Distance and time based road pricing trial in Dublin

The objective of the work was to evaluate the potential user response to distance and time based road pricing of a sample of individuals drawn randomly from a group of volunteers in Dublin. The road use pricing charge levels were selected to match the marginal external costs of car transport i.e. those costs not currently paid by the car user. Such costs include marginal external costs of congestion, air pollution and noise. The project formed part of the EU DGXVII EUROPRICE project where one of the objectives was to evaluate the impact of road use pricing on private transport demand. Estimates of the marginal external costs of car travel had been previously made for Dublin in an EU DGVII project entitled TRENEN II STRAN and the results were used to select the road pricing charges in the trial. The distance travelled and travel time of a particular individual's work trip were noted. Charges per unit distance and time were applied so that the individual would incur a total charge for their average peak period work trip of 6.4 euro; the average marginal external cost of a peak period trip in Dublin, as estimated by the TRENEN model. Although the sample of individuals was relatively small, the indications from the results are worthy of note and further investigation on a larger sample. A significant reduction in the number of peak period trips was evident, of the order of 22%, resulting from trip suppression and transfer to other modes. This revised version was published online in June 2006 with corrections to the Cover Date.     

Impact of road gradient on energy consumption of electric vehicles

We investigate the impact of road gradient on the electricity consumption of electric vehicles (EVs) by combining long-term GPS tracking data with digital elevation map (DEM) data for roads in Aichi prefecture, Japan. Eight regression models are constructed and analysed to compare the differences between linear and logarithmic forms of trip energy consumption, differences between considering the road gradient or not, and differences between considering the fixed effects of EVs or not. By categorizing gradients and assigning a percentage of the trip distance to each category, a significantly better model of electricity consumption can be achieved. The results of this study are a novel contribution toward understanding the challenges and benefits associated with downgrade braking on energy regeneration.     

Analysis of the optimal length of road expansion – A case study of the Taipei metropolitan area

This study explores the optimal investment in the length of an expanded section of road to mitigate the congestion on a transportation corridor. It is assumed that one end of the road is in the central business district (CBD) and that the households are uniformly distributed along the road. Each individual makes trips from his/her residence to the CBD. Trip demand is elastic and depends on the cost of the trip (including congestion costs). During the first stage, the government determines the length of the expanded section given the width of that section. In the second stage, road users determine their trip demands by taking into consideration the trip cost function. In the process of solving this problem, the equilibrium traffic volume is first solved using differential equations. The optimal length of the expanded section is then solved by maximizing the social welfare. The analysis is then applied to the case of the Tucheng city – Banciao city – Taipei CBD corridor in the Taipei metropolitan area. The scheme of road expansion without tolling performs closely to the first-best scheme for the case of a high potential demand. This study’s approach can serve as valuable reference for city planners engaged in road planning in a transportation corridor between the CBD and satellite cities in a metropolitan area.     

Simulation of electric vehicle driver behaviour in road transport and electric power networks

The integration of electric vehicles (EVs) will affect both electricity and transport systems and research is needed on finding possible ways to make a smooth transition to the electrification of the road transport. To fully understand the EV integration consequences, the behaviour of the EV drivers and its impact on these two systems should be studied. This paper describes an integrated simulation-based approach, modelling the EV and its interactions in both road transport and electric power systems. The main components of both systems have been considered, and the EV driver behaviour was modelled using a multi-agent simulation platform. Considering a fleet of 1000 EV agents, two behavioural profiles were studied (Unaware/Aware) to model EV driver behaviour. The two behavioural profiles represent the EV driver in different stages of EV adoption starting with Unaware EV drivers when the public acceptance of EVs is limited, and developing to Aware EV drivers as the electrification of road transport is promoted in an overall context. The EV agents were modelled to follow a realistic activity-based trip pattern, and the impact of EV driver behaviour was simulated on a road transport and electricity grid. It was found that the EV agents’ behaviour has direct and indirect impact on both the road transport network and the electricity grid, affecting the traffic of the roads, the stress of the distribution network and the utilization of the charging infrastructure.     

Maximum car ownership under constraints of road capacity and parking space

This paper presents a model for determining the maximum number of cars by zones in view of the capacity of the road network and the number of parking spaces available. In other words, the proposed model is to examine whether existing road network and parking supply is capable of accommodating future zonal car ownership growth (or the reserve capacity in each zone); i.e. the potential maximum zonal car ownership growth that generates the road traffic within the network capacity and parking space constraints. In the proposed model, the vehicular trip production and attraction are dependent on the car ownership, available parking spaces and the accessibility measures by traffic zones. The model is formulated as a bi-level programming problem. The lower-level problem is an equilibrium trip distribution/assignment problem, while the upper-level problem is to maximize the sum of zonal car ownership by considering travellers’ route and destination choice behaviour and satisfying the network capacity and parking space constraints. A sensitivity analysis based heuristic algorithm is developed to solve the proposed bi-level car ownership problem and is illustrated with a numerical example.     

The environmental impact caused by road access to Timanfaya Natural Park on Lanzarote Island

This paper evaluates the impact of road transport usage in accessing the Timanfaya Natural Park on Lanzarote Island, and its implications for sustainable tourism development. This evaluation is based on projections of the trip matrix estimated for Lanzarote Island. First, we estimate the global environmental impact, or the contribution of the road transport required for accessing the natural park to climate change. The methodology employed is the Ecological Footprint indicator. The study analyses how to manage the impact of road access to tourist activities through a price intervention; i.e. fuel tax. Redesigning the public transport supply is proposed as an alternative to the pricing policy. Finally, conclusions are drawn.     

Driver requirements and road traffic informatics

Initially the driver's role as a link in the driver-vehicle-road-traffic control-chain is discussed in a historical perspective. The gradual changes and the advantages and problems arising from these changes are discussed from behavioural point of view.Then the driver tasks are analyzed. A separation is made between trip planning, navigation, road following, traffic interaction, rule compliance, other than traffic tasks, car handling and speed choice. The relations between and the weights of these subtasks are discussed. Some existing driver behaviour models are reviewed in relation to the above mentioned tasks.Finally an effort is made based on the analyses of driver tasks and driver models to specify some general and some more specific potential advantages and problems with expected future RTI-systems.     

A systematic analysis of multimodal transport systems with road space distribution and responsive bus service

A smart design of transport systems involves efficient use and allocation of the limited urban road capacity in the multimodal environment. This paper intends to understand the system-wide effect of dividing the road space to the private and public transport modes and how the public transport service provider responds to the space changes. To this end, the bimodal dynamic user equilibrium is formulated for separated road space. The Macroscopic Fundamental Diagram (MFD) model is employed to depict the dynamics of the automobile traffic for its state-dependent feature, its inclusion of hypercongestion, and its advantage of capturing network topology. The delay of a bus trip depends on the running speed which is in turn affected by bus lane capacity and ridership. Within the proposed bimodal framework, the steady-state equilibrium traffic characteristics and the optimal bus fare and service frequency are analytically derived. The counter-intuitive properties of traffic condition, modal split, and behavior of bus operator in the hypercongestion are identified. To understand the interaction between the transport authority (for system benefit maximization) and the bus operator (for its own benefit maximization), we examine how the bus operator responds to space changes and how the system benefit is influenced with the road space allocation. With responsive bus service, the condition, under which expanding bus lane capacity is beneficial to the system as a whole, has been analytically established. Then the model is applied to the dynamic framework where the space allocation changes with varying demand and demand-responsive bus service. We compare the optimal bus services under different economic objectives, evaluate the system performance of the bimodal network, and explore the dynamic space allocation strategy for the sake of social welfare maximization.     

Speed,travel time and delay for intersections and road segments in the Montreal network using cyclist Smartphone GPS data

Very little is known about cyclist speeds and delays at the disaggregate level of each road segment and intersection in an entire city network. Speeds and delays serve as vital information for planning, navigation and routing purposes including how they differ for different times of the day and across road and bicycle facility types, after controlling for other factors. In this work, we explore the use of recent GPS cyclist trip data, from the Mon RésoVélo Smartphone application, to identify different performance measures such as travel time, speed and delay at the level of the entire network of roads and intersections on the island of Montreal. Also, a linear regression model is formulated to identify the geometric design and built environment characteristics affecting cyclist speeds on road segments. Among other results, on average, segment speeds are greater along arterials than on local streets and greater along segments with bicycle infrastructure than those without. Incorporating different measures of cyclist personality in the models revealed that the following characteristics all affect cyclist speeds along segments, each cyclist’s average speed on uphill, downhill and level segments as well as geometric design and built environment characteristics. The model results also identify that the factors that increase cyclist speeds along segments include, segments which have cyclists biking for work or school related purposes, segments used during morning peak and segments which do not have signalized intersections at either end.     

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.     

Estimating the willingness to pay and value of risk reduction for car occupants in the road environment

In recent years there has been a re-focus on the valuation of a statistical life from the ex post or human capital method to an ex ante willingness to pay (WTP) approach. This is in part a recognition that we may have been undervaluing the cost of fatalities and injuries to society associated with crashes, but also a strong belief in the need to focus on establishing the amount, ex ante, that individuals are willing to pay to reduce the risk of exposure to circumstances that might lead to death or degree of injury on the road network. This study has developed a framework in which to identify the degree of preference heterogeneity in willingness to pay by individuals who are drivers or passengers in cars to avoid being killed or injured. A stated choice experiment approach is developed. The empirical setting is a choice of route for a particular trip that a sample of individuals periodically undertakes in Australia. The particular trip is described in enough detail to provide the respondent with a familiar market environment, providing all the relevant background information required for making a decision. Mixed logit models are estimated to obtain the marginal (dis)utilities associated with each influence on the choice amongst the attribute packages offered in the stated choice scenarios. These estimates are used to obtain the WTP distributions for fatality and injury avoidance, which are then aggregated to obtain estimates of the value of risk reduction (VRR), of which the fatality class is also known as the value of a statistical life (VSL).     

Travel time estimation for urban road networks using low frequency probe vehicle data

The paper presents a statistical model for urban road network travel time estimation using vehicle trajectories obtained from low frequency GPS probes as observations, where the vehicles typically cover multiple network links between reports. The network model separates trip travel times into link travel times and intersection delays and allows correlation between travel times on different network links based on a spatial moving average (SMA) structure. The observation model presents a way to estimate the parameters of the network model, including the correlation structure, through low frequency sampling of vehicle traces. Link-specific effects are combined with link attributes (speed limit, functional class, etc.) and trip conditions (day of week, season, weather, etc.) as explanatory variables. The approach captures the underlying factors behind spatial and temporal variations in speeds, which is useful for traffic management, planning and forecasting. The model is estimated using maximum likelihood. The model is applied in a case study for the network of Stockholm, Sweden. Link attributes and trip conditions (including recent snowfall) have significant effects on travel times and there is significant positive correlation between segments. The case study highlights the potential of using sparse probe vehicle data for monitoring the performance of the urban transport system.     

Evaluating road safety audit procedures: some questions and a new method of study

This article discusses the current views on the application of road safety audits (RSAs) as a tool for the improvement of road safety and proposes a new method of study for detailed evaluation of some features that can influence their effectiveness. This is demonstrated in the practical setting of RSAs applied to existing road reviews or inspections. Starting from a review of published sources on RSAs in different countries, a set of questions has been identified and a case study undertaken on the impact of alternative RSA procedures on its overall effectiveness. RSA effectiveness is measured both as agreement with a safety expert assessment and to an accident-based study. The main features analyzed in the case study include the type of observer used for data collection and the type of checklist used as a guide to field work. Based on an exploratory study, the performance of RSA application is evaluated using weighted indices of concordance and disagreement, and the rating of detection or omission for the observations gathered in the accident diagnosis of the safety problems at the intersection studied, supplemented by a statistical analysis of the influence of selected covariates on these scores. The main results of the case study can be summarized as clear support to team work for field observation and also to employing less-experienced personnel for field observation. The study also stresses the need for procedures/criteria for priority setting. These conclusions are useful for the selection of alternative RSA procedures in agencies responsible for promoting or enforcing RSA and in professional teams carrying out RSA tasks. Several features deserving further study are also identified.     

Structural equation approach to investigate trip-chaining and mode choice relationships in the context of developing countries

This paper investigates empirical relationships between trip chain type and mode class choice for developing countries. To formulate these two sets of decisions, four empirical models are developed using structural equation modeling (SEM). Those models are calibrated using one-month travel diary data collected in Dhaka city. SEM correlates the observed variables and identifies their relationship with trip-chaining type utility and mode class choice utility. The fitted models are selected based on statistical results and similarity with the real-life situation. Direct relationships between trip-chaining and mode choice utilities are found insignificant. However, several socio-demographic factors influence both simultaneously. Consequently, it is essential to consider mode class choice concurrently for modeling trip chains. This study also investigates the influencing factors for work-based and non-work-based trip chains separately and effects of road users’ heterogeneity. The research results can be utilized to perceive trip chain-mode choice patterns for developing countries.     

Study on road section environmental traffic capacity model and algorithm under double constraints

The coordinated development of city traffic and environment is a key research content in traffic field in twenty-first Century. Among them, road section environmental traffic capacity analysis is one of the important research issues. It can provide solid theoretical basis and reliable data support for road network traffic optimization control, road traffic pollution control and city traffic structure optimization. This paper analyzed main factors which impacted environmental traffic capacity from two aspects, including road capacity constraint conditions and road traffic pollution control constraint conditions. Then, road section environmental traffic capacity optimization model was established, and method of improved augmented Lagrange function was used to solve the model. Case study showed that, (1) The environmental traffic capacity optimal model and methodology were effective; (2) In order to ensure road section environmental traffic capacity greater than (or equal to) road capacity, some measures could be taken including adjusting motor vehicle type proportion as well as improving emission characteristics of motor vehicles exhausting pollutants.     

Capturing value of reliability through road pricing in congested traffic under uncertainty

Empirical studies showed that travel time reliability, usually measured by travel time variance, is strongly correlated with travel time itself. Travel time is highly volatile when the demand approaches or exceeds the capacity. Travel time variability is associated with the level of congestion, and could represent additional costs for travelers who prefer punctual arrivals. Although many studies propose to use road pricing as a tool to capture the value of travel time (VOT) savings and to induce better road usage patterns, the role of the value of reliability (VOR) in designing road pricing schemes has rarely been studied. By using road pricing as a tool to spread out the peak demand, traffic management agencies could improve the utility of travelers who prefer punctual arrivals under traffic congestion and stochastic network conditions. Therefore, we could capture the value of travel time reliability using road pricing, which is rarely discussed in the literature. To quantify the value of travel time reliability (or reliability improvement), we need to integrate trip scheduling, endogenous traffic congestion, travel time uncertainty, and pricing strategies in one modeling framework. This paper developed such a model to capture the impact of pricing on various costs components that affect travel choices, and the role of travel time reliability in shaping departure patterns, queuing process, and the choice of optimal pricing. The model also shows the benefits of improving travel time reliability in various ways. Findings from this paper could help to expand the scope of road pricing, and to develop more comprehensive travel demand management schemes.     

Wooded area,forest road-killed animals: Intensity and seasonal differences of road mortality on a small,newly upgraded road in western Romania

The roads are one of the most obvious expressions of modern society, being considered vital for economical growth. Nevertheless, roads have a very strong negative impact upon environment, manifested, among others, by road mortality. In Romania numerous minor roads are currently upgraded and asphalted. In the year 2016, on a road of this kind, in a wooded mountain area, we recorded 1628 road killed animals belonging to 48 taxons. The majority were forest and wet areas animals (earthworms, snails, amphibians, etc), characteristic for the road’s vicinity. Flying or dry areas animals were fewer. The road crosses the forest and the wet areas animals’ habitats. Now, they are certain victims on the road, because its recent upgrade had increased the cars’ speed. Road mortality differed between periods and according to the road surroundings aspect. The highest road mortality intensity was registered at the end of the spring. It has dropped in the summer and then rose again in the autumn, but just moderately. The animals were affected according to their life cycle and ecological demands. On this minor road surrounded by relatively uniform wooded habitats, the road mortality differences were determined in the first place by the demandings and life cycle of the victims, which were affected by meteorological conditions. This studied road is a proof of how forest native animals are exposed once their habitat is crossed by a road.     

Using smartphones as a very low-cost tool for road inventories

Road inventories are a key component in the planning of road networks as they allow for efficient management and a better return on the investment. Current techniques for carrying out road inventories are expensive and entail long planning processes and data postprocessing. Furthermore, these inventories are only useful to those parties interested in designing and building road networks. This study presents a new method for create road inventories based on the use of the latest generation cellular phones, also called smartphones. This paper describes the use of several mobile apps developed for this project that were implemented during the different stages of road inventory process. The results indicate that the data processing speed, its low cost, and the ease of implementation from any type of vehicle validate the proposed procedure as an invaluable tool (1) to do inventories of all types of road networks that are not accessible to cars; (2) to manage the routine maintenance of small road networks; and (3) as a basis for future research projects on road design and outline.     

Bayesian network-based formulation and analysis for toll road utilization supported by traffic information provision

Congestion pricing has been proposed and investigated as an effective means of optimizing traffic assignment, alleviating congestion, and enhancing traffic operation efficiencies. Meanwhile, advanced traffic information dissemination systems, such as Advanced Traveler Information System (ATIS), have been developed and deployed to provide real-time, accurate, and complete network-wide traffic information to facilitate travelers’ trip plans and routing selections. Recent advances in ATIS technologies, especially telecommunication technology, allow dynamic, personalized, and multimodal traffic information to be disseminated and impact travelers’ choices of departure times, alternative routes, and travel modes in the context of congestion pricing. However, few studies were conducted to determine the impact of traffic information dissemination on toll road utilizations. In this study, the effects of the provisions of traffic information on toll road usage are investigated and analyzed based on a stated preference survey conducted in Texas. A Bayesian Network (BN)-based approach is developed to discover travelers’ opinions and preferences for toll road utilization supported by network-wide traffic information provisions. The probabilistic interdependencies among various attributes, including routing choice, departure time, traffic information dissemination mode, content, coverage, commuter demographic information, and travel patterns, are identified and their impacts on toll road usage are quantified. The results indicate that the BN model performs reasonably well in travelers’ preference classifications for toll road utilization and knowledge extraction. The BN Most Probable Explanation (MPE) measurement, probability inference and variable influence analysis results illustrate travelers using highway advisory radio and internet as their primary mode of receiving traffic information are more likely to comply with routing recommendations and use toll roads. Traffic information regarding congested roads, road hazard warnings, and accident locations is of great interest to travelers, who tend to acquire such information and use toll roads more frequently. Travel time formation for home-based trips can considerably enhance travelers’ preferences for toll road usage. Female travelers tend to seek traffic information and utilize toll roads more frequently. As expected, the information provided at both pre-trip and en-route stages can positively influence travelers’ preferences for toll road usage. The proposed methodology and research findings advance our previous study and provide insight into travelers’ behavioral tendencies concerning toll road utilization in support of traffic information dissemination.     

An econometric approach to the planning of road development in developing countries

The tools and techniques of econometrics are conventionally used in the estimation and testing of relationships between different economic variables, and their application features in the literature of transport economics.

This paper seeks to make use of econometrics in a wider field to solve a number of economic problems that crop up in investment decisions on road development in developing countries.

This study is divided into four sections with a brief conclusion. Section 1 deals with the problems that should be taken into account when taking investment decisions on road systems. In Section 2, an attempt is made to show how econometric tools can be applied in sorting out those problems. Section 3 highlights the limitations of the approach, and in Section 4, a case study is undertaken to verify the applicability of the model in reality.