•Examine emergency vehicles (EV) priority on highway segments with explicit solutions.•A computational efficient two stage optimization model.•Guarantee the desired speed of emergency vehicles in ...feasible traffic conditions, while minimizing its impact on surrounding traffic.•Applications to EV routing problems.
Emergency vehicles (EVs) play a crucial role in providing timely help for the general public in saving lives and avoiding property loss. However, very few efforts have been made for EV prioritization on normal road segments, such as the road section between intersections or highways between ramps. In this paper, we propose an EV lane pre-clearing strategy to prioritize EVs on such roads through cooperative driving with surrounding connected vehicles (CVs). The cooperative driving problem is formulated as a mixed-integer nonlinear programming (MINP) problem aiming at (i) guaranteeing the desired speed of EVs, and (ii) minimizing the disturbances on CVs. To tackle this NP-hard MINP problem, we formulate the model in a bi-level optimization manner to address these two objectives, respectively. In the lower-level problem, CVs in front of the emergency vehicle will be divided into several blocks. For each block, we developed an EV sorting algorithm to design optimal merging trajectories for CVs. With resultant sorting trajectories, a constrained optimization problem is solved in the upper-level to determine the initiation time/distance to conduct the sorting trajectories. Case studies show that with the proposed algorithm, emergency vehicles are able to drive at a desired speed while minimizing disturbances on normal traffic flows. We further reveal a linear relationship between the optimal solution and road density, which could help to improve EV routing decision makings when high-resolution data is not available.
In this paper, a novel robust torque control strategy for permanent magnet assisted synchronous reluctance machine drives applied to electric vehicles and hybrid electric vehicles is presented. ...Conventional control techniques can highly depend on machine electrical parameters, leading to poor regulation under electrical parameters deviations or, in more serious cases, instabilities. Additionally, machine control can be lost if field weakening is not properly controlled and, as a consequence, uncontrolled regeneration is produced. Thus, advanced control techniques are desirable to guarantee electric vehicle drive controllability in the whole speed/torque operation range and during the whole propulsion system lifetime. In order to achieve these goals, a combination of a robust second-order current-based sliding mode control and a look-up table/voltage constraint tracking based hybrid field weakening control is proposed, improving the overall control algorithm robustness under parameter deviations. The proposed strategy has been validated experimentally in a full-scale automotive test bench (51-kW prototype) for being further implemented in real hybrid and electric vehicles.
•Shared autonomous vehicle (SAV) fleet size is the most important factor in pickup response time.•Increasing electric SAV (SAEV) range above 110 mi does not improve response times in this ...region.•Reducing charge times improves response times, but only when charge times exceed 90 min.•Each SAEV can service about 27 trips per day with 489 miles of daily average travel.•Average response times in this region were as low as 5 min, with 1 SAEV for every 5 travelers.
Shared autonomous vehicles, or SAVs, have attracted significant public and private interest because of their opportunity to simplify vehicle access, avoid parking costs, reduce fleet size, and, ultimately, save many travelers time and money. One way to extend these benefits is through an electric vehicle (EV) fleet. EVs are especially suited for this heavy usage due to their lower energy costs and reduced maintenance needs. As the price of EV batteries continues to fall, charging facilities become more convenient, and renewable energy sources grow in market share, EVs will become more economically and environmentally competitive with conventionally fueled vehicles. EVs are limited by their distance range and charge times, so these are important factors when considering operations of a large, electric SAV (SAEV) fleet.
This study simulated performance characteristics of SAEV fleets serving travelers across the Austin, Texas 6-county region. The simulation works in sync with the agent-based simulator MATSim, with SAEV modeling as a new mode. Charging stations are placed, as needed, to serve all trips requested (under 75 km or 47 miles in length) over 30 days of initial model runs. Simulation of distinctive fleet sizes requiring different charge times and exhibiting different ranges, suggests that the number of station locations depends almost wholly on vehicle range. Reducing charge times does lower fleet response times (to trip requests), but increasing fleet size improves response times the most. Increasing range above 175 km (109 miles) does not appear to improve response times for this region and trips originating in the urban core are served the quickest. Unoccupied travel accounted for 19.6% of SAEV mileage on average, with driving to charging stations accounting for 31.5% of this empty-vehicle mileage. This study found that there appears to be a limit on how much response time can be improved through decreasing charge times or increasing vehicle range.
The predominant strategy to reduce CO2 emissions in the transport sector is its renewable based electrification. It implies mobile storages that could – during long phases of immobility – provide ...services for the electricity sector. However, this technical option – called vehicle-to-grid (V2G) – requires the vehicle users to temporarily abstain from the usage of their batteries for V2G. A reasonable estimate of the potential of V2G thus considers which individual, technical and economic parameters are decisive for the willingness of vehicle users to participate. To answer these questions a representative sample of vehicle users in Germany has been surveyed – including a discrete choice experiment.
'Range anxiety' and the 'minimum range' proved most important determinants of the willingness of vehicle users to participate in V2G. If these concerns are smoothed out, even without remuneration, high participation rates might be achieved. To increase the participation in the V2G technology, the transition from ‘tank control’ to ‘mobility demand articulation’ should be facilitated for vehicle users. Therefore, companies could tailor the V2G design to customers’ needs and policy could improve information about V2G. Remuneration, however, cannot be expected to be very supportive.
•A reasonable estimate of the V2G potential includes the willingness of vehicle users.•‘Range anxiety’ and guaranteed ‘minimum range’ dominated this willingness.•High V2G participation is possible even without remuneration.•Transition from battery to mobility control should be facilitated by third parties.
•911 Surveys r.e. plug-in hybrid electric vehicles (PHEVs) extensively analyzed.•Collected on Amazon Mechanical Turk crowd-sourcing platform and posted online.•Strongest climate or energy concerns ...raise odds of PHEV acceptance by 44 or 71.•Those most open to PHEVs will only pay average of $1858 to save $500/yr in gas.•Up-front incentives and ads targeting environmentalists may be most effective.
Plug-in Hybrid Electric Vehicles (PHEVs) show potential to reduce greenhouse gas (GHG) emissions, increase fuel efficiency, and offer driving ranges that are not limited by battery capacity. However, these benefits will not be realized if consumers do not adopt this new technology. Several agent-based models have been developed to model potential market penetration of PHEVs, but gaps in the available data limit the usefulness of these models. To address this, we administered a survey to 1000 stated US residents, using Amazon Mechanical Turk, to better understand factors influencing the potential for PHEV market penetration. Our analysis of the survey results reveals quantitative patterns and correlations that extend the existing literature. For example, respondents who felt most strongly about reducing US transportation energy consumption and cutting greenhouse gas emissions had, respectively, 71 and 44 times greater odds of saying they would consider purchasing a compact PHEV than those who felt least strongly about these issues. However, even the most inclined to consider a compact PHEV were not generally willing to pay more than a few thousand US dollars extra for the sticker price. Consistent with prior research, we found that financial and battery-related concerns remain major obstacles to widespread PHEV market penetration. We discuss how our results help to inform agent-based models of PHEV market penetration, governmental policies, and manufacturer pricing and marketing strategies to promote consumer adoption of PHEVs.
China is a major energy-consuming country and is under great pressure to improve its energy efficiency as well as reduce its carbon emissions. Hybrid electric vehicles (HEVs), as an energy-efficient ...transport innovation, have the potential to reduce gasoline consumption, carbon emissions and alleviate environmental problems. Diffusion of HEVs’ adoption is a significant initiative. A sample of 433 respondents has been collected in China to predict the customers’ intention to adopt HEVs, using an extended model of the theory of planned behavior (TPB). The empirical results show that the attitude toward HEVs, subjective norm, perceived behavioral control (the three primary elements of the TPB model) and personal moral norm partially mediate the effect of consumers’ environmental concern on their intention to adopt HEVs. Consumers’ environmental concern affects the adoption intention indirectly and is significantly positively related to the attitude toward HEVs, subjective norm, perceived behavioral control and personal moral norm, which in turn influence the adoption intention positively. The results confirm the appropriateness of the TPB model and verify that the extended TPB model has good explanatory power in predicting consumers’ intention to adopt HEVs. Based on the empirical results, we discuss the implications for promoting the adoption of HEVs and provide suggestions for future study.
While connected, highly automated, and autonomous vehicles (CAVs) will eventually hit the roads, their success and market penetration rates depend largely on public opinions regarding benefits, ...concerns, and adoption of these technologies. Additionally, the introduction of these technologies is accompanied by uncertainties in their effects on the carsharing market and land use patterns, and raises the need for tolling policies to appease the travel demand induced due to the increased convenience. To these ends, this study surveyed 1088 respondents across Texas to understand their opinions about smart vehicle technologies and related decisions. The key summary statistics indicate that Texans are willing to pay (WTP) $2910, $4607, $7589, and $127 for Level 2, Level 3, and Level 4 automation and connectivity, respectively, on average. Moreover, affordability and equipment failure are Texans’ top two concerns regarding AVs. This study also estimates interval regression and ordered probit models to understand the multivariate correlation between explanatory variables, such as demographics, built-environment attributes, travel patterns, and crash histories, and response variables, including willingness to pay for CAV technologies, adoption rates of shared AVs at different pricing points, home location shift decisions, adoption timing of automation technologies, and opinions about various tolling policies. The practically significant relationships indicate that more experienced licensed drivers and older people associate lower WTP values with all new vehicle technologies. Such parameter estimates help not only in forecasting long-term adoption of CAV technologies, but also help transportation planners in understanding the characteristics of regions with high or low future-year CAV adoption levels, and subsequently, develop smart strategies in respective regions.
Vehicle taxes and purchase subsidies have been used frequently to provide incentives for electric vehicle adoption. To examine the role of the incentives in reducing total ownership costs of battery ...electric vehicles (BEVs), increasing BEV sales, and obtaining environmental benefits from switching to BEVs, we carry out cost–benefit analyses and ordinary least square regressions. We study 10 pairs of BEVs and their internal combustion engine vehicle (ICEV) counterparts across 28 European countries from 2012 to 2014. The results show that, under the incentive schemes, the costs reduced by switching to large BEVs from their ICEV counterparts are larger than the costs reduced by switching to small BEVs from their ICEV counterparts. Owing to the cost-reduction effect, a 10% increase of the total tax incentive leads to an increase in the sales share of BEVs by around 3% on average. Finally, we find that it is still costly to use the tax incentives to reduce CO2 emissions and other environmental externalities through transport electrification, despite recent improvements in greening electricity generation and lowering battery costs.
•The tax incentives for BEVs vary among vehicles, across countries and over years.•The tax incentives are the main reasons for that BEVs are cheaper than ICEVs.•Large BEVs benefit more from the tax incentives than small BEVs do.•The influence of the tax incentives on BEV sales is lower than that for HEVs.•It is costly to reduce externalities through transport electrification.
•Traditional business models based on manufacturers selling trucks to operators will likely all but disappear.•The paper identifies the network operator concept, fulfilling the prediction of the ...networked society in logistics.•Current road transport providers will be squeezed out of the market by the network operator.•Manufacturers will also find their value capture threatened, unless they take on the network operator role themselves.
The full adoption of electric autonomous vehicles (EAVs) will revolutionise the global transport system in general and road freight transport in particular. Traditional business models based on manufacturers selling trucks to operators could conceivably disappear. As with passenger transport, the rapid obsolescence of the technology and the cost will drive a non-ownership model and an evolution from products to services. Therefore it is expected that a new network operator will emerge to run this service, which in the future will likely develop into a fully smart network. As the value of the truck technology is reduced and the software component becomes the core source of value creation, it opens up the possibility of new entrants to the market who do not need to purchase physical assets at all and may instead rent them from a competitive pool of asset providers.
Despite the recent growth in research on Mobility as a Service (MaaS) in passenger transport, these issues have been neglected in freight transport. The goal of this paper is to establish the features of this new smart network and derive a range of potential business models incorporating the changing roles of each actor, which are then evaluated against an analytical framework of business model innovation. The research concludes by proposing an update to the well-known OECD transportation model to include the network operator concept.
Worldwide demand for robotic aircraft such as unmanned aerial vehicles (UAVs) and micro aerial vehicles (MAVs) is surging. Not only military but especially civil applications are being developed at a ...rapid pace. Unmanned vehicles offer major advantages when used for aerial surveillance, reconnaissance, and inspection in complex and inhospitable environments. UAVs are better suited for dirty or dangerous missions than manned aircraft and are more cost-effective. UAVs can operate in contaminated environments, for example, and at altitudes both lower and higher than those typically traversed by manned aircraft. Many technological, economic, and political factors have encouraged the development and operation of UAVs. New sensors, microprocessors, and propulsion systems are smaller, lighter, and more capable, leading to levels of endurance, efficiency, and autonomy that exceed human capacities. Comprising the latest research, this book describes step by step the development of small or miniature unmanned aerial vehicles and discusses in detail the integrated prototypes developed at the robotics laboratory of Chiba University. With demonstration videos, the book will interest not only graduate students, scientists, and engineers but also newcomers to the field.
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