Vehicle purchasing behaviors comparison in two-stage choice perspective before and after eco-car promotion policy in Japan

This paper compares the vehicle purchasing behaviors in Japan between before and after the eco-car (environmental friendly vehicle) promotion policy implemented. Consumer behaviors are modeled as a two-stage decision process: a consideration set formation stage and a choice-making stage. In the first stage, all available vehicle types are included in the choice set, and consumers are assumed to apply a conjunctive screening rule to construct consideration sets. In the second stage, consumers only evaluate the vehicles in the consideration set and choose the one with maximum utility. The applied Hierarchical Bayes model can avoid the issue of an indifferentiable and irregular likelihood surface caused by thresholds and discontinuities, and the data augmentation and Markov-Chain Monte Carlo estimation methods make it possible to estimate two stages simultaneously using only the information about the consumers’ actual choices. The estimations indicate that the change of consumer behavior during the formation of consideration sets after the policy implemented: more people preferred compact and hybrid vehicles because of their better fuel efficiency and more competitive prices under the tax reduction policy. The results show, however, that most of consumers who purchase hybrid vehicles after the policy implemented are only including hybrid vehicles in their consideration sets, and oil price and vehicle price still play important roles in the choice-making stage for these who consider both gasoline and hybrid vehicles.     

Public charging infrastructure for plug-in electric vehicles: What is it worth?

Lack of charging infrastructure is an important barrier to the growth of the plug-in electric vehicle (PEV) market. Public charging infrastructure has tangible and intangible value, such as reducing range anxiety or building confidence in the future of the PEV market. Quantifying the value of public charging infrastructure can inform analysis of investment decisions and can help predict the impact of charging infrastructure on future PEV sales. Estimates of willingness to pay (WTP) based on stated preference surveys are limited by consumers’ lack of familiarity with PEVs. As an alternative, we focus on quantifying the tangible value of public PEV chargers in terms of their ability to displace gasoline use for PHEVs and to enable additional electric (e−) vehicle miles for BEVs, thereby mitigating the limitations of shorter range and longer recharging time. Simulation studies provide data that can be used to quantify e-miles enabled by public chargers and the value of additional e-miles can be inferred from econometric estimates of WTP for increased vehicle range. Functions are synthesized that estimate the WTP for public charging infrastructure by plug-in hybrid and battery electric vehicles, conditional on vehicle range, annual vehicle travel, pre-existing charging infrastructure, energy prices, vehicle efficiency, and household income. A case study based on California’s public charging network in 2017 indicates that, to the purchaser of a new BEV with a 100-mile range and home recharging, existing public fast chargers are worth about $1500 for intraregional travel, and fast chargers along intercity routes are valued at over $6500.     

广西高等级公路交通噪声预测值的衰减规律的研究

文章根据广西高速公路目前车流量、车型比以及车速情况,结合交通环境噪声的实测数据,对高速公路交通噪声的变化规律进行分析研究。     

Projecting adoption of truck powertrain technologies and CO2 emissions in line-haul networks

In this paper we present a mixed-integer linear program to represent the decision-making process for heterogeneous fleets selecting vehicles and allocating them on freight delivery routes to minimize total cost of ownership. This formulation is implemented to project alternative powertrain technology adoption and utilization trends for a set of line-haul fleets operating on a regional network. Alternative powertrain technologies include compressed (CNG) and liquefied natural gas (LNG) engines, hybrid electric diesel, battery electric (BE), and hydrogen fuel cell (HFC). Future policies, economic factors, and availability of fueling and charging infrastructure are input assumptions to the proposed modeling framework. Powertrain technology adoption, vehicle utilization, and resulting CO₂ emissions predictions for a hypothetical, representative regional highway network are illustrated. A design of experiments (DOE) is used to quantify sensitivity of adoption outcomes to variation in vehicle performance parameters, fuel costs, economic incentives, and fueling and charging infrastructure considerations. Three mixed-adoption scenarios, including BE, HFC, and CNG vehicle market penetration, are identified by the DOE study that demonstrate the potential to reduce cumulative CO₂ emissions by more than 25% throughout the period of study.     

Personal tradable carbon permits for road transport: Why, why not and who wins?

Personal road transport sector poses a significant challenge in reducing carbon emissions. This paper evaluates a policy approach known as personal tradable carbon permits to reduce carbon emissions from personal vehicles. The policy is a downstream tradable permit where individuals are allocated carbon emission caps. The policy is qualitatively evaluated in the context of carbon taxes and some upstream tradable permit options. The biggest disadvantage of such a policy is the initial set up costs. Personal tradable permits, however, are more effective than carbon taxes and are also capable of stabilizing the gasoline prices faced by the consumers when the underlying oil prices fluctuate. Since equity effects are often a concern to policy makers, the effect of such personal carbon permits on the distribution of burden is quantified in a partial equilibrium framework for the US population. Different permit allocation strategies are investigated in this regard. Using US consumer expenditure survey data, and incorporating a differentiated price response for different households, we find that all three allocation strategies considered are progressive: a per adult based allocation is the most progressive, a per vehicle allocation nearer to proportional, and a per capita allocation in between the two. Personal tradable permits therefore take care of equity concerns directly through the design of the policy.     

A comparison of hedonic price and stated preference methods to derive monetary values for aircraft noise disturbance and annoyance

This paper compares monetary values for aircraft noise disturbance and annoyance derived using hedonic price and stated preference methods in the same sample areas and over the same sampling time periods. The hedonic price method compares house prices in residential areas across a range of aircraft noise sound levels. The statistical power can be compromised by the many other variables which have significant and often greater effects on prices and because only small fractions of the overall housing stock are bought and sold at any one time. The stated preference method on the other hand, by requiring study participants to trade hypothetical money against hypothetical noise, is entirely based on subjective opinion. It seems that neither method is entirely satisfactory, but there are strong positive correlations between the ratios of aggregated stated preference values to weighted average house prices and LAeq, 16 h and similar noise metrics suggesting sufficient underlying similarities     

Analysis of equilibrium automobile holdings in Israel with aggregate discrete choice models

Models of household vehicle ownership decisions do not suffice as a basis for forecasting the size and composition of aggregate vehicle holdings. Forecasting applications require that such models be imbedded in systems describing the operation of the automobile market. This paper presents a new model of short run equilibrium in the automobile market. The short run is a period within which new car designs and prices are fixed but used car prices adjust competitively to market forces. The magnitude and mix of new car sales, the extent of used car scrappage and the composition of used car holdings are determined in equilibrium with used car prices. An econometric version of the market model has been estimated on Israeli data and applied to analyze the impact of vehicle tax policy on automobile holdings in Israel. The paper describes this application.     

A dynamic Bayesian network model for real-time crash prediction using traffic speed conditions data

Traffic crashes occurring on freeways/expressways are considered to relate closely to previous traffic conditions, which are time-varying. Meanwhile, most studies use volume/occupancy/speed parameters to predict the likelihood of crashes, which are invalid for roads where the traffic conditions are estimated using speed data extracted from sampled floating cars or smart phones. Therefore, a dynamic Bayesian network (DBN) model of time sequence traffic data has been proposed to investigate the relationship between crash occurrence and dynamic speed condition data. Moreover, the traffic conditions near the crash site were identified as several state combinations according to the level of congestion and included in the DBN model. Based on 551 crashes and corresponding speed information collected on expressways in Shanghai, China, DBN models were built with time series speed condition data and different state combinations. A comparative analysis of the DBN model using flow detector data and a static Bayesian network model was also conducted. The results show that, with only speed condition data and nine traffic state combinations, the DBN model can achieve a crash prediction accuracy of 76.4% with a false alarm rate of 23.7%. In addition, the results of transferability testing imply that the DBN models are applicable to other similar expressways with 67.0% crash prediction accuracy.     

Consumer valuation of new car attributes: An econometric analysis of the demand for domestic and Japanese/Western European imports

Although previous studies of new vehicle choice decisions have shown that consumers evaluate the attributes of domestic vehicles differently from those of imported vehicles, the assumption underlying these results is overly restrictive. In particular, there is no reason to assume, a priori, that the attributes of all imported vehicles have similar effects upon consumer choice behavior. A competing hypothesis, for example, is that consumers of U.S. and European automobiles have similar attribute valuations that are differentiated from those of Japanese consumers. In the present paper, a multinomial logit model of vehicle type choice is developed which more completely differentiates imports by country of origin. Using a 1985 national sample of new car buyers to estimate the model, willingness to pay measures were calculated and nested hypothesis tests on attribute valuation performed. The results supported the hypothesis that consumers value vehicle attributes differently depending upon its country of origin. Moreover, consumers do not have similar valuations on the attributes of all imports implying that an arbitrary distinction between domestic and imported vehicles may produce misleading results.     

The role of congestion of transportation networks in urban location and travel choices

Congestion of urban transportation systems results from an equilibrium of location and travel choices with generalized travel costs which increase with vehicle flows as well as other factors. The use of network equilibrium concepts in analyzing urban policies and evaluating alternative plans is examined. Issues arising in the use of network equilibrium models are described, and formulations of urban network prediction and design models are explored.     

Internalization of Transportation External Costs: Impact Analysis of Logistics Company Mode and Route Choices

Abstract

This study focuses on the mode and route choices of a logistics company in a situation involving intercity transportation with networks of surface roads, highways and a railway. A method of transportation network analysis is applied to construct a logistics company mode and route choice models with the objective of minimizing total distribution and external costs. This study also assumes that the fleet number and vehicle capacities are given. Freight distributed from a distribution center to given retailers or consumers via surface road/highway links or via intermodal transportation involving surface road/highway links and a railway. In terms of model construction, this study first explores the routing and sequence of the retailers and consumers served by each vehicle. Second, the study internalizes the external cost of air pollution into the total distribution cost, to analyze the influences of external cost burdens on a logistics company mode and route choices from a user charge perspective. Finally, the study designs a heuristic algorithm for solving the above models, and illuminates the modeling process using a numerical example.     

A traffic congestion detection and information dissemination scheme for urban expressways using vehicular networks

The cooperative vehicle-infrastructure technologies have enabled vehicles to collect and exchange traffic information in real time. Therefore, it is possible to use Vehicular Ad-hoc NETworks (VANETs) for detecting traffic congestion on urban expressways. However, because of the special topology of urban expressways (consisting of both major and auxiliary roadways), the existing traffic congestion detection methods using VANETs do not work very well. In addition, the existing dissemination methods of congestion information lack the necessary control mechanism, so the information may be disseminated to irrelevant geographical areas. This paper proposes a congestion detection and notification scheme using VANETs for urban expressways. The scheme adopts a simplified Doppler frequency shift method to estimate and differentiate traffic conditions for major and auxiliary roadways. Vehicular cooperation and human cognition are introduced to improve the estimation accuracy and to describe the overall traffic conditions. Additionally, the scheme develops a spatial–temporal effectiveness model based on the potential energy theory to control the dissemination area and survival time of the congestion information. Meanwhile, the proposed scheme uses several broadcast control mechanisms to alleviate vehicular network congestion. Simulations through TransModeler indicate that our scheme ensures the accuracy of the estimation of congestion degree. Consequently, the scheme can provide effective references for driving decision-making and path-planning.     

Determinants of new vehicle registrations in EU countries: a panel cointegration analysis

This paper investigates the determinants of new vehicle registrations in European Union (EU) countries by focusing on four particular segments – passenger cars, light commercial vehicles, commercial vehicles, and heavy commercial vehicles. A panel cointegration analysis for a panel of 13 EU countries during the period from January 1999 to August 2010 shows that new vehicle sales have long-run cointegration relations with vehicle prices, consumer confidence, income, interest rates, fuel prices, industrial production, and trade. More effective factors in determining new vehicle sales appear to be trade, interest rates, and industrial production.     

Distance and time in intermodal goods transport networks in Europe: A generic approach

This paper is about distance and time as factors of competitiveness of intermodal transport. It reviews the relevance of the factors, evaluates time models in practice, compares network distances and times in alternative bundling networks with geometrically varied layouts, and points out how these networks perform in terms of vehicle scale, frequency and door-to-door time. The analysis focuses on intermodal transport in Europe, especially intermodal rail transport, but is in search for generic conclusions. The paper does not incorporate the distance and time results in cost models, and draws conclusions for transport innovation, wherever this is possible without cost modelling. For instance, the feature vehicle scale, an important factor of transport costs, is analysed and discussed.Distance and time are important factors of competitiveness of intermodal transport. They generate (direct) vehicle costs and – via transport quality – indirect costs to the customers. Clearly direct costs/prices are the most important performance of the intermodal transport system. The relevance of quality performances is less clarified. Customers emphasise the importance of a good match between the transport and the logistic system. In this framework (time) reliability is valued high. Often transport time, arrival and departure times, and frequency have a lower priority. But such conclusions can hardy be generalised. The range of valuations reflects the heterogeneity of situations. Some lack of clarity is obviously due to overlapping definitions of different performance types.The following parts of the paper are about two central fields of network design, which have a large impact on transport costs and quality, namely the design of vehicle roundtrips (and acceleration of transport speed) and the choice of bundling type: do vehicles provide direct services or run in what we call complex bundling networks? An example is the hub-and-spoke network. The objective of complex bundling is to increase vehicle scale and/or transport frequency even if network volumes are restricted. Complex bundling requires intermediate nodes for the exchange of load units. Examples of complex bundling networks are the hub-and-spoke network or the line network.Roundtrip and bundling design are interrelated policy fields: an acceleration of the roundtrip speed, often desirable from the cost point of view, can often only be carried out customer friendly, if the transport frequency is increased. But often the flow size is not sufficient for a higher frequency. Then a change of bundling model can be an outcome.Complex bundling networks are known to have longer average distances and times, the latter also due to the presence of additional intermediate exchange nodes. However, this disadvantage is – inside the limits of maximal vehicle sizes – overruled by the advantage of a restricted number of network links. Therefore generally, complex bundling networks have shorter total vehicle distances and times. This expression of economies of scale implies lower vehicle costs per load unit.The last part of the paper presents door-to-door times of load units of complex bundling networks and compares them with unimodal road transport. The times of complex bundling networks are larger than that of networks with direct connections, but nevertheless competitive with unimodal road transport, except for short distances.     

Effects of providing total cost of ownership information on consumers’ intent to purchase a hybrid or plug-in electric vehicle

Energy-saving technologies have a difficult time being widely accepted in the marketplace when they have a high initial purchase price and deferred financial benefits. Consumers might not realize that, in the long-run, the financial benefits from reduced energy consumption offset much or all of the initial price premium. One strategy to address consumer misconception of this advantage is to supply information on the “total cost of ownership”, a metric which accounts for the purchase price, the cost of the fuel, and other costs over the ownership period. In this article, we investigate how providing information on five-year fuel cost savings and total cost of ownership affects the stated preferences of consumers to purchase a gasoline, conventional hybrid, plug-in hybrid, or battery electric vehicle. Through an online survey with an embedded experimental design using distinct labels, we find that respondent rankings of vehicles are unaffected by information on five-year fuel cost savings. However, adding information about total cost of ownership increases the probability that small/mid-sized car consumers express a preference to acquire a conventional hybrid, plug-in hybrid, or a battery-electric vehicle. No such effect is found for consumers of small sport utility vehicles. Our results are consistent with other findings in the behavioral economics literature and suggest that further evaluation of the effects of providing consumers with information on the total cost of vehicle ownership is warranted.     

Willingness-to-pay for alternative fuel vehicle characteristics: A stated choice study for Germany

In the light of European energy efficiency and clean air regulations, as well as an ambitious electric mobility goal of the German government, we examine consumer preferences for alternative fuel vehicles (AFVs) based on a Germany-wide discrete choice experiment among 711 potential car buyers. We estimate consumers’ willingness-to-pay and compensating variation (CV) for improvements in vehicle attributes, also taking taste differences in the population into account by applying a latent class model with 6 distinct consumer segments. Our results indicate that about 1/3 of the consumers are oriented towards at least one AFV option, with almost half of them being AFV-affine, showing a high probability of choosing AFVs despite their current shortcomings. Our results suggest that German car buyers’ willingness-to-pay for improvements of the various vehicle attributes varies considerably across consumer groups and that the vehicle features have to meet some minimum requirements for considering AFVs. The CV values show that decision-makers in the administration and industry should focus on the most promising consumer group of ‘AFV aficionados’ and their needs. It also shows that some vehicle attribute improvements could increase the demand for AFVs cost-effectively, and that consumers would accept surcharges for some vehicle attributes at a level which could enable their private provision and economic operation (e.g. fast-charging infrastructure). Improvement of other attributes will need governmental subsidies to compensate for insufficient consumer valuation (e.g. battery capacity).     

A two-sided market platform analysis for the electric vehicle adoption: Firm strategies and policy design

This study explores how to facilitate the electric vehicle (EV) diffusion from a two-sided market platform competition. We develop a stylized model depicting the platform competition between electric and gasoline vehicles by combining indirect network effects of consumer and energy supplier sides as well as vehicle manufacturers’ profits. The findings of this study provide several meaningful strategic and policy implications for EV manufacturers and policymakers who wish to enhance EV diffusion. First, EV sales are significantly influenced by indirect network effects from the energy supplier side to the consumer side, and vice versa. This implies that EV manufacturers who wish to boost EV diffusion should implement a strategy providing energy suppliers with incentives to willingly join the EV platform. Second, the dynamic nature of the effects of energy costs on platform competition might render counter-intuitive evidence that the drop in oil prices does not always negatively influence EV sales. This requires EV manufacturers to prepare a contingent strategy adjusting to such unexpected conditions. Third, governments should consider the energy supplier side as well as the consumer side in designing EV diffusion policies. When governments have a very challenging EV diffusion target, a balanced policy, which treats both gasoline and electric vehicle technologies fairly, may be more effective than a consumer subsidy policy.     

Lane-harmonised passenger car equivalents for heterogeneous expressway traffic

In order to account for variations in traffic composition during traffic analysis, passenger car equivalent (PCE) factors are used to convert flow rates of various vehicle classes into flow rates in terms of passenger car units (PCUs). Earlier studies have developed various methods to estimate PCE values but only a few of them are based on uninterrupted traffic flow, particularly for flow regimes with heterogeneous traffic where differential (lower) speed limits are imposed on commercial vehicles. This paper proposes a lane-harmonisation approach, which leverages on the high variation in traffic composition across the lanes, to estimate PCE factors for urban expressways. Multiple linear regression is used and the PCE factors obtained for motorcycles, light goods vehicles, and heavy goods vehicles are 0.65, 1.53, and 2.75, respectively. The estimated capacity flow rate after the application of the obtained PCE factors is around 2200 PCUs per hour per lane.     

A travel time reliability model of urban expressways with varying levels of service

Urban expressways usually experience several levels of service (LOS) because of the stop-and-go traffic flow caused by congestion. Moreover, multiple shock waves generate at different LOS interfaces. The dynamic of shock waves strongly influences the travel time reliability (TTR) of urban expressways. This study proposes a path TTR model that considers the dynamic of shock waves by using probability-based method to characterize the TTR of urban expressways with shock waves. Two model parameters are estimated, namely distribution of travel time (TT) per unit distance and travel distances in different LOS segments. Generalized extreme value distribution and generalized Pareto distribution are derived as distributions of TT per unit distance for six different LOS. Distribution parameters are estimated by using historical floating car data. Travel distances in different LOS segments are calculated based on shock wave theory. The range of TT along the path, which can help drivers arrange their trips, can be obtained from the TTR model. Finally, comparison is made among the proposed TTR model, generalized Pareto contrast model, which does not consider different LOS or existence of shock waves, and normal contrast model, which assumes TT per unit distance as normal distribution without considering shock wave. Results show that the proposed model achieves higher prediction accuracy and reduces the prediction range of TT. The conclusions can be further extended to TT prediction and assessment of measures to improve reliability of TT in a network.     

Integrated modeling framework for leasing urban roads: A case study of Fresno,California

Increasing private sector involvement in transportation services has significant implications for the management of road networks. This paper examines a concession model’s effects on a road network in the mid-sized city of Fresno, California. Using the existing transportation planning models of Fresno, we examine the effects of privatization on a number of typical system performance measures including total travel time and vehicle miles traveled (VMT), the possibility of including arterials, and the differences between social cost prices and profit maximizing prices. Some interesting insights emerge from our analysis: (1) roads cannot be considered as isolated elements in a concession model for a road network; (2) roads can function as complements at some levels of demand and become substitutes at other levels; (3) policy makers/officials should consider privatizing/pricing arterials along with privatizing highways; (4) temporally flexible but limited price schedule regulations should be part of leasing agreements; and (5) non-restricted pricing may actually worsen system performance, while limited pricing can raise enormous profits as well as improve system performance.