“Automated Dynamic Routing Unit And Method Thereof” in Patent Application Approval Process (USPTO 20240085193): Swiss Reinsurance Company Ltd.

2024 APR 03 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- A patent application by the inventors DI LILLO, Luigi (Zurich, CH); MAFFETTI, Matteo (Zurich, CH); TISSEUR, Riccardo (Zurich, CH), filed on September 25, 2023, was made available online on March 14, 2024, according to news reporting originating from Washington, D.C., by NewsRx correspondents.

This patent application is assigned to Swiss Reinsurance Company Ltd. (Zurich, Switzerland).

The following quote was obtained by the news editors from the background information supplied by the inventors: “Navigation systems are being increasingly used to provide route planning, location information, directions to or maps of places of interest, and other details of a journey. Some navigation systems provide detailed directions from a source location (or current location) to a destination location, and may thus help a driver navigate through areas with which they are not familiar. Based upon the source location and the destination location, the navigation system generates an optimum route between the two points. Typically, the route is optimized for distance, time or avoiding freeways or tollways, etc. Route optimization is typically performed by checking a number of possible routes, and selecting the “best” route based on one or more optimization criteria and/or specific parameter values constellations or specific constellations of parameter threshold values. Various techniques have been developed for constructing a route which is the most desirable according to predetermined optimization criteria. For instance, the shortest possible route may be chosen to minimize the distance traveled or high-speed roads may be chosen to minimize travel time. Other navigation systems may utilize real-time traffic congestion data in an attempt to determine a route that may help to guide the vehicle away from traffic jams. In addition, optimization criteria have been provided for avoiding freeways, maximizing use of freeways, avoiding tollways, for example.

“Drivers and passengers assume a certain degree of risk of injury or property damage when travelling by vehicle caused by the occurrence of an impacting accident event. This risk may be mitigated by reducing or eliminating certain contributing factors. For example, a driver may avoid risky behavior, such as driving while intoxicated, driving while tired, or driving while texting. As another example, a driver may mitigate the risk of serious injury by driving a car with safety features such as airbags, seatbelts, and antilock brakes. However, certain risk factors may not be mitigated. For example, the very nature of a vehicle may present certain inherent risks. A typical car may weigh thousands of pounds and may not always maneuver or stop quickly. When travelling at even a moderate speed, a collision may result in serious physical damage to the vehicle and serious injury to the occupants. Further, a driver or passenger of a vehicle may have no control over perhaps the greatest risk factor involved with driving: other drivers or passengers in other vehicles. Further, environmental factors may contribute to the relative riskiness or safety of an area. For example, a driver approaching a one-lane bridge in a valley between two hills may not see the bridge until the vehicle has crested the hill. If the distance between the hill crest and the bridge is short, the driver may have little time to react if a second driver is approaching the bridge from the other direction. A driver may have little to no control over these environmental factors. Moreover, environmental factors contributing to the riskiness of an area may not always be readily apparent, observable, or quantifiable. For example, even if a civil engineer identifies a number of one-lane bridges as potentially dangerous, it may technically be difficult to quantifying how risky these one-lane bridges are relative to one another. Additionally, the engineer may overlook a two-lane bridge that is seemingly safe, but which is in actuality riskier than many of the identified one-lane bridges. Because the envi-ronmental factors contributing to risk may not always be 50 apparent, observable, or quantifiable, these environmental risk factors may go unnoticed. Thus, engineers and govern-ment officials may never identify certain high-risk areas, much less identify solutions to mitigate the risk and improve the safety of the areas for vehicle drivers and passengers. Further, in some situations, a driver or passenger may be exposed to high risk traffic situations that occur without advance notice and in a seemingly random fashion or at least driver-independent but merely time- and/or location-dependent. When relying on recommended routes from a navigation application or navigator during the course of travelling through unfamiliar locations, these high risk traffic situations may significantly increase travel times. Further these high risk traffic situations may be potentially dangerous to travel through. The routes may pass through hazardous areas, such as high risk intersections, road segments or portions of certain roads, abnormal traffic patterns, exit ramps, circular traffic flows, road construction areas, and the like, which may expose the driver or passenger to the risk of property damage, injury, time delay stemming from accidents, and the like.

“In summary, there is an inherent risk involved with driving the vehicle along any of the routes, i.e. an inherent physical probability to be affected by an occurring accident event. Thus, driving a vehicle, almost worldwide, means that the driver somehow must or may want to reduce and optimized the risk exposure by selecting an optimal rout involving a minimized risk occurrence and/or transfer the remaining or otherwise not evadable risk, for example, by transferring or ceding the impact caused by the remaining risks by means of appropriate risk transfer systems or by risk cover provided by automated vehicle insurance systems fencing the user of a vehicle traveling a route with a certain risk-exposure impacted by an occurring physical accident event along said route traveled. The inventions should also provide a system automatedly providing a user with an optimized risk-cover (i.e. having an optimized route-based and/or usage-based pricing) upon selecting a more optimal route, i.e. a rout with a reduced inherent risk exposure. It should be mentioned that the probability of an accident occurrence on a specific route does not need to be the same for different vehicle drivers but may depend on the user-specific characteristics parameters measured or otherwise measured by the system. Thus, for an older vehicle driver having slower reaction times, the measured risk-exposure may be lower at low speed routes though there may occur more events having the possibility to become an accident event, where, however, for a younger driver, the risk exposure may be lower at a high speed route, where the traffic flow is more uniform.

“The rate for the risk-transfer is normally assigned by a human expert, e.g., an auto insurance agent, deciding on whether a specific driver is a high or low-risk driver. Traditionally, the assigned human expert’s rating considerations depend on only few different factors. For instance, one of the most common risk factors includes personal considerations that are used to calculate a driver’s risk is age. For example, Drivers between the ages of 25 and 55 are considered to be in the prime age bracket and are considered a lower risk. Gender is another factor, since women drivers are usually considered as a lower risk in general, however, this is slowly changing because more and more registered drivers are women. Single parents are also considered as less of a risk. Risk transfer systems or insurances take into consideration that a single parent is already responsible enough to parent a child alone, so they are more likely to be financially responsible as well. In a similar vein, married drivers are normally rated better for their car risk-transfers or insurance policies than a single driver does. They are thought to be more stable than single drivers due to the fact that they often have more responsibilities. A single driver of the same age with the same driving record as a married person will be assessed as a higher risk simply because of their marital status.

“Also, driving history plays a central role in the rating. If a driver has any type of driving violation attached to his driving history, he will be rated to a higher risk-transfer rate than someone whose driving record has no infractions. Any prior accidents that a driver has been involved in will be reflected on his driving record, which increases his risk rating. In some risk-transfer systems, even a severe penalty is put on such a driving record for up to five years after the accident has occurred. Any type of speeding ticket is normally also part of the driving history and raises a driver’s risk factor. Speeding reflects carelessness and a disregard for the driving laws and official risk limits set in place by the government. Normally, risk-transfer systems will consider any type of speeding ticket as a bad reflection of the driver. This is calculated into the risk rating and will ultimately increase the rating or risk-transfer premium. Driving under the influence of alcohol or drugs, as reflected by the driving history, which may not only cause a moving violation ticket, but may also cause driver’s license to become suspended or, worse case scenario, revoked. Therefore, as per traditional systems, the better a driving record or driving history is free of accidents, tickets, moving violations, the lower the risk rating will be which will result in lower insurance rates.”

There is additional background information. Please visit full patent to read further.”

In addition to the background information obtained for this patent application, NewsRx journalists also obtained the inventors’ summary information for this patent application: “It is one object of the present invention to provide an o provide an automated dynamic routing unit and an automated dynamic routing method for providing an automatedly optimized route (typically the route having the minimal probability (risk) for a physically impacting accident event to a selected motor vehicle and/or the route with the most minimized CO₂-footprint and/or minimal CO₂ emission/output for a selected motor vehicle) between a departure location and a destination location. In particular, the optimized route should be provided by automated technical means, i.e. machine-based optimized, having a minimized actual-measurable probability of an occurring accident event with a physical impact on the vehicle driving the route at the related temporal and geographical dependent contemporaneousness. Thus, it is an object of the invention to provide an automated system enabling a driver or an autonomous driving system to select the best possible route based on its exposure to traffic crash risk (event occurrences) along a specified route, more particularly together with providing trip feedback and/or safe alternate recommendations. The crash risk measure can e.g. be generated either “directly” in the case the system is measuring the number of incidents that occur on specific roads (or has otherwise access to such measuring data) or “indirectly” i.e. by first automated analyses and/or automated recognition of the correlation of road contexts (features that are measured and/or generated by the system based e.g. on the measured or recognized number of stops, intersections per kilometer, etc.) with the measured probability value of having a crash in region for which crashes and/or claims data are assessable and subsequently by generalizing the correlations learned to regions in which crashes and/or claims measuring data are e.g. too few or even absent. The used data can e.g. also be accomplished and/or refined and/or weighted/calibrated based upon historical data e.g. accessed from crashes database information. The system is, inter alia, based on the insight that a small set of locations typically accounts for a considerable portion of total occurrences of accident events in a traffic stream (typically the top 10% of crash locations approximately account for more than 66% of all the crashes). Further, by using the smart phone’s built-in sensors or other measuring signals e.g. coming from connected cars’ hardware devices, the inventive system should be enabled to run unobtrusive in the background and automatically detects when a driving session begins and ends. It then should be able to tracks the entire trip and provide the driver automatedly with a route risk score, which, inter alia, can be measured by monitoring past and/or historical traffic accident events along the route. The present disclosure generally relates to reducing vehicle collisions and increasing vehicular safety and, further, to providing automated near real-time feedback on route safety and associated risks.

“According to the present invention, these objects are achieved, particularly with the features of the independent claims. In addition, further advantageous embodiments can be derived from the dependent claims and the related descriptions.

“According to the present invention, the above-mentioned objects for the vehicle embedded or mobile-phone-based, automated dynamic routing unit, and corresponding method thereof, associated with a vehicle and/or a user along a route traveled between a departure location and a destination location, are achieved, particularly, in that destination input parameters of a destination location and/or departure location input parameters of a departure location are received by a routing interface, one or more routes between the departure location and the destination location are generated by a routing generator, in that a measuring unit dynamically measures and forecast for each of the generated routes time- and location dependent measured exposure values given by measured and forecasted time- and location dependent probability values quantitatively measuring the probability for occurrences of impacting accident events along the one or more routes, the impacting accident events occurring temporal and spacial coincidentally at a respective location of the vehicle and/or user traveling along a route, wherein the measuring unit measures and forecasts said time- and location dependent probability values by processing measured route parameters associated with the generated routes, wherein the measured route parameters comprise at least a-priori of navigation risk parameters, weather condition parameters, driving area parameters, condition parameters, number of intersections, traffic congestion parameters and/or further risk-exposer related measure parameters along the routes, in that the measuring unit generates an aggregated exposure score measure for each of the routes based on the measured route parameters and/or the time- and location dependent exposure values, in that a route selector automatedly selects the most optimized route among the generated routes based on the aggregated exposure score measure values and/or the measured route parameters and/or the time- and location dependent exposure values and/or user-specific parameter values, and in that the automated dynamic routing unit provides the selected optimized route as output signaling on the routing interface.

“According to the present disclosure, the above-mentioned objects for the vehicle embedded or mobile-phone-based, automated dynamic routing unit and the automated dynamic routing method for providing an optimized route between a departure location and a destination location are achieved in that for minimizing the probability of being impacted by an occurring accident event, have relevant consequences and advantages for both human drivers and autonomous driving systems. Herein, instead of focusing on the mitigation of the physical impact of an accident event, such a risk-transfer solutions, the present dynamic routing unit is able to proactively effect on the prevention for the occurrence of accident events, and thus enable the drivers (or generally a user traveling from one location to another location) to enjoy safer trips by minimizing the probability of being involved in risky situations. The present dynamic routing unit minimizes both a-priori and real-time occurring risks (i.e. the physical probability to be impacted by an occurring accident event) along a route like hazardous weather conditions, driving area, dangerous roads (multiple connotations of danger), traffic congestion and/or the physical state of the user. The present dynamic routing unit may further be used for generating an optimized dynamic risk-transfer cover using mobile telematics data capturing etc. The present dynamic routing unit may not only be limited to road-based vehicle safety but also be applicable for maritime risk routing, and the like. It is to be noted that the vehicle embedded or mobile-phone-based, risk-based automated dynamic routing unit can be realized as a hardware- and/or software-based vehicle embedded unit or as a mobile application running on a mobile phone, such as a cellular smart phone.

“Further, the present invention disclose a system and method that generally is able to reduce physical vehicle collisions, and particularly, inter alia, to identifying or selecting a travel route for a vehicle (or a user, e.g. traveling from a starting hiking point to a destination hiking point, or kind of transportation means, such as bikes, ships, vessels, planes or any other flight transportation vehicle) that avoids traversing the areas that are prone to vehicle collisions. As discussed, hazardous areas (e.g., high risk intersections, road segments or portions of certain roads, bridges, abnormal traffic patterns, exit ramps, circular traffic flows, road construction areas, parking lots, and other transportation infrastructure) are prone to induce, or be associated with, vehicle collisions. A relative amount in which an area is hazardous can vary with time. As an example, a roadway may pose minimum driver risk during the daytime, but, based on any number of factors (e.g., poor illumination); the roadway may be associated with an increased number of vehicle collisions. Upon receiving a request for a desired destination for vehicular travel, both historical route measuring data and near real-time or real-time route measuring data (in particular telematics measuring and sensory data) for a number of potential travel routes is accessed. One way to measure how hazardous an area can e.g. include the generation of a risk index for the area that is based on the historical route data and/or near real-time route measuring data. The term “risk index”, as used herein, is not a human-empirical parameter, but explicitly denotes a machine- and measuring devices-based physical and thus by means of the used technical means (measuring devices, sensors, telematics, machine-learning structures etc.) automatedly reproducible, quantified physical measure. The risk index quantifies how prone or exposed the area is to vehicle collisions. When risk indices are generated for more than one area, the risk indices may be compared to one another to enable a comparison of the relative riskiness of several areas.”

There is additional summary information. Please visit full patent to read further.”

The claims supplied by the inventors are:

“1. A vehicle embedded or mobile-phone-based, automated dynamic routing unit associated with a vehicle and/or a user along a route traveled, the dynamic routing unit providing an optimized route between a departure location and a destination location, the automated dynamic routing unit comprising: processing circuitry configured to implement a routing interface for receiving destination input parameters of a destination location and/or departure location input parameters of a departure location, and wherein the automated dynamic routing unit comprises a routing generator for generating a plurality of routes between the departure location and the destination location, a measuring unit dynamically measuring and forecasting for each of the generated routes time- and location dependent measured exposure values given by measured and forecasted time- and location dependent probability values quantitatively measuring the probability for occurrences of impacting accident events along the routes, the impacting accident events occurring temporal and spacial coincidentally at a forecasted location of the vehicle or user traveling along a route, and the measuring unit measuring and forecasting said time- and location dependent probability values by processing measured route parameters associated with the generated routes and/or user-specific parameters, the measured route parameters comprising at least a-priori navigation risk parameters related inherent risks along a given route at least being based on statistical accident rate data and/or real-time accident event data and/or accident severity data and/or accident related data corresponding to particular route sections, weather condition parameters, driving area parameters, condition parameters of the routes at least comprising comprises road composition data and/or the age of the road segments and/or the composition of the road surface, number of intersections and/or traffic congestion parameters, wherein the automated dynamic routing unit comprises a data acquisition unit for continuously acquiring route and/or user-specific parameters along the routes by collecting measured telematics data via sensors embedded in a cellular smartphone or embedded in mobile telematics devices associated with the vehicle, the sensors at least comprising a GPS sensor, and, wherein the measuring unit provides an aggregated exposure score measure for each of the routes based on the measured time- and location dependent exposure values, and a route selector for selecting the a most optimized route among the routes based on at least the time- and location dependent measured exposure values along each route and/or the aggregated exposure score measures of the routes, and providing the selected optimized route as output on the embedded routing interface unit, wherein the dynamic routing unit comprises a routing layer as data processing core, wherein waypoints characterizing a route are generated based on a forecast and derived traveling conditions providing a spatial multistage grid by generating a finite set of location nodes and a finite set of linking edges based on specified departure and arrival geographic locations, the departure and arrival geographic locations specifying one node each and along the route and adding new nodes for each stage, wherein a perpendicular to the multistage grid is defined starting from the nominal route from the specified departure and arrival geographic locations and the multistage grid is composed by a finite number of stages where each node of one stage is connected to all the nodes in the next stage, wherein to generate the optimal path between the source and destination locations, each edge is associated with an overall measure for navigating through a selected edge and a pareto front is generated, wherein a set of pareto efficient route solutions is generated through a routing process in a selected scenario, and wherein the pareto route solutions are dynamically grouped based on the navigation risk to select the optimized route by the route selector.

“2. The automated dynamic routing unit according to claim 1, wherein the most optimized route is the route having a minimal measured aggregated exposure score value indicating the route with the lowest measured and forecasted probability for a physical impact to the vehicle and/or user caused by an occurring accident event.

“3. The automated dynamic routing unit according to claim 1, wherein, for selecting the most optimized route, the route selector comprises a trigger for selecting the most optimized route among the routes by using the values of the aggregated exposure score measure of the routes, wherein the most optimized route is triggered by the route having the smallest aggregated exposure score measure value, or by the route having the smallest maximum value of a time- and location dependent measured exposure values along each route.

“4. The automated dynamic routing unit according to claim 1, wherein the measuring unit provides the aggregated exposure score measure for each of the routes by aggregation of the time- and location dependent exposure values along each route.

“5. The automated dynamic routing unit according to claim 1, wherein the automated dynamic routing unit comprises a data acquisition unit for continuously and dynamically acquiring and/or monitoring measured route parameters along the routes, wherein actual route parameters are, at least partially, measured by one or more measuring devices and/or sensors associated with the vehicle and/or the mobile device and/or the user and/or external contextual measuring systems associable with the routes.

“6. The automated dynamic routing unit according to claim 1, wherein the automated dynamic routing unit comprises a route monitoring unit for continuously monitoring the route parameters along the routes to detect and measure changes in the measured values of the route parameters along the routes, wherein in response to changes in at least one of the route parameters, the route monitoring unit communicates the changes to the measuring unit, wherein the measuring unit dynamically re-determines one or more of the time- and location-dependent measured exposure values along one or more routes based on the changed route parameters and provide a dynamically updated aggregated exposure score measure for the routes concerned, wherein, in response to at least one of changed route parameters and the updated exposure score measures for each of the routes, the route selector determines a dynamically updated optimized route among the one or more routes.

“7. The automated dynamic routing unit according to claim 1, wherein the automated dynamic routing unit comprises an automobile interface unit to communicate at least one of a notification or control instructions to an automobile control unit to display the optimized route or an updated optimized route.

“8. The automated dynamic routing unit according to claim 1, wherein the automated dynamic routing unit comprises an automobile interface unit to communicate at least one of a control instructions or the optimized route to an automobile control unit, the automobile control unit being connected to or comprising an Advanced Driver Assistance System (ADAS) or an autonomous driving system of the vehicle, wherein the optimized route is automatically chosen to be driven by the autonomous driving system or upon selection by the user.”

There are additional claims. Please visit full patent to read further.

URL and more information on this patent application, see: DI LILLO, Luigi; MAFFETTI, Matteo; TISSEUR, Riccardo. Automated Dynamic Routing Unit And Method Thereof. U.S. Patent Application Number 20240085193, filed September 25, 2023 and posted March 14, 2024. Patent URL (for desktop use only): https://ppubs.uspto.gov/pubwebapp/external.html?q=(20240085193)&db=US-PGPUB&type=ids

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