C. M. S. L. Sivaram1, M. N. Kulkarni2
Department of Civil Engineering I. I. T. Bombay,
Mumbai-400 076
Tel: 91-022-5767308, Fax: 91-022-5767302
1[email protected], 2[email protected]
Abstract:
Spatial data is the crucial component of a GIS. The important sources of spatial data are the already existing digital files, maps, which can be digitized, and more recently GPS. GPS (mapping type receivers) can be used to map an area and the data can be converted into GIS compatible forms. GPS-GIS integrated systems have some important applications in the field of Transportation engineering. These applications include vehicle tracking system for fleet management, vehicle navigation systems, and network travel time studies. GPS-GIS integrated systems can be used to predict the parameters in the car following theories, improving the trip reporting procedures. The present paper gives some details of these applications and in particular the application of GPS-GIS integrated systems for network travel time studies, which areuseful for quantifying congestion in terms of various parameters. An experiment is also planned for finding the travel time on some of Mumbai’s roads. The results of this experiment are expected to be presented in the Conference.
Introduction
Transportation data is usually associated with spatial data, like traffic counts from particular sites, the traffic volumes along particular roads or links, etc. (Taylor et al, 2000). Geographical Information System (GIS) can be used as a database for storing transportation data. The primary advantage of using GIS as a database for transportation data is the fact that GIS can integrate the spatial data and display the attribute data in a user-chosen format. The chief sources of spatial data are the existing digitized files (e.g.: Topologically Integrated Geographic Encoding and Referencing (TIGER) files in the US). The Global Positioning System (GPS) is widely being used as a tool for collecting the spatial data. Systems which chiefly use GPS as a spatial data source for a GIS are called as GPS-GIS integrated systems. The use of GPS-GIS integrated systems in transportation engineering are described below. An experiment is planned to find the travel time on some of Bombay’s roads and hence to estimate the congestion on the roads. The results of this experiment are expected to be ready for being presented in the Conference.
Applications
In this section, the various applications of GPS-GIS integrated systems in transportation engineering are described.
Vehicle tracking systems
Vehicle tracking systems are usually used for managing a fleet of vehicles. The vehicles of a fleet are fitted with GPS, which usually transmit the positional data of the vehicles to a central station. The central station is a monitoring station, where the position of vehicles is displayed on a GIS map. Vehicle tracking systems will be useful for the police and emergency response services. The central station usually diverts the vehicle nearest to the site, where the vehicles are required. By using a wireless phone service or cellular phone network, real time corrections can be sent to the receivers fitted on the vehicles and better results can be obtained.
Vehicle navigation systems
Vehicle navigation systems are used for guiding vehicles to their destination. These systems usually use GPS or inertial navigation systems or a combination of both for positioning the vehicle. The advantage of using both inertial navigation systems and GPS is that navigation can be continued even when the GPS cannot receive the signals form the satellites due to obstruction. In countries like the US, vehicle navigation systems are used for guiding tourists to different tourist spots. The vehicle navigation systems use a computer, which determines the position of the vehicle, plans the route and gives the directions to the driver. The driver gives the location of his/her destination while starting his journey and the computer guides the driver by giving either audio or and visual instructions. The route the computer plans is usually optimized route; the route is the route optimized for distance or the route can be the most or the least used route (Jurgen, 1998).
The above-described applications are a part of the intelligent transportation systems, where the vehicles are navigated and help is provided to the vehicles, which are stranded due to some problem with the vehicle or any accident. Zito et al, (1995), have studied the usage of GPS for Intelligent Vehicle Highway Systems (IVHS). Much of the research and development work related to IVHS (presently it is known as intelligent transportation systems or ITS) depends upon the reliability of the methods used for locating and monitoring vehicles. Some of their observations and conclusions are:
- GPS receivers, which have the capability of displaying the speed, will be useful for determining the speed of the vehicle, even though the display might show a non-zero value of speed sometimes, when the speed of the vehicle is zero.
- The number of satellites the receiver is able to track (NSAT) and the PDOP give an indication about the reliability of the speed data. It was found that the error in speed increased when the PDOP values were high (greater than three) and the NSAT value was three.
- GPS, when integrated with GIS, is a valuable tool for travel time studies.
- The conclusion that they gave was: GPS stands ready as a valuable tool for IVHS applications, given adequate attention to its possible shortcomings.
Though, the above conclusions were drawn when Selective Availability (S/A) was on, these conclusions are still relevant and valid.
Car following analyses
The basic assumption in car following theories is that the speed and acceleration of a car are dependent upon the vehicle immediately preceding it (in a single lane of traffic). The General Motors Corporation has done some extensive studies of car following behaviour. They have used two-vehicle platoons to estimate driver behavioral responses. The Louisiana State University (LSU) has developed a new technique; it had used GPS to record aspects of vehicle motion, independently, for vehicles under open roadway conditions. A GIS was also used as tool for the creation of mapped road networks, route analysis and linear referencing.
The study involved the use of GPS and GIS to collect and process vehicle movement information. In the system used by the LSU researchers, latitude and longitude coordinate information as well as speed and time data for test vehicles were collected independently. These data were reduced and translated using a GIS linear referencing technique to prepare a set of movement data for each vehicle. The study conducted at LSU has shown that GPS was a viable and valuable tool for the collection of vehicle movement data. The research conducted at LSU has allowed the results of General Motors to be expanded and the results to be further verified through the use of open roadway car following data. They have also found that the price-to-accuracy afforded by GPS was also one of its significant advantages (Wolshon and Hatipkarasulu, 2000).
GPS for trip reporting
The problems with the existing methods of trip reporting procedures are: the poor data quality on travel start and end times, total trip times and destination locations. A project study was conducted in Lexington, Kentucky in fall, 1996 where GPS was used to capture vehicle-based, daily travel information. The project used a computer for computer-assisted self-interviewing, combined with GPS system. Though the design of equipment required the respondents to actively turn the computer on each time they made a private vehicle trip, the GPS component could capture the “actual” travel rather than the self-reported travel. The driver had to actively select the driver and passenger names, and their trip purposes. The GPS component captured date and time, and latitude/longitude data every three seconds when a trip had begun, so that the trip start and end times were passive data elements to the respondent. The advantage of passive data recording is that respondent burden is minimized and the travel times and distances that were collected represent the true picture about the length and duration of the trip.
The usage of computer for computer-assisted-self-interviewing has helped to capture data regarding trip purpose and vehicle occupancy. Having the data regarding the trip purpose, occupancy, together with the route choice and travel speed, would provide planners with the information that could be used in evaluating management systems, designing ITS, etc. To further reduce the burden on the driver, GIS can be integrated with GPS. The GPS data, after exporting to a GIS can be viewed on the map. The use of GIS helps in knowing the destination of the trip, without the driver intervention, and also in knowing the particular route the driver had chosen to reach his destination. Though GIS has not been used in the research mentioned above, its usage for the trip reporting purpose will definitely improve the trip reporting procedure (Murakami and Wagner, 1999).
Network travel time studies
Moving observer methods are commonly used for travel time surveys. In this method, the observer travels in a vehicle, which is a part of the traffic stream and notes the time required for the vehicle to travel between two specified points. The problem with the moving observer method is that to get a representative value of the travel time, different drivers should repeat the method. Another disadvantage of this method is that the exact variation of the speed of the vehicle along the link cannot be studied. The variation of the speed of the vehicle along the network gives an idea about the traffic conditions on the road. Therefore, the moving observer method cannot be used for studying the localized traffic effects. Some of these effects can be overcome by using GPS-GIS integrated systems.
Quiroga and Bullock (1995) have deduced the following, after performing experiments and collecting over 3 million GPS data points over a network of more than 300 miles. They have shown that to detect localized errors, the segment (the road networks are divided into segments whenever particular attribute changes, one such attribute may be the number of lanes on that segment) lengths of the road network should be around 0.2 to 0.5 miles. A sampling rate of 1 or 2 seconds is preferable and the sampling rate should be smaller than half the shortest travel time associated with the segment. In conducting travel time studies using GPS and GIS, the first step is to obtain a good base vector map with links to a database. It is advisable to construct the base map directly form GPS data, GPS data collected during future travel time studies is guaranteed to match the vector base map with in a tolerance defined by the GPS equipment positional accuracy. The major advantage of using a base map produced by a GPS, against previously existing maps is that the positional errors in the existing maps can be overcome.
This new automated procedure provides consistency; fine levels of resolution and better accuracy in measuring travel time and speed than traditional techniques. For detecting localized effects in traffic, detail speed-time or speed-distance profiles along the link are required. These profiles can be easily plotted in a GIS.
The travel times obtained can be used to quantify congestion in terms of parameters like delay and congestion index. Delay is defined as the excess travel time above the minimum (free flow) travel time needed to traverse a network element. Congestion index (CI) is defined as total delay divided by the free flow travel time. Congestion index is a dimensionless quantity, and can be used for comparing the congestion levels on two or more roads, as it is independent of route length, route geometry or intersection control and capacity factors that may distort comparisons of actual travel times and delays at different sites.
To alleviate the problem of congestion, Congestion Management Systems (CMS) needs to be developed. A typical CMS usually collects the travel time data and the congestion parameters are calculated as explained in the above paragraph. The congestion parameters indicate the level of congestion on the roads and necessary control measures can be taken to reduce the congestion.
Planned Experiment
In the experiment that is planned, GPS will be fitted to a probe vehicle and used to collect position, time and speed (of the vehicle) data. The GPS receiver that will be used for this purpose will be Trimble Pro-XR and the GIS software that will be used is TransCAD. TransCAD is the first and only GIS software, designed specifically for use by the transportation professionals to store, display, manage, and analyse transportation data. The Trimble Pro-XR receiver can collect Differential GPS data from the radio beacon at the Mumbai port, so higher accuracy can be obtained
After collecting the data, it will be linearly referenced in TransCAD. The linearly refernced data can be displayed either on the already existing map or can be used to create a new network. The advantage of creating a new map is that the same map can be used in the future for travel time studies. The errors will be reduced if the same map is used.
After the data management, a module in TransCAD will be developed, which calculates the travel time on a particular link. The travel time is the difference between the entrance time and exit time on the link. These times can be found out by interpolating between the two time tags, which are close to the entrance or exit of the link. Once the travel times are obtained, the congestion parameter CI can be used to calculate the congestion on the roads. The results of this experiment are expected by the end of January.
Reference
- Jurgen, R. K. 1998, Navigation and Intelligent Transportation Systems, Pennsylvania: Society of Automotive Engineers, Inc.
- Murakami, E. & D. P. Wagner, 2000, Can using Global Positioning System (GPS) improve trip reporting?, Transportation Research -C, 7C: 149-165
- Quiroga, C. A. & D. Bullock, 1995, Travel time studies with global positioning system and geographic information systems: an integrated methodology, Transportation Research-C, 6C : 101-127
- Wolshon, B. & Y. Hatipkarasulu, 2000, Results of Car following Analyses Using Global Positioning System, ASCE Journal of Transportation Engineering, 126: 324-331
- Zito, R., D’este, G., & M. A. P. Taylor, 1995, Global Positioning systems in the time domain: How useful a tool for Intelligent Vehicle-Highway systems?, Transportation Research-C, 6C: 193-209.
