Implementation of Bus Rapid Transit in Copenhagen: A Mesoscopic Model Approach

Bus Rapid Transit (BRT) has shown to be an efficient and cost-effective mode of public transport, and has gained popularity in many cities around the world. To optimise the operations and infrastructure it is advantageous to deploy transport models. However, microscopic models are very inefficient for large scale corridors due to the vast amount of data and resources required. Hence, it is relevant to investigate how to model and evaluate BRT efficiently. In this paper the effects of implementing BRT in Copenhagen is discussed including how to evaluate and model bus operations. For this purpose, a mesoscopic simulation model is developed. In the model bus operations are modelled on a microscopic level whereas the interactions with other traffic are modelled macroscopically. This makes it possible to model high-frequency bus services such as BRT lines in more details without the time consumption of micro-simulation models. The developed model is capable of modelling bus operations in terms of travel time and reliability including important mode-specific issues such as bus bunching. The model is applied to a BRT project proposal with different combinations of BRT elements. The model results show that infrastructure upgrades (busways and enhanced stations) ensure a reduction to travel time whereas no improvements to reliability occur. Upgrades to technology and service planning (pre-paid fare collection, boarding and alighting from all doors, special BRT vehicles, ITS, and active bus control) ensure an increase in service reliability whereas only small reductions to travel time are observed. By combining all BRT elements it is possible to obtain synergies where the improved reliability due to planning and technology elements makes it possible to utilise the infrastructure optimally. Hence, it is possible to increase commercial speed from 14.8 to 19.9 km/h and service reliability in terms of headway time regularity from 46% to 84% aggregated on both directions for the morning peak period making the implementation of BRT feasible from a pure financial point of view

Quantifying road traffic emissions embedded in a multi-objective traffic assignment model

In a road network, drivers typically seek to minimize their own travel time, often affecting system-wide performance. With the increasing environmental awareness, for an efficient traffic assignment (TA), besides concerns with travel times, traffic managers should not neglect the system-wide level of both global and local pollutant emissions. Measuring road traffic emissions can be costly and different models based on vehicle-specific parameters with many input variables have been suggested in the literature. This paper proposes a simple way to quantifying carbon dioxide (CO2) and nitrogen oxides (NOX) emissions with only average speed as input variable and presents a multi-objective TA approach that seeks to minimize system-wide travel time, distance travelled (associated with fuel consumption) and global and local pollutant emissions. A real-world case study on an intercity corridor with many alternative routes between two zones is presented. Experiments considering TA based on travel time, and on time, distance travelled, and pollutant emissions are reported. Results highlight that system optimal distribution based on the suggested multi-objective TA based on three components yields savings in terms of distance travelled (2.6%) and emissions (1.3% for CO2 and 1.1% for NOX), but penalizes travel time 3%, which is translated in an increase of 20sec per vehicle, when compared to the solution only focused on minimizing travel time. The developed methodology is a suitable tool for traffic analysts to predict vehicle system-wide travel time, distance travelled and pollutant emissions with few vehicle information but with a reasonable detail for a specific traffic flow on a given road network, to support analyses for sustainable transport policies and may be used, for instance, as an environmental impact component of a pricing scheme, traffic signal control strategies based on emissions reduction, or to minimize congestion by giving prior information to drivers on the specific routes to be chosen.publishe

A Review of Models of Urban Traffic Networks (With Particular reference to the Requirements for Modelling Dynamic Route Guidance Systems)

This paper reviews a number of existing models of urban traffic networks developed in Europe and North America. The primary intention is to evaluate the various models with regard to their suitability to simulate traffic conditions and driver behavior when a dynamic route guidance system is in operation

Impact of traffic management on black carbon emissions: a microsimulation study

This paper investigates the effectiveness of traffic management tools, includ- ing traffic signal control and en-route navigation provided by variable message signs (VMS), in reducing traffic congestion and associated emissions of CO2, NOx, and black carbon. The latter is among the most significant contributors of climate change, and is associated with many serious health problems. This study combines traffic microsimulation (S-Paramics) with emission modeling (AIRE) to simulate and predict the impacts of different traffic management measures on a number traffic and environmental Key Performance Indicators (KPIs) assessed at different spatial levels. Simulation results for a real road network located in West Glasgow suggest that these traffic management tools can bring a reduction in travel delay and BC emission respectively by up to 6 % and 3 % network wide. The improvement at local levels such as junctions or corridors can be more significant. However, our results also show that the potential benefits of such interventions are strongly dependent on a number of factors, including dynamic demand profile, VMS compliance rate, and fleet composition. Extensive discussion based on the simulation results as well as managerial insights are provided to support traffic network operation and control with environmental goals. The study described by this paper was conducted under the support of the FP7-funded CARBOTRAF project

Analysing improvements to on-street public transport systems: a mesoscopic model approach

Light rail transit and bus rapid transit have shown to be efficient and cost-effective in improving public transport systems in cities around the world. As these systems comprise various elements, which can be tailored to any given setting, e.g. pre-board fare-collection, holding strategies and other advanced public transport systems (APTS), the attractiveness of such systems depends heavily on their implementation. In the early planning stage it is advantageous to deploy simple and transparent models to evaluate possible ways of implementation. For this purpose, the present study develops a mesoscopic model which makes it possible to evaluate public transport operations in details, including dwell times, intelligent traffic signal timings and holding strategies while modelling impacts from other traffic using statistical distributional data thereby ensuring simplicity in use and fast computational times. This makes it appropriate for analysing the impacts of improvements to public transport operations, individually or in combination, in early planning stages. The paper presents a joint measure of reliability for such evaluations based on passengers’ perceived travel time by considering headway time regularity and running time variability, i.e. taking into account waiting time and in-vehicle time. The approach was applied on a case study by assessing the effects of implementing segregated infrastructure and APTS elements, individually and in combination. The results showed that the reliability of on-street public transport operations mainly depends on APTS elements, and especially holding strategies, whereas pure infrastructure improvements induced travel time reductions. The results further suggested that synergy effects can be obtained by planning on-street public transport coherently in terms of reduced travel times and increased reliability

Present and future methodology for the implementation of decision support systems for traffic management

Real-time predictions are an indispensable requirement for traffic management in order to be able to evaluate the effects of different available strategies or policies. The combination of predicting the state of the network and the evaluation of different traffic management strategies in the short term future allows system managers to anticipate the effects of traffic control strategies ahead of time in order to mitigate the effect of congestion. This paper presents the current framework of decision support systems for traffic management based on short and medium-term predictions and includes some reflections on their likely evolution, based on current scientific research and the evolution of the availability of new types of data and their associated methodologies

Geospatial Framework for the Use of Natural Resource Extraction in Public Private Partnerships

Resources for the maintenance and expansion of existing highway infrastructure are scarce. Public Private Partnerships (PPP) are feasible solutions to the concern of lagging investment. PPP are increasingly used for the procurement of services and goods, because of their flexibility and ability to channel private resources. This research addresses the possible implementation of a barter approach in Public Private Partnerships (PPP), which includes natural resources for trade model to offset costs.;Federal law permits the extraction of coal when it is a byproduct of the construction process, coal which under normal circumstances would not be economically feasible to extract. West Virginia law allows PPP to extract coal by surface mining when they develop road beads for new highways. There is no exchange of funds between the coal company and the West Virginia Department of Transportation; the benefits are derived entirely from the construction cost savings for roadbed construction.;This dissertation develops a geospatial method to quantify the availability of natural resources along predetermined roadway alignments. The methodology is divided in three phases: Macroscopic (Level I), Mesoscopic (Level II) and Microscopic (Level III), for the King Coal Highway. The process considers laws and industry best practices in the calculation. The research outcome suggests that there are segments of the road with enough, as well as segments of the road without enough coal