A cellular automata (CA) model for motorized vehicle flows influenced by bicycles along the roadside

On many urban low‐grade or branch roads, especially in medium or small cities in China, bicyclists and motorists commonly share the non‐barrier road surface. Because bicycles are unpredictable and unstable when moving, motorized vehicles must reduce their speed to safely approach and overtake them. In this study, the gradual deceleration process a motorized vehicle undergoes before it passes a bicycle was analyzed. The motorist was assumed to prefer a comfortable deceleration and to select a higher deceleration rate only when the distance to the bicycle was insufficient to reduce the car's speed to the expected value at a comfortable deceleration rate. Cellular automata (CA) simulations were used to reveal the flow characteristics of motorized vehicles reacting to bicycles traveling along the roadside, and the results show that for the general velocities of motorized vehicles and bicycles traveling on urban branch roads, the road capacity for motorized vehicles is not related to the number of bicycles present. However, the average travel time of motorized vehicles is significantly affected by the presence of bicycles when the number of motorized vehicles on the road is small. In addition, motorized vehicles' average travel time is more influenced by disturbances in the flow of motorized vehicles than by bicycles when the number of motorized vehicles on the road is large. Field observations and surveys were used to validate the traffic behaviors and simulation results. Copyright © 2016 John Wiley & Sons, Ltd.     

Adapting interactive stated response techniques to a self-completion survey

We report here on how we adapted Interactive Stated Response Methods to use in a self-completion survey of 454 California households to measure the market for electric vehicles in California. Electric vehicles are a novel product and have many features unfamiliar to consumers, in particular their home recharging capability and limited range. Reflexive techniques were designed to draw households into a deeper exploration of the lifestyle implications of electric vehicles than can be done in more typical self-completion surveys, and to stimulate key decision processes previously observed in detailed gaming interviews with 51 households. Reflexive self-completion techniques provide a middle course between typical large sample quantitative surveys and small sample, detailed gaming interviews. One of the benefits of the more intensive techniques was that participants reported finding the surveys interesting and return rates were high for a self-completion approach – over sixty percent. We review previous transportation and sociological methods which inspired our design, describe the design goals and features of our research, and summarize research results pertinent to testing the validity of our approach.     

Including heavy vehicles in a car‐following model: modelling,calibrating and validating

Heavy vehicles influence general traffic in many different ways compared with passenger vehicles, and this may result in different levels of traffic instability. Increases in the number and proportion of heavy vehicles in the traffic stream will therefore result in different traffic flow conditions. This research initially outlines the different car‐following behaviour of drivers in congested heterogeneous traffic conditions indicating the necessity for developing a car‐following model, which includes these differences. A psychophysical car‐following model, similar in form to Weideman's car‐following model, was developed. Due to the complexity of the developed model, the calibration of the model was undertaken using a particle swarm optimisation algorithm with the data recorded under congested traffic conditions. This was then incorporated into a traffic microsimulation model. The results showed that the car‐following perceptual thresholds and thus action points of drivers differ based on their vehicle and the lead vehicle types. The inclusion of the heavy vehicles in the model showed significant impacts on the traffic dynamic and interactions amongst different vehicles. Copyright © 2016 John Wiley & Sons, Ltd.     

Comparing high-end and low-end early adopters of battery electric vehicles

Battery electric vehicle adoption research has been on going for two decades. The majority of data gathered thus far is taken from studies that sample members of the general population and not actual adopters of the vehicles. This paper presents findings from a study involving 340 adopters of battery electric vehicles. The data is used to corroborate some existing assumptions made about early adopters. The contribution of this paper, however, is the distinction between two groups of adopters. These are high-end adopters and low-end adopters. It is found that each group has a different socio-economic profile and there are also some psychographic differences. Further they have different opinions of their vehicles with high-end adopters viewing their vehicles more preferentially. The future purchase intentions of each group are explored and it is found that high-end adopters are more likely to continue with ownership of battery electric vehicles in subsequent purchases. Finally reasons for this are explored by comparing each adopter group’s opinions of their vehicles to their future purchase intentions. From this is it suggested that time to refuel and range for low-end battery electric vehicles should be improved in order to increase chances of drivers continuing with BEV ownership.     

Including congestion effects in urban road traffic CO2 emissions modelling: Do Local Government Authorities have the right options?

Tailpipe emissions from vehicles on urban road networks have damaging impacts, with the problem exacerbated by the common occurrence of congestion. This article focuses on carbon dioxide because it is the largest constituent of road traffic greenhouse gas emissions. Local Government Authorities (LGAs) are typically responsible for facilitating mitigation of these emissions, and critical to this task is the ability to assess the impact of transport interventions on road traffic emissions for a whole network.This article presents a contemporary review of literature concerning road traffic data and its use by LGAs in emissions models (EMs). Emphasis on the practicalities of using data readily available to LGAs to estimate network level emissions and inform effective policy is a relatively new research area, and this article summarises achievements so far. Results of the literature review indicate that readily available data are aggregated at traffic level rather than disaggregated at individual vehicle level. Hence, a hypothesis is put forward that optimal EM complexity is one using traffic variables as inputs, allowing LGAs to capture the influence of congestion whilst avoiding the complexity of detailed EMs that estimate emissions at vehicle level.Existing methodologies for estimating network emissions based on traffic variables typically have limitations. Conclusions are that LGAs do not necessarily have the right options, and that more research in this domain is required, both to quantify accuracy and to further develop EMs that explicitly include congestion, whilst remaining within LGA resource constraints.     

Are Longer and Heavier Vehicles (LHVs) Beneficial for Society? A Cost Benefit Analysis to Evaluate their Potential Implementation in Spain

Abstract

In this paper we carry out a thorough review of the current research related to the benefits and costs arising from the implementation of longer and heavier vehicles (LHVs). From this review we concluded that despite the many studies available, little has been said about the sensitivity of the benefits and costs to the ultimate performance of the key variables related to the evolution of the economy, road transport performance, safety, and so on. In order to fill this gap, we have designed a sensitivity approach based on a cost benefit analysis tool to determine which variables demonstrate the greatest influence on the benefits and costs stemming from the implementation of LHVs. In order to test the methodology, we have used it in an analysis of the Spanish trunk network. The results show that the benefits of LHVs for society are significant. Even in the least favorable scenario, the economic benefits are greater than €3500 million over 15 years, and the environment enhanced as well, for CO₂ emissions are reduced by 2 Million tonnes. Overall we noted how the results are not very sensitive to the evolution of key variables in determining the final outcome. However, we found that the variables that have the greatest affect on the final benefit, such as traffic growth and social discount rate, depend basically on the performance of the overall economy. Moreover, the private cost for haulers seems to be more important in determining the final benefit than externality costs.     

Consumer preferences for electric vehicles: a literature review

Widespread adoption of electric vehicles (EVs) may contribute to the alleviation of problems such as environmental pollution, global warming and oil dependency. However, the current market penetration of EV is relatively low in spite of many governments implementing strong promotion policies. This paper presents a comprehensive review of studies on consumer preferences for EV, aiming to better inform policy-makers and give direction to further research. First, we compare the economic and psychological approach towards this topic, followed by a conceptual framework of EV preferences which is then implemented to organise our review. We also briefly review the modelling techniques applied in the selected studies. Estimates of consumer preferences for financial, technical, infrastructure and policy attributes are then reviewed. A categorisation of influential factors for consumer preferences into groups such as socio-economic variables, psychological factors, mobility condition, social influence, etc. is then made and their effects are elaborated. Finally, we discuss a research agenda to improve EV consumer preference studies and give recommendations for further research.

Abbreviations: AFV: alternative fuel vehicle; BEV: battery electric vehicle; CVs: conventional vehicles; EVs: electric vehicles; FCV: fuel cell vehicle; HCM: hybrid choice model; HEV: hybrid electric vehicle (non plug-in); HOV: high occupancy vehicle; MNL: MultiNomial logit; MXL: MiXed logit model; PHEV: plug-in hybrid electric vehicle; RP: revealed preference; SP: stated preference.     

Impact of interviewing by proxy in travel survey conducted by telephone

Telephone‐interview surveys are a very efficient way of conducting large‐scale travel surveys. Recent advancements in computer technology have made it possible to improve upon the quality of data collected by telephone surveys through computerization of the entire sample‐control process, and through the direct recording of the collected data into a computer. Notwithstanding these technological advancements, potential sources of bias still exist, including the reliance on an adult member of the household to report the travel information of other household members. Travel data collected in a recent telephone interview survey in the Toronto region is used to examine this issue. The statistical tool used in the research was the Analysis of Variance (ANOVA) technique as implemented within the general linear model framework in SAS. The study‐results indicate that reliance on informants to provide travel information for non‐informant members of their respective households led to the underreporting of some categories of trips. These underreported trip categories were primarily segments of home‐based discretionary trips, and non home‐based trips. Since these latter two categories of trips are made primarily outside the morning peak period, estimated factors to adjust for their underreporting were time‐period sensitive. Further, the number of vehicles available to the household, gender, and driver license status respectively were also found to be strongly associated with the underreporting of trips and thus were important considerations in the determination of adjustment factors. Work and school trips were found not to be underreported, a not surprising result giving the almost daily repetitiveness of trips made for these purposes and hence the ability of the informant to provide relatively more precise information on them.     

Car fuel-type choice under travel demand management and economic incentives

Future levels of vehicle air pollution in urban areas will depend on the proportion of new car buyers who opt for less polluting vehicles, as these appear on the market. This paper examines the factors likely to influence the demand for lower emission and zero emission vehicles. Using a discrete choice experiment, suburban driver commuters choose between three types of vehicle, one conventional, one fuel-efficient and one electric. Each is characterized by varying vehicle cost and performance measures, range and refueling rates, and commuting costs and times. The latter are manipulated to determine how their use as economic instruments might influence vehicle choice. All cost and time variables are expressed as ratios of the respondent’s current situation. Parameters of a multinomial discrete choice model are used in a choice simulator to estimate the average choice probability of each type of vehicle under different scenarios reflecting possible future relative vehicle prices and performance levels as well as differential commuting costs and times based on policies aimed at encouraging the purchase of cleaner vehicles. The evidence is that the latter economic instruments will have modest effects on vehicle choice. By contrast there would be a large shift of demand to cleaner and zero-emission vehicles provided their cost and performance came within an acceptable range of conventional vehicles.     

A methodology for classification by priority for action: Selecting road stretches for network noise action plans

Road traffic noise is an element of outstanding importance within the overall context of environmental impact. This problem must be technically addressed from an efficient viewpoint, and solutions or alternatives should be considered by means of appropriate and consolidated procedures.Up to now, there is no regulated guideline for establishing well-founded priorities when dealing with the diverse road stretches included in the corresponding Action Plans against noise under the Environmental Noise Directive (2002/49/EC). To this end, the present study proposes a methodology to sort, by priority, road stretches identified by their noise problems and therefore requiring appropriate action. The methodology is based on the so-called “road stretch priority index” (henceforth referred to as RSPI). This index involves a number of variables (called “road stretch priority variables”) that are weighted according to their influence on the road traffic noise problem. Thus, the RSPI makes it possible to prioritize different stretches of the Action Plan. To illustrate the application of the proposed methodology, this paper also describes a real case entailing a difficult choice, applying the proposed methodology to a review of the Action Plan against Noise 2008–2012 in the province of Almería, for the road network of the regional government of Andalusia, Spain.     

Review of GPS Travel Survey and GPS Data-Processing Methods

Abstract

Global positioning system (GPS) devices have been utilised in travel surveys since the late 1990s. Because GPS devices are very accurate at recording time and positional characteristics of travel, they can correct the trip-misreporting issue resulting from self-reports of travel and improve the accuracy of travel data. Although the initial idea of using GPS surveys in transport data collection was just to replace paper-based travel diaries, GPS surveys currently are being applied in a number of transport fields. Several general reviews have been done about GPS surveys in the literature review sections in some papers, but a detailed systematic review from GPS data collection to the whole procedure of GPS data processing has not been undertaken. This paper comprehensively reviews the development of GPS surveys and their applications, and GPS data processing. Different from most reviews in GPS research, this paper provides a detailed and systematic comparison between different methods from trip identification to mode and purpose detection, introduces the methods that researchers and planners are currently using, and discusses the pros and cons of those methods. Based on this review, researchers can choose appropriate methods and endeavour to improve them.     

Incentivizing alternative fuel vehicles: the influence of transport policies,attitudes and perceptions

This paper aims to evaluate the influence of policies, attitudes and perceptions when incentivizing alternative fuel vehicles. The impact of possible policies such as gasoline taxes increases, purchase price subsidies, tax exemptions, and increases in fuel recharging station availability for alternative fuelled vehicles is evaluated using hybrid choice models. The models also allow assessing the sensitivity of latent variables (i.e., attitudes and perceptions) in the car purchase behaviour. The models are estimated using data from a stated choice survey collected in five Colombian cities. The latent variables are obtained from the rating of statements related to the transport system, environmental concern, vehicle preferences, and technology. The modelling approach includes regression between latent variables. Results show that environmental concern and the support for green transport policies have a positive influence on the intention to purchase alternative fuel vehicles. Meanwhile, people who reveal to be car-dependent prefer to buy standard fuelled vehicles. The analysis among cities shows similar trends in individual behaviour, although there are differences in attribute sensitivities. The policy scenario analysis revealed high sensitivity to capital cost and the need for extensive investments in refuelling stations for alternative fuel vehicles to become attractive. Nevertheless, all policies should not only be directed at infrastructure and vehicles but also be focused on user awareness and acceptance of the alternative fuel vehicles. The analysis suggests that in an environmentally conscious market, people prefer alternative fuels. However, if the transport policies support private transport, the market shares of alternative fuel vehicles will decrease.     

Estimating link travel time functions for heterogeneous traffic flows on freeways

Oversized vehicles, such as trucks, significantly contribute to traffic delays on freeways. Heterogeneous traffic populations, that is, those consisting of multiple vehicles types, can exhibit more complicated travel behaviors in the operating speed and performance, depending on the traffic volume as well as the proportions of vehicle types. In order to estimate the component travel time functions for heterogeneous traffic flows on a freeway, this study develops a microscopic traffic‐simulation based four‐step method. A piecewise continuous function is proposed for each vehicle type and its parameters are estimated using the traffic data generated by a microscopic traffic simulation model. The illustrated experiments based on VISSIM model indicate that (i) in addition to traffic volume, traffic composition has significant influence on the travel time of vehicles and (ii) the respective estimations for travel time of heterogeneous flows could greatly improve their estimation accuracy. Copyright © 2016 John Wiley & Sons, Ltd.     

Estimating daily vehicle usage distributions and the implications for limited-range vehicles

Understanding the potential market for limited-range vehicles is important to planning research and development programs for electric and hybrid vehicles and for gaseous-fueled vehicles as well. Studies of consumer preferences and perceptions have shown vehicle range to be a very important vehicle attribute. Studies of household vehicle use, on the other hand, have suggested that the range requirements most households place on vehicles are quite modest. The latter, however, have been severely limited by the absence of longitudinal data on the usage of individual vehicles. Instead, they have relied on single-day surveys on many vehicles, an inappropriate data source. This study develops a method for estimating daily travel distributions for individual vehicles and applies it to a recent longitudinal survey of miles and days between refuelings for over 2000 vehicles. Every vehicle in the sample has at least 30 consecutive refueling intervals. A variety of measures of “range requirement” are defined and calculated. The results confirm the existence of a substantial potential market (20–50% of all household vehicles) for vehicles with ranges on the order of 100 miles. Future research using these data and this method could describe the nature of vehicles with limited-range needs and the households which own them.     

Preferences of travellers for using automated vehicles as last mile public transport of multimodal train trips

In the recent years many developments took place regarding automated vehicles (AVs) technology. It is however unknown to which extent the share of the existing transport modes will change as result of AVs introduction as another public transport option. This study is the first where detailed traveller preferences for AVs are explored and compared to existing modes. Its main objective is to position AVs in the transportation market and understand the sensitivity of travellers towards some of their attributes, focusing particularly on the use of these vehicles as egress mode of train trips. Because fully-automated vehicles are not yet a reality and they entail a potentially high disruptive way on how we use automobiles today, we apply a stated preference experiment where the role of attitudes in perceiving the utility of AVs is particularly explored in addition to the classical instrumental variables and several socio-economic variables. The estimated discrete choice model shows that first class train travellers on average prefer the use of AVs as egress mode, compared to the use of bicycle or bus/tram/metro as egress. We therefore conclude that AVs as last mile transport between the train station and the final destination have most potential for first class train travellers. Results show that in-vehicle time in AVs is experienced more negatively than in-vehicle time in manually driven cars. This suggests that travellers do not perceive the theoretical advantage of being able to perform other tasks during the trip in an automated vehicle, at least not yet. Results also show that travellers’ attitudes regarding trust and sustainability of AVs are playing an important role in AVs attractiveness, which leads to uncertainty on how people will react when AVs are introduced in practice. We therefore state the importance of paying sufficient attention to these psychological factors, next to classic instrumental attributes like travel time and costs, before and during the implementation process of AVs as a public transport alternative. We recommend the extension of this research to revealed preference studies, thereby using the results of field studies.     

A review of consumer preferences of and interactions with electric vehicle charging infrastructure

This paper presents a literature review of studies that investigate infrastructure needs to support the market introduction of plug-in electric vehicles (PEVs). It focuses on literature relating to consumer preferences for charging infrastructure, and how consumers interact with and use this infrastructure. This includes studies that use questionnaire surveys, interviews, modelling, GPS data from vehicles, and data from electric vehicle charging equipment. These studies indicate that the most important location for PEV charging is at home, followed by work, and then public locations. Studies have found that more effort is needed to ensure consumers have easy access to PEV charging and that charging at home, work, or public locations should not be free of cost. Research indicates that PEV charging will not impact electricity grids on the short term, however charging may need to be managed when the vehicles are deployed in greater numbers. In some areas of study the literature is not sufficiently mature to draw any conclusions from. More research is especially needed to determine how much infrastructure is needed to support the roll out of PEVs. This paper ends with policy implications and suggests avenues of future research.     

Transport studies research in U.K. universities

British universities have entered a period of crisis. The outward manifestation of the current malady has appeared as a general cut-back in university spending. Until two or three years ago, most universities looked forward to a modest growth in activity. This has now been changed and the expectations of growth have been replaced by the reality of consolidation and modest decline. However, the universities are not alone in their dilemma. The general downturn in economic prosperity has left few institutions unscathed. Most universities, both in Britain and abroad, have therefore been forced to review their expectations and their ongoing commitments in teaching and research. The review of university activity goes much deeper than the immediate problems of finance. The current soul-searching has been sparked off by the crisis of finance, but has roots which go much deeper and touch on the very fundamentals of university education itself. In a sense, one is witnessing a belated form of public accountability: what is the purpose of a university; should its subjects be demonstrably relevant (both in themselves, as well as in their capacity to prepare students for a career); should universities engage in research and, if so, should it complement their teaching functions or be additional to it? These, and many other issues, are currently being discussed, and it is specifically with reference to their role in the field of transport research that this paper is addressed.     

Travel-based multitasking: review of the empirical evidence

This paper reviews 58 studies with empirical evidence on travel-based multitasking, identifies gaps in terms of data collection methods and provides a comprehensive review of findings about the significance of variables with an impact on the prevalence and type of multitasking. We identified the limitations of quantitative or qualitative surveys and advocate a mixed methods approach to provide an in-depth understanding of travel-based multitasking. We revealed that cross-country comparisons are missing due to the lack of empirical evidence outside the developed countries. While there are indications of increasing multitasking with mobile devices, we found only two longitudinal surveys that provide evidence. We call for a standardisation of definitions of multitasking activities to enable more longitudinal research. We identified 75 variables that were tested for impact on travel-based multitasking in previous research, of which 60 were found to be significant. Sufficient evidence (i.e. minimum three papers), however, only exists for age, gender, trip duration, travel mode, trip purpose, time of the day and day of the week of the trip and the presence of a travel companion. Therefore, more research is suggested to determine the influence of attitude, comfort, availability of equipment, time use and spatial attributes on the type and prevalence of travel-based multitasking.     

Effect of road width and traffic volume on vehicular interactions in heterogeneous traffic

Highway traffic flow phenomena involve several complex and stochastic variables with high interdependencies. The variations in roadway, traffic and environmental factors influence the traffic flow quality significantly. Capacity analysis of road sections under different traffic and geometric conditions need to quantify the vehicles of widely varying characteristics to a common and universally acceptable unit. Passenger car unit (PCU) is the universally adopted unit of traffic volume, keeping the passenger car as the ‘standard vehicle’ with reference to its static and dynamic characteristics; other vehicles are expressed to its equivalent number in terms of PCUs. The studies carried out in this aspect represent the dynamic nature of impedance caused by a vehicle while moving through a traffic stream. The PCU values recommended by the Highway Capacity Manual are widely applied in many countries; however, their applicability is highly under debate because of the variations in prevailing local traffic conditions. There are several factors that influence the PCU values such as traffic, roadway, vehicle, environmental and control conditions, etc. Apart from vehicular characteristics, the other two major factors that influence the PCU of vehicles are the following: (i) road width and (ii) traffic volume. In this study, estimation of PCU values for the different types of vehicles of a highly heterogeneous traffic on 7.5‐ and 11.0‐m‐wide roads, using micro‐simulation technique, has been dealt with. It has been found that the PCU value of a vehicle type varies significantly with variation in road width and traffic volume. The results of the study indicate that the PCU values are significantly influenced by the said two factors. Copyright © 2012 John Wiley & Sons, Ltd.     

Optimal speed advisory for connected vehicles in arterial roads and the impact on mixed traffic

Connected Vehicles (CV) equipped with a Speed Advisory System (SAS) can obtain and utilize upcoming traffic signal information to manage their speed in advance, lower fuel consumption, and improve ride comfort by reducing idling at red lights. In this paper, a SAS for pre-timed traffic signals is proposed and the fuel minimal driving strategy is obtained as an analytical solution to a fuel consumption minimization problem. We show that the minimal fuel driving strategy may go against intuition of some people; in that it alternates between periods of maximum acceleration, engine shut down, and sometimes constant speed, known in optimal control as bang-singular-bang control. After presenting this analytical solution to the fuel minimization problem, we employ a sub-optimal solution such that drivability is not sacrificed and show fuel economy still improves significantly. Moreover this paper evaluates the influence of vehicles with SAS on the entire arterial traffic in micro-simulations. The results show that SAS-equipped vehicles not only improve their own fuel economy, but also benefit other conventional vehicles and the fleet fuel consumption decreases with the increment of percentage of SAS-equipped vehicles. We show that this improvement in fuel economy is achieved with a little compromise in average traffic flow and travel time.