Berkeley, CA, United States
Berkeley, CA, United States

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The following are disclosed: Vehicle parking detection, sensors and an On-Board Device (OBD) to create a parking session. Radars, microwave antennas, rechargeable power supplies and their power management circuits. A localized communications protocol between the wireless nodes and repeaters within a wireless network is disclosed. Wireless sensors and wireline sensors. The networks and/or systems may support parking spot management/monitoring, vehicle traffic analysis and/or management of stationary and/or moving vehicles, monitor storage areas and/or manage production facilities. These networks and/or systems may be operated to generate reports of incorrectly parked vehicles, such as reserved parking spots for other vehicles, vehicles parked in multiple parking spots and/or overstaying the time they are permitted to park.


A package, wireless sensor module, wireless sensor node and wireline sensor node are disclosed including a radar configured to embed beneath vehicles in pavements, walkways, parking lot floors and runways referred to herein as in ground usage. An access point interfacing to at least one of the sensors is disclosed to provide traffic reports, parking reports, landing counts, takeoff counts, aircraft traffic reports and/or accident reports based upon the sensors messages regarding the radar and possibly magnetic sensor readings. A runway sensor network is disclosed of radar sensors embedded in lanes of at least one runway for estimating the landing count and/or takeoff count effect of aircraft.


The invention includes using multiple wireless vehicular sensor nodes to wirelessly receive multiple, time-interleaved vehicular waveform reports from the nodes. Each vehicular waveform report approximates a raw vehicular sensor waveform observed by a magnetic sensor at the node based upon the presence of a vehicle. The vehicular waveform reports are products of this wirelessly receiving process. The invention includes apparatus supporting the above outlined process. The vehicular waveform reports may be time synchronized.


Grant
Agency: National Science Foundation | Branch: | Program: SBIR | Phase: Phase I | Award Amount: 146.24K | Year: 2012

This Small Business Innovation Research (SBIR) Phase I project will pursue an innovation that can dramatically improve traffic mobility and safety. This study is based on an open wireless sensor network platform that supports many sensing modes, and time-stamps all measurements. The sensing modalities include magnetic sensors that detect vehicles; new micro-radar sensors that detect bicycles, pedestrians and parked vehicles; GPS-based sensors that locate vehicles; conflict monitoring cards that measure traffic signal phase; and environmental sensors that can be added as they become cheaper. The proposed concept can be incrementally deployed to augment sensing capability and coverage area; it can be deployed over all major arterials in a city within one month. Being time-synchronous, different data sources can be combined to develop innovative applications about intersection safety, arterial delay and emissions, signal coordination, transit priority, vehicle location, and parking availability. Today, this information is unavailable (e.g. intersection safety) or needs special purpose systems (e.g. pedestrian presence. The broader impact/commercial potential of this project will benefit city administrations. Poor intersection control causes 5 to 10 percent of traffic delay on major roads. Congestion costs the peak-period traveler 38 hours of travel time and 26 gallons of fuel annually. 36 percent of crashes are intersection-related. Faced with this high cost of poor road management, city administrations are looking to analyze data to efficiently deliver transportation services. This "analytics" approach brings rich dividends through improved mobility and safety. However, collecting the data to implement this approach today is prohibitively expensive. Existing intersection safety products are primarily Red Light Enforcement (RLE) cameras. RLE is controversial. An Insurance Institute of Highway Safety (IIHS) report states: More than 25 percent of drivers oppose red light cameras; they believe that cameras can make mistakes, are used to generate revenue for governments rather than for safety; lead to more crashes because drivers speed up to beat the red light or stop suddenly and are rear-ended; or invade privacy.


Grant
Agency: NSF | Branch: Standard Grant | Program: | Phase: | Award Amount: 146.24K | Year: 2012

This Small Business Innovation Research (SBIR) Phase I project will pursue an innovation that can dramatically improve traffic mobility and safety. This study is based on an open wireless sensor network platform that supports many sensing modes, and time-stamps all measurements. The sensing modalities include magnetic sensors that detect vehicles; new micro-radar sensors that detect bicycles, pedestrians and parked vehicles; GPS-based sensors that locate vehicles; conflict monitoring cards that measure traffic signal phase; and environmental sensors that can be added as they become cheaper. The proposed concept can be incrementally deployed to augment sensing capability and coverage area; it can be deployed over all major arterials in a city within one month. Being time-synchronous, different data sources can be combined to develop innovative applications about intersection safety, arterial delay and emissions, signal coordination, transit priority, vehicle location, and parking availability. Today, this information is unavailable (e.g. intersection safety) or needs special purpose systems (e.g. pedestrian presence.

The broader impact/commercial potential of this project will benefit city administrations. Poor intersection control causes 5 to 10 percent of traffic delay on major roads. Congestion costs the peak-period traveler 38 hours of travel time and 26 gallons of fuel annually. 36 percent of crashes are intersection-related. Faced with this high cost of poor road management, city administrations are looking to analyze data to efficiently deliver transportation services. This analytics approach brings rich dividends through improved mobility and safety. However, collecting the data to implement this approach today is prohibitively expensive. Existing intersection safety products are primarily Red Light Enforcement (RLE) cameras. RLE is controversial. An Insurance Institute of Highway Safety (IIHS) report states: More than 25 percent of drivers oppose red light cameras; they believe that cameras can make mistakes, are used to generate revenue for governments rather than for safety; lead to more crashes because drivers speed up to beat the red light or stop suddenly and are rear-ended; or invade privacy.


Grant
Agency: NSF | Branch: Standard Grant | Program: | Phase: SMALL BUSINESS PHASE II | Award Amount: 537.17K | Year: 2013

This Small Business Innovation Research (SBIR) Phase II project should dramatically improve intersection safety and mobility in a practical way. Safety is measured by the risk of collision between pedestrians, bicycles and vehicles; safety is improved by better signal timing, warnings, and possibly enforcement. Mobility is measured by vehicle delay, number of stops, and throughput; it is improved by better signal control, and adaptation to current traffic conditions. Today traffic data collected in 300,000 intersections in the US consists of manual vehicle counts conducted every couple of years; bicycles or pedestrians are almost never measured. Traffic signal settings are based on these inadequate measurements. Safety risk is measured by counting crashes; there is no account of near-crashes. Measurement of intersection performance (level of service, throughput, and delay) is rarely attempted since it requires continuous monitoring of traffic. Nevertheless major signalized intersections do detect the presence of vehicles, and do receive push button signals from pedestrians if they wish to cross. A few intersections have bicycle detectors. What is lacking is the means to collect these measurements and intelligently fuse them to estimate the traffic state in real-time. This innovation is the only system that can do this.

The broader and commercial impact of this innovation is the savings in lives and lost productivity. Inefficient operation of intersections is costly. Poor intersection control causes 295 million vehicle-hours of traffic delay, and annually costs the peak-period traveler $710 in additional travel time and fuel. An estimated 2.3M crashes occurred at intersections in 2008, accounting for 40 percent of 5.8M crashes, 7,421 fatalities (including 4,092 pedestrians) and 733,000 crashes with injuries. Unless urban roads are carefully managed, these mobility and safety costs will only increase as cities try to provide convenient multimodal transportation choices to all citizens, whether it?s by driving, walking, bicycling, or transit, leading to greater interaction between the modal types. But careful management requires the ability to evaluate, predict and identify means to improve intersection mobility and safety. Today the data needed to conduct such studies on a routine basis are not available anywhere. This innovation is the only system that can provide such data in real time. It will be an exceptionally low-cost system that can be installed in a few hours, with data available the next day. This innovation will address the emerging requirements of the recent federal MAP-21 legislation.


Grant
Agency: National Science Foundation | Branch: | Program: SBIR | Phase: Phase II | Award Amount: 450.59K | Year: 2013

This Small Business Innovation Research (SBIR) Phase II project should dramatically improve intersection safety and mobility in a practical way. Safety is measured by the risk of collision between pedestrians, bicycles and vehicles; safety is improved by better signal timing, warnings, and possibly enforcement. Mobility is measured by vehicle delay, number of stops, and throughput; it is improved by better signal control, and adaptation to current traffic conditions. Today traffic data collected in 300,000 intersections in the US consists of manual vehicle counts conducted every couple of years; bicycles or pedestrians are almost never measured. Traffic signal settings are based on these inadequate measurements. Safety risk is measured by counting crashes; there is no account of near-crashes. Measurement of intersection performance (level of service, throughput, and delay) is rarely attempted since it requires continuous monitoring of traffic. Nevertheless major signalized intersections do detect the presence of vehicles, and do receive push button signals from pedestrians if they wish to cross. A few intersections have bicycle detectors. What is lacking is the means to collect these measurements and intelligently fuse them to estimate the traffic state in real-time. This innovation is the only system that can do this. The broader and commercial impact of this innovation is the savings in lives and lost productivity. Inefficient operation of intersections is costly. Poor intersection control causes 295 million vehicle-hours of traffic delay, and annually costs the peak-period traveler $710 in additional travel time and fuel. An estimated 2.3M crashes occurred at intersections in 2008, accounting for 40 percent of 5.8M crashes, 7,421 fatalities (including 4,092 pedestrians) and 733,000 crashes with injuries. Unless urban roads are carefully managed, these mobility and safety costs will only increase as cities try to provide convenient multimodal transportation choices to all citizens, whether it?s by driving, walking, bicycling, or transit, leading to greater interaction between the modal types. But careful management requires the ability to evaluate, predict and identify means to improve intersection mobility and safety. Today the data needed to conduct such studies on a routine basis are not available anywhere. This innovation is the only system that can provide such data in real time. It will be an exceptionally low-cost system that can be installed in a few hours, with data available the next day. This innovation will address the emerging requirements of the recent federal MAP-21 legislation.


Grant
Agency: National Science Foundation | Branch: | Program: SBIR | Phase: Phase II | Award Amount: 500.00K | Year: 2011

This Small Business Innovation Research (SBIR) Phase II project will develop a fully functional prototype of an accelerometer-based wireless Weigh In Motion (WIM) station. The WIM system will comprise an array of battery-powered 3? cubes, embedded in the pavement, each consisting of an accelerometer, a microprocessor for local signal processing, and a radio that sends the processed measurements to an Access Point (AP) on the side of the road. The AP estimates the pavement load from each axle of a truck at freeway speeds and the truck?s class, and transmits these estimates to the traffic management center. The cubes take up minimal space and are installed within minutes, so WIM systems can be deployed anywhere at a fraction of the cost of traditional WIM stations. Phase I research demonstrated the technical feasibility and commercial potential of the WIM. The technical objectives of Phase II concern the WIM packaging and installation; calibration: sensitivity to weight, speed and temperature (especially for asphalt pavements); signal compression and source coding; channel coding; wide area data backhaul; overall system design; manufacturing prototype samples; and extensive testing. The broader impact/commercial potential of this project is to dramatically enhance the regulation of truck weights and provide data to greatly improve the maintenance of the US road and bridge infrastructure by drastically reducing the costs of WIM stations. Current WIM stations have limited deployment as they are costly to install requiring shutting the road for days and needing expensive maintenance and re-calibration. The new WIM stations could be widely deployed in additional locations on arterial streets and near ports to monitor truck traffic and be a component in a truck weight-based enforcement and toll system. These WIM stations could also meet similar objectives in overseas markets creating employment for US residents with diverse skills in the design, manufacturing, sales, and installation.


Grant
Agency: NSF | Branch: Standard Grant | Program: | Phase: | Award Amount: 599.80K | Year: 2011

This Small Business Innovation Research (SBIR) Phase II project will develop a fully functional prototype of an accelerometer-based wireless Weigh In Motion (WIM) station. The WIM system will comprise an array of battery-powered 3? cubes, embedded in the pavement, each consisting of an accelerometer, a microprocessor for local signal processing, and a radio that sends the processed measurements to an Access Point (AP) on the side of the road. The AP estimates the pavement load from each axle of a truck at freeway speeds and the truck?s class, and transmits these estimates to the traffic management center. The cubes take up minimal space and are installed within minutes, so WIM systems can be deployed anywhere at a fraction of the cost of traditional WIM stations. Phase I research demonstrated the technical feasibility and commercial potential of the WIM. The technical objectives of Phase II concern the WIM packaging and installation; calibration: sensitivity to weight, speed and temperature (especially for asphalt pavements); signal compression and source coding; channel coding; wide area data backhaul; overall system design; manufacturing prototype samples; and extensive testing.

The broader impact/commercial potential of this project is to dramatically enhance the regulation of truck weights and provide data to greatly improve the maintenance of the US road and bridge infrastructure by drastically reducing the costs of WIM stations. Current WIM stations have limited deployment as they are costly to install requiring shutting the road for days and needing expensive maintenance and re-calibration. The new WIM stations could be widely deployed in additional locations on arterial streets and near ports to monitor truck traffic and be a component in a truck weight-based enforcement and toll system. These WIM stations could also meet similar objectives in overseas markets creating employment for US residents with diverse skills in the design, manufacturing, sales, and installation.


A package, wireless sensor module, wireless sensor node and wireline sensor node are disclosed including a radar configured to embed beneath vehicles in pavements, walkways, parking lot floors and runways referred to herein as in ground usage. An access point interfacing to at least one of the sensors is disclosed to provide traffic reports, parking reports, landing counts, takeoff counts, aircraft traffic reports and/or accident reports based upon the sensors messages regarding the radar and possibly magnetic sensor readings. A runway sensor network is disclosed of radar sensors embedded in lanes of at least one runway for estimating the landing count and/or takeoff count effect of aircraft.

Loading Sensys Networks, Inc. collaborators
Loading Sensys Networks, Inc. collaborators