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An important aspect of an autonomous vehicle system, aside from the crucial features of path following and obstacle detection, is the ability to accurately and effectively recognize visual cues present on the roads, such as traffic lanes, signs and lights. This ability is important because very few vehicles are autonomously driven, and must integrate with conventionally operated vehicles. An enhanced infrastructure has yet to be available solely for autonomous vehicles to more easily navigate lanes and intersections non-visually. Recognizing these cues efficiently can be a complicated task as it not only involves constantly gathering visual information from the vehicle’s surroundings, but also requires accurate real time processing. Ambiguity of traffic control signals challenges even the most advanced computer decision making algorithms. The vehicle then must keep a predetermined position within its travel lane based on its interpretation of its surroundings.

This paper investigates the performance of an indirect injection (IDI) diesel engine fueled with Bu25, 75% ultra-low sulfur diesel (ULSD#2) blended with 25% n-butanol by mass. N-butanol, derivable from biomass feedstock, was used given its availability as an alternative fuel that can supplement the existing limited fossil fuel supply. Combustion and emissions were investigated at 2000 rpm across loads of 4.3-7.2 bar indicated mean effective pressure (IMEP). Cylinder pressure was collected using Kistler piezoelectric transducers in the precombustion (PC) and main combustion (MC) chambers. Ignition delays ranged from 0.74 - 1.02 ms for both operated fuels. Even though n-butanol has a lower cetane number, the high swirl in the separate combustion chamber would help advance its premixed combustion. The heat release rate of Bu25 became initially 3 J/crank-angle-degree (CAD) higher than that of ULSD#2 as load increased to 7.2 bar IMEP.

This study investigates the use of a natural gas derived fuel, synthetic Fischer-Tropsch (F-T) paraffinic kerosene, in both it’s neat form and blended with ultra-low sulfur diesel (ULSD#2), in a naturally aspirated indirect injected engine. A blend of a mass ratio with 20% of the F-T fuel and 80% ULSD#2 was studied for its combustion characteristics, emissions, and efficiency compared to conventional ULSD#2 at a constant speed of 2400 RPM and operating at IMEP range from 4.5 to 6.5 bar. The F-T blend produced ignition delays 17% shorter than ULSD#2 resulting in slightly lower peak apparent heat release rates (AHRR) along with decreased peak combustion temperatures, by up to 50°C. Nitrogen Oxide (NOx) emissions of the F-T blend decreased by 4.0% at 4.5 bar IMEP and at negligible amounts at 6.5 bar IMEP. The F-T blend decreased soot significantly at 5.4 bar IMEP by 40%. Efficiencies of the F-T blend were similar to ULSD#2.

In order to advance the current research engine to operate in advanced combustion modes such as reactivity controlled compression ignition RCCI a diesel common rail fuel injection system for the experimental research engine has been designed and developed through testing the hydraulic, electrical and electronics, mechanical subcomponents, and the controls strategies. This study presents the process taken based on the verification and validation model of design and development for the fuel injection system incorporating hardware-in-the-loop (HIL) testing prior to engine operation and subsequent engine validation. Software verification was completed through signal converting circuits to confirm precise injection timing and to test the system in a mean effective model to incorporate a PI speed controller along with consistent rail pressure.

The Cottonseed biodiesel combustion, sound and vibrations have been evaluated in a medium duty single cylinder DI engine (1.1L/cyl) by comparison with s ULSD#2 reference values. The engine was supercharged and had 20% EGR and all tests were conducted at 1400 rpm and at 4 bar BMEP load. Cylinder pressure was determined using a Kistler piezoelectric transducer. Combustion pressures peaked at 76 bar for both fuels. Ignition delay for CS100 decreased by 0.16 ms when compared to the ULSD#2 baseline. This would lead to a 23% lower peak heat release rate when operating CS100. The pressure rise rate for CS100 was 20% lower than ULSD#2, which related to the reduced ringing intensity for the biodiesel. The sound and vibrations were measured using a B&K condenser type multi-field microphone, and a tri-axial, piezoelectric accelerometer. All noise & vibration signals were analyzed with CPB and FFT Analysis, and Crank Angle Domain Analysis with B&K Pulse Platform software.

Autonomous vehicles must possess the capability to navigate complex intersections, which do not conform to typical models. Such intersections may have multiple roadways of different classes, highly acute angles, or unique multi-modal combinations. These may include railway grade crossings, bicycle lanes, or unique signal arrangements. Conventional navigation systems, which gather data from the surrounding area then plan a path through the collected data require faultless and complex analysis of extremely unstructured environments. The vehicle must then avoid obstacles as well as successfully navigate the intersection with extremely low tolerance for error. Computer decision making challenges can arise from this method of navigation, especially when interacting with non-autonomous vehicles.