Sustainability Considerations in AV Exclusive Lane Deployment
2019-12-02T17:28:31Z (GMT) by
Autonomous vehicles (AVs) are a disruptive technology that is expected to vastly change the current transportation system. AV potential benefits in terms of safety, mobility, efficiency and other impacts types have been documented in the literature. AVs are expected to increase travel demand due to the enhanced ease of making trips and provision of mobility to people currently with travel-limiting disabilities. The potential increase in travel demand, with its attendant congestion, may probably be offset by the transportation network capacity increase due to the reduced operational headways between AVs. However, such capacity benefits can be fully realized only when AVs fully saturate the market, because operating at low headways may be unsafe for Human Driven Vehicles (HDVs). Thus, to promote AV ownership while capturing the capacity benefits of an AV-only traffic stream, the conversion of traditional lanes to AV-exclusive use is prescribed often. In the AV-exclusive lanes, the vehicles can operate at reduced headways and at higher speeds, sharply increasing throughput. However, the metric used frequently by researchers for AV-exclusive lane evaluation is the total system travel time. AV-exclusive lanes may appear to be beneficial in terms of total system travel time but may come at a cost of environmental protection and social equity, the other two elements of sustainable development. Appropriating HDV lanes for AV-exclusive use will cause congestion on HDV lanes thereby increasing their emissions. Further, the AVs benefits may be accompanied by increased cost of HDV travel, which raises questions about equity. This thesis therefore presents a sustainable AV-exclusive lane deployment strategy by formulating and solving a multicriteria bi-level optimization problem with equity-related constraints. Mathematically, the problem is described as a discrete network design problem. Recognizing the difficulty of solving this NIP hard problem, the thesis combines the active set method with heuristic conditionalities to improve computational efficiency. The thesis’s framework can be used by agencies for evaluation and decision support regarding AV-exclusive lane deployment in a manner that fosters long-term sustainability.