Variable-message sign

About: Variable-message sign is a research topic. Over the lifetime, 470 publications have been published within this topic receiving 4724 citations. The topic is also known as: CMS.

Vehicle speeding detection and identification

Abstract: A method and system in automobile traffic control for warning drivers that they are exceeding the speed limit using an alpha-numeric variable message sign (50) proximate the roadway. The sign displays the license plate number, owner's name and the vehicle's speed. The system includes an opto-electric license plate reader (10) and a computer system (31) having a database of license numbers and associated information, including owner's names and make and model of licensed vehicles.

Transport Planning and Traffic Engineering

Abstract: This new book, a worthy successor to the widely acclaimed first volume of O'Flaherty's Highway has been expanded and thoroughly updated to reflect the many changes that have taken place in this topical area. Transport Planning and Traffic Engineering is a comprehensive textbook on the relevant principles and practice. It includes sections on transport policy and planning, traffic surveys and accident invesitgation, road design for capacity and safety, and traffic management.

Driver response to variable message sign information in London

Abstract: Variable message signs (VMS) have been installed in London to notify motorists of planned events and current network problems. To guide investment and operational decisions an understanding is required of the impacts of VMS information. This paper presents the results of a study of driver response to VMS information. The study employed questionnaires to investigate the effect of different messages on route choice. A statistical analysis of stated intention questionnaire data enabled logistic regression models to be developed relating the probability of route diversion to driver, journey and message characteristics. The resultant models indicate that the location of the incident and the message content are important factors influencing the probability of diversion. A survey of drivers' actual responses to a message activation showed that only one third of drivers saw the information presented to them and few of these drivers diverted, although many found the information useful. Only one-fifth of the number of drivers diverted compared to that expected from the results of the stated intention questionnaire. It is thought that the low response rate achieved for the stated intention survey will have exaggerated drivers' responsiveness to VMS messages. Interestingly, survey data for another UK city with a newly installed VMS system showed that the number of drivers diverting due to VMS information was very similar to that expected from the results of the stated intention questionnaire. It is suggested that the use of London's VMS signs to display warnings of disruptions expected on future dates may be reducing their effectiveness as a channel for more urgent warnings.

Driver response to variable message signs: a stated preference investigation

Abstract: This paper uses a Stated Preference approach to undertake a detailed assessment of the effect on drivers’ route choice of information provided by variable message signs (VMS). Although drivers’ response to VMS information will vary according to the availability of alternative routes and the extent to which they are close substitutes, our findings show that route choice can be strongly influenced by the provision of information about traffic conditions ahead. This has important implications for the use of VMS systems as part of comprehensive traffic management and control systems. The principal findings are that the impact of VMS information depends on: the content of the message, such as the cause of delay and its extent; local circumstances, such as relative journey times in normal conditions; and drivers’ characteristics, such as their age, sex and previous network knowledge. The impact of qualitative indicators, visible queues and delays were examined. It was found that not only is delay time more highly valued than normal travel time, which is to be expected, but that drivers become more sensitive to delay time as delay times increased across the range presented.

Online Learning Solutions for Freeway Travel Time Prediction

Abstract: Providing travel time information to travelers on available route alternatives in traffic networks is widely believed to yield positive effects on individual drive behavior and (route/departure time) choice behavior, as well as on collective traffic operations in terms of, for example, overall time savings and-if nothing else-on the reliability of travel times. As such, there is an increasing need for fast and reliable online travel time prediction models. Previous research showed that data-driven approaches such as the state-space neural network (SSNN) are reliable and accurate travel time predictors for freeway routes, which can be used to provide predictive travel time information on, for example, variable message sign panels. In an operational context, the adaptivity of such models is a crucial property. Since travel times are available (and, hence, can be measured) for realized trips only, adapting the parameters (weights) of a data-driven travel time prediction model such as the SSNN is particularly challenging. This paper proposes a new extended Kalman filter (EKF) based online-learning approach, i.e., the online-censored EKF method, which can be applied online and offers improvements over a delayed approach in which learning takes place only as realized travel times are available.