01595983

Component

https://doi.org/10.3141/2581-03

Current curve speed warning systems take into account mostly vehicle and road factors but not driver behavior. The systems aim at detecting sideslips of small cars on curves without consideration of rollovers for vehicles with an elevated center of gravity. In this study, a curve speed model that considers human, vehicle, and road factors is built to prevent not only sideslips but also rollover accidents for vehicles with an elevated center of gravity. In addition, a risk prediction model is presented to judge accident risk levels and determine levels of warning. Finally, the effectiveness of the presented system is validated with one skilled driver who carries out one test through a simulator under different curve scenarios. To verify the system, data from simulator tests were collected for offline checking of the system. The data were used to calculate safe speeds by using the curve speed model and to determine the levels of risk based on the risk prediction model. The results show that the system is highly compatible with the skilled driver in terms of warning accuracy and timing. Specifically, the correct alarm rate (i.e., the driver brakes and the system’s alarm goes off) of the system is 83.57% and the error alarm rate (i.e., the driver does not brake but the system’s alarm goes off) is 9.79%. Moreover, more than 80% of the time the difference between the system warning time and the operating time of the skilled driver is less than 2 s.

01595165

16-2737

English

pp 18–26

2016

Transportation Research Record: Journal of the Transportation Research Board

9780309369695

Print

Figures (6) ; References (22) ; Tables (2)

Crash risk forecasting; Driver support systems; Highway curves; Highway factors in crashes; Human factors in crashes; Speed; Vehicle safety; Warning systems

Data and Information Technology; Highways; Safety and Human Factors

TRIS, TRB, ATRI

Jan 12 2016 5:13PM

• Al Colegio en Bici: Bike-to-School Program in Bogotá, Colombia
• Assessing Motor Vehicle Quota Policies in China: Social Welfare Perspective
• Bus Financing in Urban Transport Projects in Mexico: Challenges and Opportunities
• Clustering of Several Typical Behavioral Characteristics of Commercial Vehicle Drivers Based on GPS Data Mining: Case Study of Highways in China
• Determination of Pedestrian Level of Service for Undivided Stairways at Suburban Rail Stations in Developing Countries
• Economic Impact of High-Speed Rail on Household Income in China
• Evaluation of Fluctuating Speed and Lateral Movement of Vehicles: Comparison Between Mixed Traffic and Homogeneous Traffic
• Evaluation of Pedestrian–Vehicle Conflict Severity at Unprotected Midblock Crosswalks in India
• Examining Implementation and Labor Market Outcomes of Targeted Transit Subsidies: Subsidy by Sistema Nacional de Selección de Beneficiarios for Urban Poor in Bogotá, Colombia
• Exploring Central Government Assistance for Urban Public Transport: A Mobility-Based Social Exclusion Perspective
• Future Travel Demand in China: Scenarios for Year 2030
• Mapping the Jitney Network with Smartphones in Accra, Ghana: The AccraMobile Experiment
• Market and Institutional Characteristics of Passenger Van Services in Bangkok, Thailand
• Modeling Mode Choice of Low-Income Commuters with Sociodemographics, Activity Attributes, and Latent Attitudinal Variables: Case Study in Fushun, China
• Pedestrian Crossing Treatment Warrants for Midblock Crosswalks Under Mixed Traffic Conditions
• Review of Pedestrian Level of Service: Perspective in Developing Countries
• Waiting Endurance Time of Pedestrians Crossing at Signalized Intersections in Beijing
• When Walking Becomes Praying: Walking Environment Survey and Improvement for Circumambulation Paths in Lhasa, Tibet, China