Efficacy and acceptance of driver support under possible mismatches between driver's intent and traffic conditions

2006 ◽  
Author(s):  
T. Inagaki ◽  
M. Itoh ◽  
Y. Nagai
Keyword(s):  
Traffic Conditions ◽  
Driver Support

scholarly journals Development of a Methodology for Estimating the Availability of ADAS-Dependent Road Infrastructure

2021 ◽  
Vol 13 (17) ◽  
pp. 9512
Author(s):  
Sujanie Peiris ◽  
Janneke Berecki-Gisolf ◽  
Stuart Newstead ◽  
Bernard Chen ◽  
Brian Fildes
Keyword(s):  
Support Systems ◽  
Aerial Imagery ◽  
Mapping Data ◽  
High Quality ◽  
Road Infrastructure ◽  
Remote Areas ◽  
Traffic Conditions ◽  
Funding Model ◽  
Driver Support

Advanced driver assist systems are being promoted with the expectation that enhanced driver support will mitigate road trauma. While these technologies are optimised for certain road and traffic conditions, not all roads across Australasia are equipped with ADAS-supportive infrastructure. This study developed a desk-top methodology for using road classes (disaggregated by remoteness levels) to estimate the presence of quality roads, road delineation and speed signage in Victoria, Australia. Aerial imagery and mapping data were used to assess a number of random locations based on a developed protocol. The methodology demonstrated that in Victoria, major and arterial roads across all remoteness levels had high-quality sealed surfaces but 42% of all remote roads were unsealed. Delineation (crucial for lane support systems) were absent across 73% of sub-arterial roads independent of remoteness, and absent across 96% of sub-arterial roads in regional and remote areas. Speed sign availability across remote and regional areas was sparse, with only 65% of all roads assessed having signage. Results are reflective of Victoria’s road funding model and consistent with on-road audits conducted by other researchers. This methodology enables the proportion ADAS-ready roads to be estimated so the benefits of ADAS technologies can be quantified and investments into ADAS-supportive infrastructure be readily allocated.

Driver behavioral adaptation in response to a novel haptic driver support system

2005 ◽  
Author(s):  
Michael P. Manser ◽  
Nicholas J. Ward ◽  
Nobuyuki Kuge ◽  
Erwin Boer
Keyword(s):  
Support System ◽  
Behavioral Adaptation ◽  
Driver Support System ◽  
Driver Support

Smart Driving System for Improving Traffic Flow

2017 ◽  
Vol 7 (7) ◽  
pp. 236
Author(s):  
Rajesh Kumar Gupta ◽  
L. N. Padhy ◽  
Sanjay Kumar Padhi
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Urban Areas ◽  
Adaptive Cruise Control ◽  
Human Perception ◽  
Cruise Control ◽  
Driving System ◽  
V2v Communication ◽  
Traffic Conditions ◽  
Cooperative Adaptive Cruise Control

Traffic congestion on road networks is one of the most significant problems that is faced in almost all urban areas. Driving under traffic congestion compels frequent idling, acceleration, and braking, which increase energy consumption and wear and tear on vehicles. By efficiently maneuvering vehicles, traffic flow can be improved. An Adaptive Cruise Control (ACC) system in a car automatically detects its leading vehicle and adjusts the headway by using both the throttle and the brake. Conventional ACC systems are not suitable in congested traffic conditions due to their response delay.  For this purpose, development of smart technologies that contribute to improved traffic flow, throughput and safety is needed. In today’s traffic, to achieve the safe inter-vehicle distance, improve safety, avoid congestion and the limited human perception of traffic conditions and human reaction characteristics constrains should be analyzed. In addition, erroneous human driving conditions may generate shockwaves in addition which causes traffic flow instabilities. In this paper to achieve inter-vehicle distance and improved throughput, we consider Cooperative Adaptive Cruise Control (CACC) system. CACC is then implemented in Smart Driving System. For better Performance, wireless communication is used to exchange Information of individual vehicle. By introducing vehicle to vehicle (V2V) communication and vehicle to roadside infrastructure (V2R) communications, the vehicle gets information not only from its previous and following vehicle but also from the vehicles in front of the previous Vehicle and following vehicle. This enables a vehicle to follow its predecessor at a closer distance under tighter control.

Black Spot Identification and Audit Analysis for Heterogeneous Traffic Conditions in Hyderabad City � a Case Study

2015 ◽  
Vol 4 (3) ◽  
pp. 34-42
Author(s):  
T. Sri Lakshmi Sowmya ◽  
◽  
A. Ramesh ◽  
B.N.M. Rao ◽  
M. Kumar ◽  
...  
Keyword(s):  
Black Spot ◽  
Heterogeneous Traffic ◽  
Traffic Conditions
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