Browsing by Subject "Driver support systems"

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Assessing the Energy Impacts of Cyberattacks on Low-Level Automated Vehicles
(Center for Transportation Studies, University of Minnesota, 2023-08) Stern, Raphael; Li, Tianyi; Rosenblad, Benjamin; Shang, Mingfeng
In this study, we investigate the potential impact of stealthy cyberattacks on automated or partially automated vehicles, and consider how they will influence traffic flow and fuel consumption. Specifically, we define stealthy cyberattacks on automated vehicles where driving behavior deviates only slightly from normal driving behavior. We use simulation analysis to consider different cyberattacks, and investigate their impact on traffic flow and aggregate fuel consumption of all vehicles in the traffic flow. We find that such attacks, while difficult to detect, may substantially degrade traffic flow, and, to a lesser extent, vehicle emissions across the traffic flow.
Cooperative Intersection Collision Avoidance System – Stop Sign Assist: Experiments to Validate Use of an In-Vehicle Interface Design
(Center for Transportation Studies, University of Minnesota, 2012-04) Becic, Ensar; Manser, Michael; Creaser, Janet; Donath, Max
The three studies included in the current report examine the transition from an infrastructure-based rural intersection crossing assist system to one located inside a vehicle. The primary goals of the first study, conducted in a simulator, were to examine the effect of potentially confounding factors, such as the drivers’ familiarity with the assist system and the impact of cognitive load on the drivers’ performance. Next, we examined the efficacy of several different designs of such system to determine the optimal interface design to be used for the in-vehicle system. Finally, the optimal design of the system was examined in the third study, as a field test. The results showed that the use of the system under cognitively demanding conditions did not result in any adverse consequences, which suggested that the processing of the system required minimal cognitive resources. Additionally, the results showed that the benefits of the assist system, such as reduced probability of accepting a critical gap were exhibited under the limited visibility conditions when the perceptual task of determining an appropriate crossing gap became overly demanding. The results from the field study showed that the use of the assist system resulted in improved intersection crossing performance exhibited in increased likelihood of making a complete stop at the stop sign and showed a strong trend toward a decreased probability of accepting critical gaps. Additionally, the impact of the in-vehicle CICAS-SSA was equivalent for older and younger drivers; that is, both age groups benefited from the use of the system.
Development and Demonstration of a Cost-Effective In-Vehicle Lane Departure and Advanced Curve Speed Warning System
(Minnesota Department of Transportation, 2018-12) Faizan, Muhammad; Hussain, Shah; Hayee, M. I.
A Lane-Departure Warning System (LDWS) and Advance Curve -Warning System (ACWS) are critical among several Advanced Driver- Assistance Systems (ADAS) functions, having significant potential to reduce crashes. Generally, LDWS us e different image processing or optical s canning techniques to detect a lane departure. Such LDWS have some limitations such as harsh weather or irregular la ne markings can influence their performance. Other LDWS use a GPS receiver with access to digital maps with lane-level resolution to improve the system's efficiency but make the overall system more complex and expensive. In this report, a lane-departure detection method is proposed, which uses a standard GPS receiver to determine the lateral shift of a vehicle by comparing a vehicle’s trajectory to a reference road direction without the need of any digital maps with lane-level resolution. This method only needs road-level information from a standard digital mapping database. Furthermore, the system estimates the road curvature and provides advisory speed for a given curve simultaneously. The field test results show that the proposed system can detect a true lane departure with an accuracy of almost 100%. Although no true lane departure was left undetected, occasional false lane departures were detected about 10% of the time when the vehicle did not actually depart its lane. Furthermore, system always issues the curve warning with an advisory speed at a safe distance well ahead of time.
Development and Demonstration of an In-Vehicle Lane Departure Warning System Using Standard GPS Technology
(Minnesota Department of Transportation, 2021-06) Chowdhury, Shahnewaz; Hossain, Md Touhid; Hayee, M. I.
A lane departure warning system (LDWS) has significant potential to reduce crashes on roads. Most existing commercial LDWSs use some kind of image processing techniques with or without Global Positioning System (GPS) technology and/or high-resolution digital maps to detect unintentional lane departures. However, the performance of such systems is compromised in unfavorable weather or road conditions, e.g., fog, snow, or irregular road markings. Previously, we proposed and developed an LDWS using a standard GPS receiver without any high-resolution digital maps. The previously developed LDWS relies on a road reference heading (RRH) of a given road extracted from an open-source, low-resolution mapping database to detect an unintentional lane departure. This method can detect true lane departures accurately but occasionally gives false alarms, i.e., it can issue lane departure warnings even when a vehicle is within its lane. The false alarms occur due to the inaccuracy of how the RRH originated from an inherent lateral error in open-source, low-resolution maps. To overcome this problem, we proposed and developed a novel algorithm to generate an accurate RRH for a given road using a vehicle's past trajectories on that road. The newly developed algorithm that generates an accurate RRH for any given road has been integrated with the previously developed LDWS and extensively evaluated in the field for detection of unintentional lane departures. The field test results showed that the newly developed RRH Generation algorithm significantly improved the performance of the previously developed LDWS by accurately detecting all true lane departures while practically reducing the frequency of false alarms to zero.
Development of a Sensor Platform for Roadway Mapping: Part A - Road Centerline and Asset Management
(Center for Transportation Studies, University of Minnesota, 2014-06) Davis, Brian; Donath, Max
Collecting information about the roadway infrastructure is a task that DOTs at all governmental levels need to accomplish. One way to increase the operational efficiency of these efforts is to use a relatively inexpensive mobile data collection platform that acquires information that is general enough to serve multiple purposes. The design and evaluation of one such platform that costs roughly $40,000 is described. It primarily consists of a differential GPS receiver providing vehicle location, and a LIDAR scanner that generates geometric profiles of the area between the vehicle and just beyond the road’s edge. The vehicle collects data along the road by driving it in both directions. The system post-processes the data to automate feature extraction. For roads with simple geometry such as two-lane, undivided highways, the road’s centerline can be calculated by finding the midline between the vehicle’s paths from each direction of travel. Algorithms process the LIDAR scans to automatically detect the presence of curbs and guardrails, which is then combined with location information to yield the position of these features in world coordinates. The centerline calculation was determined to be accurate to within 6 cm in areas where its use was applicable. Curbs and guardrails were generally detected with an accuracy of better than 10 cm. The results demonstrate that it is feasible to use a relatively inexpensive mobile data collection system to acquire road centerline and roadside features such as curbs and guardrails.
Development of a Sensor Platform for Roadway Mapping: Part B – Mapping the Road Fog Lines
(Minnesota Department of Transportation, 2015-04) Davis, Brian; Donath, Max
Our objective is the development and evaluation of a low-cost, vehicle-mounted sensor suite capable of generating map data with lane and road boundary information accurate to the 10 cm (4 in) level. Such a map could be used for a number of different applications including GNSS/GPS based lane departure avoidance systems, smart phone based dynamic curve speed warning systems, basemap improvements, among others. The sensor suite used consists of a high accuracy GNSS receiver, a side-facing video camera, and a computer. Including cabling and mounting hardware, the equipment costs were roughly $30,000. Here, the side-facing camera is used to record video of the ground adjacent to the passenger side of the vehicle. The video is processed using a computer vision algorithm that locates the fog line within the video frame. Using vehicle position data (provided by GNSS) and previously collected video calibration data, the fog line is located in real-world coordinates. The system was tested on two roads (primarily two-lane, undivided highway) for which high accuracy (<10 cm) maps were available. This offset between the reference data and the computed fog line position was generally better than 7.5 cm (3 in). The results of this work demonstrate that it is feasible to use a camera to detect the position of a road’s fog lines, or more broadly any other lane markings, which when integrated into a larger mobile data collection system, can provide accurate lane and road boundary information about road geometry.
Development of Driver Assistance Systems to Support Snowplow Operations
(Center for Transportation Studies, University of Minnesota, 2018-08) Liao, Chen-Fu; Morris, Nichole L.; Achtemeier, Jacob; Alexander, Lee; Davis, Brian; Donath, Max; Parikh, Gordon
Snowplow operators are often tasked with numerous monitoring and operational activities that they need to do simultaneously while removing snow and spreading deicing agents on the road. Driver assist systems were considered for 3 applications: gang plowing, backup assist, and lane boundary guidance. We evaluated the system performance and position accuracy of commercially available Dedicated Short Range Communication (DSRC) Onboard Units (OBU) for gang plowing. Our results indicated that the positioning accuracy of the OBUs was inadequate for providing the plow operator with sufficient information to maintain spacing between two vehicles. The backup assist system and lane boundary guidance system were developed and successfully deployed to support snowplow operations. Human factors studies were also conducted using a driving simulator to better understand the needs prior to designing an appropriate Human Machine Interface (HMI) for these plow operations. The radar-based backup assist system was installed on a snowplow that operates on Highway 169. The backup assist system provides an audio warning to the operator to look at the display from a rear-view camera when an object is detected. The Global Navigation Satellite System (GNSS)-based lane boundary guidance system was developed to assist plow operations when visibility is poor and lane boundary cues are limited. The lane boundary guidance system was installed on a second snowplow operating on MN-25 running between Belle Plaine and Green Isle. The lane boundary guidance received the most positive feedback from operators and is recommended for further development.
A High Accuracy Vehicle Positioning System Implemented in a Lane Assistance System when GPS Is Unavailable
(Intelligent Transportation Systems Institute Center for Transportation Studies University of Minnesota, 2011-07) Arpin, Eddie; Shankwitz, Craig; Donath, Max
The use of lane assistance systems can reduce the stress levels experienced by drivers and allow for better lane keeping in narrow, bus-dedicated lanes. In 2008, the Intelligent Vehicles (IV) Lab at the University of Minnesota has developed such a system for this purpose. The IV Lab lane-assist system uses dual frequency differential GPS (DGPS) for high accuracy position information. This position information is used in conjunction with a geospatial database containing the road geometry and lane boundary positions required for a lane-assistance system. In urban environments, where tall buildings, overpasses, and other obstructions to the sky are present, DGPS suffers from inaccuracies and outages. This report proposes a method for replacing DGPS sensing with a high accuracy vehicle positioning system which fuses data from RFID (Radio Frequency IDentification) and LiDAR (Light Detection and Ranging) curb detection. A Vehicle Positioning System (VPS) was originally developed by the IV Lab to provide the lane level ("which lane on the road") position of a vehicle with respect to a known reference (i.e., a mile marker or start of roadway) by the use of encoded position information in RFID tags on the roadway, read by the vehicle. The lateral position resolution of VPS is constrained to one lane width, which is insufficient for lane-assistant systems. Thus, in-lane level ("where in the lane") lateral position estimation was supplemented by a LiDAR unit that generates an accurate position of the vehicle with respect to the curb, which is cross referenced with a map database that provides the distance from the lane center to the curb, thus providing the vehicle's lateral offset from the lane center. On-board odometry is used to maintain accurate longitudinal position in between tag reads. By fusing the information from the VPS, LiDAR, and on-board odometry, high accuracy, "where in lane" level vehicle positioning can be maintained from this enhanced VPS during DGPS outages.
Inexpensive 2D Optical Sensor for GPS Augmentation
(Intelligent Transportation Systems Institute, Center for Transportation Studies, University of Minnesota, 2012-12) Cheng, Pi-Ming; Shankwitz, Craig; Arpin, Eddie
Differential Global Positioning Systems (DGPS) are susceptible to outages due to blocked or missing satellite signals and/or blocked or missing DGPS correction messages. Outages arise primarily due to environmental reasons: passing under bridges, passing under overhead highway signs, adjacent foliage, etc. Generally, these outages are spatially deterministic, and can be accurately predicted. These outages distract drivers using DGPS-based driver assistive systems, and limit the system robustness. Inertial measurements have been proposed as an augmentation for DGPS. Tests have shown that error rates for even emerging technologies are still too high; a vehicle can maintain lane position for less than three to four seconds. Ring laser gyros can do the job, but $100K per axis is still too expensive for road-going vehicles. To provide robust vehicle positioning in the face of DGPS outages, the IV Lab has developed a technique by which a non-contact, 2D true ground velocity sensor is used to guide the vehicle. Although far from fully developed, the system can maintain vehicle position within a lane for GPS outages of up to 20 seconds. New dual frequency, carrier phase DGPS systems generally require less than 20 seconds to acquire a "fix" solution after a GPS outage, so the performance of this system should be adequate for augmentation. Proposed herein is basic research which may lead to the development of an inexpensive, 2D, non-contact velocity sensor optimized for vehicle guidance during periods of DGPS outages.
Influence of Autonomous and Partially Autonomous Vehicles on Minnesota Roads
(Minnesota Department of Transportation, 2023-05) Espindola, Andre; Alexander, Lee; Rajamani, Rajesh
This project focuses on experimental tests of the performance characteristics of autonomous vehicles (AVs) on highways and local roads in Minnesota. The project provides detailed data characterizing AV performance, which in turn can be used to inform the transportation community on implications for infrastructure maintenance, winter road maintenance, work zone guidelines, safety, and traffic capacity. The experimental work presented here makes use of a new autonomous vehicle purchased by the Center for Transportation Studies at the University of Minnesota. The key aspects of the autonomous functions of the vehicle studied in this project include winter performance and implications for road maintenance, characterization of the driving performance of the AV and its likely influence on safety, traffic flow and fuel economy, and the ability of the AV to handle work zones and the implications on changes needed to the guidelines for work zones. The project documents the major challenges and obstacles ahead in the way of true autonomy on Minnesota roads, but also outlines further areas for research with which it will be possible to facilitate the improvement of the capabilities of autonomous vehicles in Minnesota in the future.
Teen Driver Support System (TDSS) Field Operational Test
(Center for Transportation Studies, University of Minnesota, 2015-11) Creaser, Janet; Morris, Nichole L.; Edwards, Christopher; Manser, Michael; Cooper, Jennifer; Swanson, Brandy; Donath, Max
Although teen drivers make up a small percentage of the U.S. driving population, they are at an especially high risk of being involved in a crash. Factors that contribute to teen drivers’ risk include their lack of experience and their tendency to engage in unsafe behaviors such as speeding, driving aggressively, or using a cell phone while behind the wheel. To help teen drivers stay safe on the road, we developed the Teen Driver Support System (TDSS), a smartphonebased system that provides real-time, in-vehicle feedback to teens about their risky behaviors—and reports the behaviors to parents via text message if teens don’t heed the system’s warnings. The TDSS provides geographically specific, realtime feedback to a teen driver at the time unsafe driving behavior occurs so that behaviors can be immediately corrected. This report documents a 12-month field operational test of the system involving 300 newly licensed teens driving on Minnesota roads. The test included a control group that received no feedback, a treatment group that received only TDSS in-vehicle feedback, and a second treatment group that received both TDSS in-vehicle and TDSS parental notifications. Research results indicate an overall safety benefit of TDSS, demonstrating that in-vehicle monitoring and driver alerts, coupled with parental notifications, is a meaningful intervention to reduce the frequency of risky driving behaviors that are correlated with novice teen driver crashes. In particular, the system was shown to be an effective strategy for reducing excessive speeds when used with parental feedback and potentially even without parental involvement.
Teen Driver Support System Technology Transfer
(Center for Transportation Studies, University of Minnesota, 2019-07) Davis, Brian
The Teen Driver Support System (TDSS) is a smartphone application designed to provide real-time, in-vehicle feedback to novice drivers about their driving behavior to help them make safer driving decisions. The app provides warnings to the driver using in-phone sensors and maps to determine when the driver engages in in risky behavior. TDSS was evaluated in a field operational test that showed the system successfully helps reduce certain risky behaviors among teens using the system. The project documented in this report seeks to extend prior work on the system to make it suitable for future applications. This work included adding features, fixing bugs, and rebranding the system as Road Coach. It also included identifying and pursuing possible future applications of the technology. These efforts enabled the app’s use in a new application focused on providing in-vehicle feedback to older drivers. This application was evaluated as part of two separate projects. These usability and field operational test projects had positive results, notably high user acceptance and system efficacy in reducing certain risky driving behaviors. Future work in this area will continue to pursue this application of the technology as well as others.
Usability Evaluation of a Smart Phone-based Teen Driver Support System (TDSS)
(Minnesota Department of Transportation Research Services Section, 2011-05) Creaser, Janet; Gorjestani, Alec; Manser, Michael; Donath, Max
Motor vehicle crashes are the leading cause of teen fatalities. A Teen Driver Support System (TDSS) was developed by the ITS Institute that can allow parents to accurately monitor their teen's driving behavior in relation to known risk factors and Graduated Driver Licensing (GDL) provisions. The TDSS, based on a teen's smart phone, provides real-time, contextual in-vehicle feedback to the teen about his or her driving behavior and helps parents monitor certain known risk factors. The system does not allow incoming or outgoing phone calls (except 911) or texting while driving. Feedback to the teen driver includes visual and auditory warnings about speeding, excessive maneuvers (e.g., hard braking, cornering), and stop sign violations. The TDSS prototype also monitors seat belt use and detects the presence of passengers (e.g., based on GDL provisions), two known factors that increase the risk of fatalities among teen drivers. The TDSS can also be programmed to monitor driving during the GDL curfew or a curfew set by parents. A usability review of the prototype TDSS using 30 parent-teen dyads from Washington Country, MN, found that teens and parents held favorable opinions about most of the TDSS functions. Teens and parents both felt that use of the system early in licensure may result in the adoption of safer driving habits even after the system is removed from the vehicle. Several recommendations to improve the system’s usability are made based on the results.

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