Exploring smarter solutions for public transportation

Congested roads and traffic jams cost American drivers over $100 billion a year in wasted fuel and lost time. According to APTA’s Transit Saving Report, a two-person household can save, on the average, more than $10,174 a year by downsizing to one car. There is a significant positive need to motivate commuters to reduce the use of the private vehicles and make use of the public transport instead. Unarguably, the public transit systems should go through a transformative change for reliability, efficiency and personalization of the commuter’s experiences.

Recently, there have been significant advancements in the use of smart computing and Internet of Things (IoT) paradigms to improve transportation systems. Public transit systems connect to the cellular networks with the use of wireless machine-to-machine (M2M) solutions. These networks are real-time, ubiquitous and reliable. Using the data collected from IoT paradigms, the 5 As’ principles of smart computing – Awareness, Analysis, Alternatives, Actions, Auditability is applied. The applications built on the combination of IoT and Smart Computing technologies have a potential to intelligently support a variety of use cases such as safety systems, operational excellence, fuel efficiency and predictive maintenance.

Vehicle health monitoring systems improve the safety with the use of diagnostics and prognostics to fix faults before they are an issue. The telematics data from vehicle sensors can be used to build failure prediction models, analyze the incidents and to optimise the performance at the vehicle component level. Additionally, by extracting unique features from the readings of smartphones sensors and the telematics data, driving behavioral patterns can be modelled. The combination of vehicle health monitoring and driving behaviour modelling can potentially lead to many powerful use-cases which can optimise the predictability, improve the safety and reduce the cost of public transportation systems. With the fine-grained driving behaviour monitoring approach, a considerable reduction in fuel consumption patterns and fuel economy can be achieved. Transit agencies can smartly allocate the lesser maintained vehicles to expert drivers for careful handling and avoid wear and tears. Transit agencies can provide specific interventions to enhance situational, real-time awareness of physical environments, climatic conditions and traffic congestions to the drivers. Suitable interventions and training can be planned to improve drivers’ awareness of their driving habits so as to prevent potential accidents.

While commuting is the fifth most time-consuming activity (6.5 hours per week) per person globally, the static and disparate information, old ticketing systems and inefficient crowd management have inversely affected the use of public transportation by the commuters. Ever increasingly, the commuters use smartphones to manage their travel, wherever and whenever the public transport cannot provide them with the convenience they seek. With the use of mobile computing, real-time data and Internet of Things (IoT) paradigms, several user scenarios can be engineered to personalize the commuting experiences. Awareness can be provided to familiarize them with various commuting options and co-modal services available in a city - Supplying information on the combination of public transport modes to complement their travel and improving efficiency, lowering costs and travel time they can save on their commute. The IoT can also provide data to build solutions to improve predictability of the commute and feature real-time route alternatives. The perception of the efficiency of public transport and service quality can be communicated to build the trust. Additionally, information about environmental impact with the use of public transport can be shared to motivate the commuters.

The use of Smart Computing and IoT in the domain of Public Transit Systems holds promise, as it would be useful for developing both assistive and informative technology for the users. Further developments in the fields of sensing and communication, analytics and machine learning coupled with the increasing availability of computational power on the device as well as cloud storage will pave the way for exploring new vistas and development of smarter solutions for public transportation.

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