CASA: An Alternative Smartphone-Based ADAS

2021 ◽  
pp. 1-41
Author(s):  
Manolo Dulva Hina ◽  
Hongyu Guan ◽  
Assia Soukane ◽  
Amar Ramdane-Cherif
Keyword(s):  
Low Cost ◽  
Electronic System ◽  
Time Data ◽  
Case Scenario ◽  
Safe Driving ◽  
The Road ◽  
Driving Assistance ◽  
Alternative Means ◽  
On The Road ◽  
Driving Assistance System

Advanced driving assistance system (ADAS) is an electronic system that helps the driver navigate roads safely. A typical ADAS, however, is suited to specific brands of vehicle and, due to proprietary restrictions, has non-extendable features. Project CASA is an alternative, low-cost generic ADAS. It is an app deployable on smartphone or tablet. The real-time data needed by the app to make sense of its environment are stored in the vehicle or on the cloud, and are accessible as web services. They are used to determine the current driving context, and, if needed, decide actions to prevent an accident or keep road navigation safe. Project CASA is an undertaking of a consortium of industrial and academic partners. A use case scenario is tested in the laboratory (virtual) and on the road (actual) to validate the appropriateness of CASA. It is a contribution to safe driving. CASA’s contribution also lies in its approach in the semantic modeling of the context of the environment, the vehicle and the driver, and on the modeling of rules for fusion of data and fission process yielding an action to be implemented. In addition, CASA proposes a secured means of transmitting data using light, via light fidelity (LiFi), itself an alternative means of wireless vehicle–smartphone communication.

scholarly journals Development of driving cycle under real world traffic conditions: A case study

2019 ◽  
Vol 9 (6) ◽  
pp. 4798
Author(s):  
Geetha A. ◽  
Subramani C.
Keyword(s):  
Driving Cycle ◽  
Time Dependent ◽  
Maximum Speed ◽  
Time Data ◽  
Maximum Acceleration ◽  
The Road ◽  
Traffic Conditions ◽  
Condensed Form ◽  
On The Road

<p><span>The modeling of a car is essentially done by taking into consideration the driving terrain, traffic conditions, driver’s behavior and various other factors which may directly or indirectly affect the vehicle’s performance. A vehicle is modeled for given specifications and constraints like maximum speed, maximum acceleration, and braking time, appropriate suspension for the gradient of the road and fuel consumption. Henceforth, a profound study and analysis of different drive cycles are essential. A time dependent drive cycle is a condensed form of data that helps us to determine the time taken to conduct the driving test on the road. This article highlights the development of a real driving cycle in the area of Tamilnadu, India. On-road vehicle’s speeds versus time data were obtained along the selected route. The data obtained were analyzed first and then a new driving cycle was developed.</span></p>

Predictive Eco-Driving Assistance on the Road

2021 ◽  
pp. 205-226
Author(s):  
Craig K. Allison ◽  
James M. Fleming ◽  
Xingda Yan ◽  
Roberto Lot ◽  
Neville A. Stanton
Keyword(s):  
The Road ◽  
Driving Assistance ◽  
On The Road

Inter-vehicle distance estimation considering camera attitude angles based on monocular vision

2020 ◽  
pp. 095440702094139
Author(s):  
Jun Liu ◽  
Rui Zhang ◽  
Shihao Hou
Keyword(s):  
Distance Estimation ◽  
Estimation Methods ◽  
Vanishing Point ◽  
Estimation Model ◽  
The Road ◽  
Attitude Angle ◽  
Driving Assistance ◽  
Lane Line ◽  
Texture Orientation ◽  
On The Road

Perceiving the distance between vehicles is a crucial issue for advanced driving assistance systems. However, most vision-based distance estimation methods do not consider the influence of the change in camera attitude angles during driving or only use the vanishing point detected by lane lines to correct the pitch angle. This paper proposed an improved pinhole distance estimation model based on the road vanishing point without the lane line information. First, the road vanishing point is detected based on the dominant texture orientation, and the yaw and pitch angles of the camera are estimated. Then, a distance estimation model considering attitude angle compensation is established. Finally, the experimental results show that the proposed method can effectively correct the influence of the camera attitude angle on the distance estimation results.

scholarly journals Raspberry Pi-Based Low-Cost Connected Device for Assessing Road Surface Friction

Electronics ◽  
2019 ◽  
Vol 8 (3) ◽  
pp. 341 ◽  
Author(s):  
Miha Ambrož ◽  
Uroš Hudomalj ◽  
Alexander Marinšek ◽  
Roman Kamnik
Keyword(s):  
Traffic Safety ◽  
Road Network ◽  
Low Cost ◽  
Measurement Data ◽  
Automatic Measurement ◽  
Raspberry Pi ◽  
Measuring Device ◽  
The Road ◽  
Measuring Devices ◽  
On The Road

Measuring friction between the tyres of a vehicle and the road, often and on as many locations on the road network as possible, can be a valuable tool for ensuring traffic safety. Rather than by using specialised equipment for sequential measurements, this can be achieved by using several low-cost measuring devices on vehicles that travel on the road network as part of their daily assignments. The presented work proves the hypothesis that a low cost measuring device can be built and can provide measurement results comparable to those obtained from expensive specialised measuring devices. As a proof of concept, two copies of a prototype device, based on the Raspberry Pi single-board computer, have been developed, built and tested. They use accelerometers to measure vehicle braking deceleration and include a global positioning receiver for obtaining the geolocation of each test. They run custom-developed data acquisition software on the Linux operating system and provide automatic measurement data transfer to a server. The operation is controlled by an intuitive user interface consisting of two illuminated physical pushbuttons. The results show that for braking tests and friction coefficient measurements the developed prototypes compare favourably to a widely used professional vehicle performance computer.

scholarly journals Empirical Analysis of Safe Distance Calculation by the Stereoscopic Capturing and Processing of Images Through the Tailigator System

Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 5044
Author(s):  
Gerd Christian Krizek ◽  
Rene Hausleitner ◽  
Laura Böhme ◽  
Cristina Olaverri-Monreal
Keyword(s):  
Low Cost ◽  
Field Tests ◽  
Warning System ◽  
Collision Warning ◽  
The Road ◽  
Cost System ◽  
Straight Line ◽  
Real Value ◽  
On The Road ◽  
Forward Collision Warning

Driver disregard for the minimum safety distance increases the probability of rear-end collisions. In order to contribute to active safety on the road, we propose in this work a low-cost Forward Collision Warning system that captures and processes images. Using cameras located in the rear section of a leading vehicle, this system serves the purpose of discouraging tailgating behavior from the vehicle driving behind. We perform in this paper the pertinent field tests to assess system performance, focusing on the calculated distance from the processing of images and the error margins in a straight line, as well as in a curve. Based on the evaluation results, the current version of the Tailigator can be used at speeds up to 50 km per hour without any restrictions. The measurements showed similar characteristics both on the straight line and in the curve. At close distances, between 3 and 5 m, the values deviated from the real value. At average distances, around 10 to 15 m, the Tailigator achieved the best results. From distances higher than 20 m, the deviations increased steadily with the distance. We contribute to the state of the art with an innovative low-cost system to identify tailgating behavior and raise awareness, which works independently of the rear vehicle’s communication capabilities or equipment.

High precision and high resolution monitoring of subsurface changes with DAS and airgun

2020 ◽  
Author(s):  
Baoshan Wang ◽  
Xiangfang Zeng ◽  
Jun Yang ◽  
Yuansheng Zhang ◽  
Zhenghong Song ◽  
...  
Keyword(s):  
Large Scale ◽  
Fiber Optic ◽  
Epicentral Distance ◽  
Low Cost ◽  
Fiber Optic Cable ◽  
The Road ◽  
Air Gun ◽  
Distributed Acoustic Sensing ◽  
On The Road ◽  
Road Crossing

&lt;p&gt;Recently large-volume airgun arrays have been used to explore and monitor the subsurface structure. The airgun array can generate highly repeatable seismic signals, which can be traced to more than 200 km. And the airgun source can be ignited every 10 minutes. The airgun source makes it possible to precisely monitor subsurface changes at large scale. The spatial resolution of airgun monitoring is poor subjecting to the receiver distribution. The distributed acoustic sensing (DAS) technique provides a strategy for low-cost and high-density seismic observations. Two experiments combing DAS technique and airgun source were conducted at two sites with different settings. At the first site, a telecommunication fiber-optic cable in urban area was used. After moderate stacking, the airgun signal emerges on the 30-km DAS array at about 9 km epicentral distance. In the second experiment, a 5-km cable was deployed from the airgun source to about 2 km away. About 800-m cable was frozen into the ice above the air-gun, the rest cable was cemented on the road crossing through a fault. And the airgun has been fired continuously for more than 48 hours with one-hour interval. On the stacking multiple shots&amp;#8217; records, the wavefield in fault zone emerges too. These two experiments demonstrate the feasibility of using various fiber-optic cables as dense array to acquire air-gun signal in different environments and to monitor the subsurface changes.&lt;/p&gt;

scholarly journals An advanced planner for urban freight delivering

2018 ◽  
Vol 4 (48) ◽  
pp. 27-40 ◽  
Author(s):  
Antonio COMI ◽  
Berta BUTTARAZZI ◽  
Massimiliano SCHIRALDI ◽  
Rosy INNARELLA ◽  
Martina VARISCO ◽  
...  
Keyword(s):  
Real Time ◽  
Web Application ◽  
Road Network ◽  
Time Windows ◽  
Mobile App ◽  
Delivery Time ◽  
Time Data ◽  
Urban Freight ◽  
The Road ◽  
On The Road

The paper aims at introducing an advanced delivery tour planner to support operators in urban delivery operations through a combined approach which chooses delivery bays and delivery time windows while optimizing the delivery routes. After a literature review on tools for the management and the control of the delivery system implemented for optimizing the usage of on-street delivery bays, a prototypical tour delivery planner is described. The tool allows transport and logistics operators to book the delivery bays and to have real-time suggestions on the delivery tour to follow, through the minimization of the total delivery time. Currently, at development phase, the tool has been tested in a target zone, considering the road network and time/city delivering constraints and real-time data about vehicles location, traffic and delivery bay availability. The tool identifies the possible tours based on the delivery preferences, ranks the possible solutions according to the total route time based on information on the road network (i.e. travel time forecasts), performs a further optimization to reduce the total travel times and presents the user the best alternative along with the indications of which delivery bay to use in each delivery stop. The developed prototype is composed by two main parts: a web application that manages communication between the database and the road network simulation, and, an Android mobile App that supports transport and logistic operators in managing their delivering, pre trip and en route, showing and updating routing based on real-time information.

scholarly journals CoDRIVE – Delivering High Accuracy, Ubiquitous Positioning Through Combined Radio Navigation and Inertial Sensing Technologies

2020 ◽  
Author(s):  
Simon Roberts
Keyword(s):  
Radio Frequency Identification ◽  
Autonomous Vehicles ◽  
Low Cost ◽  
Maximum Error ◽  
Precision Data ◽  
The Road ◽  
Frequency Identification ◽  
High Precision Data ◽  
On The Road ◽  
The University

The CoDRIVE solution builds on R&amp;amp;D in the development of connected and autonomous vehicles (CAVs). The mainstay of the system is a low-cost GNSS receiver integrated with a MEMS grade IMU powered with CoDRIVE algorithms and high precision data processing software. The solution integrates RFID (radio-frequency identification) localisation information derived from tags installed in the roads around the University of Nottingham. This aids the positioning solution by correcting the long-term drift of inertial navigation technology in the absence of GNSS. The solution is informed of obscuration of GNSS through city models of skyview and elevation masks derived from 360-degree photography. The results show that predictive intelligence of the denial of GNSS and RFID aiding realises significant benefits compared to the inertial only solution. According to the validation, inertial only solutions drift over time, with an overall RMS accuracy over a 300 metres section of GNSS outage of 10 to 20 metres. After deploying the RFID tags on the road, experiments show that the RFID aided algorithm is able to constrain the maximum error to within 3.76 metres, and with 93.9% of points constrained to 2 metres accuracy overall.

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