.     

Bi-level optimization approach for configuring population and employment distributions with minimized vehicle travel demand

Compact development aims to lead to dense and mixed distributions of population and employment in land use planning which may result in reduced vehicle miles traveled (VMT). However, determining an optimum or desirable configuration of population and employment distribution to achieve the compact development goal remains challenging due to numerous competitive development alternatives or possible exacerbated traffic congestion as a result of over-intensification of urban land use. To address this challenge, a systematic approach is proposed with a bi-level optimization model aiming to find out an efficient population and employment map for vehicle travel reduction. The upper level of the model is formulated to minimize VMT and vehicle hours traveled (VHT) varying with possible changes in population and employment densities. The lower level is based on a tour-based travel demand model to mechanistically represent the response of travel choices to those changes. The programming is solved by a Genetic Algorithm. The proposed method is demonstrated through a case study of Hamilton County, Ohio, U.S. The results indicate that a more compact urban form reduces VMT; however, it may cause longer VHT depending upon the density. To avoid urban overconcentration and reduce both VMT and VHT simultaneously, a compact urban development configuration with a population density < 5289 persons/mi² and the employment density < 3282 jobs/mi² is recommended for the area. As a negative relationship demonstrated between transit headway reduction and vehicle travel demand, strategies for improving transit provision are helpful to reducing vehicle travels in compact development scenarios.     

Employment centers and travel behavior: exploring the work commute of Mumbai’s rapidly motorizing middle class

In the Greater Mumbai Region (GMR), jobs and housing are agglomerating in nodes in the periphery of Mumbai City. However, current transportation investments focus on strengthening connections within Mumbai City, while these outlying nodes have received less attention. As housing and jobs move out, given limited travel choices, the need for mobility nudges many middle class Indian households into owning private vehicles. Using household travel survey data from the GMR, this paper develops an understanding of how worker’s trips are different for those who commute to the city versus the exurbs. Socio-economic and transportation indicators for middle class workers going to the city versus the exurbs show that these populations are quite similar demographically. However, those traveling to the exurbs, on average, tend to be at a socio-economic disadvantage with respect to income, education and out-of-pocket travel burdens. Those traveling to exurban work locations have shorter travel times and trip distances, and make much higher use of walking, biking, rickshaws, and motorized two-wheelers compared to commuters to Mumbai City. Across the GMR, car users travel longer and farther compared to motorized two-wheeler users. On average, traveling by a private vehicle is faster than bus or rickshaw travel revealing advantages of private vehicle use. These mode choices in the middle class have resulted in rapid motorization and negative externalities such as traffic congestion and emissions. Evidence of large increases in motorized two-wheelers and cars in India suggests that these modes will likely keep growing, unless competing efficient travel options are supplied.     

Potential cost savings of frequent flyer miles for business travel

The mileage redemption strategy is a procedure used by many business firms to reduce air travel costs, in which the frequent flyer miles of traveling employees accumulated during business trips are applied to their future business trips to obtain “free” air tickets. This paper presents a framework that investigates how the frequent flyer miles can be used in the most effective way to reduce air travel costs by those firms that are either using the mileage redemption strategy or considering the use of the strategy. The framework can be implemented quite easily by a spreadsheet software such as Microsoft Excel.