DEVELOPMENT OF PASSENGER TRANSPORT INFORMATION SYSTEM USING GIS AND GPS

Abstract

Passenger information is vital for developing a user-friendly public transportation system. Passenger information dissemination however is accorded low priority in cities of developing countries such as India due to resource constraints and lack of interest from transit agencies. The ―service for poor‖ image of existing transit systems and absence of reliable information, discourage potential users from using public transit. Websites are rapidly gaining popularity for public transport information dissemination, particularly due to their anytime-anywhere availability, suitability for multimodal applications and support for multilingual interface. While websites are common medium of communication between transit operators and passengers in developed countries, they are rare in most of the Indian cities. Transit on Google Maps provides transit information on internet for over 500 cities globally including nine cities in India. Critical appraisal of available passenger information in Ahmedabad city indicated severe shortcomings of existing systems, particularly with respect to its content and quality. Ahmedabad, like several other Indian cities, has fixed-route regular bus services operated by Ahmedabad Municipal Transport Service (AMTS) in conjunction with Bus Rapid Transit System (BRTS) operated by Ahmedabad Janmarg Limited (AJL). Information on conventional buses is available from printed transit timetables, website of AMTS and Google Transit. Information on BRTS is available from the website of AJL in addition to its on-board and in-terminal PIS. Printed transit time-tables are not easy to use and information content therein is incomplete. It was observed that merely 40% of bus stops in a given route are listed in the timetable. Google Transit‘s trip planner is certainly superior in terms of user-friendliness and information content, when compared with the websites of public transport agencies and their printed transit timetables. However, the map-based search of bus stops was able to locate 62.8 % while the text-based search, using name of bus stop as keyword, was merely able to identify 50% of total bus stops. It was observed that merely 48% of stop names have a similarity score greater than 95% on Jaro Winkler similarity, while 33% have Levenshtein distance above 95%. Implying that not only the conventional key-word ii based searches are liable to fail, but they will also need significant efforts to rectify the errors in database. Multi-modal information incorporating both conventional buses and BRTS is not available from any source in Ahmedabad city. Moreover, the estimate of travel time during peak and off-peak hours from transit systems which is necessary for passenger route choice decision was also not available from any information source. Geographic Information System (GIS) and Global Positioning System (GPS) technologies in recent years have extensively penetrated in to transportation space, becoming a backbone of several ITS implementations. GPS technology is being commonly adopted for Automatic Vehicle Location (AVL) systems by public transport operators for fleet operation and management, even in India. Large volume of GPS data is thus continuously being collected by transit agencies. GPS data logged by AMTS and BRT buses was used in this study for evaluating travel speeds of public transport systems and assigning network impedances for estimating travel times on AMTS and BRTS routes. The study estimated day-to-day variability, hour-to-hour variability, and space-time variations in travel speed in AMTS and BRTS network. It was observed that average travel speed on AMTS and BRTS buses in Ahmedabad city is 21.10 km/hr and 23.77 km/hr respectively with corresponding standard deviations at 8.3 km/hr and 5.77 km/hr. AMTS network has relatively higher inter-day as well as intra-day variations in travel speed as compared to BRTS network. Link travel speeds estimated in this study were used to assign network impedances for morning-off peak hours (06:00 AM – 09:00 AM), morning peak hours (09:00 AM – 11:00 AM), inter-peak hours (11:00 AM – 06:00 PM), evening peak hours (06:00 PM – 08:00 PM) and evening off-peak hours (08:00 PM – 12:00 PM). GIS was not only useful in creating spatial database but was also used for spatial queries, network analysis, map composition and geo-statistical analysis. Information on transit systems obtained from multiple sources needs to be integrated in order to minimize errors in database creation. Very High Resolution Satellite image (Cartosat-1 + LISS-IV) was used as base map for identifying the location of bus stops. Automated / Semi-automated procedures were developed to prevent errors in creation of spatial database of public transport network and to expedite process of updating database. iii Oracle 11g ORDBMS was used for organisation of spatial and non-spatial datasets used by the PIS. Web-based PIS was developed for Ahmedabad using GIS and GPS technologies. Web GIS was used to spatially enable website of PIS. GPS data was used to assign network impedances for computation of travel time during different hours of the day. In order to provide user-friendly and attractive website, Oracle‘s ADF Faces Rich Client Components were used in the website. Oracle MapViewer‘s Oracle Maps technology provided high-performance interactive AJAX-based web mapping client to support map navigation and visualisation of spatial data. Model-View-Controller architecture driven website not only provides information on transit routes and schedules, but also supports multi-modal transit trip planning using the regular fixed-route and rapid transit bus services. Transit nodes can be located by map-based or text-based search implemented in the web-based PIS. Text-based search is enabled by keywords as well as by name of locality. In order to avoid typographical errors in keyword-based search on bus stop names, Jaro-Winkler distance of greater than 80% was adopted. Map-based search determines the location of nearest bus stop from user specified location on the satellite image of the study area. Capability to search correct location of transit ingress and egress nodes is necessary for using public transport. General Service information, which is usually published by transit agencies in form of printed transit time tables, is important for web-based PIS also. Websites can be useful for sharing most up-to-date and accurate information on operational routes, route maps, en-route stoppages and route timetables. Web-based PIS further implemented transit trip planner enabling users to plan their trip by providing choice of mode (AMTS, BRTS, car, walk), time of departure or arrival and maximum allowable walking distance, while minimizing time or distance of travel. Multi-modal trips including journey by both, AMTS and BRTS vehicles, can also be planned using transit trip planner. Network impedances as estimated by GPS data analysis for AMTS and BRTS buses, are used for estimating In-Vehicle Travel Time. Arrival time of AMTS bus at intermediate stops were computed using time of departure of bus from its origin stop and travel time from origin stop to its iv intermediate stop while visiting all preceding stops, as determined by solving for travelling salesman problem. Web-based PIS thus developed, not only meets the requirements of regular transit users but also provides information at pre-trip planning stage to incidental users and visitors to the city. Mobile application was developed on Android operating system to support information requirement during the journey, when the internet access is not available. While the website can be accessed over internet even from the mobile devices, users of GPRS connectivity for data access over mobile phones in India are very low. Mobile PIS integrated device GPS in locating nearest transit stop. It also provides a transit trip planner providing AMTS bus route between a pair of origin and destination stops. Furthermore, a domain-specific ontology for public transport systems was developed, which was further integrated with the domain-ontology of urban features with an objective of supporting multi-modal public transport information retrieval. The ontology thus developed was formalised using Web Ontology Language. In order to evaluate the capability of ontology in passenger information retrieval, the proposed ontology was implemented for five regular bus service routes and one bus rapid transit route in Ahmedabad city. Public transport ontology and its integration with urban features ontology, has potential to service the passenger information requirements. Ontology is capable of providing information on general service operations, itinerary planning and multimodal trip planning, as desired by commuters during pre-trip stage of a transit trip. Ontology, not only enables sharing of data across multiple agencies, but also improves its understanding by sharing meaning of the content of information. Ontology thus developed, can be extended to incorporate other related concepts such as real time arrival information, weather information, road conditions etc. Moreover, the flexibility offered by RDF/OWL languages enable addition of further details to individual concept e.g. tourist attraction concept can be expanded to include details on opening hours, significance of features, etc. An Android Application was developed for mobile devices to use ontology for finding transit nodes and plan for multimodal trips. SPARQL queries using ARQoid API was used to query ontology model to retrieve passenger information from ontology.