In order to provide better quality of service while at the same time cutting costs, many fleet management companies are turning to machine learning and IoT technologies to improve various aspects of their day-to-day operations such as vehicle maintenance, route optimization, logistics, vehicle tracking and behavioral monitoring among others.
1) More HI-TECH Integrations: AI in Advanced Driver Assistance Systems
The rise and evolution of Advanced driver-assistance systems (ADAS) will continue in 2018 as well. More companies will look at developing and deploying such systems that leverage Artificial Intelligence, deep learning and machine vision technologies and are far more superior than previous generation of ADAS solutions. From sensor driven systems such as lane changing assistance to visual analytics based systems that can identify any objects on the road or its conditions to avoid accidents, ADAS will keep getting smarter and offer much more safety for drivers and other road-users. Not to mention the cost efficiency it will bring with saving on maintenance and un planned downtime across the fleet.
2) SD-WAN is not Just for the Enterprise Branches, Its coming to the roads!
With the continuing adoption of Intelligent Transportation Systems and rapidly improving wireless communications networks, more and more automation and IoT devices will begin to appear frequently both within fleet vehicles and roadside infrastructures, enhancing connectivity both on and off the road. Advances in WiFi and cellular technologies such as 4G LTE and the upcoming 5G will also enable on-the-move software-defined wide area networks (SD-WAN’s) allowing for consistent and economical V2X networking, better bandwidth for multimedia data transfer to fleet managers and enhance road safety for all vehicles including the commercial fleets.
3) More Autonomous Truck Pilot Programs To Pop-Up
Driver-less vehicles is probably the biggest talk in the fleet management industry at the moment for particularly being the pinnacle of automation currently in this domain. With a handful of trial schemes already going on, such as that of autonomous trucks built and operated by Embark delivering Frigidaire refrigerators from Texas to California, expect to see more manufacturers coming up with advanced autonomous trucks and more companies opting in to do autonomous fleet pilot programs such as the one mentioned before.
Of course the state laws do not permit use of absence of human from the driving seat as yet, but we certainly can expect to see fast advancements in autonomous driving technologies and gradual success in building trust on these initiatives with public and therefore the legislators. It make take some time though and may not happen quickly in 2018.
4) More Real-time Analytics, More Safety.
The safety of drivers, vehicles, and assets is of critical importance to all commercial and industrial fleet management or distribution organisations and, throughout 2018, expect to see an increasing number of safety enhancements and functions coming within both vehicles and hardware. Events reporting systems, for example, are capable of recording lane departures and other such deviations along journeys and presenting them as event logs for analysis and evaluation. This data could then be used in order to determine whether certain drivers would benefit from educational driver safety programs or some other form of safety training.
Accident reduction schemes are also likely to feature heavily throughout 2018 as advances in on-board audio and visual technologies are allowing control center personnel to provide environmental and traffic updates to drivers in real-time, keeping them aware of any potential hazards along their route. In-vehicle sensors will also most likely play a large part in notifying the driver of any potentially hazardous driving conditions. External temperature sensors could alert drivers when the there is an elevated risk of ice, snow, fog, or other environmental hazards.
5) Push for Operational Efficiency Still A Major Driving Force
Technologies such as those featured in telematics and fleet management systems will also likely become much more widespread as the year goes on, with a particular focus on collecting actionable data from the implementation of IoT technologies, fuel-saving schemes, route optimization systems, vehicle and driver data and any other information they are capable of collecting. Companies will continue to enhance their profitability from fleet operations by consistently looking to use better technology and make the best use of it.
6) Vehicle IoT, Video Analytics to Power Improved Driver Behavior Monitoring Solutions
One of the more recent trends within fleet management is behavior monitoring and tracking thanks to the proliferation of integrated on board computers with LTE/4G and GPS, visual analytics software, G-sensors and IP cameras. While keeping track of the well-being of drivers can help to reduce accidents and keep drivers, assets, and vehicles safer, but also help cut down on wasteful activities such as unnecessary fuel consumption. By providing and implementing enhanced tracking solutions, fleet operators could provide much more accurate information to drivers about their location, including live route optimization.
Another reason why advanced behavior monitoring technologies that use G-Sensor data as well as visual intelligence to prompt fleet operators and drivers of their behavior will likely become a widespread feature for a large proportion of commercial fleet managers. By continuous automated monitoring for road safety and predictive maintenance and recording certain features of their driving, how many stops they’ve made or breaks they’ve had as well as bodily signs such as heart rate, behavior monitoring systems could then attempt to predict driver fatigue and send alerts to drivers notifying them they need to take a break or stop for the night.
7) Predictive Maintenance
With the increasing adoption of IoT sensors and devices, predictive maintenance has become one of the hottest topics among nearly every industry being touched by Internet of Things and wireless communications technologies. Using on board sensors and Can-Bus, fleet managers can use the data collected to predict when vehicles, may need repairs or servicing and schedule downtime to get this done rather than have the equipment fail or malfunction and force them to suspend activities.
Within fleet management, the use of predicative maintenance will likely be adopted further as the technologies that enable it become much more widespread and integrated into a larger number of fleet management systems. Using predictive maintenance, the life-cycles of both vehicles and technological systems could be extended significantly through strategically scheduled downtime while also having the potential to substantially cut equipment and replacement costs.