TRACER: In-Vehicle, GPS-Based Wireless Technology for Traffic Surveillance and Management. - eScholarship

The fundamental principle of intelligent transportation systems is to match the complexity of travel demands with advanced supply-side analysis, evaluation, management, and control strategies. A fundamental limitation is the lack of basic knowledge of travel demands at the network level. Modeling and sensor technology is primarily limited to aggregrate parameters or micro-simluations based on aggregate distributions of behavior. Global Positioning Systems (GPS) are one of several available technologies which allow individual vehicle trajectories to be recorded and analyzed. Potential applications of GPS which are relevant to the ATMS Testbed are implemented in probe vehicles to deliver real-time performance data to complement loop and other sensor data and implementation in vehicles from sampled households to record route choice behavior. An Extensible GPS-based in-vehicle Data Collection Unit (EDCU)has been designed, tested, and applied in selected field tests. Each unit incorporates GPS, data logging capabilities, two-way wireless communications, and a user interface in an extensible system which eliminates driver interaction. Together with supporting software, this system is referred to as TRACER. The design and initial implementation tests Testbed are presented herein. This research is a continuation of PATH MOU 3006; selected portions of the interim report for that MOU are repeated here to provide a complete overview of the research effort

[1]  Darcy M. Bullock,et al.  Travel time studies with global positioning and geographic information systems: an integrated methodology , 1998 .

[2]  Randall Guensler,et al.  Elimination of the Travel Diary: Experiment to Derive Trip Purpose from Global Positioning System Travel Data , 2001 .

[3]  Laura L Higgins,et al.  Assessment of METROLift Automatic Vehicle Location System , 1995 .

[4]  Tae-Kyung Sung,et al.  Development of a map matching method using the multiple hypothesis technique , 2001, ITSC 2001. 2001 IEEE Intelligent Transportation Systems. Proceedings (Cat. No.01TH8585).

[5]  J K Shadewald.  GIS BASED MODEL INTERFACING: INCORPORATING EXISTING SOFTWARE AND NEW TECHNIQUES INTO A STREAMLINED INTERFACE PACKAGE , 2000 .

[6]  E. Murakami,et al.  Can using global positioning system (GPS) improve trip reporting , 1999 .

[7]  Nelly Kalfs,et al.  Global Positioning System as Data Collection Method for Travel Research , 2000 .

[8]  Shauna L. Hallmark,et al.  Accuracy Issues with Route Choice Data Collection by Using Global Positioning System , 1999 .

[9]  Elaine Murakami,et al.  Global Positioning Systems for Personal Travel Surveys - Lexington Area Travel Data Collection Test: Appendixes , 1997 .

[10]  Liping Fu,et al.  Assessing Expected Accuracy of Probe Vehicle Travel Time Reports , 1999 .

[11]  Piyushimita Thakuriah,et al.  FREQUENCY OF PROBE REPORTS AND VARIANCE OF TRAVEL TIME ESTIMATES , 1997 .

[12]  Francois Dion,et al.  Metropolitan Model Deployment Initiative : San Antonio evaluation report , 2000 .

[13]  R. R. Joshi,et al.  A new approach to map matching for in-vehicle navigation systems: the rotational variation metric , 2001, ITSC 2001. 2001 IEEE Intelligent Transportation Systems. Proceedings (Cat. No.01TH8585).

[14]  Yanying Li,et al.  Link travel time estimation using single GPS equipped probe vehicle , 2002, Proceedings. The IEEE 5th International Conference on Intelligent Transportation Systems.

[15]  Ram M. Pendyala,et al.  Analysis of Global Positioning System-Based Data Collection Methods for Capturing Multistop Trip-Chaining Behavior , 1999 .

[16]  Robert J Benz,et al.  Development and Benefits of Computer-Aided Travel Time Data Collection , 1996 .

[17]  E Michler.  STATISTICAL ANALYSIS OF FLOATING CAR DATA SYSTEMS , 2001 .

[18]  Shawn Turner.  ADVANCED TECHNIQUES FOR TRAVEL TIME DATA COLLECTION , 1996 .

[19]  James E. Moore,et al.  Use of Los Angeles Freeway Service Patrol Vehicles as Probe Vehicles , 2001 .

[20]  K El-Araby,et al.  TRADE-OFFS BETWEEN ROBUSTNESS, ACCURACY, AND RESOLUTION FOR FLOATING CAR AND LOOP DETECTOR DATA FUSION , 2001 .

[21]  Michael F. Goodchild,et al.  GIS and Transportation: Status and Challenges , 2000, GeoInformatica.

[22]  Sean T. Doherty,et al.  MOVING BEYOND OBSERVED OUTCOMES: INTEGRATING GLOBAL POSITIONING SYSTEMS AND INTERACTIVE COMPUTER-BASED TRAVEL BEHAVIOR SURVEYS , 2001 .

[23]  Chen zewang,et al.  Development of an algorithm for car navigation system based on Dempster-Shafer evidence reasoning , 2002, Proceedings. The IEEE 5th International Conference on Intelligent Transportation Systems.

[24]  Jim Gallagher,et al.  TRAVEL TIME DATA COLLECTION USING GPS , 1996 .

[25]  Hesham Rakha,et al.  VEHICLE PROBES AS REAL-TIME ATMS SOURCES OF DYNAMIC O-D AND TRAVEL TIME DATA , 1993 .

[26]  Frank S. Koppelman,et al.  Field Test of the Effectiveness of ADVANCE Dynamic Route Guidance on a Suburban Arterial Street Network: ADVANCE Project Document 8463.01 , 1996 .

[27]  Darcy M. Bullock,et al.  A DATA MODEL FOR MANAGING GPS TRAVEL TIME DATA , 1998 .

[28]  William L Eisele,et al.  TRAVEL TIME DATA COLLECTION HANDBOOK , 1998 .