Designing optimal urban transport strategies : the role of individual policy instruments and the impact of financial constraints

This paper presents a methodology for the design of optimal transport strategies and the case study results of the methodology for the City of Edinburgh, using the two multi-modal transport/land-use models MARS and TPM. First, a range of policy instruments are optimised in turn and their relative impacts explored. Second, optimisations with and without financial constraints are performed and compared. Although both models produce similar optimal policies, the relative contribution of the instruments differs between models as does the impact on outcome indicators. It is also shown that by careful design it is possible to identify a strategy which costs no more than the do-minimum but which can generate substantial additional benefits. The optimisation methodology is found to be robust, and is able to be used with different transport models, and with and without financial constraints

Modeling Weather Conditions Consequences on Road Trafficking Behaviors

We provide a model to understand how adverse weather conditions modify traffic flow dynamic. We first prove that the microscopic Free Flow Speed of the vehicles is changed and then provide a rule to model this change. For this, we consider a thresholded linear model, corresponding to an application of a MARS model to road trafficking. This model adapts itself locally to the whole road network and provides accurate unbiased forecasted speed using live or short term forecasted weather data information

Uncertainties in Forecasting: The Role of Strategic Modeling to Control Them

The growing concern about environmental depredations from transport activity at short-range and long-range horizon calls for policies aiming at reorientation of travel demand trends. However every transport policy is subject to risks, environmental or financial ones, and has often long-range effects. This explains the renewed interest in tools which allow detection of these risks and their consequences. There is however a methodological challenge in the elaboration of these simulation tools because we have to take into account many different uncertainties.This paper analyzes the uncertainties associated with transport forecasts using a strategic model recently developed for Lyon's conurbation. Different sources of error and uncertainly are tested and compared by means of the model. It is argued that a strategy of systematic exploration of uncertainly is the preferred way to cope with it and to detect long-term risks associated with transport policy.Travel modelling ; Strategic planning ; Urban area ; Uncertainty ; Forecasting

Short-term Traffic Flow Prediction Method in Bayesian Networks Based on Quantile Regression

With the popularization of intelligent transportation system and Internet of vehicles, the traffic flow data on the urban road network can be more easily obtained in large quantities. This provides data support for shortterm traffic flow prediction based on real-time data. Of all the challenges and difficulties faced in the research of short-term traffic flow prediction, this paper intends to address two: one is the difficulty of short-term traffic flow prediction caused by spatiotemporal correlation of traffic flow changes between upstream and downstream intersections; the other is the influence of deviation of traffic flow caused by abnormal conditions on short-term traffic flow prediction. This paper proposes a Bayesian network short-term traffic flow prediction method based on quantile regression. By this method the trouble caused by spatiotemporal correlation of traffic flow prediction could be effectively and efficiently solved. At the same time, the prediction of traffic flow change under abnormal conditions has higher accuracy

New horizons

The contribution of space exploration and space related research to the future of man and the accomplishments of the space program are assessed. Topics discussed include: the role of applications satellites in crop surveillance, land use surveys, weather forecasting, education, communications, and pollution monitoring; planetary studies which examine the origin and evolution of the solar system, including dynamic processes that bear directly on earth's environment; and fuel conservation and development of new energy sources

A review of system dynamics models applied in transportation

It is 20 years since Abbas and Bell [1994. “System Dynamics Applicability to Transportation Modeling.” Transportation Research Part A 28 (5): 373–390] evaluated the strengths and weaknesses of system dynamics (SD) as an approach for modelling in the transportation area. They listed 12 advantages of the approach and in particular suggested it was well suited to strategic issues and that it could provide a useful tool for supporting policy analysis and decision-making in the transport field. This paper sets out a review of over 50 peer-reviewed journal papers since 1994 categorising them by area of application and providing a summary of particular insights raised. The fields of application include the take-up of alternate fuel vehicles, supply chain management affecting transport, highway maintenance, strategic policy, airport infrastructure and airline business cycles and a set of emerging application areas. The paper concludes with recommendations for future application of the SD approach