Space Division Freeway Traffic Management Meets Mass Mobility Requirements


Since transportation industries emerged as the backbone of well-performing modern economies, it is essential that transportation performs at high levels of productivity and is able to keep up with the exceptional trend toward demanding mass mobility. Unfortunately, though, traditional transportation infrastructures do not provide the functionality required to handle current and future traffic loads.  Traffic flow tends to break down and is trapped into stop-and-go conditions.  Slow-moving traffic causes lost time for society, the transportation industry and individual drivers.  Frustrated drivers tend to practice risky driving behavior and cause fatal crashes.

As the population across the US and the world continues to rise at an alarming rate, so do traffic loads on all roadways, which indicates that the traffic dilemma will get worse unless a paradigm shift for traffic management is defined and implemented.

Hansa Tek Netics LLC (HTN), an entrepreneurial research and development company in California that is well versed in process automation and digital technology applications, has investigated for the past ten years the full spectrum of ongoing traffic flow phenomena and created breakthrough solutions.  HTN’s innovative visions for advanced management of traffic flow on freeways and county roads are manifested in three US patents., 

Observing that expansions of existing physical infrastructures cause high costs and achieve limited improvements, HTN envisions solutions that allow existing physical infrastructures to remain unchanged and introduce technology-enabled virtual infrastructures that are superimposed on existing infrastructures.  While physical infrastructures are stationary assets that continue serving the transportation industry, virtual infrastructures resemble invisible, software-defined forward-moving platforms, which provide intangible space holders for vehicles and are designed to move at pre-set velocities. Vehicles can enter them and travel along with them without experiencing traffic, inhibiting congestion and traffic breakdowns.  Lane throughput and traffic flow velocities exceed traditionally expected growth rates and meet mass mobility requirements while saving lives.

HTN created meticulous designs of virtual infrastructures for traffic on freeways and county roads.  This article describes design features and performance aspects associated with HTN’s tech-enabled freeway traffic management concept.   

Current Traffic Flow Dilemmas on Freeways

The purpose of freeways is to provide an intersection-free transportation mode for commerce and the society as a whole with the objective to offer high lane capacity (i.e., high throughput), high velocity (i.e., low travel time), and safety. These goals were achieved as long as the traffic loads remained modest. It has long been observed that, with rising traffic loads and correspondingly higher vehicle densities on all freeway lanes, traffic tends to slow down, forms slow-moving traffic jams causing top-and-go situations, and eventually, the traffic breaks down and collapses completely.  

Stop-and-go conditions demand drivers’ intense attention to avoid crashes.  In addition, long travel times cause frustrated drivers to become impatient and engage in risky driving behavior. The California Department of Transportation (Caltrans) reports that accidents and fatal car crashes on California’s freeways are rising as traffic loads and congestion are rising. Traffic crashes are the largest cause of death in the US. All combined, transportation yields poor productivity for commerce and for the economy as a whole.  

  • Limited Impact of Network Analysis and Predictive Analytics  

Network analysis is being considered for predicting traffic loads and redirecting traffic to less congested roads.  The idea is to lessen traffic congestions and optimize the balanced utilization of the entire network of interconnected roadways.  This approach can offer an interim relief but as traffic loads continue to rise, the entire network of roadways will experience congested situations.

  • Limited Impact of Automotive ACC and CACC Technologies

Current attempts to cure the problem are focused on improved automotive technologies, including automated cruise control (ACC) and cooperative ACC (CACC).  These technologies are expected to enhance driver comfort and safety and to allow shorter following distances at higher velocities.  ACC- and CACC-enabled vehicles improve human driving habits and can raise throughput and average velocities. As traffic loads keep rising, these methodologies will reach their limits.  It can be concluded that eventually, technology must replace the human factor completely to meet mass mobility requirements.

  • Limited Impact of Autonomous Driving Technology

Autonomous driving technology, which eliminates the human factor, is typically viewed as the ultimate solution to raise throughput, velocity and safety on all roads including freeways.  Early-stage autonomous vehicles (AV) are used to successfully illustrate AV characteristics and their potential beneficial impact on traffic performance.

A decisive characteristic of AVs is their extremely short following distance at high velocities, which is indeed a critically important feature in achieving high lane capacity, high throughput, and short travel time.  AV technology developers are performing field tests and demonstrations with closely packed caravans of AV-enabled vehicles.  Experts are envisioning platoons of 25 vehicles and more to illustrate the capability of AV technology.

HTN believes that as the human factor is completely eliminated, AV technology is taking the traffic scenario to a completely new level of traffic dynamics.  It is believed that technology developers must transition their strategic thinking from current vehicle-focused strategies to traffic-flow-focused strategies.  Traffic dynamics must be arranged to take full advantage of AV technology possibilities.  For example, the question arises how vehicles can change lanes and join fast-moving platoons if platoons entail 25 and more closely stacked vehicles.  

HTN analyzed the full range of anticipated AV-enabled traffic flow dynamics and found that digital technologies can be employed to create virtual infrastructures as engineered frameworks for moving AV-enabled vehicles in disciplined platoon arrangements.   

HTN’s Space Division Freeway Traffic Management (SDFTM)

While the transportation industry envisions solutions involving automotive technologies, HTN takes a completely different route.  Under the leadership of Dr. Georg Schlueter and Dr. Reza Hosseini, HTN addresses traffic flow and envisions ideal conflict-free solutions, which consider the power of virtual infrastructures and results in HTN’s novel Space Division Freeway Traffic Management platform (SDFTM).

HTN’s traffic configuration meets mass mobility requirements and can be facilitated using digital technologies, such as AI and IoT.  HTN specifies that the platoons can embody 8 or less vehicles and that platoons need to be separated to allow system dynamics involving primarily lane changes.

The basic feature of HTN’s SDFTM is its virtual infrastructure. The latter is an invisible framework resembling a series of invisible platoons moving along the freeway lane at a preset velocity. The invisible platoons resemble space holders for AVs, which can enter empty space holder positions. The process of entering and exiting platoons is accomplished in an automated fashion. When a vehicle has left a platoon, the remaining AVs must move up within the platoon so that the empty space holder positions are always toward the end of a platoon to ease the AV entry procedure.

The platoons travel at slightly different velocities on adjacent lanes so that VS can line up with empty positions when AV occupants want to change lanes.  The velocities are staggered such that the number one freeway lane features the highest velocity.  It is envisioned that Lane 1 can accommodate a vehicle density equivalent to 160 AVs per mile traveling at a velocity of 100 mph, which results in a lane capacity of 16,000 Avs per hour.  This compares to 4.000 vph at 40 mph and 2,000 vph at 80 mph under current human-controlled manual driving.  In either case, HTN’s SDFTM system proves an improvement equivalent to 1,000%.

  • SDFTM Performance Creates Environmental and Societal Benefits

Under SDFTM conditions, the substantially reduced travel time will boost the transportation industry’s annual productivity growth.  As the US transportation industry represents 5.6% of the economy’s Gross Domestic Product, the affect on the nations annual productivity growth can be markable and stem inflation accordingly.

Environmentally, the US transportation sector adds 27% to the nation’s greenhouse gas emissions. Substantially less stop-and-go conditions on freeways enabled by HTN’s SDFTM will substantially reduce the transportation sector’s emissions.

Statistics reveal that the US endures 42,000 deaths caused by car crashes each year, causing 127,000 injuries and 1,100 deaths.  It is anticipated that HTN’s SDFTM can reduce drivers’ impatience and their risky driving behavior thus reducing injuries and deaths by 50%, i.e., injuries may be reduced by 65,000 and the number of deaths can be reduced by 550 per year across the US. 

Digital Twin Simulation of Commercial SDFTM Implementation

The practical feasibility of HTN’s SDFTM hinges on the completion and perfection of AV technologies.  AV Technology developers should be able to view the ultimately intended performance characteristics of AVs within HTN’s SDFTM system.  Thus, the development of a Digital Twin simulation of combined AV and SDFTM technologies should be considered as a first step toward a commercial implementation. 

All Rights Reserved © copyright, 2023, Hansa Tek Netics LLC, San Marcos, California

  • Paten 1: Multi-Lane Traffic Management System for Platoons of Autonomous Vehicles
  • Patent 3: Method of generating Bidirectional Green Waves of Traffic by Alternating Lights by Zones.
  • Caltrans, August 2023
  • Recovered from the Internet at httsp://
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