00821019

Component

https://doi.org/10.3141/1771-26

http://scholar.google.com...avar&publication_year=2001

Efficient storage, processing, and communication of dynamic data are at the heart of intelligent transportation systems (ITS) applications. The speed of communication and processing as well as the storage space required by such data depend on the method used for its representation. ITS applications typically involve dynamic data that are discrete and require fast computation and communication speeds to support real-time operations. An efficient representation method is presented, which is called the bit-stream representation, for discrete-time dynamic data. Its positive impacts are presented by developing efficient representations for storage and communication of travel times in dynamic transportation networks. It is shown theoretically that this representation method typically leads to an L/2-fold gain in both storage space and communication speed compared with methods that represent discrete-time dynamic data using L-bits to store an integer. The proposed representation holds the potential to develop new faster algorithms that would directly operate on dynamic data represented as bit streams.

This paper appears in Transportation Research Record No. 1771, Transportation Network Modeling 2001.

English

p. 209-218

2001

Transportation Research Record

0309072298

Figures (4) ; References (15)

Algorithms; Data communications; Data storage; Intelligent transportation systems; Real time data processing; Travel time

Bit streams; Discrete time dynamic data

Highways; Operations and Traffic Management; Planning and Forecasting; I72: Traffic and Transport Planning

TRIS, TRB, ATRI

Dec 13 2001 12:00AM

• ACCELERATING STRATEGIES AND COMPUTATIONAL STUDIES OF THE FRANK-WOLFE ALGORITHM FOR THE TRAFFIC ASSIGNMENT PROBLEM
• ANALYTICAL DYNAMIC NETWORK LOADING PROBLEM: FORMULATION, SOLUTION ALGORITHMS, AND COMPUTER IMPLEMENTATIONS
• ASSESSING FINANCIAL FEASIBILITY OF A BUILD-OPERATE-TRANSFER PROJECT UNDER UNCERTAIN DEMAND
• ASSESSING PERFORMANCE RELIABILITY OF ROAD NETWORKS UNDER NONRECURRENT CONGESTION
• ASSIGNMENT MODELS FOR LOCAL TRUCKLOAD TRUCKING PROBLEMS WITH STOCHASTIC SERVICE TIMES AND TIME WINDOW CONSTRAINTS
• BITWISE ALGORITHM FOR FASTEST PATHS IN TIME-DEPENDENT NETWORKS
• CALIBRATION AND PATH DYNAMICS ISSUES IN MICROSCOPIC SIMULATION FOR ADVANCED TRAFFIC MANAGEMENT AND INFORMATION SYSTEMS
• COMBINED REVEALED AND STATED PREFERENCE NESTED LOGIT ACCESS AND MODE CHOICE MODEL FOR MULTIPLE MASS TRANSIT TECHNOLOGIES
• COMPARISON OF THREE METHODS FOR DYNAMIC NETWORK LOADING
• COMPUTER VISION DETECTION SYSTEM FOR NETWORK MODEL VALIDATION
• COMPUTING FASTEST PATHS IN CONTINUOUS-TIME DYNAMIC NETWORKS WITH PIECEWISE LINEAR LINK TRAVEL-TIME FUNCTIONS
• DECISION SUPPORT SYSTEM FOR SNOW EMERGENCY VEHICLE ROUTING: ALGORITHMS AND APPLICATION
• DEMAND MATRIX ADJUSTMENT FOR MULTIMODAL FREIGHT NETWORKS
• DESIGN AND IMPLEMENTATION OF PARALLEL DYNAMIC SHORTEST PATH ALGORITHMS FOR INTELLIGENT TRANSPORTATION SYSTEMS APPLICATIONS
• DYNAMIC TRIP ASSIGNMENT-SIMULATION MODEL FOR INTERMODAL TRANSPORTATION NETWORKS
• EFFECTS OF FLOW UPDATE STRATEGIES ON IMPLEMENTATION OF THE FRANK-WOLFE ALGORITHM FOR THE TRAFFIC ASSIGNMENT PROBLEM
• ESTIMATION OF ORIGIN-DESTINATION DEMAND FOR DYNAMIC ASSIGNMENT WITH SIMULTANEOUS ROUTE AND DEPARTURE TIME CHOICE
• EVALUATION WITH TRAFFIC ASSIGNMENT UNDER DEMAND UNCERTAINTY
• GENETIC ALGORITHM FOR THE TIME-DEPENDENT VEHICLE ROUTING PROBLEM
• LEAST EXPECTED TIME HYPERPATHS IN STOCHASTIC, TIME-VARYING MULTIMODAL NETWORKS
• MODELING OF NONLINEAR STOCHASTIC DYNAMIC TRAFFIC FLOW
• ORIGIN-DESTINATION MATRICES ESTIMATED WITH A GENETIC ALGORITHM FROM LINK TRAFFIC COUNTS
• PARAMETRIC EVALUATION FOR ROUTE GUIDANCE SYSTEMS WITH ANALYSIS OF SUSTAINABLE DRIVER COMPLIANCE
• SOLUTION ALGORITHM FOR COMBINED INTERREGIONAL COMMODITY FLOW AND TRANSPORTATION NETWORK MODEL WITH LINK CAPACITY CONSTRAINTS
• STOCHASTIC DYNAMIC NETWORK DESIGN PROBLEM
• TRANSIT VEHICLE ARRIVAL PREDICTION: ALGORITHM AND LARGE-SCALE IMPLEMENTATION