The trucking and logistics industry is built upon constant innovation in pursuit of efficiency, speed, and safety. Modern long-distance truck drivers now operate highly advanced machines that would be barely recognizable to their driving ancestors only a few decades ago. Modern commercial vehicles are assisted by advanced computers and monitored extensively. The trucking industry always keeps moving forwards. Here is a quick guide to some of the technologies influencing the modern field of trucking. Read on to learn more.
Vehicle Tracking
Almost all large trucking companies insist that all of their fleet machines are fitted with some kind of vehicle tracker device. Modern commercial vehicle tracker devices record the route, speed, and sometimes even the fuel consumption of the machine they are fitted into. This information is then relayed back to trucking companies and can be accessed during court cases and government investigations, if necessary. Trucking companies use vehicle tracking devices to find optimal routes, prevent drivers from driving in an unsafe manner, and ensure that drivers are taking their legally required breaks. These devices are now an industry standard.
Situational Awareness Cameras
Large commercial vehicles have historically had very bad situational awareness. While the limited rear vision and view of the immediate underside of trucks is not a problem when driving on motorways, it can severely impact safety when vehicles are being driven in crowded city centers or construction sites.
The best modern heavy goods vehicles are equipped with a network of cameras that enable drivers to get an almost 360-degree view of the exterior space around their vehicles. These cameras can also be used to back up any insurance claims that carrier companies need to make.
Truck companies tend to be held responsible for the majority of crashes involving their vehicles, regardless of whether it was their drivers at fault. The capture of video footage can be used to defend the conduct of a driver and their employing company in court.
Collision Avoidance Systems
Most top of the range heavy goods vehicles come equipped with some form of collision avoidance system these days. These collision systems were developed in response to a large number of rear-end crashes that heavy vehicles are typically involved in. Modern collision avoidance systems usually work using the RADAR principle, or a similar light-based beam reflection principle. A beam of light or a sound wave is emitted, which then bounces off any object it encounters. By measuring the time it takes the beam to bounce back onto a receiver, a computer can assess whether a collision is about to take place.
Although some collision avoidance systems activate an alarm when they detect a potential collision, others are far more ‘involved’ in the avoidance process. These involved systems activate the truck brakes if they sense an oncoming object. Some even more intrusive (and helpful) systems log the instances of potential crashes so that a driver can be trained to avoid them in the future.
Electric Vehicles
Electric vehicles are nothing new. The first truly practical electric road vehicles were developed in the 1870s. There was a time when you were almost as likely to be run over by an electric car in New York City as you were by a petrol vehicle. Pioneers, like Robert Anderson and Brighton’s Magnus Volk, developed a truly practical battery-powered cars and vans. Electric vehicles were quite swiftly adopted and adapted for commercial use, usually delivering light loads within city limits. Until recently, however, electric vehicles were nearly useless for intercity and international commercial conveyance.
Huge advances in battery and motor technology, spurred on by a growing understanding of climate change, have provoked the development of a whole new generation of truly long-range electric trucks.
Tesla has unveiled a semi-truck capable of near-conventional levels of performance. Mercedes have been hot on the tesla tail with the development of its own vehicle. Other large companies, like Navistar, are following suit. Large logistics companies are queuing up to order electric vehicles to replace their gas-guzzling fleets of diesel trucks.
Dynamic Routing
Dynamic routing is extremely popular in the modern logistics and trucking industries. Generally speaking, there are two kinds of routing used in the trucking industry: static and dynamic. If a company chooses to structure deliveries statically, it will send drivers to set pickup and drop-off points along set routes every day. This is a simple and useful way of working when the number and location of pickup and drop-off points rarely change.
Dynamic routing involves the calculation of new, optimized routes, as a reaction to an ever-changing environment. Modern delivery windows are getting smaller, and companies are taking on more varied and mutable groups of clients. Dynamic routing programs take in data about client locations, delivery windows, traffic, weather, and load type. These programs then use this data to create the optimal route for each driver in real-time. Ideally, all vehicles in a fleet will be as full as possible at any given time and use as little fuel as possible to get where they need to go.
Dynamic routing is essential for companies that offer next-day delivery. Using algorithms to predict ideal routes, dynamic routing software enables delivery promises to be met each time a job is taken on.
Driver Scorecarding
Driver scorecarding is the use of vehicle tracking, cameras, and collision avoidance data to create a ‘profile’ for each driver that is working for a company. This profile can then be used to assess the competency of each driver. Company leaders can use scorecards to focus their training and onboarding efforts.
Driver scorecarding has been criticized by some truckers that are worried about an increasingly impersonal and surveillance-driven workplace culture. Some trucking companies even pride themselves on offering their employees a surveillance-free working day. Companies ideally need to figure out a way of finding a middle ground between the allowance of driver freedom and the gathering of useful information. Although data can help to drive useful training methods, it can also be seen as invasive.