1 Introduction
2 Research approach
3 Method
3.1 Definition of a scenario
Conditions | Parameters |
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1. the driver | age, gender, driver type, driving experience |
2. the vehicle | type (light vehicle—heavy vehicle), status |
3. the road infrastructure | road type (urban, rural, motorway) |
4. the traffic conditions | density, speed |
5. the environmental conditions | weather, road surface, lighting |
3.2 Accident statistics
Error Level | Description | Errors |
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Level 1: “accident type” | Result of the execution of an error | •Single vehicle accident (with or without collision with an obstacle) |
•Frontal collision | ||
•Lateral collision | ||
•Chain/rear collision | ||
•Collision with parked vehicle | ||
•Collision with animal | ||
Level 2: “driving error” | Action that has led to the accident. | •Driving too fast in an unexpected bend on rural roads (error 1) |
•Speeding (error 2) | ||
•Wrong use of the lane (error 3) | ||
•Violation of priority rules (error 4) | ||
•Failure when overtaking (error 5) | ||
•Insufficient safety distance (error 6) | ||
Level 3: “human error” | Psychological process that is basis to the driving error. | •information error (lack of perception: e.g. having not noticed the traffic sign while passing) |
•diagnostic error (incorrect evaluation of available information) | ||
•performance error (incorrect execution: e.g. having not found the brake pedal) | ||
Level 4: “psycho-physiological condition” | Condition that can influence the psychological process. | •impairment |
•exhaustion, fatigue | ||
•disorders (neurological, cardiovascular) | ||
•intoxication (alcohol, drugs) |
3.3 Safety measures generation
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Co-operative solutions
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Infrastructure to Vehicle (signals from the infrastructure are sent to the vehicle: e.g. curvature of the bend)
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Vehicle to Vehicle; (signals from one vehicle to one or more other vehicles)
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Infrastructure to Vehicle and Vehicle to Vehicle (combination of the former two solutions)
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Vehicle to Infrastructure (signals from vehicle to infrastructure)
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Autonomous solutions
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Only Infrastructure
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Only Vehicle
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Only road design
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Road Safety Functions | Infrastructure Type | Road Safety Measures |
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Collision warning and avoidance | Road | Obstacle Free Zone |
Road | Median Barrier | |
Road | Safety Barrier | |
Traffic Management | Dynamic hazard warning (VMS) | |
Traffic Management | Dynamic Speed—(VMS) | |
Longitudinal Support | Road | Protecting Shoulder |
Road | static traffic signs | |
Road | traffic lights | |
Road | VMS | |
Traffic Management | Section speed management system (line or stretch control) | |
Lateral Support | Road | Lane width |
Road | Rumble Strips | |
Navigation based | Road | Route signing |
Traffic Management | Dynamic Route guidance system (VMS) RDS-TMS Radio-Data-System Traffic | |
Traffic Management | Message Channel | |
Perception Enhancement | Traffic Management | Fog warning system (VMS) |
Traffic Management | Low friction warning system (VMS) | |
Road | Reflecting road markings | |
Road | Special street light | |
Driver-/Vehicle Status Monitoring |
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Road design
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Traffic management
Road Safety Functions | ADAS Type | Road Safety Measures |
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Collision warning and avoidance | Autonomous in-vehicle | Near field collision warning or Side Obstacle detection |
Autonomous in-vehicle | Obstacle & Collision Avoidance | |
Autonomous in-vehicle Co-operative | Obstacle & collision warning | |
Vehicle Vehicle / Vehicle Infra and Infra Vehicle | Local hazard warning | |
Longitudinal Support | Autonomous in-vehicle Co-operative | Speed Alert or ISA based on traffic sign recognition |
Vehicle Infra and Infra Vehicle | Speed Alert or ISA based on digital map data | |
Autonomous in-vehicle | ACC-Stop & Go | |
Co-operative V V | ACC-Stop & Go + Foresight | |
Lateral Support | Autonomous in-vehicle | Blind Spot detection |
Autonomous in-vehicle | Lane change assistant | |
Autonomous in-vehicle | Lane departure warning | |
Autonomous in-vehicle Co-operative | Lane keeping assistant | |
Navigation based | Vehicle Infra and Infra Vehicle | Navigation system |
Perception Enhancement | Autonomous in-vehicle | Low friction warning system (in-vehicle) |
Autonomous in-vehicle | Vision enhancement | |
Driver-/Vehicle Status Monitoring | Autonomous in-vehicle | Driver Monitoring |
Autonomous in-vehicle | Vehicle Monitoring | |
Several | Autonomous in-vehicle | In-Vehicle HMI (Displays, …) |
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Longitudinal support
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Collision warning and avoidance
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Lateral support
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Navigation based
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Perception enhancement
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Driver vehicle status monitoring
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Other
Problem | Alternative | Scenario | Technology | Communication type |
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Impaired visibility of the road (at night, fog, rain) | A. Head Up display showing road curvature | Rural, Highway, all drivers all vehicles all traffic and bad visibility conditions | GPS info, head up display | Only Infra (TMC)a |
Impaired visibility of the road (at night, fog, rain) | B. Light sensitive sensors (solar cell based) helping the driver to see the edge and centre lines. Running light inserted in the road surface | Rural, all drivers all vehicles all traffic conditions—all weather especially reduced visibility conditions | Light sensitive sensors (solar cells based) will help the driver to see the edge and centre lines. | Only Infra (Road design) |
Unexpected sharp bends | C. Unexpected sharp bends are registered in a digital map of the navigationsystem and presented to the driver | Rural, Highway | GPSb info, digital map and HMIc | Only Vehicle |
Vehicle approaching bend at high speed | D. Vehicle is “analysed” (e.g. speed), VMS signalize the danger of the bend depending on the actual speed | Rural, Highway | Speed sensors and VMSd display | Only Infra (TMC) |
Unexpected sharp bends or other road characteristics | E. Electronic beacons (special reflexion posts) give additional information on displays in the vehicle about the road (e.g. warning: sharp bend) | Rural, Highway | Infra → Vehicle |
Problem | Alternative | Scenario | Technology | Communication type |
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The LDWSystem is deactivated at the beginning of long construction sites to avoid false alarms. | F. communication with the local infrastructure | Rural, Highway, all drivers all vehicles all traffic conditions, near construction sites | Digital maps/GPS—speed, ldentity and indicator use system, Car-to-car communication via physicaland link-layer based on an UMTS terrestrial radio access network or local area network | Infra → Vehicle |
When leaving Road Constructions the driver is reminded to reactivate his LDW-System | Infra → Vehicle → Vehicle | |||
In-vehicle warning of oncoming vehicles In curves. | G. communication with the local infrastructure | Rural, Highway, all drivers all vehicles all traffic conditions | Digital maps/GPS—speed, ldentity and indicator use system, Car-to-car communication via physical and link-layer based on an UMTS terrestrial radio access network or local area network | Infra → Vehicle |
Infra → Vehicle → Vehicle | ||||
Intelligent edge lines (triggered by vehicle turn indicator) showing a the right way to a vehicle exiting the motorway in case of impaired visibility. | H. Light sensitive sensors (solar cells based) will help the driver to see the edge and centre lines | Rural, all drivers all vehicles all traffic conditions—running light inserted in road surface- all weather esp. reduced visibility | Light sensitive sensors (solar cells based) | Vehicle → Infra |
In case of inattention the driver is drifting off the lane | I. CCDa camera, LDW system to detect unintended lane departure and warn the driver | Rural, Highway, all drivers all vehicles all traffic conditions roads without rumble lines | CCD camera, LDW system: virtual rumble strips | Infra → Vehicle |
Road works, tunnels, narrowing road | J. Adaptive LDWA; Sensitivity of Lane Departure warning Assistant is adapted in special conditions, | Rural, Highway, all drivers, all vehicles, special traffic conditions and roads without hard shoulder | Communication with the local infrastructure, LDW | Infra → Vehicle |
3.4 Evaluation of safety effects
3.5 Selection of 18 alternatives
3.6 Estimation of potential of safety effects
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If the measure needs equipment in vehicles how many of the vehicles might be equipped with the system?
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If the measure is informative (not “overruling”) how many drivers might follow the recommendations?
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If the measure is not addressing ALL drivers equally which type of drivers should be addressed?
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etc.