Indian cities are struggling with a rising number of vehicles on the road and poor public transportation systems, which will ultimately hamper economic growth and worsen air quality. What is needed to keep pace with the growth is an intelligent, technology-based transportation system that provides a complete view of transit and traffic data to enable better forecasting, analysis and management of traffic and reduce emissions. This will not only offer environmental and quality of life benefits to citizens, but economic benefits in the form of reduced infrastructure and congestion costs and economic development.
In the coming years, as India becomes more and more urbanised, urban areas will play a critical role in sustaining a high rate of economic growth. But for this to happen, cities must function efficiently – such that their resources are used to maximise their contribution to the nation’s income. A city’s efficiency greatly depends upon the effectiveness of its transport systems in moving people and goods around the city.
Urban India has seen a 15% per annum growth in motorised transport. If we look at the existing modal split, we find that the share of mass transport is well below the desired range whereas the share of personalised transport is above the optimal range in most Indian cities. The level of infrastructure investment required to accommodate this growth is difficult to afford. Like other global cities, Indian cities have not been able to add new roads to keep up with the avalanche of new vehicles. Consequently, the existing transportation network is inadequate and many cities are facing the problems of congestion, pollution and insufficient parking, along with a public transportation system that is over its capacity and difficult to use. In this paper we discuss how Indian cities can support growth while reducing environmental impacts.
Creating a Smarter Transportation Infrastructure to Support Growth
India’s cities need to have a better understanding of the overall movement of people in and around the city and the interdependence of multiple modes of transportation in order to more effectively balance supply and demand and manage these movements. To gain greater insight into mobility patterns, cities must integrate sensors that are built into the physical infrastructure, using vision-based systems, vehicles as mobile sensors and computer-aided decision-making tools that are based on specific real-world scenarios. Public transportation systems can greatly help to alleviate traffic congestion in a city if their operations are managed efficiently. But the solution goes beyond integrating sensors: a best-of-breed transportation management system requires the integration of other capabilities – data, analytics, mobile and social, decision-making and operations – along with the ability to manage it all.
When a city integrates sensors into its systems and starts to analyse the resulting data, it provides transportation managers with a far clearer view of the current situation. For instance, a large city in Europe uses an analytics solution that enables near real-time collection, aggregation and analysis of huge volumes of people movement data. This “city in motion” solution calibrates data against surveys and other sources and then converts it into demand models that the city can use to optimise its transit systems. Using aggregated mobile phone location and transit system data, the solution creates a heat map that depicts the density of people on the roads during different periods of the day, such as morning and evening commutes. It can also drill down to show individual patterns of movement; for example, the city uses the data to scientifically model from where and when commuters are travelling to optimise the bus routes that will connect to a new metro rail line.
To manage its public transportation system efficiently, a provincial-level city in China uses an advanced analytics platform to understand ridership levels as well as traffic and usage patterns across the city’s transportation systems. This powerful solution helps the city’s transportation administration officials accurately identify and forecast transportation demands and take proactive measures to improve and adjust the transportation infrastructure as needed. For instance, if analysis indicates that during certain times and days of the week, a certain bus line is more congested than others, officials can determine the precise number of lines to add, reconfigure routes using less congested areas and modify schedules to ensure that only a certain number of buses are on the transport networks at various times of the day. By optimising capacity, routes and schedules, the city can encourage the use of public transportation over private vehicles, reduce the number of vehicles on the road and improve traffic flow to help alleviate the city’s traffic congestion.
To gain greater insight into mobility patterns, cities must integrate sensors that are built into the physical infrastructure, using vision-based systems, vehicles as mobile sensors and computer-aided decision-making tools that are based on specific real-world scenarios. But the solution goes beyond integrating sensors: a best-of-breed transportation management system requires the integration of other capabilities – data, analytics, mobile and social, decision-making and operations – along with the ability to manage it all.
Increased efficiency and sustainability, along with lower economic costs, are just a few of the many benefits cities stand to gain when implementing a smarter transportation management infrastructure. Proactive planning, improved traffic forecasting and management, greater system-wide visibility and more effective use of the existing transportation infrastructure can lead to dramatically improved situational awareness and decision-making for cities. Citizens can benefit from lower congestion, shorter travel times, increased safety and improved incident response times, as well as reduced emissions and noise, all of which can greatly improve the liveability of a city.
Cities that invest in smarter transportation systems will see a clear return on their investment. Reduced vehicle use has many economic benefits including reduced transport network and infrastructure costs and less pollution, not to mention the business and economic development engendered by such cost and quality of life benefits.
Lowering the Economic Costs of Congestion
Congestion costs time and money and is a drain on the economy. As a May 2012 The Times of India article indicated, the cost of pollution, accidents and congestion adds up to more than 10% of India’s gross domestic product (GDP). However, a 10% reduction in traffic during congestion hours and peak demand periods will almost eliminate all congestion. Eliminating congestion can lead to a 2% increase in regional GDP. Indian cities cannot afford to make the mistakes made by developed countries when building their transportation networks. Every investment has to create efficiencies and support economic development.
Cities that invest in smarter transportation systems will see a clear return on their investment. Reduced vehicle use has many economic benefits including reduced transport network and infrastructure costs and less pollution, not to mention the business and economic development engendered by such cost and quality of life benefits. Cities struggling with congested transport networks have a further incentive to make public transportation more attractive. Schedulers can place buses where they are most needed to ensure they operate at full capacity without wasting time, fuel and money. This will help ensure that commuters consistently arrive for work ready to be fully productive.
Reducing Environmental Impact
Air pollution caused by traffic is cause for serious concern from both an environmental and economic standpoint. In October 2013, thick smog blanketed parts of China for two days, blocking road, train and air traffic, and forcing the closure of primary and secondary schools. The visibility in urban areas was less than 50 metres. Residents and traffic police in these areas were forced to wear masks to protect themselves from the foul stench and adverse health effects of the smog.
Smarter traffic management will have a significant impact on reducing emission rates. Cities can promote highly efficient public transport and improve the flow of traffic to reduce idling vehicles. Smarter cities can use GPS-based tools that measure transport network conditions, speeds, travel times, road closures and road work performance. Such tools can help drivers choose a route that leaves a minimal environmental footprint and provide them with environmentally relevant real-time transportation data.
Building a Resilient, Sustainable Transportation Infrastructure
Intelligent transportation systems give planners and responders a comprehensive look at the state of their city’s roadways at the ground level. But not all systems are created equal. What do cities need to build a resilient, sustainable infrastructure that provides essential services that are flexible and efficient? An intelligent, future-oriented transportation system that uses the latest technology can help cities perform advanced traffic analysis and optimisation for better decision support. It can help cities increase situational awareness across the entire transportation network and analyse traffic performance to improve the travel experience. It can also serve as a tool to centralise the monitoring of vehicles and estimate transit and arrival times.
When evaluating an intelligent transportation system, Indian cities should look for standards-based integration, which makes it possible to aggregate data from a wide variety of traffic and transport network data capture systems spanning multiple device types and vendors. This aggregation helps provide a unified view of traffic data that can be a valuable tool to gain actionable intelligence. Centralising access to this wealth of traffic-related data, combined with the ability to analyse both historical traffic patterns and real-time data, gives cities an opportunity to not only improve traffic congestion in the short term, but also to address long-range policy goals. Armed with reports that monitor traffic performance and patterns over time, cities can make significant progress in cutting congestion, emissions and noise.
Using Predictive Analytics to Manage Transportation
Intelligent traffic management based on precise forecasting techniques can help cities anticipate and avoid traffic congestion and possibly reduce the volume of traffic, resulting in a more sustainable transportation network. IBM has conducted multiple pilots to predict and manage traffic flow and transport network congestion. These pilots have demonstrated how the city can anticipate, better manage and, in many cases, avoid traffic jams and trouble spots across the city by using analytics technology. The city’s traffic engineers were able to predict traffic volume and flow with over 90% accuracy up to 30 minutes in advance. This technology would allow travellers to plan ahead and determine whether they should leave at a different time, plan an alternate route or use a different mode of transportation.
To improve public transport services, the Dublin City Council in Ireland sought a way to dynamically monitor the movement of each of the city’s 1,000 buses and better gauge if each one was operating on time. The city deployed an intelligent traffic control solution that uses geospatial data from GPS-equipped buses to visually display the near real-time position of each bus on a digital city map. Controllers can locate areas experiencing delays at a glance and instantly drill down to live camera feeds to identify root causes. Predictive analytics take into account speed, traffic flow and other factors to continually generate up-to-date estimates for bus arrival and transit times.
How Can Technology Help?
Indian cities are reinventing themselves. They are reimagining essential systems, infrastructure and service delivery to promote growth, sustainability and enhanced quality of life. To improve transportation management, ease traffic flow and enable continued growth, cities need to know where citizens are trying to go and what may stand in their way. By integrating traffic and transit data and sharing that information with citizens, cities can reduce congestion and plan proactively for the future. The intelligent transportation family of solutions integrates both the traffic and transit domains to provide a complete view of the transportation network. It offers capabilities for the management of traffic operations in order to help reduce traffic congestion, improve incident response and traffic flow, and proactively manage traffic conditions to enhance the travel experience for commuters. The solution implements capabilities for the management of transit operations, which can help to provide current situational awareness of the operations, identify and correct events and performance issues, and proactively manage schedule deviations. These capabilities will also contribute significantly towards improving the commuter experience.
An intelligent, future-oriented transportation system that uses the latest technology can help cities perform advanced traffic analysis and optimisation for better decision support. It can help cities increase situational awareness across the entire transportation network and analyse traffic performance to improve the travel experience. It can also serve as a tool to centralise the monitoring of vehicles and estimate transit and arrival times.
In addition, intelligent transportation is designed to be an ideal platform for building transportation management centre solutions by leveraging a documented programming model to build integrations with data capture solutions and device control applications in the transportation domain. Further, it offers predictive analytics functionality that, in addition to helping traffic and transit operation roles, also enhances the ability of multimodal travel planning applications to help deliver more accurate information to citizens.
References
Dash, Dipak K (2012). “India Loses ` 60,000 Crore Due to Traffic Congestion: Study”, Times of India, May 31.
Kharola, P S, G Tiwari, and D Mohan, Dinesh (2010), “Traffic Safety and City Public Transport System: Case Study of Bengaluru, India”, Journal of Public Transportation, 13(4):63-91, http://tripp.iitd.ernet.in/publications/paper/safety/JPT13-4_khrola.pdf
Vijayakumar, N and G Mehendiratta (2011) “Role of ICT in Sustainable Transportation,” University of Boras.
Additional Resources
“Stockholm, Smarter Transportation”, video, http://www.youtube.com/watch?v=SQX_dy9fI-Q.
“Singapore: A Smarter City Powered by IBM”, video, – http://www.youtube.com/watch?v=vcjFGn3YBg8.