Advanced Driver-Assistance Systems for City Bus Applications

Abstract

The bus sector is currently lagging behind when it comes to implementing autonomous systems for improved vehicle safety. However, in cities such as London, public transport strategies are changing, with requirements being made for advanced driverassistance systems (ADAS) on buses. This study discusses the adoption of ADAS systems within the bus sector. A review of the onroad ADAS bus trials shows that passive forward collision warning (FCW) and intelligent speed assistance (ISA) systems have been successful in reducing the number of imminent pedestrian/vehicle collision events and improving speed limit compliance, respectively. Bus accident statistics for Great Britain have shown that pedestrians account for 82% of all fatalities, with three quarters occurring with frontal bus impacts. These statistics suggest that the bus forward collision warning system is a priority for inclusion in future vehicles to enhance the driver's direct vision, and to increase reaction time for earlier brake application. Almost 80% of bus occupant casualties occurred in non-impact situations, mainly during acceleration/deceleration events. Therefore, care must be taken in implementing autonomous braking in buses, to ensure that it does not cause an increased number of deceleration events beyond the safe stability limits for passengers. Real on-road drive cycle data has shown that while instances of unsafe braking events do not occur regularly, there are instances of braking events that would present a hazard to both seated and standing passengers, therefore systems that would mitigate these issues would have real benefits to both passenger comfort and safety. During tests to simulate the use of the vehicle retarder for an autonomous braking system, deceleration rates largely remained safely within standee and seated passenger stability limits, whereas an emergency stop test showed a peak deceleration 3.5 times the limit of a standee supported by a vertical handrail, and 4 times the limit for a forward/backward facing seated passenger.

A Novel Triple Radar Arrangement for Level 2 ADAS Detection System in Autonomous Vehicles

“…AEB system is the most beneficial and efficient ADAS system for passenger and target safety [28]. The AEB acts automatically when the space between the driver and the hazard decreases, and the driver does not respond the hazard in time.…”

Smart Tramway Systems for Smart Cities: A Deep Learning Application in ADAS Systems

“…Experiments have been conducted in controlled zones such as the university campus, parking areas and small villages [4]. Autonomous vehicles can be classified as follows: (1) private autonomous cars, (2) shared autonomous cars/taxis, (3) autonomous buses and trucks; (4) autonomous Trams (5); autonomous-rail rapid tram (ART) [4][5][6][7].…”

ADAS at work: assessing professional bus drivers’ experience and acceptance of a narrow navigation system

“…Most often, the focus in research has been on ADAS in private cars. However, ADAS in heavy vehicles has garnered increasing attention in recent years (Blades et al 2020;Richardson et al 2018). Moreover, commercial fleets have increasingly implemented ADAS (such as lane departure warning and forward collision warnings) with the aim of improving safety (Mele 2018).…”

“…Even though interest in ADAS is growing and the work tasks are complicated, there has been little research into ADAS in buses. However, Blades et al (2020) suggest that systems, such as forward collision warning (FCW) and intelligent speed assistance (ISA) systems, have been successful in, for example, reducing the number of imminent pedestrian/vehicle collision events and improving speed limit compliance. One specific situation identified as particularly demanding for bus drivers is docking at bus-stops (e.g., Dukic Willstrand et al 2017) which can occur several hundred times per work shift.…”