Geetam Tiwari and Kalaga Ramchandra Rao
Brief introduction about the project:
This project includes major interventions at two levels – product and process. The product involves use of Intelligent Transportation Systems (ITS) technology, for developing performance indicators for bus systems. At the process level, the aim is to improve the operation of bus by means of branching modules, dealing with new indicators in an existing management system exploiting an existing real time data acquisition system (AVLS).
The objective is to assess some of the existing well known quality-of-service indicators, and to develop new ones. Performance indicators should be clear, easily understandable, and useful to the audience. The main outcome of this research is to develop a computer-based research tool consisting of different modules. This could be integrated into an operational platform for analysis and diagnosis of the quality of service of bus systems lines in different operational use. The applications will be tested in Delhi, and generic modules will be developed for other cities.
DIMTS (Delhi Integrated Multi-Modal Transit System Ltd.) has been managing bus operations of cluster buses in Delhi. The GPS data and AFC data available from Delhi cluster bus system will be used to develop various indicators which measure level of service of Bus system.
A multimodal platform, like ClaireSITI developed in France, is a research tool that allows accessing real-time and multi-sources transport information. All gathered multi-sources data are formalized through a generic data model. It includes a supervisory system which could be linked to any AVL system to provide both on-line and off-line performance analysis and diagnosis of the public transport operations. The ClaireSITI platform includes a supervisory system which is currently implemented in operational context in Toulouse and in Brussels with the STIB multimodal public transport operator (bus, metro and tram). This observatory gives both on-line and off-line performance analysis and diagnosis of the public transport operations.
Our objective in this research is to design a bus fleet "supervision cockpit" for both operators and public transport authorities. First, this project will set up the ClaireSiti platform on the Indian data; and second it will enrich its observatory with new relevant indicators. Performance indicators should be clear, easily understandable and useful to the audience. Four types of indicators are considered for measuring LOS for bus systems:
Operators are interested in maximizing revenue and minimizing operational expenses. While revenue maximizing is dependent on better fleet utilization-operational expenses are dependent on improved speed, minimizing fuel consumption, minimizing delays, minimizing crashes involving buses (compensation paid to the victims), minimizing bus break downs. These can be measured in terms of: 1- Expected system capacity, 2- Expected Operational or commercial speed (Km/h), 3- Average per bus stop and junction delay to a unit bus, 4- Number of fatal and injury crashes /100000 km of bus km, etc.
A module can be developed for the operators to monitor system wide performance and incident detection using GPS and AFC data.
Indicators that measure passenger preference are important for LOS measure. Passenger choice of using a bus system depends on these indicators. These can be measured in terms of: 1- Passenger speed or door to door travel time. 1-Waiting time and comfort, 2-Total walk distance for passengers in a one way trip, 3- Total delay to a unit passenger in a one way trip
Passenger information system module can be developed to give information about bus arrival, expected journey time and access information around the origin and destination bus stops.
Knowing that, a disturbance on a vehicle has consequences on its successors and can disrupt the whole line over long periods. To avoid these disturbances, an accurate diagnosis of the sources and the impact of these disturbances situation are necessary. A special care will be given to these indicators within this project, giving rise to new relevant indicators of: 1- Reliability and 2- Indicators of Resilience
These can be measured by designing special indicators based on the variances of the different stochastic processes which model the flows.
Bus bunching is a consequence and after a cause for such kind of deviations from the schedules/headways. Using the metrics that identify bus bunching and algorithms to correct or minimizing the deviations, would be one of the indicators interesting tool.
What are the impacts of bus systems with consideration of Human as a traveller and as a customer? These can be measured in terms of: 1- Peak Bus Speeds (due to its impact on fatal crashes), 2- Potential for Shift from Private Transport – based on passenger travel time comparison between buses and private vehicles, 3- Potential for retaining existing public transport demand by improving the performance of current bus system, 4- Allowing universal access and barrier free mobility for primarily in terms of disabled friendly infrastructure and fleet.
The analysis of such indicators can deliver different services and utilities: enhance the passenger information in real time to include level of service inside the bus; identify locations prone to bus delays; identify black spot locations(locations experiencing repeated delays), the origin of these malfunction and some elements for enhancement.
WP1 : Data interfaces
Define and model the structure and the functioning of the bus lines within its road and public transport network surroundings and integrate this description within the ClaireSITI platform. Develop the interfaces between the AVL and the ClaireSiti platform.
Offline interface with 25 bus route data tested.
WP2 : Key performance indicators modeling
Assess some of the existing known quality of service indicators and develop new ones. Performance indicators should be clear, easily understandable and useful to the audience. The analysis of the indicators can deliver different services and utilities: enhance the passenger information in real time to include level of service inside the bus, identify locations prone to bus delays, detect black spot locations with the origin of these malfunction and some elements for enhancement.
WP3 : Cockpit Development
Develop different modules which would be integrated into the operational platform for analysis and diagnosis of the quality of service of the bus lines in different operational use. The modules for the operators and the regulators will help to monitor system wide performance and incident detection using GPS and AFC data. The existing Passenger information system which gives information about bus arrival, expected journey time and access information around the origin and destination bus stops, can be complemented.
WP4 : Operational tests
Test the applications in Delhi. DIMTS will participate at the test of the indicators usage and the evaluation of the impact of this new management practice on the organization and the overall performance of the bus system in the city. The evaluation tests will concern not only the efficiency of the indicators but also the supervision cockpit usability by operators and public transport authorities
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