Showing papers in "Transportation Research Part C-emerging Technologies in 2001"

A real-time traffic signal control system: architecture, algorithms, and analysis

Abstract: The paper discusses a real-time traffic-adaptive signal control system referred to as RHODES. The system takes as input detector data for real-time measurement of traffic flow, and “optimally” controls the flow through the network. The system utilizes a control architecture that (1) decomposes the traffic control problem into several subproblems that are interconnected in an hierarchical fashion, (2) predicts traffic flows at appropriate resolution levels (individual vehicles and platoons) to enable pro-active control, (3) allows various optimization modules for solving the hierarchical subproblems, and (4) utilizes a data structure and computer/communication approaches that allow for fast solution of the subproblems, so that each decision can be downloaded in the field appropriately within the given rolling time horizon of the corresponding subproblem. The RHODES architecture, algorithms, and its analysis are presented. Laboratory test results, based on implementation of RHODES on simulation models of actual scenarios, illustrate the effectiveness of the system.

Towards an understanding of adaptive cruise control

Abstract: Adaptive cruise control (ACC) provides assistance to the driver in the task of longitudinal control of their vehicle during motorway driving. The system controls the accelerator, engine powertrain and vehicle brakes to maintain a desired time-gap to the vehicle ahead. This research describes the results of a detailed microscopic simulation investigation into the potential impacts of ACC on motorway driving. In addition to simulation, real vehicle driving profiles, obtained from instrumented vehicle experiments in three European countries, have been used to compare real following behaviour with that of a simulated ACC equipped vehicle. This new approach has shown that following with an ACC system can provide considerable reductions in the variation of acceleration compared to manual driving. This indicates a potential comfort gain for the driver and environmental benefits. A number of critical situations in which ACC does not perform well have also been identified. The research also highlights the limitations of microscopic simulation in modelling the impacts of ACC because of the lack of understanding of the interaction between the driver and the ACC system relative to the traffic conditions.

Impacts of information technology on personal travel and commercial vehicle operations: research challenges and opportunities

Abstract: Travel, like many other aspects of daily life is being transformed by the information technology (IT) revolution. Accessibility can no longer be measured only in terms of travel time, distance or generalized travel cost. IT gives people virtual accessibility to a rapidly growing range of activities. E-commerce has become a catalyst for structural changes in the freight transportation industry and is changing where freight moves, the size of typical shipments and the time within which goods must be delivered. In this paper, we explore some of the potential effects of IT on transportation, both personal and freight.

An Experimental Comparative Study of Autonomous and Co-operative Vehicle-follower Control Systems

Abstract: This paper is a comparative study of the performance of constant-time-gap autonomous control systems and co-operative longitudinal control systems that use inter-vehicle communication. Analytical results show that the minimum time gap that can be achieved in autonomous control is limited by the bandwidth of the internal dynamics of the vehicle. Experimental results from typical sensors and actuators are used to show that in practice it is very difficult to achieve a time gap less than 1 s with autonomous vehicle following. This translates to an inter-vehicle spacing of 30 m at highway speeds and a theoretical maximum traffic flow of about 3000 vehicles per hour. The quality of radar range and range rate measurements pose limitations on the spacing accuracy and ride quality that can be achieved in autonomous control. Dramatic improvements in the trade-off between ride quality and spacing accuracy can be obtained merely by replacing radar range rate in the autonomous control algorithm with the difference between the measured velocities of the two cars (a rudimentary form of co-operation). As a baseline comparison, the experimental performance of fully co-operative control is presented. An inter-vehicle spacing of 6.5 m is maintained in a platoon of 8 co-operative vehicles with an excellent ride quality and an accuracy of ±20 cm. Extending this to a 10-vehicle platoon makes it possible to achieve theoretical maximum traffic flows of about 6400 vehicles per hour. Another issue of importance addressed in the paper is the need to accommodate malfunctions in radar (ranging sensor) measurements. Measurement errors can occur due to hardware malfunctions as well as due to road curves, grades and the highway environment in the case of large inter-vehicle spacing. The ability of a co-operative control system to monitor the health of the radar and correct for such errors and malfunctions is demonstrated experimentally.

Use of sequential learning for short-term traffic flow forecasting

Abstract: Accurate short-term traffic flow forecasting has become a crucial step in the overall goal of better road network management. Previous research [H. Kirby, M. Dougherty, S. Watson, Should we use neural networks or statistical models for short term motorway traffic forecasting, International Journal of Forecasting 13 (1997) 43–50.] has demonstrated that a straightforward application of neural networks can be used to forecast traffic flows along a motorway link. The objective of this paper is to report on the application and performance of an alternative neural computing algorithm which involves ‘sequential or dynamic learning’ of the traffic flow process. Our initial work [H. Chen, S. Clark, M.S. Dougherty, S.M. Grant-Muller, Investigation of network performance prediction, Report on Dynamic Neural Network and Performance Indicator development, Institute for Transport Studies, University of Leeds Technical Note 418, 1998 (unpublished)] was based on simulated data (generated using a Hermite polynomial with random noise) that had a profile similar to that of traffic flows in real data. This indicated the potential suitability of dynamic neural networks with traffic flow data. Using the Kalman filter type network an initial application with M25 motorway flow data suggested that a percentage absolute error (PAE) of approximately 9.5% could be achieved for a network with five hidden units (compared with 11% for the static neural network model). Three different neural networks were trained with all the data (containing an unknown number of incidents) and secondly using data wholly obtained around incidents. Results showed that from the three different models, the ‘simple dynamic model’ with the first five units fixed (and subsequent hidden units distributed amongst these) had the best forecasting performance. Comparisons were also made of the networks’ performance on data obtained around incidents. More detailed analysis of how the performance of the three networks changed through a single day (including an incident) showed that the simple dynamic model again outperformed the other two networks in all time periods. The use of ‘piecewise’ models (i.e. where a different model is selected according to traffic flow conditions) for data obtained around incidents highlighted good performance again by the simple dynamic network. This outperformed the standard Kalman filter neural network for a medium-sized network and is our overall recommendation for any future application.

Random utility models with implicit availability/perception of choice alternatives for the simulation of travel demand

Abstract: Random utility models are undoubtedly the most used models for the simulation of transport demand. These models simulate the choice of a decision-maker among a set of feasible alternatives and their operational use requires that the analyst is able to correctly specify this choice-set for each individual. Some early applications basically ignored this problem by assuming that all decision-makers chose from the same pre-specified choice-set. This assumption may be unrealistic in many practical cases and cause significant misspecification problems (P. Stopher, Transportation Journal of ASCE 106 (1980) 427; H. Williams, J. Ortuzar, Transportation Research B 16 (1982) 167). The problem of choice-set simulation has been dealt within the literature following two basically different approaches: • simulating the perception/availability of an alternative implicitly in the choice model, • simulating the choice-set generation explicitly in a separate model. The implicit approach is more convenient from an operational point of view, while the explicit one is more appealing from a theoretical point of view. In this paper, a different approach to the modeling of availability/perception of alternatives in the context of random utility model is proposed. This approach is based on the concept of intermediate degrees of availability/perception of each alternative simulated through a model (or “inclusion function”) which in turn is introduced in the systematic utility of standard random utility models. This model, named implicit availability/perception (IAP), may be differently specified depending on assumptions made on the joint distribution of random residuals and the way in which the average degree of availability/perception is modeled. In this paper, a possible specification of the IAP model, based on the assumption of random residual distributed as i.i. Gumbel and with the average degree of availability/perception modeled as a binomial logit, is proposed. The paper also proposes ML estimation models in two cases: in the first, only information on alternatives choices is available, while in the second, this information is complemented with others on variables related to a latent (i.e., non-observable) alternatives availability/perception degree (e.g., information on car availability of decision-maker i used as an indirect measurement of the unknown and non-observable availability/perception degree of alternative car for decision-maker i in a modal split). The proposed specification is tested on mode choice data; the calibration results are compared with those of a similar logit specification with encouraging results in terms of goodness of fit.

A prototype fuel-efficiency support tool

Abstract: An effective way to reduce fuel consumption in the short run is to induce a change in driver behaviour. If drivers are prepared to change their driving habits they can complete the same journeys within similar travel times, but using significantly less fuel. In this paper, a prototype fuel-efficiency support tool is presented which helps drivers make the necessary behavioural adjustments. The support tool includes a normative model that back-calculates the minimal fuel consumption for manoeuvres carried out. If actual fuel consumption deviates from this optimum, the support tool presents advice to the driver on how to change his or her behaviour. To take account of the temporal nature of the driving task, advice is generated at two levels: tactical and strategic. Evaluation of the new support tool by means of a driving simulator experiment revealed that drivers were able to reduce overall fuel consumption by 16% compared with ‘normal driving’. The same drivers were only able to achieve a reduction of 9% when asked to drive fuel efficiently without support; thus, the tool gave an additional reduction of 7%. Within a simulated urban environment, the additional reduction yielded by the support tool rose to 14%. The new support tool was also evaluated with regard to secondary effects.

The effects of in-car speed limiters – Field studies

Abstract: Field trials in three European countries, the Netherlands, Spain and Sweden were carried out in order to investigate the effects of an in-car speed limiter. The trials were carried out on urban and rural roads including motorways. A so-called unobtrusive instrumented car was used, where all the measuring equipment was hidden. All the speed limit categories in the respective countries, ranging from 30 km/h to 120 km/h were included. The results showed that the effects of the limiter were greatest in free driving conditions outside platoons. How-ever, the limiter also had effects in congested traffic. Momentary high speeds were suppressed effectively, which resulted in less variation of speeds. Approach speeds at roundabouts, inter-sections and curves became smoother, car-following behaviour became safer in the speed range of 30 km/h to 50 km/h. On the other hand, in the speed range of 70 km/h to 90 km/h a slightly higher number of short time-gaps suggested less safe car-following behaviour. Other negative behavioural effects were slightly increased travel time and the increased frustration and stress for the drivers caused by the limiter. The majority of the subjects accepted the speed limiter as a driver-operated system. Half of the drivers would accept the limiter volun-tarily in their cars. (Less)

Using ordered probit modeling to study the effect of ATIS on transit ridership

Abstract: A computer-aided telephone interview was conducted in two metropolitan areas in northern California. The survey included an innovative stated preference design to collect data that address the potential of advanced transit information systems. The study’s main objectives are to investigate whether advanced transit information would increase the acceptance of transit, and to determine the types and levels of information that are desired by commuters. The survey included a customized procedure that presents realistic choice sets, including the respondent’s preferred information items and realistic travel times. The ordered probit modeling technique was used. The results indicated a promising potential of advanced transit information in increasing the acceptance of transit as a commute mode. It also showed that the frequency of service, number of transfers, seat availability, walking time to the transit stop and fare information are among the significant information types that commuters desire. Commute time by transit, income, education, and whether the commuter is currently carpooling, were among the factors that contribute to the likelihood of using transit given information was provided.

Investigating the learning effects of route guidance and traffic advisories on route choice behavior

Abstract: This paper describes a study to investigate the effects of route guidance and traffic advisories on driver's route choice behavior. The study is a two-factor experiment with repeated measures on one factor where the between-subjects factor is the type of traveler information provided and the repeated, within-subjects factor is trips made between a specified origin and destination. Participants were recruited and randomly assigned to one of four groups: group 1 having only a basic map of the network; group 2 having access only to route guidance, group 3 having access to traffic advisory information, and group 4 having access to both route guidance and traffic advisory information. Each participant completed 15 trips between a specified origin-destination pair on a hypothetical network. The results of this study indicate that there may be significant short-term advantages to providing in-vehicle routing and navigation information to unfamiliar drivers. However, the results also indicate that the format and amount of information provided may not be significant as the benefits to having route guidance diminish when drivers become more familiar with the travel network.

Optimisation of parking guidance and information systems display configurations

Abstract: Operators of parking guidance and information (PGI) systems often have difficulty in determining the best car park availability information to present to drivers in periods of high demand. This paper describes a behavioural model of parking choice incorporating drivers perceptions of waiting times at car parks based on PGI signs. This model was used to predict the influence of PGI signs on the overall performance of the traffic system. Relationships were developed for estimating the arrival rates at car parks based on trip patterns, driver characteristics, car park attributes as well as the car park availability information displayed on PGI signs. Drivers' perceptions of waiting times at car parks were assumed to be influenced by the PGI signs for observers of the signs and actual car park utilisation levels for non-observers. The model assumes that the choice of car park does not change after entering the city centre, even if conditions observed are different from those initially perceived. A mathematical programme was formulated to determine the optimal display PGI sign configuration to minimise queue lengths and vehicle kilometres of travel (VKT). The model was limited to off-street parking choices and illegal parking was not incorporated. A simple genetic algorithm was used to identify solutions that significantly reduced queue lengths and VKT compared with existing practices. These procedures were applied to an existing PGI system operating in Tama New Town near Tokyo. Significant reductions in queue lengths and VKT were predicted using the optimisation model. This would reduce traffic congestion and lead to various environmental benefits.

Integrating vehicle design and human factors: minimizing elderly driving constraints

Abstract: With a projected rise in the number of elderly, most of whom have also relied primarily on the private automobile for their mobility, it is likely that future adaptations in vehicle design will be linked in some part to the physical infirmities often faced by the elderly. This paper oAers a bridge between medical research on the physical impairments of the elderly and automobile design and driving safety. We describe recent findings on the driving-related physical and cognitive impairments faced by the elderly. We then propose two major types of vehicle design and infrastructure adaptations: (1) modifications for private vehicles, and (2) intelligent technology and support services for private vehicles, which can help to minimize the driving- related eAects of these impairments. For example, we present a range of modest vehicle design adaptations for components such as seats and doorways, handles, knobs, and steering wheels, and seat belts. We find that many of these improvements can be made to standard passenger vehicles with little additional design eAort, and that the adaptations should also increase overall vehicle marketability. Finally, we argue that while most, if not all, of our proposed adaptations would be made to largely benefit the elderly, they will nevertheless support and improve driving across all age groups. " 2001 Elsevier Science Ltd. All rights reserved.

Driver fatigue: a vision-based approach to automatic diagnosis

Abstract: In this paper, we describe a system that locates and tracks the eyes of a driver. The purpose of such a system is to perform detection of driver fatigue. By mounting a small camera inside the car, we can monitor the face of the driver and look for eye movements which indicate that the driver is no longer in condition to drive. In such a case, a warning signal should be issued. This paper describes how to find and track the eyes. We also describe a method that can determine if the eyes are open or closed. The primary criterion for this system is that it must be highly non-intrusive. The system must also operate regardless of the texture and the color of the face. It must also be able to handle changing conditions such as changes in light, shadows, reflections, etc. Initial experimental results are very promising even when the driver moves his/her head in a way such that the camera does not have a frontal view of the driver’s face.

Coordinated traffic-responsive ramp control via nonlinear state feedback

Abstract: In this paper, we develop a coordinated traffic responsive ramp control strategy based on feedback control and artificial neural networks. The proposed feedback control law is nonlinear and realized by a series of neural networks. The parameters of the neural networks are obtained through a nonlinear optimization procedure. Traffic simulations show that the proposed nonlinear ramp control strategy compares favorably against the well-known linear quadratic (LQ) control strategy in reducing total travel times, particularly at situations where drastic changes in traffic demand and road capacity occur.

Fleet purchase behavior: decision processes and implications for new vehicle technologies and fuels

Abstract: Vehicle fleets are a poorly understood part of the economy. They are important, though, in that they purchase a large share of light-duty vehicles and are often targeted by governments as agents of change. We investigate fleet purchase behavior, using focus groups, interviews, and mail and telephone surveys. We categorize fleets into four different decision-making structures (autocratic, bureaucratic, hierarchic, and democratic), determine what share of the market sector each represents, describe salient features of each behavioral model, and explore implications of that behavior for industry investment and public policy.

Automatic vehicle classification system with range sensors

Abstract: Traffic management systems use inductive loop detectors and more recently video cameras to detect vehicles. Loop detectors are expensive to maintain and video-based systems are sensitive to environmental conditions and do not perform well in vehicle classification. Cameras based upon range sensors are not sensitive to lighting and may be less sensitive to other environmental conditions. In addition, range imagery should provide data to form a good basis for vehicle classification applications. In this paper, we describe methods for processing range imagery and performing vehicle detection and classification. A vehicle classification rate of over 92% accuracy was obtained in classifying vehicles into different vehicle classes.

A prototype case-based reasoning system for real-time freeway traffic routing

Abstract: With the recent advances in communications and information technology, real-time traffic routing has emerged as a promising approach to alleviating congestion. Existing approaches to developing real-time routing strategies, however, have limitations. This study examines the potential for using case-based reasoning (CBR), an emerging artificial intelligence paradigm, to overcome such limitations. CBR solves new problems by reusing solutions of similar past problems. To illustrate the feasibility of the approach, the study develops and evaluates a prototype CBR routing system for the interstate network in Hampton Roads, Virginia. Cases for building the system’s case-base are generated using a heuristic dynamic traffic assignment (DTA) model designed for the region. Using a second set of cases, the study evaluates the performance of the prototype system by comparing its solutions to those of the DTA model. The evaluation results demonstrate that the prototype system is capable of running in real-time , and of producing high quality solutions using case-bases of reasonable size.

Constraint handling methods in pavement maintenance programming

Abstract: The problem of pavement maintenance management at the network level is one of maintaining as high a level of serviceability as possible for a pavement network system through reactive and proactive repair actions, whilst optimising the use of available resources. This problem has traditionally been solved using techniques like mathematical programming and heuristic methods. Lately, the use of genetic algorithms (GAs) to solve resource allocation problems like the network pavement maintenance problem has received increased attention from researchers. GAs have been demonstrated to be better than traditional techniques in terms of solution quality and diversity. However, the performance of the GAs is affected by the method used to handle the many constraints present in the formulation of such resource allocation methods. Penalty as well as generate and repair methods are the usual techniques used to handle constraints, but these have their drawbacks in terms of computational efficiency and tendency to get trapped in sub-optimal solution spaces. The paper proposes a third method that is computationally more efficient than the previous methods. The method is based on prioritised allocation of resources to maintenance activities and the maximum utilisation of resources. Constraints on maximum resource availability are no longer used passively to check on solution feasibility (as in the previous methods) but are used to help generate feasible solutions during the resource allocation phase of the algorithm itself. It is demonstrated that the GA with the prioritised resource allocation method (PRAM) outperforms the traditional GA with repair or penalty methods. PRAM was able to consistently outperform the other two GA based methods, both in terms of solution quality as well as computational time. It is concluded that PRAM can be used as the basis of more efficient resource allocation procedures in the area of pavement maintenance management.

Development and evaluation of a knowledge-based system for traffic congestion management and control

Abstract: This paper describes a real-time knowledge-based system (KBS) for decision support to Traffic Operation Center personnel in the selection of integrated traffic control plans after the occurrence of non-recurring congestion, on freeway and arterial networks. The uniqueness of the system, called TCM, lies in its ability to cooperate with the operator, by handling different sources of input data and inferred knowledge, and providing an explanation of its reasoning process. A data fusion algorithm for the analysis of congestion allows to represent and interpret different types of data, with various levels of reliability and uncertainty, to provide a clear assessment of traffic conditions. An efficient algorithm for the selection of control plans determines alternative traffic control responses. These are proposed to an operator, along with an explanation of the reasoning process that led to their development and an estimation of their expected effect on traffic. The validation of the system, which is one of only few examples of validation of a KBS in transportation, demonstrates the validity of the approach. The evaluation results, in a simulated environment demonstrate the ability of TCM to reduce congestion, through the formulation of traffic diversion and control schemes.

Privacy issues in electronic toll collection

Abstract: This paper summarises privacy issues in the context of electronic toll collection (ETC). Developments in ETC are noted, and the ways in which privacy is being addressed are discussed. The development of privacy codes of practice by toll road operators is discussed, mentioning in particular recent development in Australia involving the alignment of such codes with Standards Australia (SA) draft guidelines and the privacy principles developed by the Australian Federal Privacy Commissioner are noted.

New technologies for transport route selection

Abstract: Planning a new road or railway can be an expensive and time-consuming process. There are numerous environmental issues that need to be addressed, and the problem is exacerbated where the alignment is also influenced by the location of services, existing roads and buildings, and the financial, social and political costs of land resumption. A comprehensive approach to the problem is available through the recent convergence of: geospatial imaging, softcopy photogrammetry, regional significance analysis and alignment optimisation. The first technology is concerned with obtaining low cost data containing far more information than was available in the past. The second two are concerned with extracting from that data, information essential to the planning process. The final technology is about automating the way alignments are generated to produce low cost, high quality routes. The convergence of these enabling technologies can have a major impact on the way that various jobs are performed – or whether they are done at all. Separately, they can have a major influence on a large number of disciplines, but taken in combination they can change the paradigm of alignment planning completely. By taking tasks that were previously difficult, time-consuming and expensive, and making them easy, fast and cheap, they can change completely the way alignments are planned.

A combined methodology for transportation planning assessment. Application to a case study

Abstract: Traffic assignment models based on the user-equilibrium approach are one of the most widely used tools in transportation planning analysis. Resulting flows offer a static average view of the expected use of the road infrastructure under the modeling hypothesis. This information has usually been enough for the planning decisions. The planned infrastructure is probably sufficient for average demand, but time-varying traffic flows, i.e., at peak periods, combined with the influence of road geometry, can produce undesired congestion that can not be forecasted or analysed with the static tools. There is a clear case for a change in the analysis methodology such as combination of a traffic assignment tool, with a microscopic traffic simulator. This paper illustrates, by means of a case study, the combination of a well-known traffic assignment tool, the EMME/2 model, with a microscopic traffic simulator, Advanced Interactive Microscopic Simulator For Urban And Non-Urban Networks (AIMSUN2) with emphasis on the description of the specific interfaces that make consistent the combination of both tools in the Generic Environment for Traffic Analysis and Modeling (GETRAM) environment. Models for complex transportation systems should be the combination of mathematical models and computer models, to overcome, for example, the difficulties of the integration of modeling tools. GETRAM environment has an open and flexible computer architecture suitable for such purposes.

Modeling the effects of traveler information on freeway origin-destination demand prediction

Abstract: The primary focus of this research is to develop an approach to capture the effect of travel time information on travelers’ route switching behavior in real-time, based on on-line traffic surveillance data. It also presents a freeway Origin–Destination demand prediction algorithm using an adaptive Kalman Filtering technique, where the effect of travel time information on users’ route diversion behavior has been explicitly modeled using a dynamic, aggregate, route diversion model. The inherent dynamic nature of the traffic flow characteristics is captured using a Kalman Filter modeling framework. Changes in drivers’ perceptions, as well as other randomness in the route diversion behavior, have been modeled using an adaptive, aggregate, dynamic linear model where the model parameters are updated on-line using a Bayesian updating approach. The impact of route diversion on freeway Origin–Destination demands has been integrated in the estimation framework. The proposed methodology is evaluated using data obtained from a microscopic traffic simulator, INTEGRATION. Experimental results on a freeway corridor in northwest Indiana establish that significant improvement in Origin–Destination demand prediction can be achieved by explicitly accounting for route diversion behavior.

Production and analysis of coordination plans using a geographic information system

Abstract: The TRANSYT program is one of the most extensively used programs for the production of signal coordination plans. The impediments to the development of signal coordination plans are associated with data collection and data input. GIS offers a natural solution to these problems. This paper presents the SIGTRAF system, which uses GIS-T technology for the production of coordination plans using TRANSYT. This system is able to extract topological information from the GIS-T, thus simplifying the process of coding TRANSYT models. A case study was performed, providing insight on how the GIS-T’s thematic mapping capabilities can be used to visually compare different timing plans.