The importance of GPS accuracy for logistics and how it impacts last-mile delivery
FocalPoint CEO Scott Pomerantz discusses the importance of GPS accuracy for logistics and how it impacts last-mile delivery. This article was first published in Warehouse & Logistics News.
The logistics industry, encompassing giants like Deliveroo and Amazon, relies heavily on GPS technology to streamline operations, improve efficiency, and reduce costs. The cost of fuel is one of the largest expenses in this sector, accounting for about 10% of total last-mile delivery expenses. Due to the significant impact of navigation accuracy on operational efficiency, it's crucial to study how precise GPS positioning could impact business costs and performance.
According to the World Bank, today, some 56% of the world’s population – 4.4 billion inhabitants – live in cities. Nearly seven out of ten people will live in cities by 2050, when the urban population is expected to double.
GPS is the most famous of the Global Navigation Satellite Systems (GNSS) and one of the marvels of the modern world. Satellite constellations that provide worldwide position, time, and velocity information are known as GNSS constellations. Since these are low power signals and won’t travel through solid objects, it is normally important to have a clear view of the sky to get an accurate location.
Since its introduction for civilian use in the 1980s, GNSS has created $1.4 trillion in benefits for the U.S. private sector. The annual market is now valued at over €150 billion, through the explosive growth of location-based services offered through smartphones, watches and automotive vehicles. Google maps, Waze, and Uber have become part of our everyday lives and our transportation, logistics, and financial systems are highly dependent on them.
Signal blockage and reflections from buildings, bridges, and trees can significantly compromise GNSS accuracy in urban areas, which in the industry is referred to as signal occlusion and multipath interference. These effects are the primary reason for poor positioning in urban environments and to date have been very challenging problems to solve.
GPS accuracy is becoming increasingly critical, driving innovations that improve transportation efficiency, safety, and sustainability - especially as we advance to a world of autonomous driving.
GPS accuracy is problematic, but what is the cause?
Multipath interference is a major limitation of GNSS receivers today. This occurs when satellite signals reflect off buildings, trees, or other obstacles before reaching the receiver in your smartphone, watch or automobile. These reflected signals can cause significant inaccuracies in the measurements, which degrades the overall performance of a position calculation.
With couriers working daily in the hardest GNSS environments, it becomes almost impossible for companies to know exactly what’s happening as drivers are dispatched. Logistic businesses require systems that function seamlessly in all operational environments, so that end user customers receive the highest-level of customer service and the companies can operate at maximum efficiency.
Efficiency is key to success
There are 1.6 million packages shipped every day by Amazon alone. Customers in urban jungles need parcels delivered accurately to their doors. Each driver is required to deliver between 250-300 packages a day to approximately 200 stops. Efficiency is absolutely key to success.
The cost of poor positioning can be significant. Besides posing safety concerns, positioning errors can also result in substantial economic losses due to inefficient routing, increased fuel consumption, and delays that impact delivery schedules, customer satisfaction, and profitability.
GPS Spoofing
A troubling rise in interference to GNSS known as spoofing is being used by criminal networks, malevolent actors, and fraudsters to broadcast fake satellite signals that confuse receiving devices such as a mobile phone, automobile, aeroplane or ship. How would any logistics company like DHL or JustEat work if GNSS was unusable for a day?
As a form of cyber attack, spoofers attack a GNSS receiver by broadcasting fake satellite signals to override legitimate satellite signals, ultimately confusing the GNSS receiver and causing potentially harmful disruption to the positioning systems.
Spoofing attacks are becoming worryingly frequent, with broadly reported events like the European Union Aviation Safety Agency issuing an alert warning about satellite navigation systems being jammed or spoofed around Ukraine and in nearby regions in 2022. The reality is that these interference events are more common and daily as can be seen on this open source project that maps live interference events such as jamming and spoofing.
Modern vehicles rely on GNSS for route guidance and to determine absolute location for driving assistance systems. Spoofed signals can interfere with the vehicle navigation, ADAS or autonomous driving systems, putting passengers and other vehicles at risk.
The dangers of spoofing were reported back in 2019 when a Tesla Model 3 was experimentally spoofed successfully. Using off-the-shelf hardware and software, fake satellite signals were illegally broadcast by a spoofer, disrupting the behaviour of the vehicle.
This proved the vulnerability of a modern vehicle to an attack, where the spoofer can disrupt the computed location, speed and heading of a victim’s receiver, causing vehicles to believe they are in a different location and even potentially provide false information about road conditions, traffic, or obstacles. Spoofing can also be used as a method for theft and to hide the true location of a stolen vehicle as reported by its onboard security tracking systems.
Today's GNSS receivers must be accurate, reliable, and secure in all environments, including suburban, urban, and skyscraper jungle environments. In order to resolve this challenge, GNSS receivers can be upgraded to interpret satellite signals more accurately. This would be a simple but seismic change for GNSS technology.
Using modern signal processing and machine learning techniques, the problem of multipath and spoofing can be solved, dramatically improving the performance of smartphones, wearables and automobiles in the deepest of urban and forest environments.