Miles,speed, and technology: Traffic safety under oligopolistic insurance

We study road safety when insurance companies have market power, and can influence drivers’ behavior via insurance premiums. We obtain first- and second-best premiums for different insurance market structures. The insurance program consists of an insurance premium, and marginal dependencies of that premium on speed and own safety technology choice of drivers. A private monopolist internalizes collision externalities up to the point where compensations to users’ benefit matches the full (intangible) costs; in oligopolistic markets, insurers do not fully internalize collision externalities. Analytical results demonstrate how insurance firms’ incentives to influence traffic safety coincide with or deviate from socially optimal incentives. Our results may be useful for design of pay-as-you-speed and alike insurances as well as policies related to driving safety.     

Vertical separation as means to establish interoperability in road tolling in Europe

As more European roads become tolled by various means, an increasing share of road users become subject to more than one tolling scheme in their regular driving. This can be especially burdensome for long distance hauliers, who may pass several countries and tolled motorway systems during the course of 1 day. For this reason, a range of projects have been initiated attempting to increase the level of interoperability between tolling systems, many of which with only limited success. By analyzing current incentives, costs and benefits for toll operators and road users, we conclude firstly that the current level of interoperability is likely to be lower than socially optimal, and secondly that a direct regulation making the provision of interoperability mandatory is likely to be in excess of what is socially optimal. We argue that vertically separating the monopolistic toll operators could be a cost-efficient way to achieve a socially optimal level of interoperability as a equilibrium market outcome.     

Pruning and ranking the Pareto optimal set,application for the dynamic multi‐objective network design problem

Solving the multi‐objective network design problem (MONDP) resorts to a Pareto optimal set. This set can provide additional information like trade‐offs between objectives for the decision making process, which is not available if the compensation principle would be chosen in advance. However, the Pareto optimal set of solutions can become large, especially if the objectives are mainly opposed. As a consequence, the Pareto optimal set may become difficult to analyze and to comprehend. In this case, pruning and ranking becomes attractive to reduce the Pareto optimal set and to rank the solutions to assist the decision maker. Because the method used, may influence the eventual decisions taken, it is important to choose a method that corresponds best with the underlying decision process and is in accordance with the qualities of the data used. We provided a review of some methods to prune and rank the Pareto optimal set to illustrate the advantages and disadvantages of these methods. The methods are applied using the outcome of solving the dynamic MONDP in which minimizing externalities of traffic are the objectives, and dynamic traffic management measures are the decision variables. For this, we solved the dynamic MONDP for a realistic network of the city Almelo in the Netherlands using the non‐dominated sorting genetic algorithm II. For ranking, we propose to use a fuzzy outranking method that can take uncertainties regarding the data quality and the perception of decision makers into account; and for pruning, a method that explicitly reckons with significant trade‐offs has been identified as the more suitable method to assist the decision making process. Copyright © 2012 John Wiley & Sons, Ltd.     

Multicriteria evaluation on accessibility‐based transportation equity in road network design problem

This paper investigates the performance of accessibility‐based equity measurements in transportation and proposes a multiobjective optimization model to simulate the trade‐offs between equity maximization and cost minimization of network construction. The equity is defined as the spatial distribution of accessibilities across zone areas. Six representative indicators were formulated, including GINI coefficient, Theil index, mean log deviation, relative mean deviation, coefficient of variation, and Atkinson index, and incorporated into an equity maximization model to evaluate the performance sensitivity. A bilevel multiobjective optimization model was proposed to obtain the Pareto‐optimal solutions for link capacity enhancement in a stochastic road network design problem. A numerical analysis using the Sioux Falls data was implemented. Results verified that the equity indicators are quite sensitive to the pattern of network scenarios in the sense that the level of equity varies according to the amount of overall capacity enhancement as well as the assignment of improved link segments. The suggested multiobjective model that enables representing the Pareto‐optimal solutions can provide multiple options in the decision making of road network design. Copyright © 2012 John Wiley & Sons, Ltd.     

Effectiveness of safety-based incentives in Public Private Partnerships: Evidence from the case of Spain

Many countries around the world are implementing Public–Private–Partnership (PPP) contacts to manage road infrastructure. In some of these contracts the public sector introduces economic incentives to the private operator to foster the accomplishment of social goals. One of the incentives that have been introduced in some PPP contracts is related to safety in such a way that the better the safety outcome the greater will be the economic reward to the contractor. The aim of this paper is at identify whether the incentives to improve road safety in highway PPPs are ultimately effective in improving safety ratios. To this end Poisson and negative binomial regression models have been applied using information from highway sections in Spain. The findings indicate that even though road safety is highly influenced by variables that are not much controllable by the contractor such as the Average Annual Daily Traffic and the percentage of heavy vehicles, the implementation of safety incentives in PPPs has a positive influence in the reduction of fatalities, injuries and accidents.     

The effect of contract renewal and competitive tendering on public transport costs,subsidies and ridership

In this paper, we aim to estimate the effect of contract renewal as well as competitive tendering on public transport costs, subsidies, and ridership. More specifically, we examine to what extent (multiple) contract renewals and introduction of competitive tendering for long-term public transport contracts affect ridership, operational costs and subsidies in concession areas governed by public transportation authorities from 2001 until 2013 in the Netherlands. Our identification strategy improves on the literature as we are able to control for all time-invariant unobserved factors, such as network and area characteristics by using panel data. We show that when renewing long-term contracts, operational costs are reduced by at least 10%, whereas subsidies fall even stronger. For contracts that are renewed at least twice, the reduction in costs is even more substantial and in the order of 16%. We find that the effect of competitive tendering is completely absent, suggesting that the threat of competitive tendering is sufficient in a market where the majority of concessions is competitive tendered. Contract renewal not only reduces costs and subsidies, but simultaneously increases public transport ridership by 7.7%. Furthermore the vehicle-hours elasticity of operational costs is 0.40, pointing to strong economies of density. The geographical scale elasticity of operational costs is around one, which indicates constant returns to scale with respect to the geographical size of the concession area. This suggest that the current size of the Dutch concession area is optimal with respect to costs.     

A new era for airport regulators through capacity investments

Private and public airports’ optimal actions may not coincide. While private airports usually pursue profit maximization, publicly owned airports look for maximum social welfare. Thus, the prices charged by private airports may differ from the socially optimal charges and public intervention may be needed. In this paper, we analyze airport charges when an increase in frequency produces positive or negative externalities and carriers have market power. We use the methodology of game theory to show that there may exist a level of capacity for which private and social objectives coincide, so no price regulation is needed. Thus, the usual role of regulators and planners could be modified in order to decide the appropriate capacity investments for which airport regulation is no longer necessary.     

Improved models for technology choice in a transit corridor with fixed demand

We present three extensions to a base optimization model for a transit line which can be used to strategically evaluate technology choices. We add to the base model optimal stop spacing and train length, a crowding penalty, and a multi-period generalization. These extensions are analytically solvable by simple approximations and lead to meaningful insights. Their significance is illustrated by means of an example in which two road modes and two rail modes are defined by a set of techno-economical parameters. These parameters loaded in the base model yield dominance of road modes for all but the largest demand levels. We consistently keep this set of parameters for all models, and show how the break-even points between road and rail modes progressively recede toward lower demand levels when model refinements – not parameter changes – are applied. Scenario analyses of plausible parameter sets highlight the model’s versatility, and caution on general conclusions regarding technology dominance.     

Vehicle insurance and the risk of road traffic accidents

Given the upward trend in incidences of road traffic accidents (RTAs) over recent years, in order to mitigate the financial losses arising from such accidents, governments around the world nowadays generally encourage, or even require, drivers to purchase appropriate vehicle insurance. The primary aim of this study is to examine whether RTAs are directly related to the purchase of vehicle insurance, with our examination of data on vehicle damage insurance policyholders revealing that those drivers who purchase more insurance coverage have a higher probability of being involved in accidents, as a result of which, they will tend to submit more claims. This indicates that insurance coverage might contain information which can be used to assess the probability risk levels of RTAs. We also find that drivers with less safety awareness will tend to purchase more coverage, and that those who purchase more coverage will, in turn, tend to have more accidents and submit more claims. Our findings, which provide a number of road traffic policy implications, would appear to justify the use of the bonus–malus system.     

Incentive subsidy scheme design with elastic transport demand

Huge public transport subsidies caused by deficits have become a heavy financial burden on some local governments due to the decline of bus passenger numbers. It is essential to apply the performance‐based contract to bus services considering maximization of social welfare. This paper constructs an incentive subsidy contract considering the decision‐making powers of the service level and calculating the proper frequency elasticity aiming at two problems of performance‐based contracts. Meanwhile, we consider a role of bus operators ignored by most researchers. Under the scheme, the decision‐making power of the service level is discussed based on five assumptions, and meanwhile, bus operators are motivated to reduce cost and improve service level in the scheme. The case of the bus service of Arao city indicates that the optimal frequency equals to zero when bus operators decide frequency. If bus operators determine efforts, the optimal effort also equals to zero with the goal of maximizing the profit. Also, bus operators can play their roles in lessening cost and improving service level to help bus operators and the local government achieve a win‐win situation, which maximizes the social benefit in this subsidy scheme when all factors are decided by the government. Copyright © 2013 John Wiley & Sons, Ltd.     

Should subsidies to urban passenger transport be increased? A spatial CGE analysis for a German metropolitan area

In many countries passenger transport is significantly subsidized in a variety of ways for various reasons. The objective of this paper is to examine efficiency, distributional, environmental (CO₂ emissions) and spatial effects of increasing different kinds of passenger transport subsidies discriminating between household types, travel purposes and travel modes. The effects are calculated by applying a numerical spatial general equilibrium approach calibrated to an average German metropolitan area. In extension to most studies focusing on only one kind of subsidy, we compare the effects of different transport subsidies within the same unified framework that allows to account for two features not yet considered simultaneously in studies on transport subsidies: endogenous labor supply and location decisions. Furthermore, congestion, travel mode choice, travel related CO₂ emissions and institutional details regarding the tax system in Germany are taken into account. The results suggest that optimal subsidy levels are either small or even zero. While subsidizing public transport is welfare enhancing, subsidies to urban road traffic reduce aggregate urban welfare. Concerning the latter it is shown that making investments in urban road infrastructure capacity or reducing gasoline taxes may even be harmful to residents using predominantly automobile. In contrast, pure commuting subsidies hardly affect aggregate urban welfare, but distributional effects are substantial. All policies cause suburbanization of city residents and (except for subsidizing public transport) contribute to urban sprawl by raising the spatial imbalance of residences and jobs but the effect is relatively small. In addition, the policies induce a very differentiated pattern regarding distributional effects, benefits of landowners and environmental effects.     

Do people drive safer when accidents are more expensive: Testing for moral hazard in experience rating schemes

Using individual policies and claims data from the Croatian mandatory motor insurance we test the theoretical proposition that under moral hazard, experience rated pricing scheme should generate the negative state dependence in claims, i.e. that drivers should drive more safely after they had an accident. The empirical challenge in these tests is to disentangle the state dependence from unobserved heterogeneity. We propose a simple approach based on the explicit reliance on the cost of future accidents function which is used to filter out the pure incentives effect, whereas the bonus-malus scale is used to control for pure heterogeneity. Our results confirm the existence of negative dependence in claims indicating the presence of significant moral hazard effect. Increasing a 3-year cost of having an accident by approximately US$20 decreases the probability of having an accident by 6.5%.     

Road pricing: The right solution for the right problem?

Road-pricing theory asserts that the optimal speed of a road network is that where vehicles pay the marginal social cost of their journey, rather than an average private cost if no price is imposed. This paper aims to show that this is misconceived. In big congested cities, the running speed of the road network is set by the direct journey speed achieved on the appropriate mass-transit network, both within and to the city centre. After dividing by the appropriate route factors to convert running speed to direct speed and allowing for access to convert kerb-to-kerb to door-to-door speed, the average direct journey speeds by car are identical to those on the mass-transit system for equivalent journeys when there is suppressed demand for car travel. Road pricing should thus be seen, not as a tool for increasing road speeds, which it cannot do whilst sufficient suppressed demand exists, but as a tool for estimating the socially desirable demand level on the roads as opposed to on the mass-transit systems. Road speeds in big, congested cities can only be increased by increasing the direct speeds of the mass-transit systems. Methods of achieving such increases are discussed.     

How to road price in a world with electric vehicles and government budget constraints

In this paper we examine what characterizes second-best road prices targeting external costs from driving electric (EV) and conventional (ICEV) vehicles when there are distortionary labor taxes and binding government budget constraints. Further, we examine how this second-best pricing fits with government set goals of reducing CO₂ emissions. The paper further develops an analytical framework for assessing first- and second-best road prices on vehicle kilometers, extending it to include EVs and externalities that vary geographically and by time of day. We find that optimal road prices largely vary with external cost, but are also significantly affected by the interactions with the rest of the fiscal system. Not surprisingly, the highest road prices should be for ICEVs in large cities during peak hours due to high external costs. More surprisingly, we find that the road price for ICEVs in rural areas should be lower than that for EVs due to large fiscal interaction effects. These road prices give large welfare gains, but they lead to no reduction in carbon emissions when applying the currently recommended social cost of carbon.     

A piecewise-constant congestion taxing policy for repeated routing games

In this paper, we consider repeated routing games with piecewise-constant congestion taxing in which a central planner sets and announces the congestion taxes for fixed windows of time in advance. Specifically, congestion taxes are calculated using marginal congestion pricing based on the flow of the vehicles on each road prior to the beginning of the taxing window (and, hence, there is a time-varying delay in setting the congestion taxes). We motivate the piecewise-constant taxing policy by that users or drivers may dislike fast-changing prices and that they also prefer prior knowledge of the prices. We prove for this model that the multiplicative update rule and the discretized replicator dynamics converge to a socially optimal flow when using vanishing step sizes. Considering that the algorithm cannot adapt itself to a changing environment when using vanishing step sizes, we propose adopting constant step sizes in this case. Then, however, we can only prove the convergence of the dynamics to a neighborhood of the socially optimal flow (with the size of the neighbourhood being of the order of the selected step size). The results are illustrated on a nonlinear version of Pigou’s famous routing game.     

An analysis of airport–airline vertical relationships with risk sharing contracts under asymmetric information structures

We analyze the double moral hazard problem at the joint venture type airport–airline vertical relationship, where two parties both contribute efforts to the joint venture but neither of them can see the other’s efforts. With the continuous-time stochastic dynamic programming model, we show that by the de-centralized utility maximizations of two parties under very strict conditions, i.e., optimal efforts’ cost being negligible and their risk averse parameters both asymptotically approaching to zero, the vertical contract could be agreed as the optimal sharing rule, which is the linear function of the final state with the slope being the product of their productivity difference and uncertainty (diffusion rate) level index.If both parties’ productivities are same, or the diffusion rate of the underlying process is unity, optimal linear sharing rule do not depend on the final state. If their conditions not dependent on final state are symmetric as well, then risk sharing disappears completely. In numerical examples, we illustrate the complex impact of uncertainty increase and end-of-period load factor improvement on the optimal sharing rule, and the relatively simple impact on total utility levels.     

Analysis of factors that may be essential in the decision to fly on fully autonomous passenger airliners

This research investigates factors that influence opinion in the decision to fly on fully autonomous passenger airliners primarily from the perspective of aviation and technology professionals. Bayesian statistical inference and a two‐level fractional factorial survey are used to sample passengers' views on fully autonomous airliners. Eight trust, safety, and cost factors are incorporated into a vignette set in the future. Factors include automation levels, safety records, liability guarantees, airline integrity, and service disruptions. Dependent variables exist in five post‐vignette questions and essentially ask “Would you” or “Would you not” be willing to fly on a fully autonomous airliner? Sixteen versions of the vignette, each with unique trust, safety, and cost levels, present varying (unknown) degrees of influence to the survey respondents. For every demographic, the research shows a 99% statistically significant difference between the “prior” and “posterior” sampled population proportions willing to fly. The most significant positive influence involves integrity characteristics of the airline, while the most negative influence relates to life insurance liability guarantees. Research from 2003 suggested that this mode of travel would be acceptable to only 10.5% of respondents. When the 2003 research is used as a Bayesian prior probability, the resulting posterior probability for the demographics sampled can be modeled as a beta distribution, indicating 95% probability that the sampled proportion of the population willing to fly is between 33.2% and 36.4%. After adjusting for age and profession demographics to match the US population, the 95% probability bounds on the proportion willing to fly are 31.35% and 34.15%. Copyright © 2015 John Wiley & Sons, Ltd.     

Benchmarking road safety performance by grouping local territories: A study in the Netherlands

The method of benchmarking provides an opportunity to learn from better performing territories to improve the effectiveness and efficiency of activities in a particular field of interest. Such a field of interest could be road safety. Road safety benchmarking can include several indicators, ranging from performance indicated by crash statistics, to indicators that also account for consequences in costs or the underlying state of the road safety system and relevant organisation and processes at actor level. The structure and culture of a territory is identified as a basic context of road safety performance. This is regarded as important information to use in grouping of territories to get more homogenous or equal and comparable conditions to learn from ‘the best in class’.The main aim of this study is to assess the usability of different groupings using the physical structure for benchmarking road safety performance at local territorial level. A traditional grouping of municipalities in the Netherlands was compared with a simple grouping of these municipalities based on their level of urbanisation and an advanced grouping in which more indicators such as differences in demography, growth and road structure were taken into account. As in other studies, urbanisation showed to be the most predominant structural factor for grouping local territories and related to differences in road safety performance. However, if information would be needed for specific target groups, other factors like age and gender distribution or the distribution of the road network can provide valuable additional insight and better homogenous starting points for benchmarking. Especially benchmarking of rural territories may profit from such extra distinctive characteristics.     

Multi-objective optimization of a road diet network design

The present study focuses on the development of a model for the optimal design of a road diet plan within a transportation network, and is based on rigorous mathematical models. In most metropolitan areas, there is insufficient road space to dedicate a portion exclusively for cyclists without negatively affecting existing motorists. Thus, it is crucial to find an efficient way to implement a road diet plan that both maximizes the utility for cyclists and minimizes the negative effect on motorists. A network design problem (NDP), which is usually used to find the best option for providing extra road capacity, is adapted here to derive the best solution for limiting road capacity. The resultant NDP for a road diet (NDPRD) takes a bi-level form. The upper-level problem of the NDPRD is established as one of multi-objective optimization. The lower-level problem accommodates user equilibrium (UE) trip assignment with fixed and variable mode-shares. For the fixed mode-share model, the upper-level problem minimizes the total travel time of both cyclists and motorists. For the variable mode-share model, the upper-level problem includes minimization of both the automobile travel share and the average travel time per unit distance for motorists who keep using automobiles after the implementation of a road diet. A multi-objective genetic algorithm (MOGA) is mobilized to solve the proposed problem. The results of a case study, based on a test network, guarantee a robust approximate Pareto optimal front. The possibility that the proposed methodology could be adopted in the design of a road diet plan in a real transportation network is confirmed.     

Vehicle Positioning for Improving Road Safety

Abstract

Vehicle positioning is a key requirement for many safety applications. Active safety systems require precise vehicle positioning in order to assess the safety threats accurately, especially for those systems which are developed for warning/intervention in safety critical situations. When warning drivers of a local hazard (e.g. an accident site), accurate vehicle location information is important for warning the right driver groups at the right time. Global positioning system and digital maps have become major tools for vehicle positioning providing not only vehicle location information but also geometry preview of the road being used. Advances in wireless communication have made it possible for a vehicle to share its location information with other vehicles and traffic operation centres which greatly increases the opportunities to apply vehicle positioning technologies for improving road safety. This paper presents a state‐of‐the‐art review of vehicle positioning requirements for safety applications and vehicle positioning technologies. The paper also examines key issues relating to current and potential future applications of vehicle positioning technologies for improving road safety.