Advanced Traveler Information System for Guiding Route Choice to Ocean City, Maryland

Abstract

A real-time advanced traveler information system for traffic heading to Ocean City, Maryland, is presented. It can provide dynamic route choice guidance for en route travelers, offer web-based historical data for pretrip tourists, and perform real-time traffic monitoring as well as emergency evacuation for responsible agencies with its 40 detectors. The proposed system is designed to contend with most critical issues associated with real-time operations, including automated detection of incidents, reliable estimation of missing data, and continuous updates of historical databases. Implementation results demonstrate that the travel time information displayed by the proposed system has been well received by drivers and is viewed as the primary resource for choice of routes to Ocean City. The evolution of traffic volumes on alternative routes during congested periods reveals that the travel time information from variable message signs not only provides guidance to drivers but also leads to better use of roadway capacity and results in more throughputs for the same period of operation.

Anticipatory traveller information system for freeway‐arterial networks

“…The reasons were investigated and reported in detail [1] by studying the factors that affects driver behaviour and the spatiotemporal coordination and consistencies in VMS‐based route guidance strategies. One of the main reasons is that the home‐based work trips during the morning peak hours are higher than those during the other periods at the same road section.…”

“…Development of an advanced traveller information system (ATIS) is receiving increasing attention from both researchers and practitioners. Real world ATISs have been implemented in the USA [1]; for example, TranStar in Houston, Texas, and the ATIS in Chicago, Illinois, post the average travel time of completed trips of commuters. Georgia navigator software has been used in several states to display the travel time computed by current average speeds collected on each link, including Atlanta and Macon, Georgia; Portland, Oregon; and Nashville, Tennessee [1].…”

“…Dynamic models [1], as reported in the literature, also appear to fit best for predicting travel times for short freeway segments. However, parameters of dynamic models cannot be updated until the trips have been completed.…”