This session covers information on testing of automated braking systems and driver assistance systems
Risk Mitigation Planning for Revenue Service Testing of Bus Automated Emergency Braking
Jerome Lutin, New Jersey TransitShow Abstract
Heidi Soule, Pierce Transit
Adam Davis, Pierce Transit
Andrew Krum, Virginia Polytechnic Institute and State University (Virginia Tech)
Yinhai Wang, University of Washington
Ruimin Ke, University of Washington
Dave Valadez, DCS Technologies, Inc.
Daniel Sellers, DCS Technologies, Inc.
Steve Roberts, Veritas Forensic Accounting and Economics
Luke Fischer, Veritas Forensic Accounting and Economics
In 2017 the Federal Transit Administration (FTA) awarded Pierce Transit of Lakewood, WA a $1.66 million grant for a bus collision avoidance and mitigation safety research and demonstration project. The project scope includes installation of an advanced technology package, the Pedestrian Avoidance Safety System (PASS) that uses light detection and ranging (lidar) sensors to trigger automated deceleration and braking. Thirty transit buses are being equipped with PASS and will be monitored using telematics to transmit and collect critical test data. The test plan includes collecting data while operating the buses in “stealth mode” with PASS detecting and logging events but not activating brakes automatically or warning the drivers. At the conclusion of “stealth mode” operation, Pierce Transit will make a go no-go decision on whether to activate PASS’s automatic braking functionality for revenue service with passengers. This paper describes the risk mitigation process developed to determine if the system is safe enough to allow operation in revenue service. The process includes: broad stakeholder engagement, constituting an ad-hoc working group within Pierce Transit to advise executive management, development of decision-making criteria, risk and hazard analysis, consultation with state and Federal officials on regulatory requirements and compliance, review of applicable standards and engineering test protocols, engineering consultations with the bus original equipment manufacturer (OEM), and road testing to simulate revenue service, collect data, and obtain feedback from drivers and maintainers.
Evaluation of an Advanced Driver Assistance System to Reduce Pedestrian and Rear-End Crashes of Transit Vehicles
Mohammed Hadi, Florida International UniversityShow Abstract
Mohammad Atonu Islam, VIBEngineering, Inc.
Sohana Afreen, Florida International University
Tao Wang, Florida International University
This paper reports on the results of an evaluation of a rear end and pedestrian crash warning system installed on a transit agency buses with the goal of collecting and providing information to help agencies in making decisions regarding investment in such systems. The results from this evaluation indicate that the tested crash warning system had a positive effect on improving the reaction times to rear-end and pedestrian conflicts and in increasing the yield of drivers to pedestrians. The results from the evaluation also indicate improvement in driver’s behavior as reflected by the increase in the time headways between vehicles, reduction in the number of alerts for both rear-end and pedestrian crashes, and the reduction in the number of hard break events. However, the bus operators’ acceptance of the system seems to be low, pointing to the need for additional outreach and education of the drivers of the system and its effectiveness. The results from the return-on-investment analysis show that although installing the system on every bus of the transit agency may not be cost-effective, installing the devices on only the buses that operate on the high crash bus routes is cost-effective. Keywords: Advanced Driver Assistance Systems, Crash Warning Systems, Rear-end Collisions, Pedestrian Collisions, Transit Vehicle Safety
Research on the Influence of Bus Bay on Heterogeneous Traffic Flow Consisting of Human Driving and Autonomous Driving Vehicles in Adjacent Lane
Xiaojian Hu, Southeast UniversityShow Abstract
Tenghui Liu, Southeast University
With the deployment of Autonomous vehicles (AV), it can be assumed that a heterogeneous flow consisting of human driving and autonomous driving vehicles will appear in urban city. Numerous studies have shown that bus stop always has great effect on traffic flow near the bus stop, but few insightful researches have been conducted on the influence of bus bay on the heterogeneous traffic flow consisting of human driving cars, buses and autonomous vehicles in adjacent lane. In this paper, a new KKSW (Kerner–Klenov–Schreckeneberg–Wolf)-BB (Bus Bay)-AVHV (Human Driving and Autonomous Driving Vehicles) CA (cellular automaton) model is proposed to study the influence of bus bay on heterogeneous traffic flow based on the well-known KKSW CA model. Through numerical simulation, the traffic flow characteristics in adjacent lane are studied in the framework of Kerner’s three-phase traffic theory. The frequency and severity of rear-end collisions are analyzed to research the influence of bus bay on traffic safety in adjacent lane. The results show that both the traffic efficiency and safety in adjacent lane can be negatively affected by the buses entering and leaving the bus bay, and the introduction of AVs in the heterogeneous traffic flow can greatly improve the traffic efficiency and safety of traffic flow under the condition of heavy traffic.
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