John Golias

Short‐term traffic forecasting: Overview of objectives and methods

In the last two decades, the growing need for short‐term prediction of traffic parameters embedded in a real‐time intelligent transportation systems environment has led to the development of a vast number of forecasting algorithms. Despite this, there is still not a clear view about the various requirements involved in modelling. This field of research was examined by disaggregating the process of developing short‐term traffic forecasting algorithms into three essential clusters: the determination of the scope, the conceptual process of specifying the output and the process of modelling, which includes several decisions concerning the selection of the proper methodological approach, the type of input and output data used, and the quality of the data. A critical discussion clarifies several interactions between the above and results in a logical flow that can be used as a framework for developing short‐term traffic forecasting models.

Spatio-Temporal Short-Term Urban Traffic Volume Forecasting Using Genetically Optimized Modular Networks

Current interest in short-term traffic volume forecasting focuses on incorporating temporal and spatial volume characteristics in the forecasting process. This paper addresses the problem of integrating and optimizing predictive information from multiple locations of an urban signalized arterial roadway and proposes a modular neural predictor consisting of temporal genetically optimized structures of multilayer perceptrons that are fed with volume data from sequential locations to improve the accuracy of short-term forecasts. Results show that the proposed methodology provides more accurate forecasts compared to the conventional statistical methodologies applied, as well as to the static forms of neural networks.

COMPARATIVE EVALUATION OF EXISTING AND INNOVATIVE RAIL-ROAD FREIGHT TRANSPORT TERMINALS

Abstract The paper evaluates technical and logistics developments that could lead to increased economic and technical efficiency of rail–road transport terminals. The main design parameters are identified (length and utilisation of transhipment tracks, train and truck arrival behaviour/patterns, type and number of handling equipment, mean stacking height in the storage area, terminal access system and procedures) and analysed. A comparative evaluation of selected conventional and advanced technologies is performed by use of an analysis tool that was developed on purpose. This tool consists of three modules (an expert system, a simulation model and a cost calculation module). The overall outcome of the analysis is a number of cost-versus-volume curves for various terminal configurations. The paper concludes with two groups of results: (a) a comparative evaluation of conventional and advanced technologies that reveals similarities in terms of track numbers and the associated area requirements as well as differences in terms of layout flexibility, number of equipment, stacking policies and personnel requirements. Each design is proved effective for a certain cargo volume range. (b) A critical assessment of terminal capacity issues. It is identified that the capacity limitations are imposed mainly by the sidings/transhipment track sub-system rather than by the handling equipment.

Towards the improvement of a combined transport chain performance

Abstract Within the framework of the promotion of the environmental friendly modes, the European Commission has launched a number of research projects aiming at evaluating technical and organisational innovations that can improve the performance of the freight transport operations in the rail sector. The scope of this paper is to present a modelling approach focusing on the comparative evaluation of conventional and advanced rail-road terminal equipment. The set of models used, consists of an expert system for the terminal design, a model simulating terminal operations and a macro-model implementing rail operating forms and assigning freight flows in the transport network. This approach stems from the fact that the time savings due to efficient terminal transshipment can be used effectively only in combination with advanced rail operating forms.

Temporal Evolution of Short‐Term Urban Traffic Flow: A Nonlinear Dynamics Approach

Recognizing temporal patterns in traffic flow has been an important consideration in short- term traffic forecasting research. However, little work has been conducted on identifying and associating traffic pattern occurrence with prevailing traffic con- ditions. We propose a multilayer strategy that first identifies patterns of traffic based on their structure and evolution in time and then clusters the pattern- based evolution of traffic flow with respect to pre- vailing traffic flow conditions. Temporal pattern iden- tification is based on the statistical treatment of the recurrent behavior of jointly considered volume and oc- cupancy series; clustering is done via a two-level neural network approach. Results on urban signalized arterial 90-second traffic volume and occupancy data indicate that traffic pattern propagation exhibits variability with respect to its statistical characteristics such as determinis- tic structure and nonlinear evolution. Further, traffic pat- tern clustering uncovers four distinct classes of traffic pat- tern evolution, whereas transitional traffic conditions can be straightforwardly identified.

Effects of Urban Delivery Restrictions on Traffic Movements

Abstract This article investigates the effects of the adoption of restrictions in vehicle movements associated with urban delivery operations on traffic. A wide range of data (including land use, delivery requirements per type of service, traffic mix, traffic flows and capacities) are used within suitable models to assess the traffic and environmental effects in Athens, Greece. The findings suggest that restricting delivery to specific types of businesses during rush hours can lead to positive traffic and environmental effects. The effectiveness of urban delivery restriction policies depends on the careful selection of the time periods and types of businesses for which they will apply.

Differences between Vehicle Lateral Displacement on the Road and in a Fixed-Base Simulator

This work investigates differences in lateral displacement when driving on curved and straight road sections in real-road and simulator conditions. We observed 100 licensed drivers on a rural road and 100 in a fixed-base simulator. Speed and lateral position on the real road were measured using videocameras. The analysis indicates that the mean vehicle lateral displacement is in general higher on the real road than in the simulator. However, these differences decrease for higher speeds at curved sections and for lower speeds at straight sections. It was also found that the standard deviation of the vehicle lateral displacement is significantly lower on the real road than the corresponding values in the simulator, at either curved or straight sections. Actual or potential applications of this research are related to a more realistic assessment of driving behavior scenarios derived on the basis of simulation experiment results.

Analysis of traffic corridor impacts from the introduction of the new Athens Metro system

New transit systems are viewed as an effective approach to dealing with concerns about automobile dependence and a degrading quality of life in many large cities. This paper concentrates on evaluating the impacts from the construction of a new subway system as these impacts pertain to traveler behavior and mode choice. Using the results from a revealed preference combined roadside and on-board survey from Athens, Greece, and utilizing a flexible disaggregate model specification (the heteroskedastic extreme value model) the results from the introduction of a new Metro system are evaluated. The results indicate that the demand for auto usage is fairly inelastic (with respect to both cost and time), and that Athens transit users are more sensitive to changes in cost rather than travel time. Further, the results indicate that increases in travel time and cost for the auto would increase the demand for the Metro, but not as much for the bus. 2002 Elsevier Science Ltd. All rights reserved.

Freeway Operations, Spatiotemporal-Incident Characteristics, and Secondary-Crash Occurrence

Incidents are a major source of uncertainty in freeway operations. Secondary crashes are an important category of freeway incidents. Until now, secondary crashes have been assumed to occur at the boundary of high-density queues formed upstream of an initial crash. While much research has concentrated on the relationship between incident duration and secondary-crash likelihood, the incidents influence area is widely treated as independent of prevailing traffic conditions and incident characteristics. This paper extends research by developing a Bayesian network for the probabilistic estimation of different influence areas for secondary-crash occurrence with respect to various incident and traffic characteristics. Results indicate that traffic conditions at the time of an incident, as well as the time needed to respond to and clear the crash scene, are the most significant determinants in defining the upstream influence area of a crash.

Pattern-Based Short-Term Urban Traffic Predictor

Short-term urban traffic predictor is a prediction system based on artificial intelligence and advanced analysis of nonlinear dynamics of short-term traffic flow. The aim is to address: (1) the need for accurate anticipated traffic information, (2) the ability to cope with various traffic conditions in an integrated up-to-date functional structure and (3) the need for accurate and timely predictive short-term traffic information in an extended time horizon in cases of data collection malfunction. The conceptual and functional framework of short-term urban traffic predictor is presented. The above are encapsulated in a user-friendly application. Finally, some interesting results regarding computational time and accuracy of recursive predictions are presented