Required navigation performance for connected and autonomous vehicles: where are we now and where are we going?

ABSTRACT

While automotive original equipment manufacturers and IT companies are developing and demonstrating self-driving cars, true autonomy will not be realised in the near future due in part to the technology readiness level of the existing systems as well as issues of ethics, security, governance and standards surrounding the implementation of autonomy for road transport. However, advances in cellular phones and networks, satellite-based positioning and communications, cloud computing, combined with a rise in the volumes of available data, allied with a reduction in their costs, offer the very real possibility of connecting vehicles, one to another and to smart city infrastructure as part of the Internet of Things (IoT). Data from connected vehicles, when combined with other information, may provide valuable intelligence to traffic managers and other stakeholders via cooperative intelligent transport system (C-ITS) platforms. Nevertheless, many issues face the implementation of a truly connected IoT in general and C-ITS in particular.     

Railway station choice modelling: a review of methods and evidence

Since the first railway station choice studies of the 1970s, a substantial body of research on the topic has been completed, primarily in North America, the U.K. and the Netherlands. With many countries seeing sustained growth in rail passenger numbers, which is forecast to continue, station choice models have an important role to play in assessing proposals for new stations or service changes. This paper reviews the modelling approaches adopted, the factors found to influence station choice and the application of models to real-world demand forecasting scenarios. A consensus has formed around using the closed-form multinomial logit and nested logit models, with limited use of more advanced simulation-based models, and the direction effects of a range of factors have been consistently reported. However, there are questions over the validity of applying non-spatial discrete choice models to a context where spatial correlation will be present, in particular with regard to the models’ ability to adequately represent the abstraction behaviours resulting from competition between stations. Furthermore, there has been limited progress towards developing a methodology to integrate a station choice element into the aggregate models typically used to forecast passenger demand for new stations.     

Reducing CO<Subscript>2</Subscript> from cars in the European Union

The European Union (EU) recently adopted CO₂ emissions mandates for new passenger cars, requiring steady reductions to 95 gCO₂/km in 2021. We use a multi-sector computable general equilibrium (CGE) model, which includes a private transportation sector with an empirically-based parameterization of the relationship between income growth and demand for vehicle miles traveled. The model also includes representation of fleet turnover, and opportunities for fuel use and emissions abatement, including representation of electric vehicles. We analyze the impact of the mandates on oil demand, CO₂ emissions, and economic welfare, and compare the results to an emission trading scenario that achieves identical emissions reductions. We find that vehicle emission standards reduce CO₂ emissions from transportation by about 50 MtCO₂ and lower the oil expenditures by about €6 billion, but at a net added cost of €12 billion in 2020. Tightening CO₂ standards further after 2021 would cost the EU economy an additional €24–63 billion in 2025, compared with an emission trading system that achieves the same economy-wide CO₂ reduction. We offer a discussion of the design features for incorporating transport into the emission trading system.     

Bayesian imputation of non‐chosen attribute values in revealed preference surveys

Obtaining attribute values of non‐chosen alternatives in a revealed preference context is challenging because non‐chosen alternative attributes are unobserved by choosers, chooser perceptions of attribute values may not reflect reality, existing methods for imputing these values suffer from shortcomings, and obtaining non‐chosen attribute values is resource intensive. This paper presents a unique Bayesian (multiple) Imputation Multinomial Logit model that imputes unobserved travel times and distances of non‐chosen travel modes based on random draws from the conditional posterior distribution of missing values. The calibrated Bayesian (multiple) Imputation Multinomial Logit model imputes non‐chosen time and distance values that convincingly replicate observed choice behavior. Although network skims were used for calibration, more realistic data such as supplemental geographically referenced surveys or stated preference data may be preferred. The model is ideally suited for imputing variation in intrazonal non‐chosen mode attributes and for assessing the marginal impacts of travel policies, programs, or prices within traffic analysis zones. Copyright © 2012 John Wiley & Sons, Ltd.     

Road user charging design: dealing with multi-objectives and constraints

This paper proposes an innovative approach for designing a road user charging scheme to meet multiple policy objectives. Three practical features are integrated into the design methodology including (i) cordon formation, (ii) a set of design constraints, and (iii) multiple objectives of the scheme. The methods also consider possible responses of road travellers to the charging scheme. Two methods based on genetic algorithms (GA) are developed for optimising a charging cordon scheme with constraints and with multiple objectives. The dynamic self-adaptive penalty GA and Non-dominated Sorting GA II (NSGA-II) are applied to the constrained design and multi-objective design respectively. The objective functions or constraints considered include social welfare improvement, revenue generation, and distributional equity impact. A case study of the City of Edinburgh is presented and common characteristics of charging cordon designs which perform well against the three objectives are discussed.

A novel tracking control approach for unmanned underwater vehicles based on bio-inspired neurodynamics

A novel hybrid control approach is presented for trajectory tracking control of unmanned underwater vehicles in this paper. The kinematic and dynamic controllers are integrated by the proposed control strategy. The paper has two objectives. Firstly, an improved backstep method is proposed to generate the virtual velocity using a bio-inspired neurodynamics model in the kinematic controller. The bio-inspired neurodynamics model is intended to smooth the virtual velocity output to avoid speed jumps of the unmanned underwater vehicle caused by tracking errors and to meet the thruster control constraints. Secondly, a new sliding-mode method is added to the dynamic controller, which is robust against parameter inaccuracy and disturbances. The combined kinematic–dynamic control law is applied to the trajectory tracking problem of two different types of unmanned underwater vehicle. Finally, simulation results illustrate the performance of the proposed controller.     

这盒香烟不太毒

Cigarette公司的拥有者Skip Braver龇牙咧嘴地走上码头。这是一个云开雾散的早晨,那些敞篷快艇正在波浪中把它们的9升排量双发动机全都开到1350马力的极致。"我浑身湿透了。"他苦笑着说。他的船员都是那种如果没有更有趣的事儿可干,就会     

Towards marginal cost pricing: A comparison of alternative pricing systems

European urban areas are marred by the problems of congestion and environmental degradation due to the prevailing levels of car use. Strong arguments have thus been put forward in support of a policy based on marginal cost pricing (European Commission 1996). Such policy measures – which would force private consumers to pay for a public service that was previously provided "for free" – are, however, notoriously unpopular with the general public and hence also with their elected representatives – the politicians. There is thus an obvious tension between economic theory, which suggests that marginal cost pricing is the welfare maximising solution to urban transport problems, and practical experience, which suggests that such pricing measures are unwanted by the affected population and hence hard to implement through democratic processes. The AFFORD Project for the European Commission has aimed to investigate this paradox and its possible solutions, through a combination of economic analysis, predictive modelling, attitudinal surveys, and an assessment of fiscal and financial measures within a number of case study cities in Europe. In this paper the methodology and results obtained for the Edinburgh case study are reported in detail. The study analyses alternative road pricing instruments and compares their performance against the theoretical first best situation. It discusses the effect of coverage, location, charging mechanism and interaction with other instruments. The paper shows that limited coverage in one mode may lead to a deviation from the user pays principle in other modes, that location is as important as charge levels and that assumptions about the use of revenues are critical in determining the effect on equity and acceptability. Finally the results show that a relatively simple smart card system can come close to providing the economic first best solution, but that this result should be viewed in the context of the model assumptions.     

Cordon tolls and competition between cities with symmetric and asymmetric interactions

The aim of this paper is to model the impacts of competition between cities on both the optimal welfare generating tolls and upon longer-term decisions such as business and residential location choices. The research uses a dynamic land use transport interaction model of two neighbouring cities and analyses the impacts by setting up a game between the two cities to maximise the welfare of their own residents. The work builds on our earlier research which studied competition in a small network using a static equilibrium approach for private car traffic without accounting for the land use responses to the change in accessibility. This paper extends the earlier work by setting up a dynamic model which includes active modes of travel and the more usual car and public transport in a realistic twin city setting and assesses the longer term relocation responses. This paper firstly sets out the competition between two hypothetical identical cities i.e. the symmetric case; and then sets out the real world asymmetric case in which the cities are of different size representative of Leeds and Bradford in the UK but equally applicable elsewhere too. We found that the level of interaction between the two cities is a key determinant to the optimal tolls and welfare gains. Our findings show that the competition between cities could lead to a Nash Trap at which both cities are worse off in terms of welfare gains. On the other hand, we found that cities, if regulated, would gain in terms of welfare and yet charge only half the toll compared with tolls under competition. We then show that the effect of competition increases with increased interaction between cities. In terms of residential location, cities with higher charges benefit from an increase in residents, though as with other studies, the relative change in population in response to cordon charging is small. The policy implications are threefold—(i) while there is an incentive to cooperate at local authority level, this is not achieved due to competition; (ii) where cities compete they may fall into a Nash Trap where both cities will be worse off compared to the regulated solution; and (iii) regulation is recommended when there is a strong interaction between the cities but that the benefits of regulation decrease as interaction between cities decreases and the impact of competition is lessened.     

The effect of complex models of externalities on estimated optimal tolls

Transport externalities such as costs of emissions and accidents are increasingly being used within appraisal and optimisation frameworks alongside the more traditional congestion analysis to set optimal transport policies. Models of externalities and costs of externalities may be implemented by a simple constant cost per vehicle-km approach or by more complex flow and speed dependent approaches. This paper investigates the impact of using both simple and more complex models of CO₂ emissions and cost of accidents on the optimal toll for car use and upon resulting welfare levels. The approach adopted is to use a single link model with a technical approach to the representation of the speed-flow relationship as this reflects common modelling practice. It is shown that using a more complex model of CO₂ emitted increases the optimal toll significantly compared to using a fixed cost approach while reducing CO₂ emitted only marginally. A number of accident models are used and the impact on tolls is shown to depend upon the assumptions made. Where speed effects are included in the accident model, accident costs can increase compared to the no toll equilibrium and so tolls should in this case be reduced compared to the congestion optimal toll. Finally it is shown that the effect of adding variable CO₂ emission models along with a fixed cost per vehicle-km for accidents can increase the optimal toll by 44% while increasing the true welfare gained by only 8%. The results clearly demonstrate that model assumptions for externalities can have a significant impact on the resulting policies and in the case of accidents the policies can be reversed.